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180 Commits

Author SHA1 Message Date
Jeffrey Morgan
5534f2cc6a llm: consider head_dim in llama arch (#5817) 2024-07-20 21:48:12 -04:00
Daniel Hiltgen
d321297d8a Merge pull request #5815 from dhiltgen/win_rocm_gfx_features
Adjust windows ROCm discovery
2024-07-20 16:02:55 -07:00
Daniel Hiltgen
06e5d74e34 Merge pull request #5506 from dhiltgen/sched_tests
Refine scheduler unit tests for reliability
2024-07-20 15:48:39 -07:00
Daniel Hiltgen
5d707e6fd5 Merge pull request #5583 from dhiltgen/integration_improvements
Fix context exhaustion integration test for small gpus
2024-07-20 15:48:21 -07:00
Daniel Hiltgen
283948c83b Adjust windows ROCm discovery
The v5 hip library returns unsupported GPUs which wont enumerate at
inference time in the runner so this makes sure we align discovery.  The
gfx906 cards are no longer supported so we shouldn't compile with that
GPU type as it wont enumerate at runtime.
2024-07-20 15:17:50 -07:00
Jeffrey Morgan
1475eab95f add patch for tekken (#5807) 2024-07-20 13:41:21 -04:00
Jeffrey Morgan
20090f3172 preserve last assistant message (#5802) 2024-07-19 20:19:26 -07:00
Jeffrey Morgan
69a2d4ccff Fix generate test flakyness (#5804) 2024-07-19 19:11:25 -07:00
Josh
e8b954c646 server: validate template (#5734)
add template validation to modelfile
2024-07-19 15:24:29 -07:00
royjhan
c57317cbf0 OpenAI: Function Based Testing (#5752)
* distinguish error forwarding

* more coverage

* rm comment
2024-07-19 11:37:12 -07:00
royjhan
51b2fd299c adjust openai chat msg processing (#5729) 2024-07-19 11:19:20 -07:00
Michael Yang
d0634b1596 Merge pull request #5780 from ollama/mxyng/tools
fix parsing tool calls: break on unexpected eofs
2024-07-18 12:14:10 -07:00
Michael Yang
43606d6d6a fix parsing tool calls 2024-07-18 12:08:11 -07:00
Jeffrey Morgan
70b1010fa5 server: check for empty tools array too (#5779) 2024-07-18 11:44:57 -07:00
Jeffrey Morgan
84e5721f3a always provide content even if empty (#5778) 2024-07-18 11:28:19 -07:00
Jeffrey Morgan
319fb1ce03 server: only parse tool calls if tools are provided (#5771)
* server: only parse tool calls if tools are provided

* still set `resp.Message.Content`
2024-07-18 08:50:23 -07:00
Michael Yang
b255445557 marshal json automatically for some template values (#5758) 2024-07-17 15:35:11 -07:00
Michael Yang
b23424bb3c Merge pull request #5753 from ollama/mxyng/parse-tool-call
parse tool call as individual objects
2024-07-17 11:47:53 -07:00
Michael Yang
5fd6988126 parse tool call as individual objects 2024-07-17 11:19:04 -07:00
Michael Yang
5b82960df8 stub response (#5750) 2024-07-17 10:39:22 -07:00
Michael Yang
cc9a252d8c Merge pull request #5732 from ollama/mxyng/cleanup
remove ToolCall from GenerateResponse
2024-07-17 10:26:54 -07:00
Pákozdi György
d281a6e603 add sidellama link (#5702) 2024-07-17 10:24:44 -07:00
royjhan
154f6f45d4 OpenAI: Support Tools (#5614)
* reopen pr

* tools

* remove tc from stream for now

* ID and Function

* openai expects arguments to be a string (#5739)

* mutually exclusive content and tool calls

* clean up

---------

Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>
2024-07-16 20:52:59 -07:00
royjhan
0d41623b52 OpenAI: Add Suffix to v1/completions (#5611)
* add suffix

* remove todo

* remove TODO

* add to test

* rm outdated prompt tokens info md

* fix test

* fix test
2024-07-16 20:50:14 -07:00
Michael Yang
c279f96371 remove ToolCall from GenerateResponse 2024-07-16 15:22:49 -07:00
Michael Yang
499e87c9ba Merge pull request #5730 from ollama/mxyng/cleanup
remove unneeded tool calls
2024-07-16 14:42:13 -07:00
Michael Yang
cd0853f2d5 Merge pull request #5207 from ollama/mxyng/suffix
add insert support to generate endpoint
2024-07-16 14:37:32 -07:00
Michael Yang
d290e87513 add suffix support to generate endpoint
this change is triggered by the presence of "suffix", particularly
useful for code completion tasks
2024-07-16 14:31:35 -07:00
Thorsten Sommer
97c20ede33 README: Added AI Studio to the list of UIs (#5721)
* Added AI Studio to the list of UIs
2024-07-16 14:24:27 -07:00
Michael Yang
5a83f79afd remove unneeded tool calls 2024-07-16 13:48:45 -07:00
royjhan
987dbab0b0 OpenAI: /v1/embeddings compatibility (#5285)
* OpenAI v1 models

* Empty List Testing

* Add back envconfig

* v1/models docs

* Remove Docs

* OpenAI batch embed compatibility

* merge conflicts

* integrate with api/embed

* ep

* merge conflicts

* request tests

* rm resp test

* merge conflict

* merge conflict

* test fixes

* test fn renaming

* input validation for empty string

---------

Co-authored-by: jmorganca <jmorganca@gmail.com>
2024-07-16 13:36:08 -07:00
Michael Yang
a8388beb94 Merge pull request #5726 from ollama/mxyng/tools-templates
fix unmarshal type errors
2024-07-16 12:12:10 -07:00
Michael Yang
5afbb60fc4 fix unmarshal type errors 2024-07-16 11:39:34 -07:00
Jeffrey Morgan
4cb5d7decc server: omit model system prompt if empty (#5717) 2024-07-16 11:09:00 -07:00
Michael Yang
8eac50dd4f Merge pull request #5684 from ollama/mxyng/tests
add chat and generate tests with mock runner
2024-07-16 09:44:45 -07:00
Michael Yang
4a565cbf94 add chat and generate tests with mock runner 2024-07-16 09:39:31 -07:00
Michael Yang
64039df6d7 Merge pull request #5284 from ollama/mxyng/tools
tools
2024-07-15 18:03:37 -07:00
Jeffrey Morgan
7ac6d462ec server: return empty slice on empty /api/embed request (#5713)
* server: return empty slice on empty `/api/embed` request

* fix tests
2024-07-15 17:39:44 -07:00
Michael Yang
ef5136a745 tools test 2024-07-15 17:18:21 -07:00
Daniel Hiltgen
8288ec8824 Merge pull request #5710 from dhiltgen/rocm_bump
Bump linux ROCm to 6.1.2
2024-07-15 15:32:18 -07:00
Michael Yang
d02bbebb11 tools 2024-07-15 15:26:16 -07:00
Daniel Hiltgen
224337b32f Bump linux ROCm to 6.1.2 2024-07-15 15:10:22 -07:00
Jeffrey Morgan
9e35d9bbee server: lowercase roles for compatibility with clients (#5695) 2024-07-15 13:55:57 -07:00
royjhan
b9f5e16c80 Introduce /api/embed endpoint supporting batch embedding (#5127)
* Initial Batch Embedding

* Revert "Initial Batch Embedding"

This reverts commit c22d54895a.

* Initial Draft

* mock up notes

* api/embed draft

* add server function

* check normalization

* clean up

* normalization

* playing around with truncate stuff

* Truncation

* Truncation

* move normalization to go

* Integration Test Template

* Truncation Integration Tests

* Clean up

* use float32

* move normalize

* move normalize test

* refactoring

* integration float32

* input handling and handler testing

* Refactoring of legacy and new

* clear comments

* merge conflicts

* touches

* embedding type 64

* merge conflicts

* fix hanging on single string

* refactoring

* test values

* set context length

* clean up

* testing clean up

* testing clean up

* remove function closure

* Revert "remove function closure"

This reverts commit 55d48c6ed1.

* remove function closure

* remove redundant error check

* clean up

* more clean up

* clean up
2024-07-15 12:14:24 -07:00
royjhan
e9f7f36029 Support image input for OpenAI chat compatibility (#5208)
* OpenAI v1 models

* Refactor Writers

* Add Test

Co-Authored-By: Attila Kerekes

* Credit Co-Author

Co-Authored-By: Attila Kerekes <439392+keriati@users.noreply.github.com>

* Empty List Testing

* Use Namespace for Ownedby

* Update Test

* Add back envconfig

* v1/models docs

* Use ModelName Parser

* Test Names

* Remove Docs

* Clean Up

* Test name

Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>

* Add Middleware for Chat and List

* Testing Cleanup

* Test with Fatal

* Add functionality to chat test

* Support image input for OpenAI chat

* Decoding

* Fix message processing logic

* openai vision test

* type errors

* clean up

* redundant check

* merge conflicts

* merge conflicts

* merge conflicts

* flattening and smaller image

* add test

* support python and js SDKs and mandate prefixing

* clean up

---------

Co-authored-by: Attila Kerekes <439392+keriati@users.noreply.github.com>
Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>
2024-07-13 22:07:45 -07:00
Patrick Devine
057d31861e remove template (#5655) 2024-07-13 20:56:24 -07:00
jmorganca
f7ee012300 server: prepend system message in chat handler 2024-07-13 15:08:00 -07:00
Jeffrey Morgan
1ed0aa8fea server: fix context, load_duration and total_duration fields (#5676)
* server: fix `contet`, `load_duration` and `total_duration` fields

* Update server/routes.go
2024-07-13 09:25:31 -07:00
Jeffrey Morgan
ef98803d63 llm: looser checks for minimum memory (#5677) 2024-07-13 09:20:05 -07:00
Jarek
02fea420e5 Add Kerlig AI, an app for macOS (#5675) 2024-07-13 08:33:46 -07:00
Michael Yang
22c5451fc2 fix system prompt (#5662)
* fix system prompt

* execute template when hitting previous roles

* fix tests

---------

Co-authored-by: jmorganca <jmorganca@gmail.com>
2024-07-12 21:04:44 -07:00
Patrick Devine
23ebbaa46e Revert "remove template from tests"
This reverts commit 9ac0a7a50b.
2024-07-12 15:47:17 -07:00
Patrick Devine
9ac0a7a50b remove template from tests 2024-07-12 15:41:31 -07:00
Michael Yang
e5c65a85df Merge pull request #5653 from ollama/mxyng/collect-system
template: preprocess message and collect system
2024-07-12 12:32:34 -07:00
Jeffrey Morgan
33627331a3 app: also clean up tempdir runners on install (#5646) 2024-07-12 12:29:23 -07:00
Michael Yang
36c87c433b template: preprocess message and collect system 2024-07-12 12:26:43 -07:00
Jeffrey Morgan
179737feb7 Clean up old files when installing on Windows (#5645)
* app: always clean up install dir; force close applications

* remove wildcard

* revert `CloseApplications`

* whitespace

* update `LOCALAPPDATA` var
2024-07-11 22:53:46 -07:00
Michael Yang
47353f5ee4 Merge pull request #5639 from ollama/mxyng/unaggregated-system 2024-07-11 17:48:50 -07:00
Josh
10e768826c fix: quant err message (#5616) 2024-07-11 17:24:29 -07:00
Michael Yang
5056bb9c01 rename aggregate to contents 2024-07-11 17:00:26 -07:00
Jeffrey Morgan
c4cf8ad559 llm: avoid loading model if system memory is too small (#5637)
* llm: avoid loading model if system memory is too small

* update log

* Instrument swap free space

On linux and windows, expose how much swap space is available
so we can take that into consideration when scheduling models

* use `systemSwapFreeMemory` in check

---------

Co-authored-by: Daniel Hiltgen <daniel@ollama.com>
2024-07-11 16:42:57 -07:00
Michael Yang
57ec6901eb revert embedded templates to use prompt/response
This reverts commit 19753c18c0.

for compat. messages will be added at a later date
2024-07-11 14:49:35 -07:00
Michael Yang
e64f9ebb44 do no automatically aggregate system messages 2024-07-11 14:49:35 -07:00
Jeffrey Morgan
791650ddef sched: only error when over-allocating system memory (#5626) 2024-07-11 00:53:12 -07:00
Jeffrey Morgan
efbf41ed81 llm: dont link cuda with compat libs (#5621) 2024-07-10 20:01:52 -07:00
Michael Yang
cf15589851 Merge pull request #5620 from ollama/mxyng/templates
update embedded templates
2024-07-10 17:16:24 -07:00
Michael Yang
19753c18c0 update embedded templates 2024-07-10 17:03:08 -07:00
Michael Yang
41be28096a add system prompt to first legacy template 2024-07-10 17:03:08 -07:00
Michael Yang
37a570f962 Merge pull request #5612 from ollama/mxyng/mem
chatglm graph
2024-07-10 14:18:33 -07:00
Michael Yang
5a739ff4cb chatglm graph 2024-07-10 13:43:47 -07:00
Jeffrey Morgan
4e262eb2a8 remove GGML_CUDA_FORCE_MMQ=on from build (#5588) 2024-07-10 13:17:13 -07:00
Daniel Hiltgen
4cfcbc328f Merge pull request #5124 from dhiltgen/amd_windows
Wire up windows AMD driver reporting
2024-07-10 12:50:23 -07:00
Daniel Hiltgen
79292ff3e0 Merge pull request #5555 from dhiltgen/msvc_deps
Bundle missing CRT libraries
2024-07-10 12:50:02 -07:00
Daniel Hiltgen
8ea500441d Merge pull request #5580 from dhiltgen/cuda_overhead
Detect CUDA OS overhead
2024-07-10 12:47:31 -07:00
Daniel Hiltgen
b50c818623 Merge pull request #5607 from dhiltgen/win_rocm_v6
Bump ROCm on windows to 6.1.2
2024-07-10 12:47:10 -07:00
Daniel Hiltgen
b99e750b62 Merge pull request #5605 from dhiltgen/merge_glitch
Remove duplicate merge glitch
2024-07-10 11:47:08 -07:00
Daniel Hiltgen
1f50356e8e Bump ROCm on windows to 6.1.2
This also adjusts our algorithm to favor our bundled ROCm.
I've confirmed VRAM reporting still doesn't work properly so we
can't yet enable concurrency by default.
2024-07-10 11:01:22 -07:00
Daniel Hiltgen
22c81f62ec Remove duplicate merge glitch 2024-07-10 09:01:33 -07:00
Daniel Hiltgen
73e2c8f68f Fix context exhaustion integration test for small gpus
On the smaller GPUs, the initial model load of llama2 took over 30s (the
default timeout for the DoGenerate helper)
2024-07-09 16:24:14 -07:00
Daniel Hiltgen
f4408219e9 Refine scheduler unit tests for reliability
This breaks up some of the test scenarios to create a
more reliable set of tests, as well as adding a little more
coverage.
2024-07-09 16:00:08 -07:00
Daniel Hiltgen
2d1e3c3229 Merge pull request #5503 from dhiltgen/dual_rocm
Workaround broken ROCm p2p copy
2024-07-09 15:44:16 -07:00
royjhan
4918fae535 OpenAI v1/completions: allow stop token list (#5551)
* stop token parsing fix

* add stop test
2024-07-09 14:01:26 -07:00
royjhan
0aff67877e separate request tests (#5578) 2024-07-09 13:48:31 -07:00
Daniel Hiltgen
f6f759fc5f Detect CUDA OS Overhead
This adds logic to detect skew between the driver and
management library which can be attributed to OS overhead
and records that so we can adjust subsequent management
library free VRAM updates and avoid OOM scenarios.
2024-07-09 12:21:50 -07:00
Daniel Hiltgen
9544a57ee4 Merge pull request #5579 from dhiltgen/win_static_deps
Statically link c++ and thread lib on windows
2024-07-09 12:21:13 -07:00
Daniel Hiltgen
b51e3b63ac Statically link c++ and thread lib
This makes sure we statically link the c++ and thread library on windows
to avoid unnecessary runtime dependencies on non-standard DLLs
2024-07-09 11:34:30 -07:00
Michael Yang
6bbbc50f10 Merge pull request #5440 from ollama/mxyng/messages-templates
update named templates
2024-07-09 09:36:32 -07:00
Michael Yang
9bbddc37a7 Merge pull request #5126 from ollama/mxyng/messages
update message processing
2024-07-09 09:20:44 -07:00
Jeffrey Morgan
e4ff73297d server: fix model reloads when setting OLLAMA_NUM_PARALLEL (#5560)
* server: fix unneeded model reloads when setting `OLLAMA_NUM_PARALLEL`

* remove whitespace change

* undo some changes
2024-07-08 22:32:15 -07:00
Daniel Hiltgen
b44320db13 Bundle missing CRT libraries
Some users are experienging runner startup errors due
to not having these msvc redist libraries on their host
2024-07-08 18:24:21 -07:00
Daniel Hiltgen
0bacb30007 Workaround broken ROCm p2p copy
Enable the build flag for llama.cpp to use CPU copy for multi-GPU scenarios.
2024-07-08 09:40:52 -07:00
Jeffrey Morgan
53da2c6965 llm: remove ambiguous comment when putting upper limit on predictions to avoid infinite generation (#5535) 2024-07-07 14:32:05 -04:00
Jeffrey Morgan
d8def1ff94 llm: allow gemma 2 to context shift (#5534) 2024-07-07 13:41:51 -04:00
Jeffrey Morgan
571dc61955 Update llama.cpp submodule to a8db2a9c (#5530) 2024-07-07 13:03:09 -04:00
Jeffrey Morgan
0e09c380fc llm: print caching notices in debug only (#5533) 2024-07-07 12:38:04 -04:00
Jeffrey Morgan
0ee87615c7 sched: don't error if paging to disk on Windows and macOS (#5523) 2024-07-06 22:01:52 -04:00
Jeffrey Morgan
f8241bfba3 gpu: report system free memory instead of 0 (#5521) 2024-07-06 19:35:04 -04:00
Jeffrey Morgan
4607c70641 llm: add -DBUILD_SHARED_LIBS=off to common cpu cmake flags (#5520) 2024-07-06 18:58:16 -04:00
jmorganca
c12f1c5b99 release: move mingw library cleanup to correct job 2024-07-06 16:12:29 -04:00
jmorganca
a08f20d910 release: remove unwanted mingw dll.a files 2024-07-06 15:21:15 -04:00
jmorganca
6cea036027 Revert "llm: only statically link libstdc++"
This reverts commit 5796bfc401.
2024-07-06 15:10:48 -04:00
jmorganca
5796bfc401 llm: only statically link libstdc++ 2024-07-06 14:06:20 -04:00
jmorganca
f1a379aa56 llm: statically link pthread and stdc++ dependencies in windows build 2024-07-06 12:54:02 -04:00
jmorganca
9ae146993e llm: add GGML_STATIC flag to windows static lib 2024-07-06 03:27:05 -04:00
Jeffrey Morgan
e0348d3fe8 llm: add COMMON_DARWIN_DEFS to arm static build (#5513) 2024-07-05 22:42:42 -04:00
Jeffrey Morgan
2cc854f8cb llm: fix missing dylibs by restoring old build behavior on Linux and macOS (#5511)
* Revert "fix cmake build (#5505)"

This reverts commit 4fd5f3526a.

* llm: fix missing dylibs by restoring old build behavior

* crlf -> lf
2024-07-05 21:48:31 -04:00
Jeffrey Morgan
5304b765b2 llm: put back old include dir (#5507)
* llm: put back old include dir

* llm: update link paths for old submodule commits
2024-07-05 19:34:21 -04:00
Michael Yang
fb6cbc02fb update named templates 2024-07-05 16:29:32 -07:00
Jeffrey Morgan
4fd5f3526a fix cmake build (#5505) 2024-07-05 19:07:01 -04:00
Daniel Hiltgen
842f85f758 Merge pull request #5502 from dhiltgen/ci_fixes
Always go build in CI generate steps
2024-07-05 15:39:11 -07:00
Daniel Hiltgen
9d30f9f8b3 Always go build in CI generate steps
With the recent cgo changes, bugs can sneak through
if we don't make sure to `go build` all the permutations
2024-07-05 15:31:52 -07:00
Blake Mizerany
631cfd9e62 types/model: remove knowledge of digest (#5500)
This was leading to ambiguity and confusion in ollama.com, and is not
used anywhere in ollama at the moment. Once manifests are addressable by
digest, we can add this back in, and in a way that is more tailored to
the concept of addressing a manifest by digest.
2024-07-05 13:42:30 -07:00
Michael Yang
326363b3a7 no funcs 2024-07-05 13:17:25 -07:00
Michael Yang
ac7a842e55 fix model reloading
ensure runtime model changes (template, system prompt, messages,
options) are captured on model updates without needing to reload the
server
2024-07-05 13:17:25 -07:00
Michael Yang
2c3fe1fd97 comments 2024-07-05 13:17:24 -07:00
Michael Yang
269ed6e6a2 update message processing 2024-07-05 13:16:58 -07:00
Jeffrey Morgan
78fb33dd07 fix typo in cgo directives in llm.go (#5501) 2024-07-05 15:18:36 -04:00
Jeffrey Morgan
8f8e736b13 update llama.cpp submodule to d7fd29f (#5475) 2024-07-05 13:25:58 -04:00
Jeffrey Morgan
d89454de80 Use slot with cached prompt instead of least recently used (#5492)
* Use common prefix to select slot

* actually report `longest`
2024-07-05 12:32:47 -04:00
Daniel Hiltgen
af28b94533 Merge pull request #5469 from dhiltgen/prevent_system_oom
Prevent loading models larger than total memory
2024-07-05 08:22:20 -07:00
Jeffrey Morgan
e9188e971a Fix assert on small embedding inputs (#5491)
* Fix assert on small embedding inputs

* Update llm/patches/09-pooling.diff
2024-07-05 11:20:57 -04:00
Daniel Hiltgen
78eddfc068 Merge pull request #4412 from dhiltgen/win_docs
Document older win10 terminal problems
2024-07-05 08:18:22 -07:00
Daniel Hiltgen
02c24d3d01 Merge pull request #5466 from dhiltgen/fix_clip_unicode
Fix clip model loading with unicode paths
2024-07-05 08:16:58 -07:00
Daniel Hiltgen
52abc8acb7 Document older win10 terminal problems
We haven't found a workaround, so for now recommend updating.
2024-07-03 17:32:14 -07:00
Jeffrey Morgan
4d71c559b2 fix error detection by limiting model loading error parsing (#5472) 2024-07-03 20:04:30 -04:00
Anatoli Babenia
0d16eb310e fix: use envconfig.ModelsDir directly (#4821)
* Co-authored-by: Anatoli Babenia <anatoli@rainforce.org>

Co-authored-by: Maas Lalani <maas@lalani.dev>
2024-07-03 15:36:11 -07:00
Daniel Hiltgen
8072e205ff Merge pull request #5447 from dhiltgen/fix_keepalive
Only set default keep_alive on initial model load
2024-07-03 15:34:38 -07:00
Daniel Hiltgen
955f2a4e03 Only set default keep_alive on initial model load
This change fixes the handling of keep_alive so that if client
request omits the setting, we only set this on initial load.  Once
the model is loaded, if new requests leave this unset, we'll keep
whatever keep_alive was there.
2024-07-03 15:29:56 -07:00
Daniel Hiltgen
3c75113e37 Prevent loading models larger than total memory
Users may not realize the siny new model they're trying to load
fits on their disk, but can't load into system+GPU memory.  Today
we crash, but with this fix, we'll give them a better error message
before even trying to load it.
2024-07-03 14:47:42 -07:00
Daniel Hiltgen
ccd7785859 Merge pull request #5243 from dhiltgen/modelfile_use_mmap
Fix use_mmap for modefiles
2024-07-03 13:59:42 -07:00
royjhan
3b5a4a77f3 Return Correct Prompt Eval Count Regardless of Cache Prompt (#5371)
* openai compatibility

* Revert "openai compatibility"

This reverts commit d3f98a811e.

* remove erroneous subtraction of prompt cache
2024-07-03 13:46:23 -07:00
Daniel Hiltgen
daed0634a9 Merge pull request #5467 from dhiltgen/bogus_cpu_mac_error
Fix corner cases on tmp cleaner on mac
2024-07-03 13:39:36 -07:00
Daniel Hiltgen
0d4dd707bc Merge pull request #5465 from dhiltgen/better_cuda_logging
Better nvidia GPU discovery logging
2024-07-03 13:12:22 -07:00
Daniel Hiltgen
0e982bc1f4 Fix corner cases on tmp cleaner on mac
When ollama is running a long time, tmp cleaners can remove the
runners.  This tightens up a few corner cases on arm macs where
we failed with "server cpu not listed in available servers map[]"
2024-07-03 13:10:14 -07:00
Daniel Hiltgen
6298f49816 Fix clip model loading with unicode paths
On windows, if the model dir contained unicode characters
clip models would fail to load.  This fixes the file name
handling in clip.cpp to support utf16 on windows.
2024-07-03 12:46:36 -07:00
Daniel Hiltgen
ef757da2c9 Better nvidia GPU discovery logging
Refine the way we log GPU discovery to improve the non-debug
output, and report more actionable log messages when possible
to help users troubleshoot on their own.
2024-07-03 10:50:40 -07:00
Michael Yang
e5352297d9 Merge pull request #5448 from ollama/mxyng/fix-generate
use model template by default
2024-07-02 16:48:06 -07:00
Michael Yang
65a5040e09 fix generate template 2024-07-02 16:42:17 -07:00
royjhan
d626b99b54 OpenAI: v1/completions compatibility (#5209)
* OpenAI v1 models

* Refactor Writers

* Add Test

Co-Authored-By: Attila Kerekes

* Credit Co-Author

Co-Authored-By: Attila Kerekes <439392+keriati@users.noreply.github.com>

* Empty List Testing

* Use Namespace for Ownedby

* Update Test

* Add back envconfig

* v1/models docs

* Use ModelName Parser

* Test Names

* Remove Docs

* Clean Up

* Test name

Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>

* Add Middleware for Chat and List

* Completions Endpoint

* Testing Cleanup

* Test with Fatal

* Add functionality to chat test

* Rename function

* float types

* type cleanup

* cleaning

* more cleaning

* Extra test cases

* merge conflicts

* merge conflicts

* merge conflicts

* merge conflicts

* cleaning

* cleaning

---------

Co-authored-by: Attila Kerekes <439392+keriati@users.noreply.github.com>
Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>
2024-07-02 16:01:45 -07:00
Michael Yang
dddb58a38b Merge pull request #5051 from ollama/mxyng/capabilities
add model capabilities
2024-07-02 14:26:07 -07:00
Michael Yang
400056e154 Merge pull request #5420 from ollama/mxyng/insecure-path
err on insecure path
2024-07-02 14:03:23 -07:00
Daniel Hiltgen
d2f19024d0 Merge pull request #5442 from dhiltgen/concurrency_docs
Add windows radeon concurrency note
2024-07-02 12:47:47 -07:00
Daniel Hiltgen
69c04eecc4 Add windows radeon concurreny note 2024-07-02 12:46:14 -07:00
royjhan
996bb1b85e OpenAI: /v1/models and /v1/models/{model} compatibility (#5007)
* OpenAI v1 models

* Refactor Writers

* Add Test

Co-Authored-By: Attila Kerekes

* Credit Co-Author

Co-Authored-By: Attila Kerekes <439392+keriati@users.noreply.github.com>

* Empty List Testing

* Use Namespace for Ownedby

* Update Test

* Add back envconfig

* v1/models docs

* Use ModelName Parser

* Test Names

* Remove Docs

* Clean Up

* Test name

Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>

* Add Middleware for Chat and List

* Testing Cleanup

* Test with Fatal

* Add functionality to chat test

* OpenAI: /v1/models/{model} compatibility (#5028)

* Retrieve Model

* OpenAI Delete Model

* Retrieve Middleware

* Remove Delete from Branch

* Update Test

* Middleware Test File

* Function name

* Cleanup

* Test Update

* Test Update

---------

Co-authored-by: Attila Kerekes <439392+keriati@users.noreply.github.com>
Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>
2024-07-02 11:50:56 -07:00
Daniel Hiltgen
422dcc3856 Merge pull request #5439 from dhiltgen/fix_centos_7_build
Switch ARM64 container image base to rocky 8
2024-07-02 11:01:15 -07:00
Daniel Hiltgen
020bd60ab2 Switch amd container image base to rocky 8
The centos 7 arm mirrors have disappeared due to the EOL 2 days
ago, and the vault sed workaround which works for x86 doesn't work for arm.
2024-07-02 10:34:47 -07:00
Daniel Hiltgen
8e277b72bb Merge pull request #5438 from dhiltgen/fix_centos_7_build
Centos 7 EOL broke mirrors
2024-07-02 09:28:00 -07:00
Daniel Hiltgen
4f67b39d26 Centos 7 EOL broke mirrors
As of July 1st 2024: Could not resolve host: mirrorlist.centos.org
This is expected due to EOL dates.
2024-07-02 09:22:17 -07:00
Josh
2425281317 Merge pull request #5336 from ollama/jyan/from-errors
fix: trim spaces for FROM argument, don't trim inside of quotes
2024-07-01 16:32:46 -07:00
Josh
0403e9860e Merge pull request #5421 from ollama/jyan/ver
fix: add unsupported architecture message for linux/windows
2024-07-01 16:32:14 -07:00
Josh Yan
33a65e3ba3 error 2024-07-01 16:04:13 -07:00
Michael Yang
88bcd79bb9 err on insecure path 2024-07-01 15:55:59 -07:00
Josh Yan
7e571f95f0 trimspace test case 2024-07-01 11:07:48 -07:00
Michael Yang
da8e2a0447 use kvs to detect embedding models 2024-07-01 10:47:43 -07:00
Michael Yang
a30915bde1 add capabilities 2024-07-01 10:47:43 -07:00
Michael Yang
58e3fff311 rename templates to template 2024-07-01 10:40:54 -07:00
Michael Yang
3f0b309ad4 remove ManifestV2 2024-07-01 10:40:54 -07:00
Daniel Hiltgen
e70610ef06 Merge pull request #5410 from dhiltgen/ctx_cleanup
Fix case for NumCtx
2024-07-01 09:54:20 -07:00
Daniel Hiltgen
dfded7e075 Merge pull request #5364 from dhiltgen/concurrency_docs
Document concurrent behavior and settings
2024-07-01 09:49:48 -07:00
Daniel Hiltgen
173b550438 Remove default auto from help message
This may confuse users thinking "auto" is an acceptable string - it must be numeric
2024-07-01 09:48:05 -07:00
Daniel Hiltgen
cff3f44f4a Fix case for NumCtx 2024-07-01 09:43:59 -07:00
Josh Yan
26e4e66faf updated parsefile test 2024-07-01 09:43:49 -07:00
Daniel Hiltgen
97c9e11768 Switch use_mmap to a pointer type
This uses nil as undefined for a cleaner implementation.
2024-07-01 08:44:59 -07:00
Daniel Hiltgen
3518aaef33 Merge pull request #4218 from dhiltgen/auto_parallel
Enable concurrency by default
2024-07-01 08:32:29 -07:00
RAPID ARCHITECT
1963c00201 Update README.md (#5214)
* Update README.md

Added Mesop example to web & desktop

* Update README.md

---------

Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>
2024-06-30 22:00:57 -04:00
Eduard
27402cb7a2 Update gpu.md (#5382)
Runs fine on a NVIDIA GeForce GTX 1050 Ti
2024-06-30 21:48:51 -04:00
Jeffrey Morgan
c1218199cf Update api.md 2024-06-29 16:22:49 -07:00
Jeffrey Morgan
717f7229eb Do not shift context for sliding window models (#5368)
* Do not shift context for sliding window models

* truncate prompt > 2/3 tokens

* only target gemma2
2024-06-28 19:39:31 -07:00
Daniel Hiltgen
aae56abb7c Document concurrent behavior and settings 2024-06-28 13:15:57 -07:00
royjhan
5f034f5b63 Include Show Info in Interactive (#5342) 2024-06-28 13:15:52 -07:00
royjhan
b910fa9010 Ollama Show: Check for Projector Type (#5307)
* Check exists projtype

* Maintain Ordering
2024-06-28 11:30:16 -07:00
royjhan
6d4219083c Update docs (#5312) 2024-06-28 09:58:14 -07:00
Michael Yang
1ed4f521c4 Merge pull request #5340 from ollama/mxyng/mem
gemma2 graph
2024-06-27 14:26:49 -07:00
Michael Yang
de2163dafd gemma2 graph 2024-06-27 13:34:52 -07:00
Josh Yan
9bd00041fa trim all params 2024-06-27 11:18:38 -07:00
Josh Yan
4e986a823c unquote, trimp space 2024-06-27 10:59:15 -07:00
Daniel Hiltgen
642cee1342 Sort the ps output
Provide consistent ordering for the ps command - longest duration listed first
2024-06-21 15:59:41 -07:00
Daniel Hiltgen
9929751cc8 Disable concurrency for AMD + Windows
Until ROCm v6.2 ships, we wont be able to get accurate free memory
reporting on windows, which makes automatic concurrency too risky.
Users can still opt-in but will need to pay attention to model sizes otherwise they may thrash/page VRAM or cause OOM crashes.
All other platforms and GPUs have accurate VRAM reporting wired
up now, so we can turn on concurrency by default.
2024-06-21 15:45:05 -07:00
Daniel Hiltgen
17b7186cd7 Enable concurrency by default
This adjusts our default settings to enable multiple models and parallel
requests to a single model.  Users can still override these by the same
env var settings as before.  Parallel has a direct impact on
num_ctx, which in turn can have a significant impact on small VRAM GPUs
so this change also refines the algorithm so that when parallel is not
explicitly set by the user, we try to find a reasonable default that fits
the model on their GPU(s).  As before, multiple models will only load
concurrently if they fully fit in VRAM.
2024-06-21 15:45:05 -07:00
Daniel Hiltgen
784bf88b0d Wire up windows AMD driver reporting
This seems to be ROCm version, not actually driver version, but
it may be useful for toggling logic for VRAM reporting in the future
2024-06-18 16:22:47 -07:00
176 changed files with 6079 additions and 1973 deletions

View File

@@ -147,7 +147,7 @@ jobs:
run: |
$ErrorActionPreference = "Stop"
write-host "downloading AMD HIP Installer"
Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-23.Q4-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q3-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
write-host "Installing AMD HIP"
Start-Process "${env:RUNNER_TEMP}\rocm-install.exe" -ArgumentList '-install' -NoNewWindow -Wait
write-host "Completed AMD HIP"

View File

@@ -58,6 +58,7 @@ jobs:
runs-on: ${{ matrix.os }}
env:
GOARCH: ${{ matrix.arch }}
CGO_ENABLED: '1'
steps:
- uses: actions/checkout@v4
- uses: actions/setup-go@v5
@@ -79,6 +80,7 @@ jobs:
- run: go generate -x ./...
if: ${{ ! startsWith(matrix.os, 'windows-') }}
name: 'Unix Go Generate'
- run: go build .
- uses: actions/upload-artifact@v4
with:
name: ${{ matrix.os }}-${{ matrix.arch }}-libraries
@@ -124,7 +126,7 @@ jobs:
strategy:
matrix:
rocm-version:
- '6.1.1'
- '6.1.2'
runs-on: linux
container: rocm/dev-ubuntu-20.04:${{ matrix.rocm-version }}
steps:
@@ -167,7 +169,7 @@ jobs:
run: |
$ErrorActionPreference = "Stop"
write-host "downloading AMD HIP Installer"
Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-23.Q4-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
Invoke-WebRequest -Uri "https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q3-WinSvr2022-For-HIP.exe" -OutFile "${env:RUNNER_TEMP}\rocm-install.exe"
write-host "Installing AMD HIP"
Start-Process "${env:RUNNER_TEMP}\rocm-install.exe" -ArgumentList '-install' -NoNewWindow -Wait
write-host "Completed AMD HIP"

View File

@@ -2,7 +2,7 @@ ARG GOLANG_VERSION=1.22.1
ARG CMAKE_VERSION=3.22.1
# this CUDA_VERSION corresponds with the one specified in docs/gpu.md
ARG CUDA_VERSION=11.3.1
ARG ROCM_VERSION=6.1.1
ARG ROCM_VERSION=6.1.2
# Copy the minimal context we need to run the generate scripts
FROM scratch AS llm-code
@@ -70,12 +70,12 @@ RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu_avx" sh gen_linux.sh
FROM --platform=linux/amd64 cpu-builder-amd64 AS cpu_avx2-build-amd64
RUN OLLAMA_SKIP_STATIC_GENERATE=1 OLLAMA_CPU_TARGET="cpu_avx2" sh gen_linux.sh
FROM --platform=linux/arm64 centos:7 AS cpu-builder-arm64
FROM --platform=linux/arm64 rockylinux:8 AS cpu-builder-arm64
ARG CMAKE_VERSION
ARG GOLANG_VERSION
COPY ./scripts/rh_linux_deps.sh /
RUN CMAKE_VERSION=${CMAKE_VERSION} GOLANG_VERSION=${GOLANG_VERSION} sh /rh_linux_deps.sh
ENV PATH /opt/rh/devtoolset-10/root/usr/bin:$PATH
ENV PATH /opt/rh/gcc-toolset-10/root/usr/bin:$PATH
COPY --from=llm-code / /go/src/github.com/ollama/ollama/
ARG OLLAMA_CUSTOM_CPU_DEFS
ARG CGO_CFLAGS

View File

@@ -292,6 +292,10 @@ See the [API documentation](./docs/api.md) for all endpoints.
- [Olpaka](https://github.com/Otacon/olpaka) (User-friendly Flutter Web App for Ollama)
- [OllamaSpring](https://github.com/CrazyNeil/OllamaSpring) (Ollama Client for macOS)
- [LLocal.in](https://github.com/kartikm7/llocal) (Easy to use Electron Desktop Client for Ollama)
- [Ollama with Google Mesop](https://github.com/rapidarchitect/ollama_mesop/) (Mesop Chat Client implementation with Ollama)
- [Kerlig AI](https://www.kerlig.com/) (AI writing assistant for macOS)
- [AI Studio](https://github.com/MindWorkAI/AI-Studio)
- [Sidellama](https://github.com/gyopak/sidellama) (browser-based LLM client)
### Terminal

View File

@@ -347,7 +347,16 @@ func (c *Client) Heartbeat(ctx context.Context) error {
return nil
}
// Embeddings generates embeddings from a model.
// Embed generates embeddings from a model.
func (c *Client) Embed(ctx context.Context, req *EmbedRequest) (*EmbedResponse, error) {
var resp EmbedResponse
if err := c.do(ctx, http.MethodPost, "/api/embed", req, &resp); err != nil {
return nil, err
}
return &resp, nil
}
// Embeddings generates an embedding from a model.
func (c *Client) Embeddings(ctx context.Context, req *EmbeddingRequest) (*EmbeddingResponse, error) {
var resp EmbeddingResponse
if err := c.do(ctx, http.MethodPost, "/api/embeddings", req, &resp); err != nil {

View File

@@ -47,6 +47,9 @@ type GenerateRequest struct {
// Prompt is the textual prompt to send to the model.
Prompt string `json:"prompt"`
// Suffix is the text that comes after the inserted text.
Suffix string `json:"suffix"`
// System overrides the model's default system message/prompt.
System string `json:"system"`
@@ -97,17 +100,80 @@ type ChatRequest struct {
// followin the request.
KeepAlive *Duration `json:"keep_alive,omitempty"`
// Tools is an optional list of tools the model has access to.
Tools `json:"tools,omitempty"`
// Options lists model-specific options.
Options map[string]interface{} `json:"options"`
}
type Tools []Tool
func (t Tools) String() string {
bts, _ := json.Marshal(t)
return string(bts)
}
// Message is a single message in a chat sequence. The message contains the
// role ("system", "user", or "assistant"), the content and an optional list
// of images.
type Message struct {
Role string `json:"role"`
Content string `json:"content"`
Images []ImageData `json:"images,omitempty"`
Role string `json:"role"`
Content string `json:"content"`
Images []ImageData `json:"images,omitempty"`
ToolCalls []ToolCall `json:"tool_calls,omitempty"`
}
func (m *Message) UnmarshalJSON(b []byte) error {
type Alias Message
var a Alias
if err := json.Unmarshal(b, &a); err != nil {
return err
}
*m = Message(a)
m.Role = strings.ToLower(m.Role)
return nil
}
type ToolCall struct {
Function ToolCallFunction `json:"function"`
}
type ToolCallFunction struct {
Name string `json:"name"`
Arguments ToolCallFunctionArguments `json:"arguments"`
}
type ToolCallFunctionArguments map[string]any
func (t *ToolCallFunctionArguments) String() string {
bts, _ := json.Marshal(t)
return string(bts)
}
type Tool struct {
Type string `json:"type"`
Function ToolFunction `json:"function"`
}
type ToolFunction struct {
Name string `json:"name"`
Description string `json:"description"`
Parameters struct {
Type string `json:"type"`
Required []string `json:"required"`
Properties map[string]struct {
Type string `json:"type"`
Description string `json:"description"`
Enum []string `json:"enum,omitempty"`
} `json:"properties"`
} `json:"parameters"`
}
func (t *ToolFunction) String() string {
bts, _ := json.Marshal(t)
return string(bts)
}
// ChatResponse is the response returned by [Client.Chat]. Its fields are
@@ -159,49 +225,42 @@ type Options struct {
// Runner options which must be set when the model is loaded into memory
type Runner struct {
UseNUMA bool `json:"numa,omitempty"`
NumCtx int `json:"num_ctx,omitempty"`
NumBatch int `json:"num_batch,omitempty"`
NumGPU int `json:"num_gpu,omitempty"`
MainGPU int `json:"main_gpu,omitempty"`
LowVRAM bool `json:"low_vram,omitempty"`
F16KV bool `json:"f16_kv,omitempty"`
LogitsAll bool `json:"logits_all,omitempty"`
VocabOnly bool `json:"vocab_only,omitempty"`
UseMMap TriState `json:"use_mmap,omitempty"`
UseMLock bool `json:"use_mlock,omitempty"`
NumThread int `json:"num_thread,omitempty"`
UseNUMA bool `json:"numa,omitempty"`
NumCtx int `json:"num_ctx,omitempty"`
NumBatch int `json:"num_batch,omitempty"`
NumGPU int `json:"num_gpu,omitempty"`
MainGPU int `json:"main_gpu,omitempty"`
LowVRAM bool `json:"low_vram,omitempty"`
F16KV bool `json:"f16_kv,omitempty"`
LogitsAll bool `json:"logits_all,omitempty"`
VocabOnly bool `json:"vocab_only,omitempty"`
UseMMap *bool `json:"use_mmap,omitempty"`
UseMLock bool `json:"use_mlock,omitempty"`
NumThread int `json:"num_thread,omitempty"`
}
type TriState int
// EmbedRequest is the request passed to [Client.Embed].
type EmbedRequest struct {
// Model is the model name.
Model string `json:"model"`
const (
TriStateUndefined TriState = -1
TriStateFalse TriState = 0
TriStateTrue TriState = 1
)
// Input is the input to embed.
Input any `json:"input"`
func (b *TriState) UnmarshalJSON(data []byte) error {
var v bool
if err := json.Unmarshal(data, &v); err != nil {
return err
}
if v {
*b = TriStateTrue
}
*b = TriStateFalse
return nil
// KeepAlive controls how long the model will stay loaded in memory following
// this request.
KeepAlive *Duration `json:"keep_alive,omitempty"`
Truncate *bool `json:"truncate,omitempty"`
// Options lists model-specific options.
Options map[string]interface{} `json:"options"`
}
func (b *TriState) MarshalJSON() ([]byte, error) {
if *b == TriStateUndefined {
return nil, nil
}
var v bool
if *b == TriStateTrue {
v = true
}
return json.Marshal(v)
// EmbedResponse is the response from [Client.Embed].
type EmbedResponse struct {
Model string `json:"model"`
Embeddings [][]float32 `json:"embeddings"`
}
// EmbeddingRequest is the request passed to [Client.Embeddings].
@@ -250,8 +309,10 @@ type DeleteRequest struct {
// ShowRequest is the request passed to [Client.Show].
type ShowRequest struct {
Model string `json:"model"`
System string `json:"system"`
Model string `json:"model"`
System string `json:"system"`
// Template is deprecated
Template string `json:"template"`
Verbose bool `json:"verbose"`
@@ -345,6 +406,13 @@ type ProcessModelResponse struct {
SizeVRAM int64 `json:"size_vram"`
}
type RetrieveModelResponse struct {
Id string `json:"id"`
Object string `json:"object"`
Created int64 `json:"created"`
OwnedBy string `json:"owned_by"`
}
type TokenResponse struct {
Token string `json:"token"`
}
@@ -437,19 +505,6 @@ func (opts *Options) FromMap(m map[string]interface{}) error {
continue
}
if reflect.PointerTo(field.Type()) == reflect.TypeOf((*TriState)(nil)) {
val, ok := val.(bool)
if !ok {
return fmt.Errorf("option %q must be of type boolean", key)
}
if val {
field.SetInt(int64(TriStateTrue))
} else {
field.SetInt(int64(TriStateFalse))
}
continue
}
switch field.Kind() {
case reflect.Int:
switch t := val.(type) {
@@ -496,6 +551,17 @@ func (opts *Options) FromMap(m map[string]interface{}) error {
slice[i] = str
}
field.Set(reflect.ValueOf(slice))
case reflect.Pointer:
var b bool
if field.Type() == reflect.TypeOf(&b) {
val, ok := val.(bool)
if !ok {
return fmt.Errorf("option %q must be of type boolean", key)
}
field.Set(reflect.ValueOf(&val))
} else {
return fmt.Errorf("unknown type loading config params: %v %v", field.Kind(), field.Type())
}
default:
return fmt.Errorf("unknown type loading config params: %v", field.Kind())
}
@@ -538,7 +604,7 @@ func DefaultOptions() Options {
LowVRAM: false,
F16KV: true,
UseMLock: false,
UseMMap: TriStateUndefined,
UseMMap: nil,
UseNUMA: false,
},
}
@@ -608,19 +674,6 @@ func FormatParams(params map[string][]string) (map[string]interface{}, error) {
} else {
field := valueOpts.FieldByName(opt.Name)
if field.IsValid() && field.CanSet() {
if reflect.PointerTo(field.Type()) == reflect.TypeOf((*TriState)(nil)) {
boolVal, err := strconv.ParseBool(vals[0])
if err != nil {
return nil, fmt.Errorf("invalid bool value %s", vals)
}
if boolVal {
out[key] = TriStateTrue
} else {
out[key] = TriStateFalse
}
continue
}
switch field.Kind() {
case reflect.Float32:
floatVal, err := strconv.ParseFloat(vals[0], 32)
@@ -648,6 +701,17 @@ func FormatParams(params map[string][]string) (map[string]interface{}, error) {
case reflect.Slice:
// TODO: only string slices are supported right now
out[key] = vals
case reflect.Pointer:
var b bool
if field.Type() == reflect.TypeOf(&b) {
boolVal, err := strconv.ParseBool(vals[0])
if err != nil {
return nil, fmt.Errorf("invalid bool value %s", vals)
}
out[key] = &boolVal
} else {
return nil, fmt.Errorf("unknown type %s for %s", field.Kind(), key)
}
default:
return nil, fmt.Errorf("unknown type %s for %s", field.Kind(), key)
}

View File

@@ -108,25 +108,27 @@ func TestDurationMarshalUnmarshal(t *testing.T) {
}
func TestUseMmapParsingFromJSON(t *testing.T) {
tr := true
fa := false
tests := []struct {
name string
req string
exp TriState
exp *bool
}{
{
name: "Undefined",
req: `{ }`,
exp: TriStateUndefined,
exp: nil,
},
{
name: "True",
req: `{ "use_mmap": true }`,
exp: TriStateTrue,
exp: &tr,
},
{
name: "False",
req: `{ "use_mmap": false }`,
exp: TriStateFalse,
exp: &fa,
},
}
@@ -144,50 +146,52 @@ func TestUseMmapParsingFromJSON(t *testing.T) {
}
func TestUseMmapFormatParams(t *testing.T) {
tr := true
fa := false
tests := []struct {
name string
req map[string][]string
exp TriState
exp *bool
err error
}{
{
name: "True",
req: map[string][]string{
"use_mmap": []string{"true"},
"use_mmap": {"true"},
},
exp: TriStateTrue,
exp: &tr,
err: nil,
},
{
name: "False",
req: map[string][]string{
"use_mmap": []string{"false"},
"use_mmap": {"false"},
},
exp: TriStateFalse,
exp: &fa,
err: nil,
},
{
name: "Numeric True",
req: map[string][]string{
"use_mmap": []string{"1"},
"use_mmap": {"1"},
},
exp: TriStateTrue,
exp: &tr,
err: nil,
},
{
name: "Numeric False",
req: map[string][]string{
"use_mmap": []string{"0"},
"use_mmap": {"0"},
},
exp: TriStateFalse,
exp: &fa,
err: nil,
},
{
name: "invalid string",
req: map[string][]string{
"use_mmap": []string{"foo"},
"use_mmap": {"foo"},
},
exp: TriStateUndefined,
exp: nil,
err: fmt.Errorf("invalid bool value [foo]"),
},
}
@@ -195,12 +199,35 @@ func TestUseMmapFormatParams(t *testing.T) {
for _, test := range tests {
t.Run(test.name, func(t *testing.T) {
resp, err := FormatParams(test.req)
require.Equal(t, err, test.err)
require.Equal(t, test.err, err)
respVal, ok := resp["use_mmap"]
if test.exp != TriStateUndefined {
if test.exp != nil {
assert.True(t, ok, "resp: %v", resp)
assert.Equal(t, test.exp, respVal)
assert.Equal(t, *test.exp, *respVal.(*bool))
}
})
}
}
func TestMessage_UnmarshalJSON(t *testing.T) {
tests := []struct {
input string
expected string
}{
{`{"role": "USER", "content": "Hello!"}`, "user"},
{`{"role": "System", "content": "Initialization complete."}`, "system"},
{`{"role": "assistant", "content": "How can I help you?"}`, "assistant"},
{`{"role": "TOOl", "content": "Access granted."}`, "tool"},
}
for _, test := range tests {
var msg Message
if err := json.Unmarshal([]byte(test.input), &msg); err != nil {
t.Errorf("Unexpected error: %v", err)
}
if msg.Role != test.expected {
t.Errorf("role not lowercased: got %v, expected %v", msg.Role, test.expected)
}
}
}

View File

@@ -127,6 +127,10 @@ Type: filesandordirs; Name: "{%USERPROFILE}\.ollama\models"
Type: filesandordirs; Name: "{%USERPROFILE}\.ollama\history"
; NOTE: if the user has a custom OLLAMA_MODELS it will be preserved
[InstallDelete]
Type: filesandordirs; Name: "{%TEMP}\ollama*"
Type: filesandordirs; Name: "{%LOCALAPPDATA}\Programs\Ollama"
[Messages]
WizardReady=Ollama Windows Preview
ReadyLabel1=%nLet's get you up and running with your own large language models.

View File

@@ -624,13 +624,13 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
return errors.New("only one of '--license', '--modelfile', '--parameters', '--system', or '--template' can be specified")
}
if flagsSet == 1 {
req := api.ShowRequest{Name: args[0]}
resp, err := client.Show(cmd.Context(), &req)
if err != nil {
return err
}
req := api.ShowRequest{Name: args[0]}
resp, err := client.Show(cmd.Context(), &req)
if err != nil {
return err
}
if flagsSet == 1 {
switch showType {
case "license":
fmt.Println(resp.License)
@@ -647,12 +647,12 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
return nil
}
req := api.ShowRequest{Name: args[0]}
resp, err := client.Show(cmd.Context(), &req)
if err != nil {
return err
}
showInfo(resp)
return nil
}
func showInfo(resp *api.ShowResponse) {
arch := resp.ModelInfo["general.architecture"].(string)
modelData := [][]string{
@@ -672,11 +672,17 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
projectorData := [][]string{
{"arch", "clip"},
{"parameters", format.HumanNumber(uint64(resp.ProjectorInfo["general.parameter_count"].(float64)))},
{"projector type", resp.ProjectorInfo["clip.projector_type"].(string)},
{"embedding length", fmt.Sprintf("%v", resp.ProjectorInfo["clip.vision.embedding_length"].(float64))},
{"projection dimensionality", fmt.Sprintf("%v", resp.ProjectorInfo["clip.vision.projection_dim"].(float64))},
}
if projectorType, ok := resp.ProjectorInfo["clip.projector_type"]; ok {
projectorData = append(projectorData, []string{"projector type", projectorType.(string)})
}
projectorData = append(projectorData,
[]string{"embedding length", fmt.Sprintf("%v", resp.ProjectorInfo["clip.vision.embedding_length"].(float64))},
[]string{"projection dimensionality", fmt.Sprintf("%v", resp.ProjectorInfo["clip.vision.projection_dim"].(float64))},
)
mainTableData = append(mainTableData,
[]string{"Projector"},
[]string{renderSubTable(projectorData, false)},
@@ -705,8 +711,6 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
}
table.Render()
return nil
}
func renderSubTable(data [][]string, file bool) string {
@@ -839,7 +843,6 @@ type runOptions struct {
WordWrap bool
Format string
System string
Template string
Images []api.ImageData
Options map[string]interface{}
MultiModal bool
@@ -1033,7 +1036,6 @@ func generate(cmd *cobra.Command, opts runOptions) error {
Images: opts.Images,
Format: opts.Format,
System: opts.System,
Template: opts.Template,
Options: opts.Options,
KeepAlive: opts.KeepAlive,
}

View File

@@ -27,7 +27,6 @@ const (
MultilineNone MultilineState = iota
MultilinePrompt
MultilineSystem
MultilineTemplate
)
func loadModel(cmd *cobra.Command, opts *runOptions) error {
@@ -94,7 +93,6 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
fmt.Fprintln(os.Stderr, "Available Commands:")
fmt.Fprintln(os.Stderr, " /set parameter ... Set a parameter")
fmt.Fprintln(os.Stderr, " /set system <string> Set system message")
fmt.Fprintln(os.Stderr, " /set template <string> Set prompt template")
fmt.Fprintln(os.Stderr, " /set history Enable history")
fmt.Fprintln(os.Stderr, " /set nohistory Disable history")
fmt.Fprintln(os.Stderr, " /set wordwrap Enable wordwrap")
@@ -204,10 +202,6 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
opts.Messages = append(opts.Messages, api.Message{Role: "system", Content: opts.System})
fmt.Println("Set system message.")
sb.Reset()
case MultilineTemplate:
opts.Template = sb.String()
fmt.Println("Set prompt template.")
sb.Reset()
}
multiline = MultilineNone
@@ -326,17 +320,13 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
}
fmt.Printf("Set parameter '%s' to '%s'\n", args[2], strings.Join(params, ", "))
opts.Options[args[2]] = fp[args[2]]
case "system", "template":
case "system":
if len(args) < 3 {
usageSet()
continue
}
if args[1] == "system" {
multiline = MultilineSystem
} else if args[1] == "template" {
multiline = MultilineTemplate
}
multiline = MultilineSystem
line := strings.Join(args[2:], " ")
line, ok := strings.CutPrefix(line, `"""`)
@@ -356,23 +346,17 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
continue
}
if args[1] == "system" {
opts.System = sb.String() // for display in modelfile
newMessage := api.Message{Role: "system", Content: sb.String()}
// Check if the slice is not empty and the last message is from 'system'
if len(opts.Messages) > 0 && opts.Messages[len(opts.Messages)-1].Role == "system" {
// Replace the last message
opts.Messages[len(opts.Messages)-1] = newMessage
} else {
opts.Messages = append(opts.Messages, newMessage)
}
fmt.Println("Set system message.")
sb.Reset()
} else if args[1] == "template" {
opts.Template = sb.String()
fmt.Println("Set prompt template.")
sb.Reset()
opts.System = sb.String() // for display in modelfile
newMessage := api.Message{Role: "system", Content: sb.String()}
// Check if the slice is not empty and the last message is from 'system'
if len(opts.Messages) > 0 && opts.Messages[len(opts.Messages)-1].Role == "system" {
// Replace the last message
opts.Messages[len(opts.Messages)-1] = newMessage
} else {
opts.Messages = append(opts.Messages, newMessage)
}
fmt.Println("Set system message.")
sb.Reset()
sb.Reset()
continue
@@ -393,7 +377,6 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
req := &api.ShowRequest{
Name: opts.Model,
System: opts.System,
Template: opts.Template,
Options: opts.Options,
}
resp, err := client.Show(cmd.Context(), req)
@@ -404,15 +387,7 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
switch args[1] {
case "info":
fmt.Println("Model details:")
if len(resp.Details.Families) > 0 {
fmt.Printf("Family %s\n", strings.Join(resp.Details.Families, ", "))
} else if resp.Details.Family != "" {
fmt.Printf("Family %s\n", resp.Details.Family)
}
fmt.Printf("Parameter Size %s\n", resp.Details.ParameterSize)
fmt.Printf("Quantization Level %s\n", resp.Details.QuantizationLevel)
fmt.Println("")
showInfo(resp)
case "license":
if resp.License == "" {
fmt.Println("No license was specified for this model.")
@@ -445,12 +420,9 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
fmt.Println("No system message was specified for this model.")
}
case "template":
switch {
case opts.Template != "":
fmt.Println(opts.Template + "\n")
case resp.Template != "":
if resp.Template != "" {
fmt.Println(resp.Template)
default:
} else {
fmt.Println("No prompt template was specified for this model.")
}
default:
@@ -544,10 +516,6 @@ func buildModelfile(opts runOptions) string {
fmt.Fprintf(&mf, "SYSTEM \"\"\"%s\"\"\"\n", opts.System)
}
if opts.Template != "" {
fmt.Fprintf(&mf, "TEMPLATE \"\"\"%s\"\"\"\n", opts.Template)
}
keys := make([]string, 0)
for k := range opts.Options {
keys = append(keys, k)

View File

@@ -59,7 +59,6 @@ func TestModelfileBuilder(t *testing.T) {
opts := runOptions{
Model: "hork",
System: "You are part horse and part shark, but all hork. Do horklike things",
Template: "This is a template.",
Messages: []api.Message{
{Role: "user", Content: "Hey there hork!"},
{Role: "assistant", Content: "Yes it is true, I am half horse, half shark."},
@@ -75,7 +74,6 @@ func TestModelfileBuilder(t *testing.T) {
mf := buildModelfile(opts)
expectedModelfile := `FROM {{.Model}}
SYSTEM """{{.System}}"""
TEMPLATE """{{.Template}}"""
PARAMETER penalize_newline false
PARAMETER seed 42
PARAMETER stop [hi there]
@@ -97,7 +95,6 @@ MESSAGE assistant """Yes it is true, I am half horse, half shark."""
mf = buildModelfile(opts)
expectedModelfile = `FROM {{.ParentModel}}
SYSTEM """{{.System}}"""
TEMPLATE """{{.Template}}"""
PARAMETER penalize_newline false
PARAMETER seed 42
PARAMETER stop [hi there]

View File

@@ -26,7 +26,7 @@ All durations are returned in nanoseconds.
### Streaming responses
Certain endpoints stream responses as JSON objects and can optional return non-streamed responses.
Certain endpoints stream responses as JSON objects. Streaming can be disabled by providing `{"stream": false}` for these endpoints.
## Generate a completion

View File

@@ -104,7 +104,7 @@ like to use. For example, to compile an optimized binary for an Intel i9-9880H,
you might use:
```
OLLAMA_CUSTOM_CPU_DEFS="-DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_F16C=on -DLLAMA_FMA=on" go generate ./...
OLLAMA_CUSTOM_CPU_DEFS="-DGGML_AVX=on -DGGML_AVX2=on -DGGML_F16C=on -DGGML_FMA=on" go generate ./...
go build .
```

View File

@@ -257,3 +257,19 @@ If you wish to override the `OLLAMA_KEEP_ALIVE` setting, use the `keep_alive` AP
## How do I manage the maximum number of requests the Ollama server can queue?
If too many requests are sent to the server, it will respond with a 503 error indicating the server is overloaded. You can adjust how many requests may be queue by setting `OLLAMA_MAX_QUEUE`.
## How does Ollama handle concurrent requests?
Ollama supports two levels of concurrent processing. If your system has sufficient available memory (system memory when using CPU inference, or VRAM for GPU inference) then multiple models can be loaded at the same time. For a given model, if there is sufficient available memory when the model is loaded, it is configured to allow parallel request processing.
If there is insufficient available memory to load a new model request while one or more models are already loaded, all new requests will be queued until the new model can be loaded. As prior models become idle, one or more will be unloaded to make room for the new model. Queued requests will be processed in order. When using GPU inference new models must be able to completely fit in VRAM to allow concurrent model loads.
Parallel request processing for a given model results in increasing the context size by the number of parallel requests. For example, a 2K context with 4 parallel requests will result in an 8K context and additional memory allocation.
The following server settings may be used to adjust how Ollama handles concurrent requests on most platforms:
- `OLLAMA_MAX_LOADED_MODELS` - The maximum number of models that can be loaded concurrently provided they fit in available memory. The default is 3 * the number of GPUs or 3 for CPU inference.
- `OLLAMA_NUM_PARALLEL` - The maximum number of parallel requests each model will process at the same time. The default will auto-select either 4 or 1 based on available memory.
- `OLLAMA_MAX_QUEUE` - The maximum number of requests Ollama will queue when busy before rejecting additional requests. The default is 512
Note: Windows with Radeon GPUs currently default to 1 model maximum due to limitations in ROCm v5.7 for available VRAM reporting. Once ROCm v6.2 is available, Windows Radeon will follow the defaults above. You may enable concurrent model loads on Radeon on Windows, but ensure you don't load more models than will fit into your GPUs VRAM.

View File

@@ -18,7 +18,7 @@ Check your compute compatibility to see if your card is supported:
| | Quadro | `RTX 8000` `RTX 6000` `RTX 5000` `RTX 4000` |
| 7.0 | NVIDIA | `TITAN V` `V100` `Quadro GV100` |
| 6.1 | NVIDIA TITAN | `TITAN Xp` `TITAN X` |
| | GeForce GTX | `GTX 1080 Ti` `GTX 1080` `GTX 1070 Ti` `GTX 1070` `GTX 1060` `GTX 1050` |
| | GeForce GTX | `GTX 1080 Ti` `GTX 1080` `GTX 1070 Ti` `GTX 1070` `GTX 1060` `GTX 1050 Ti` `GTX 1050` |
| | Quadro | `P6000` `P5200` `P4200` `P3200` `P5000` `P4000` `P3000` `P2200` `P2000` `P1000` `P620` `P600` `P500` `P520` |
| | Tesla | `P40` `P4` |
| 6.0 | NVIDIA | `Tesla P100` `Quadro GP100` |
@@ -46,13 +46,24 @@ sudo modprobe nvidia_uvm`
## AMD Radeon
Ollama supports the following AMD GPUs:
### Linux Support
| Family | Cards and accelerators |
| -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------- |
| AMD Radeon RX | `7900 XTX` `7900 XT` `7900 GRE` `7800 XT` `7700 XT` `7600 XT` `7600` `6950 XT` `6900 XTX` `6900XT` `6800 XT` `6800` `Vega 64` `Vega 56` |
| AMD Radeon PRO | `W7900` `W7800` `W7700` `W7600` `W7500` `W6900X` `W6800X Duo` `W6800X` `W6800` `V620` `V420` `V340` `V320` `Vega II Duo` `Vega II` `VII` `SSG` |
| AMD Instinct | `MI300X` `MI300A` `MI300` `MI250X` `MI250` `MI210` `MI200` `MI100` `MI60` `MI50` |
### Overrides
### Windows Support
With ROCm v6.1, the following GPUs are supported on Windows.
| Family | Cards and accelerators |
| -------------- | ---------------------------------------------------------------------------------------------------------------------------------------------- |
| AMD Radeon RX | `7900 XTX` `7900 XT` `7900 GRE` `7800 XT` `7700 XT` `7600 XT` `7600` `6950 XT` `6900 XTX` `6900XT` `6800 XT` `6800` |
| AMD Radeon PRO | `W7900` `W7800` `W7700` `W7600` `W7500` `W6900X` `W6800X Duo` `W6800X` `W6800` `V620` |
### Overrides on Linux
Ollama leverages the AMD ROCm library, which does not support all AMD GPUs. In
some cases you can force the system to try to use a similar LLVM target that is
close. For example The Radeon RX 5400 is `gfx1034` (also known as 10.3.4)
@@ -63,7 +74,7 @@ would set `HSA_OVERRIDE_GFX_VERSION="10.3.0"` as an environment variable for the
server. If you have an unsupported AMD GPU you can experiment using the list of
supported types below.
At this time, the known supported GPU types are the following LLVM Targets.
At this time, the known supported GPU types on linux are the following LLVM Targets.
This table shows some example GPUs that map to these LLVM targets:
| **LLVM Target** | **An Example GPU** |
|-----------------|---------------------|

View File

@@ -65,6 +65,7 @@ curl http://localhost:11434/v1/chat/completions \
}
]
}'
```
## Endpoints
@@ -102,11 +103,6 @@ curl http://localhost:11434/v1/chat/completions \
- [ ] `user`
- [ ] `n`
#### Notes
- `finish_reason` will always be `stop`
- `usage.prompt_tokens` will be 0 for completions where prompt evaluation is cached
## Models
Before using a model, pull it locally `ollama pull`:

View File

@@ -70,14 +70,18 @@ curl -fsSL https://ollama.com/install.sh | OLLAMA_VERSION="0.1.29" sh
If your system is configured with the "noexec" flag where Ollama stores its temporary executable files, you can specify an alternate location by setting OLLAMA_TMPDIR to a location writable by the user ollama runs as. For example OLLAMA_TMPDIR=/usr/share/ollama/
## Container fails to run on NVIDIA GPU
## NVIDIA GPU Discovery
Make sure you've set up the container runtime first as described in [docker.md](./docker.md)
When Ollama starts up, it takes inventory of the GPUs present in the system to determine compatibility and how much VRAM is available. Sometimes this discovery can fail to find your GPUs. In general, running the latest driver will yield the best results.
Sometimes the container runtime can have difficulties initializing the GPU. When you check the server logs, this can show up as various error codes, such as "3" (not initialized), "46" (device unavailable), "100" (no device), "999" (unknown), or others. The following troubleshooting techniques may help resolve the problem
### Linux NVIDIA Troubleshooting
- Is the container runtime working? Try `docker run --gpus all ubuntu nvidia-smi` - if this doesn't work, Ollama wont be able to see your NVIDIA GPU.
- Is the uvm driver not loaded? `sudo nvidia-modprobe -u`
If you are using a container to run Ollama, make sure you've set up the container runtime first as described in [docker.md](./docker.md)
Sometimes the Ollama can have difficulties initializing the GPU. When you check the server logs, this can show up as various error codes, such as "3" (not initialized), "46" (device unavailable), "100" (no device), "999" (unknown), or others. The following troubleshooting techniques may help resolve the problem
- If you are using a container, is the container runtime working? Try `docker run --gpus all ubuntu nvidia-smi` - if this doesn't work, Ollama wont be able to see your NVIDIA GPU.
- Is the uvm driver loaded? `sudo nvidia-modprobe -u`
- Try reloading the nvidia_uvm driver - `sudo rmmod nvidia_uvm` then `sudo modprobe nvidia_uvm`
- Try rebooting
- Make sure you're running the latest nvidia drivers
@@ -85,3 +89,8 @@ Sometimes the container runtime can have difficulties initializing the GPU. When
If none of those resolve the problem, gather additional information and file an issue:
- Set `CUDA_ERROR_LEVEL=50` and try again to get more diagnostic logs
- Check dmesg for any errors `sudo dmesg | grep -i nvrm` and `sudo dmesg | grep -i nvidia`
## Windows Terminal Errors
Older versions of Windows 10 (e.g., 21H1) are known to have a bug where the standard terminal program does not display control characters correctly. This can result in a long string of strings like `←[?25h←[?25l` being displayed, sometimes erroring with `The parameter is incorrect` To resolve this problem, please update to Win 10 22H1 or newer.

View File

@@ -19,7 +19,7 @@ Logs will often be helpful in diagnosing the problem (see
## System Requirements
* Windows 10 or newer, Home or Pro
* Windows 10 22H2 or newer, Home or Pro
* NVIDIA 452.39 or newer Drivers if you have an NVIDIA card
* AMD Radeon Driver https://www.amd.com/en/support if you have a Radeon card

View File

@@ -4,12 +4,14 @@ import (
"errors"
"fmt"
"log/slog"
"math"
"net"
"os"
"path/filepath"
"runtime"
"strconv"
"strings"
"time"
)
type OllamaHost struct {
@@ -34,17 +36,17 @@ var (
// Set via OLLAMA_HOST in the environment
Host *OllamaHost
// Set via OLLAMA_KEEP_ALIVE in the environment
KeepAlive string
KeepAlive time.Duration
// Set via OLLAMA_LLM_LIBRARY in the environment
LLMLibrary string
// Set via OLLAMA_MAX_LOADED_MODELS in the environment
MaxRunners int
// Set via OLLAMA_MAX_QUEUE in the environment
MaxQueuedRequests int
// Set via OLLAMA_MODELS in the environment
ModelsDir string
// Set via OLLAMA_MAX_VRAM in the environment
MaxVRAM uint64
// Set via OLLAMA_MODELS in the environment
ModelsDir string
// Set via OLLAMA_NOHISTORY in the environment
NoHistory bool
// Set via OLLAMA_NOPRUNE in the environment
@@ -85,13 +87,13 @@ func AsMap() map[string]EnvVar {
"OLLAMA_HOST": {"OLLAMA_HOST", Host, "IP Address for the ollama server (default 127.0.0.1:11434)"},
"OLLAMA_KEEP_ALIVE": {"OLLAMA_KEEP_ALIVE", KeepAlive, "The duration that models stay loaded in memory (default \"5m\")"},
"OLLAMA_LLM_LIBRARY": {"OLLAMA_LLM_LIBRARY", LLMLibrary, "Set LLM library to bypass autodetection"},
"OLLAMA_MAX_LOADED_MODELS": {"OLLAMA_MAX_LOADED_MODELS", MaxRunners, "Maximum number of loaded models (default 1)"},
"OLLAMA_MAX_LOADED_MODELS": {"OLLAMA_MAX_LOADED_MODELS", MaxRunners, "Maximum number of loaded models per GPU"},
"OLLAMA_MAX_QUEUE": {"OLLAMA_MAX_QUEUE", MaxQueuedRequests, "Maximum number of queued requests"},
"OLLAMA_MAX_VRAM": {"OLLAMA_MAX_VRAM", MaxVRAM, "Maximum VRAM"},
"OLLAMA_MODELS": {"OLLAMA_MODELS", ModelsDir, "The path to the models directory"},
"OLLAMA_NOHISTORY": {"OLLAMA_NOHISTORY", NoHistory, "Do not preserve readline history"},
"OLLAMA_NOPRUNE": {"OLLAMA_NOPRUNE", NoPrune, "Do not prune model blobs on startup"},
"OLLAMA_NUM_PARALLEL": {"OLLAMA_NUM_PARALLEL", NumParallel, "Maximum number of parallel requests (default 1)"},
"OLLAMA_NUM_PARALLEL": {"OLLAMA_NUM_PARALLEL", NumParallel, "Maximum number of parallel requests"},
"OLLAMA_ORIGINS": {"OLLAMA_ORIGINS", AllowOrigins, "A comma separated list of allowed origins"},
"OLLAMA_RUNNERS_DIR": {"OLLAMA_RUNNERS_DIR", RunnersDir, "Location for runners"},
"OLLAMA_SCHED_SPREAD": {"OLLAMA_SCHED_SPREAD", SchedSpread, "Always schedule model across all GPUs"},
@@ -129,9 +131,10 @@ func clean(key string) string {
func init() {
// default values
NumParallel = 1
MaxRunners = 1
NumParallel = 0 // Autoselect
MaxRunners = 0 // Autoselect
MaxQueuedRequests = 512
KeepAlive = 5 * time.Minute
LoadConfig()
}
@@ -205,8 +208,8 @@ func LoadConfig() {
if onp := clean("OLLAMA_NUM_PARALLEL"); onp != "" {
val, err := strconv.Atoi(onp)
if err != nil || val <= 0 {
slog.Error("invalid setting must be greater than zero", "OLLAMA_NUM_PARALLEL", onp, "error", err)
if err != nil {
slog.Error("invalid setting, ignoring", "OLLAMA_NUM_PARALLEL", onp, "error", err)
} else {
NumParallel = val
}
@@ -251,7 +254,7 @@ func LoadConfig() {
if maxRunners != "" {
m, err := strconv.Atoi(maxRunners)
if err != nil {
slog.Error("invalid setting", "OLLAMA_MAX_LOADED_MODELS", maxRunners, "error", err)
slog.Error("invalid setting, ignoring", "OLLAMA_MAX_LOADED_MODELS", maxRunners, "error", err)
} else {
MaxRunners = m
}
@@ -260,13 +263,16 @@ func LoadConfig() {
if onp := os.Getenv("OLLAMA_MAX_QUEUE"); onp != "" {
p, err := strconv.Atoi(onp)
if err != nil || p <= 0 {
slog.Error("invalid setting", "OLLAMA_MAX_QUEUE", onp, "error", err)
slog.Error("invalid setting, ignoring", "OLLAMA_MAX_QUEUE", onp, "error", err)
} else {
MaxQueuedRequests = p
}
}
KeepAlive = clean("OLLAMA_KEEP_ALIVE")
ka := clean("OLLAMA_KEEP_ALIVE")
if ka != "" {
loadKeepAlive(ka)
}
var err error
ModelsDir, err = getModelsDir()
@@ -344,3 +350,24 @@ func getOllamaHost() (*OllamaHost, error) {
Port: port,
}, nil
}
func loadKeepAlive(ka string) {
v, err := strconv.Atoi(ka)
if err != nil {
d, err := time.ParseDuration(ka)
if err == nil {
if d < 0 {
KeepAlive = time.Duration(math.MaxInt64)
} else {
KeepAlive = d
}
}
} else {
d := time.Duration(v) * time.Second
if d < 0 {
KeepAlive = time.Duration(math.MaxInt64)
} else {
KeepAlive = d
}
}
}

View File

@@ -2,8 +2,10 @@ package envconfig
import (
"fmt"
"math"
"net"
"testing"
"time"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
@@ -23,6 +25,21 @@ func TestConfig(t *testing.T) {
t.Setenv("OLLAMA_FLASH_ATTENTION", "1")
LoadConfig()
require.True(t, FlashAttention)
t.Setenv("OLLAMA_KEEP_ALIVE", "")
LoadConfig()
require.Equal(t, 5*time.Minute, KeepAlive)
t.Setenv("OLLAMA_KEEP_ALIVE", "3")
LoadConfig()
require.Equal(t, 3*time.Second, KeepAlive)
t.Setenv("OLLAMA_KEEP_ALIVE", "1h")
LoadConfig()
require.Equal(t, 1*time.Hour, KeepAlive)
t.Setenv("OLLAMA_KEEP_ALIVE", "-1s")
LoadConfig()
require.Equal(t, time.Duration(math.MaxInt64), KeepAlive)
t.Setenv("OLLAMA_KEEP_ALIVE", "-1")
LoadConfig()
require.Equal(t, time.Duration(math.MaxInt64), KeepAlive)
}
func TestClientFromEnvironment(t *testing.T) {

3
go.mod
View File

@@ -18,6 +18,7 @@ require (
require (
github.com/agnivade/levenshtein v1.1.1
github.com/d4l3k/go-bfloat16 v0.0.0-20211005043715-690c3bdd05f1
github.com/google/go-cmp v0.6.0
github.com/mattn/go-runewidth v0.0.14
github.com/nlpodyssey/gopickle v0.3.0
github.com/pdevine/tensor v0.0.0-20240510204454-f88f4562727c
@@ -71,7 +72,7 @@ require (
golang.org/x/net v0.25.0 // indirect
golang.org/x/sys v0.20.0
golang.org/x/term v0.20.0
golang.org/x/text v0.15.0 // indirect
golang.org/x/text v0.15.0
google.golang.org/protobuf v1.34.1
gopkg.in/yaml.v3 v3.0.1 // indirect
)

View File

@@ -49,9 +49,17 @@ func rocmGetVisibleDevicesEnv(gpuInfo []GpuInfo) (string, string) {
}
func commonAMDValidateLibDir() (string, error) {
// We try to favor system paths first, so that we can wire up the subprocess to use
// the system version. Only use our bundled version if the system version doesn't work
// This gives users a more recovery options if versions have subtle problems at runtime
// Favor our bundled version
// Installer payload location if we're running the installed binary
exe, err := os.Executable()
if err == nil {
rocmTargetDir := filepath.Join(filepath.Dir(exe), "rocm")
if rocmLibUsable(rocmTargetDir) {
slog.Debug("detected ROCM next to ollama executable " + rocmTargetDir)
return rocmTargetDir, nil
}
}
// Prefer explicit HIP env var
hipPath := os.Getenv("HIP_PATH")
@@ -87,14 +95,5 @@ func commonAMDValidateLibDir() (string, error) {
}
}
// Installer payload location if we're running the installed binary
exe, err := os.Executable()
if err == nil {
rocmTargetDir := filepath.Join(filepath.Dir(exe), "rocm")
if rocmLibUsable(rocmTargetDir) {
slog.Debug("detected ROCM next to ollama executable " + rocmTargetDir)
return rocmTargetDir, nil
}
}
return "", fmt.Errorf("no suitable rocm found, falling back to CPU")
}

View File

@@ -33,9 +33,10 @@ type HipLib struct {
}
func NewHipLib() (*HipLib, error) {
h, err := windows.LoadLibrary("amdhip64.dll")
// At runtime we depend on v6, so discover GPUs with the same library for a consistent set of GPUs
h, err := windows.LoadLibrary("amdhip64_6.dll")
if err != nil {
return nil, fmt.Errorf("unable to load amdhip64.dll: %w", err)
return nil, fmt.Errorf("unable to load amdhip64_6.dll, please make sure to upgrade to the latest amd driver: %w", err)
}
hl := &HipLib{}
hl.dll = h
@@ -84,9 +85,8 @@ func (hl *HipLib) AMDDriverVersion() (driverMajor, driverMinor int, err error) {
}
slog.Debug("hipDriverGetVersion", "version", version)
// TODO - this isn't actually right, but the docs claim hipDriverGetVersion isn't accurate anyway...
driverMajor = version / 1000
driverMinor = (version - (driverMajor * 1000)) / 10
driverMajor = version / 10000000
driverMinor = (version - (driverMajor * 10000000)) / 100000
return driverMajor, driverMinor, nil
}

View File

@@ -22,8 +22,8 @@ const (
var (
// Used to validate if the given ROCm lib is usable
ROCmLibGlobs = []string{"hipblas.dll", "rocblas"} // TODO - probably include more coverage of files here...
RocmStandardLocations = []string{"C:\\Program Files\\AMD\\ROCm\\5.7\\bin"} // TODO glob?
ROCmLibGlobs = []string{"hipblas.dll", "rocblas"} // This is not sufficient to discern v5 vs v6
RocmStandardLocations = []string{"C:\\Program Files\\AMD\\ROCm\\6.1\\bin"} // TODO glob?
)
func AMDGetGPUInfo() []RocmGPUInfo {
@@ -35,12 +35,11 @@ func AMDGetGPUInfo() []RocmGPUInfo {
}
defer hl.Release()
// TODO - this reports incorrect version information, so omitting for now
// driverMajor, driverMinor, err := hl.AMDDriverVersion()
// if err != nil {
// // For now this is benign, but we may eventually need to fail compatibility checks
// slog.Debug("error looking up amd driver version", "error", err)
// }
driverMajor, driverMinor, err := hl.AMDDriverVersion()
if err != nil {
// For now this is benign, but we may eventually need to fail compatibility checks
slog.Debug("error looking up amd driver version", "error", err)
}
// Note: the HIP library automatically handles subsetting to any HIP_VISIBLE_DEVICES the user specified
count := hl.HipGetDeviceCount()
@@ -93,7 +92,8 @@ func AMDGetGPUInfo() []RocmGPUInfo {
continue
}
if gfxOverride == "" {
if !slices.Contains[[]string, string](supported, gfx) {
// Strip off Target Features when comparing
if !slices.Contains[[]string, string](supported, strings.Split(gfx, ":")[0]) {
slog.Warn("amdgpu is not supported", "gpu", i, "gpu_type", gfx, "library", libDir, "supported_types", supported)
// TODO - consider discrete markdown just for ROCM troubleshooting?
slog.Warn("See https://github.com/ollama/ollama/blob/main/docs/troubleshooting.md for HSA_OVERRIDE_GFX_VERSION usage")
@@ -115,8 +115,6 @@ func AMDGetGPUInfo() []RocmGPUInfo {
continue
}
// TODO revisit this once ROCm v6 is available on windows.
// v5.7 only reports VRAM used by this process, so it's completely wrong and unusable
slog.Debug("amdgpu memory", "gpu", i, "total", format.HumanBytes2(totalMemory))
slog.Debug("amdgpu memory", "gpu", i, "available", format.HumanBytes2(freeMemory))
gpuInfo := RocmGPUInfo{
@@ -126,15 +124,16 @@ func AMDGetGPUInfo() []RocmGPUInfo {
TotalMemory: totalMemory,
FreeMemory: freeMemory,
},
// Free memory reporting on Windows is not reliable until we bump to ROCm v6.2
UnreliableFreeMemory: true,
ID: strconv.Itoa(i), // TODO this is probably wrong if we specify visible devices
DependencyPath: libDir,
MinimumMemory: rocmMinimumMemory,
Name: name,
Compute: gfx,
// TODO - this information isn't accurate on windows, so don't report it until we find the right way to retrieve
// DriverMajor: driverMajor,
// DriverMinor: driverMinor,
DriverMajor: driverMajor,
DriverMinor: driverMinor,
},
index: i,
}

View File

@@ -202,7 +202,7 @@ func GetGPUInfo() GpuInfoList {
}()
if !bootstrapped {
slog.Debug("Detecting GPUs")
slog.Info("looking for compatible GPUs")
needRefresh = false
cpuCapability = GetCPUCapability()
var memInfo C.mem_info_t
@@ -274,6 +274,28 @@ func GetGPUInfo() GpuInfoList {
gpuInfo.DriverMajor = driverMajor
gpuInfo.DriverMinor = driverMinor
// query the management library as well so we can record any skew between the two
// which represents overhead on the GPU we must set aside on subsequent updates
if cHandles.nvml != nil {
C.nvml_get_free(*cHandles.nvml, C.int(gpuInfo.index), &memInfo.free, &memInfo.total, &memInfo.used)
if memInfo.err != nil {
slog.Warn("error looking up nvidia GPU memory", "error", C.GoString(memInfo.err))
C.free(unsafe.Pointer(memInfo.err))
} else {
if memInfo.free != 0 && uint64(memInfo.free) > gpuInfo.FreeMemory {
gpuInfo.OSOverhead = uint64(memInfo.free) - gpuInfo.FreeMemory
slog.Info("detected OS VRAM overhead",
"id", gpuInfo.ID,
"library", gpuInfo.Library,
"compute", gpuInfo.Compute,
"driver", fmt.Sprintf("%d.%d", gpuInfo.DriverMajor, gpuInfo.DriverMinor),
"name", gpuInfo.Name,
"overhead", format.HumanBytes2(gpuInfo.OSOverhead),
)
}
}
}
// TODO potentially sort on our own algorithm instead of what the underlying GPU library does...
cudaGPUs = append(cudaGPUs, gpuInfo)
}
@@ -320,6 +342,9 @@ func GetGPUInfo() GpuInfoList {
rocmGPUs = AMDGetGPUInfo()
bootstrapped = true
if len(cudaGPUs) == 0 && len(rocmGPUs) == 0 && len(oneapiGPUs) == 0 {
slog.Info("no compatible GPUs were discovered")
}
}
// For detected GPUs, load library if not loaded
@@ -335,14 +360,17 @@ func GetGPUInfo() GpuInfoList {
"before",
"total", format.HumanBytes2(cpus[0].TotalMemory),
"free", format.HumanBytes2(cpus[0].FreeMemory),
"free_swap", format.HumanBytes2(cpus[0].FreeSwap),
),
slog.Group(
"now",
"total", format.HumanBytes2(mem.TotalMemory),
"free", format.HumanBytes2(mem.FreeMemory),
"free_swap", format.HumanBytes2(mem.FreeSwap),
),
)
cpus[0].FreeMemory = mem.FreeMemory
cpus[0].FreeSwap = mem.FreeSwap
}
var memInfo C.mem_info_t
@@ -371,9 +399,14 @@ func GetGPUInfo() GpuInfoList {
slog.Warn("error looking up nvidia GPU memory")
continue
}
if cHandles.nvml != nil && gpu.OSOverhead > 0 {
// When using the management library update based on recorded overhead
memInfo.free -= C.uint64_t(gpu.OSOverhead)
}
slog.Debug("updating cuda memory data",
"gpu", gpu.ID,
"name", gpu.Name,
"overhead", format.HumanBytes2(gpu.OSOverhead),
slog.Group(
"before",
"total", format.HumanBytes2(gpu.TotalMemory),
@@ -514,7 +547,23 @@ func LoadNVCUDAMgmt(nvcudaLibPaths []string) (int, *C.nvcuda_handle_t, string) {
defer C.free(unsafe.Pointer(lib))
C.nvcuda_init(lib, &resp)
if resp.err != nil {
slog.Debug("Unable to load nvcuda", "library", libPath, "error", C.GoString(resp.err))
// Decide what log level based on the type of error message to help users understand why
msg := C.GoString(resp.err)
switch resp.cudaErr {
case C.CUDA_ERROR_INSUFFICIENT_DRIVER, C.CUDA_ERROR_SYSTEM_DRIVER_MISMATCH:
slog.Warn("version mismatch between driver and cuda driver library - reboot or upgrade may be required", "library", libPath, "error", msg)
case C.CUDA_ERROR_NO_DEVICE:
slog.Info("no nvidia devices detected", "library", libPath)
case C.CUDA_ERROR_UNKNOWN:
slog.Warn("unknown error initializing cuda driver library", "library", libPath, "error", msg)
slog.Warn("see https://github.com/ollama/ollama/blob/main/docs/troubleshooting.md for more information")
default:
if strings.Contains(msg, "wrong ELF class") {
slog.Debug("skipping 32bit library", "library", libPath)
} else {
slog.Info("unable to load cuda driver library", "library", libPath, "error", msg)
}
}
C.free(unsafe.Pointer(resp.err))
} else {
return int(resp.num_devices), &resp.ch, libPath

View File

@@ -56,7 +56,8 @@ func GetCPUInfo() GpuInfoList {
func GetCPUMem() (memInfo, error) {
return memInfo{
TotalMemory: uint64(C.getPhysicalMemory()),
FreeMemory: 0,
FreeMemory: uint64(C.getFreeMemory()),
// FreeSwap omitted as Darwin uses dynamic paging
}, nil
}

View File

@@ -2,3 +2,4 @@
#include <stdint.h>
uint64_t getRecommendedMaxVRAM();
uint64_t getPhysicalMemory();
uint64_t getFreeMemory();

View File

@@ -1,4 +1,5 @@
// go:build darwin
#import <Foundation/Foundation.h>
#import <mach/mach.h>
#include "gpu_info_darwin.h"
uint64_t getRecommendedMaxVRAM() {
@@ -8,6 +9,27 @@ uint64_t getRecommendedMaxVRAM() {
return result;
}
// getPhysicalMemory returns the total physical memory in bytes
uint64_t getPhysicalMemory() {
return [[NSProcessInfo processInfo] physicalMemory];
return [NSProcessInfo processInfo].physicalMemory;
}
// getFreeMemory returns the total free memory in bytes, including inactive
// memory that can be reclaimed by the system.
uint64_t getFreeMemory() {
mach_port_t host_port = mach_host_self();
mach_msg_type_number_t host_size = sizeof(vm_statistics64_data_t) / sizeof(integer_t);
vm_size_t pagesize;
vm_statistics64_data_t vm_stat;
host_page_size(host_port, &pagesize);
if (host_statistics64(host_port, HOST_VM_INFO64, (host_info64_t)&vm_stat, &host_size) != KERN_SUCCESS) {
return 0;
}
uint64_t free_memory = (uint64_t)vm_stat.free_count * pagesize;
free_memory += (uint64_t)vm_stat.speculative_count * pagesize;
free_memory += (uint64_t)vm_stat.inactive_count * pagesize;
return free_memory;
}

View File

@@ -7,6 +7,7 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
CUresult ret;
resp->err = NULL;
resp->num_devices = 0;
resp->cudaErr = CUDA_SUCCESS;
const int buflen = 256;
char buf[buflen + 1];
int i;
@@ -38,6 +39,7 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
nvcuda_lib_path, msg);
free(msg);
resp->err = strdup(buf);
resp->cudaErr = -1;
return;
}
@@ -52,6 +54,7 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
msg);
free(msg);
resp->err = strdup(buf);
resp->cudaErr = -1;
return;
}
}
@@ -61,12 +64,9 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
LOG(resp->ch.verbose, "cuInit err: %d\n", ret);
UNLOAD_LIBRARY(resp->ch.handle);
resp->ch.handle = NULL;
if (ret == CUDA_ERROR_INSUFFICIENT_DRIVER) {
resp->err = strdup("your nvidia driver is too old or missing. If you have a CUDA GPU please upgrade to run ollama");
return;
}
snprintf(buf, buflen, "nvcuda init failure: %d", ret);
snprintf(buf, buflen, "cuda driver library init failure: %d", ret);
resp->err = strdup(buf);
resp->cudaErr = ret;
return;
}
@@ -91,6 +91,7 @@ void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
resp->ch.handle = NULL;
snprintf(buf, buflen, "unable to get device count: %d", ret);
resp->err = strdup(buf);
resp->cudaErr = ret;
return;
}
}
@@ -106,13 +107,13 @@ void nvcuda_bootstrap(nvcuda_handle_t h, int i, mem_info_t *resp) {
CUuuid uuid = {0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0};
if (h.handle == NULL) {
resp->err = strdup("nvcuda handle isn't initialized");
resp->err = strdup("cuda driver library handle isn't initialized");
return;
}
ret = (*h.cuDeviceGet)(&device, i);
if (ret != CUDA_SUCCESS) {
snprintf(buf, buflen, "nvcuda device failed to initialize");
snprintf(buf, buflen, "cuda driver library device failed to initialize");
resp->err = strdup(buf);
return;
}
@@ -168,14 +169,14 @@ void nvcuda_bootstrap(nvcuda_handle_t h, int i, mem_info_t *resp) {
// To get memory we have to set (and release) a context
ret = (*h.cuCtxCreate_v3)(&ctx, NULL, 0, 0, device);
if (ret != CUDA_SUCCESS) {
snprintf(buf, buflen, "nvcuda failed to get device context %d", ret);
snprintf(buf, buflen, "cuda driver library failed to get device context %d", ret);
resp->err = strdup(buf);
return;
}
ret = (*h.cuMemGetInfo_v2)(&memInfo.free, &memInfo.total);
if (ret != CUDA_SUCCESS) {
snprintf(buf, buflen, "nvcuda device memory info lookup failure %d", ret);
snprintf(buf, buflen, "cuda driver library device memory info lookup failure %d", ret);
resp->err = strdup(buf);
// Best effort on failure...
(*h.cuCtxDestroy)(ctx);
@@ -193,7 +194,7 @@ void nvcuda_bootstrap(nvcuda_handle_t h, int i, mem_info_t *resp) {
ret = (*h.cuCtxDestroy)(ctx);
if (ret != CUDA_SUCCESS) {
LOG(1, "nvcuda failed to release device context %d", ret);
LOG(1, "cuda driver library failed to release device context %d", ret);
}
}
@@ -206,7 +207,7 @@ void nvcuda_get_free(nvcuda_handle_t h, int i, uint64_t *free, uint64_t *total)
ret = (*h.cuDeviceGet)(&device, i);
if (ret != CUDA_SUCCESS) {
LOG(1, "nvcuda device failed to initialize");
LOG(1, "cuda driver library device failed to initialize");
return;
}
@@ -214,13 +215,13 @@ void nvcuda_get_free(nvcuda_handle_t h, int i, uint64_t *free, uint64_t *total)
// To get memory we have to set (and release) a context
ret = (*h.cuCtxCreate_v3)(&ctx, NULL, 0, 0, device);
if (ret != CUDA_SUCCESS) {
LOG(1, "nvcuda failed to get device context %d", ret);
LOG(1, "cuda driver library failed to get device context %d", ret);
return;
}
ret = (*h.cuMemGetInfo_v2)(free, total);
if (ret != CUDA_SUCCESS) {
LOG(1, "nvcuda device memory info lookup failure %d", ret);
LOG(1, "cuda driver library device memory info lookup failure %d", ret);
// Best effort on failure...
(*h.cuCtxDestroy)(ctx);
return;
@@ -228,12 +229,12 @@ void nvcuda_get_free(nvcuda_handle_t h, int i, uint64_t *free, uint64_t *total)
ret = (*h.cuCtxDestroy)(ctx);
if (ret != CUDA_SUCCESS) {
LOG(1, "nvcuda failed to release device context %d", ret);
LOG(1, "cuda driver library failed to release device context %d", ret);
}
}
void nvcuda_release(nvcuda_handle_t h) {
LOG(h.verbose, "releasing nvcuda library\n");
LOG(h.verbose, "releasing cuda driver library\n");
UNLOAD_LIBRARY(h.handle);
// TODO and other context release logic?
h.handle = NULL;

View File

@@ -7,9 +7,12 @@
typedef enum cudaError_enum {
CUDA_SUCCESS = 0,
CUDA_ERROR_INVALID_VALUE = 1,
CUDA_ERROR_MEMORY_ALLOCATION = 2,
CUDA_ERROR_OUT_OF_MEMORY = 2,
CUDA_ERROR_NOT_INITIALIZED = 3,
CUDA_ERROR_INSUFFICIENT_DRIVER = 35,
CUDA_ERROR_NO_DEVICE = 100,
CUDA_ERROR_SYSTEM_DRIVER_MISMATCH = 803,
CUDA_ERROR_UNKNOWN = 999,
// Other values omitted for now...
} CUresult;
@@ -64,6 +67,7 @@ typedef struct nvcuda_init_resp {
char *err; // If err is non-null handle is invalid
nvcuda_handle_t ch;
int num_devices;
CUresult cudaErr;
} nvcuda_init_resp_t;
void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp);

View File

@@ -50,7 +50,7 @@ var OneapiMgmtName = "libze_intel_gpu.so"
func GetCPUMem() (memInfo, error) {
var mem memInfo
var total, available, free, buffers, cached uint64
var total, available, free, buffers, cached, freeSwap uint64
f, err := os.Open("/proc/meminfo")
if err != nil {
return mem, err
@@ -70,20 +70,21 @@ func GetCPUMem() (memInfo, error) {
_, err = fmt.Sscanf(line, "Buffers:%d", &buffers)
case strings.HasPrefix(line, "Cached:"):
_, err = fmt.Sscanf(line, "Cached:%d", &cached)
case strings.HasPrefix(line, "SwapFree:"):
_, err = fmt.Sscanf(line, "SwapFree:%d", &freeSwap)
default:
continue
}
if err != nil {
return mem, err
}
if total > 0 && available > 0 {
mem.TotalMemory = total * format.KibiByte
mem.FreeMemory = available * format.KibiByte
return mem, nil
}
}
mem.TotalMemory = total * format.KibiByte
mem.FreeMemory = (free + buffers + cached) * format.KibiByte
mem.FreeSwap = freeSwap * format.KibiByte
if available > 0 {
mem.FreeMemory = available * format.KibiByte
} else {
mem.FreeMemory = (free + buffers + cached) * format.KibiByte
}
return mem, nil
}

View File

@@ -51,5 +51,5 @@ func GetCPUMem() (memInfo, error) {
if r1 == 0 {
return memInfo{}, fmt.Errorf("GlobalMemoryStatusEx failed: %w", err)
}
return memInfo{TotalMemory: memStatus.TotalPhys, FreeMemory: memStatus.AvailPhys}, nil
return memInfo{TotalMemory: memStatus.TotalPhys, FreeMemory: memStatus.AvailPhys, FreeSwap: memStatus.AvailPageFile}, nil
}

View File

@@ -10,6 +10,7 @@ import (
type memInfo struct {
TotalMemory uint64 `json:"total_memory,omitempty"`
FreeMemory uint64 `json:"free_memory,omitempty"`
FreeSwap uint64 `json:"free_swap,omitempty"`
}
// Beginning of an `ollama info` command
@@ -29,6 +30,11 @@ type GpuInfo struct {
// Extra environment variables specific to the GPU as list of [key,value]
EnvWorkarounds [][2]string `json:"envs,omitempty"`
// Set to true if we can NOT reliably discover FreeMemory. A value of true indicates
// the FreeMemory is best effort, and may over or under report actual memory usage
// False indicates FreeMemory can generally be trusted on this GPU
UnreliableFreeMemory bool
// GPU information
ID string `json:"gpu_id"` // string to use for selection of this specific GPU
Name string `json:"name"` // user friendly name if available
@@ -47,7 +53,8 @@ type CPUInfo struct {
type CudaGPUInfo struct {
GpuInfo
index int //nolint:unused,nolintlint
OSOverhead uint64 // Memory overhead between the driver library and management library
index int //nolint:unused,nolintlint
}
type CudaGPUInfoList []CudaGPUInfo

View File

@@ -12,7 +12,7 @@ import (
func TestContextExhaustion(t *testing.T) {
// Longer needed for small footprint GPUs
ctx, cancel := context.WithTimeout(context.Background(), 6*time.Minute)
ctx, cancel := context.WithTimeout(context.Background(), 5*time.Minute)
defer cancel()
// Set up the test data
req := api.GenerateRequest{
@@ -25,5 +25,10 @@ func TestContextExhaustion(t *testing.T) {
"num_ctx": 128,
},
}
GenerateTestHelper(ctx, t, req, []string{"once", "upon", "lived"})
client, _, cleanup := InitServerConnection(ctx, t)
defer cleanup()
if err := PullIfMissing(ctx, client, req.Model); err != nil {
t.Fatalf("PullIfMissing failed: %v", err)
}
DoGenerate(ctx, t, client, req, []string{"once", "upon", "lived"}, 120*time.Second, 10*time.Second)
}

152
integration/embed_test.go Normal file
View File

@@ -0,0 +1,152 @@
//go:build integration
package integration
import (
"context"
"testing"
"time"
"github.com/ollama/ollama/api"
)
func TestAllMiniLMEmbed(t *testing.T) {
ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
defer cancel()
req := api.EmbedRequest{
Model: "all-minilm",
Input: "why is the sky blue?",
}
res, err := embedTestHelper(ctx, t, req)
if err != nil {
t.Fatalf("error: %v", err)
}
if len(res.Embeddings) != 1 {
t.Fatalf("expected 1 embedding, got %d", len(res.Embeddings))
}
if len(res.Embeddings[0]) != 384 {
t.Fatalf("expected 384 floats, got %d", len(res.Embeddings[0]))
}
if res.Embeddings[0][0] != 0.010071031 {
t.Fatalf("expected 0.010071031, got %f", res.Embeddings[0][0])
}
}
func TestAllMiniLMBatchEmbed(t *testing.T) {
ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
defer cancel()
req := api.EmbedRequest{
Model: "all-minilm",
Input: []string{"why is the sky blue?", "why is the grass green?"},
}
res, err := embedTestHelper(ctx, t, req)
if err != nil {
t.Fatalf("error: %v", err)
}
if len(res.Embeddings) != 2 {
t.Fatalf("expected 2 embeddings, got %d", len(res.Embeddings))
}
if len(res.Embeddings[0]) != 384 {
t.Fatalf("expected 384 floats, got %d", len(res.Embeddings[0]))
}
if res.Embeddings[0][0] != 0.010071031 || res.Embeddings[1][0] != -0.009802706 {
t.Fatalf("expected 0.010071031 and -0.009802706, got %f and %f", res.Embeddings[0][0], res.Embeddings[1][0])
}
}
func TestAllMiniLmEmbedTruncate(t *testing.T) {
ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
defer cancel()
truncTrue, truncFalse := true, false
type testReq struct {
Name string
Request api.EmbedRequest
}
reqs := []testReq{
{
Name: "Target Truncation",
Request: api.EmbedRequest{
Model: "all-minilm",
Input: "why",
},
},
{
Name: "Default Truncate",
Request: api.EmbedRequest{
Model: "all-minilm",
Input: "why is the sky blue?",
Options: map[string]any{"num_ctx": 1},
},
},
{
Name: "Explicit Truncate",
Request: api.EmbedRequest{
Model: "all-minilm",
Input: "why is the sky blue?",
Truncate: &truncTrue,
Options: map[string]any{"num_ctx": 1},
},
},
}
res := make(map[string]*api.EmbedResponse)
for _, req := range reqs {
response, err := embedTestHelper(ctx, t, req.Request)
if err != nil {
t.Fatalf("error: %v", err)
}
res[req.Name] = response
}
if res["Target Truncation"].Embeddings[0][0] != res["Default Truncate"].Embeddings[0][0] {
t.Fatal("expected default request to truncate correctly")
}
if res["Default Truncate"].Embeddings[0][0] != res["Explicit Truncate"].Embeddings[0][0] {
t.Fatal("expected default request and truncate true request to be the same")
}
// check that truncate set to false returns an error if context length is exceeded
_, err := embedTestHelper(ctx, t, api.EmbedRequest{
Model: "all-minilm",
Input: "why is the sky blue?",
Truncate: &truncFalse,
Options: map[string]any{"num_ctx": 1},
})
if err == nil {
t.Fatal("expected error, got nil")
}
}
func embedTestHelper(ctx context.Context, t *testing.T, req api.EmbedRequest) (*api.EmbedResponse, error) {
client, _, cleanup := InitServerConnection(ctx, t)
defer cleanup()
if err := PullIfMissing(ctx, client, req.Model); err != nil {
t.Fatalf("failed to pull model %s: %v", req.Model, err)
}
response, err := client.Embed(ctx, &req)
if err != nil {
return nil, err
}
return response, nil
}

View File

@@ -1,14 +1,13 @@
set(TARGET ollama_llama_server)
option(LLAMA_SERVER_VERBOSE "Build verbose logging option for Server" ON)
include_directories(${CMAKE_CURRENT_SOURCE_DIR})
add_executable(${TARGET} server.cpp utils.hpp json.hpp httplib.h)
install(TARGETS ${TARGET} RUNTIME)
target_compile_definitions(${TARGET} PRIVATE
SERVER_VERBOSE=$<BOOL:${LLAMA_SERVER_VERBOSE}>
)
target_link_libraries(${TARGET} PRIVATE common llava ${CMAKE_THREAD_LIBS_INIT})
if (WIN32)
TARGET_LINK_LIBRARIES(${TARGET} PRIVATE ws2_32)
endif()
set(TARGET ollama_llama_server)
option(LLAMA_SERVER_VERBOSE "Build verbose logging option for Server" ON)
include_directories(${CMAKE_CURRENT_SOURCE_DIR})
add_executable(${TARGET} server.cpp utils.hpp json.hpp httplib.h)
install(TARGETS ${TARGET} RUNTIME)
target_compile_definitions(${TARGET} PRIVATE
SERVER_VERBOSE=$<BOOL:${LLAMA_SERVER_VERBOSE}>
)
target_link_libraries(${TARGET} PRIVATE ggml llama common llava ${CMAKE_THREAD_LIBS_INIT})
if (WIN32)
TARGET_LINK_LIBRARIES(${TARGET} PRIVATE ws2_32)
endif()
target_compile_features(${TARGET} PRIVATE cxx_std_11)

View File

@@ -1382,12 +1382,50 @@ struct llama_server_context
}
}
std::string common_prefix(const std::string& str1, const std::string& str2) {
auto mismatch_pair = std::mismatch(str1.begin(), str1.end(), str2.begin());
return std::string(str1.begin(), mismatch_pair.first);
}
// Find the slot that has the greatest common prefix
server_slot *prefix_slot(const json &prompt) {
if (!prompt.is_string()) {
return nullptr;
}
std::string prompt_str = prompt.get<std::string>();
server_slot *slot = nullptr;
size_t longest = 0;
for (server_slot &s : slots) {
if (s.available() && s.prompt.is_string()) {
std::string s_prompt = s.prompt.get<std::string>();
std::string prefix = common_prefix(s_prompt, prompt_str);
if (prefix.size() > longest) {
slot = &s;
longest = prefix.size();
}
}
}
if (!slot) {
return get_slot(-1);
}
LOG_DEBUG("slot with common prefix found", {{
"slot_id", slot->id,
"characters", longest
}});
return slot;
}
void process_single_task(task_server& task)
{
switch (task.type)
{
case TASK_TYPE_COMPLETION: {
server_slot *slot = get_slot(json_value(task.data, "slot_id", -1));
server_slot *slot = prefix_slot(task.data["prompt"]);
if (slot == nullptr)
{
// if no slot is available, we defer this task for processing later
@@ -1654,22 +1692,23 @@ struct llama_server_context
if (slot.ga_n == 1 && slot.n_prompt_tokens >= slot.n_ctx)
{
const int n_left = slot.n_ctx - slot.params.n_keep;
const int n_block_size = n_left / 2;
const int erased_blocks = (slot.n_prompt_tokens - slot.params.n_keep - n_block_size) / n_block_size;
const int n_shift = n_left / 2;
const int n_erase = slot.n_prompt_tokens - slot.params.n_keep - n_shift;
std::vector<llama_token> new_tokens(
prompt_tokens.begin(),
prompt_tokens.begin() + slot.params.n_keep);
new_tokens.insert(
new_tokens.end(),
prompt_tokens.begin() + slot.params.n_keep + erased_blocks * n_block_size,
prompt_tokens.begin() + slot.params.n_keep + n_erase,
prompt_tokens.end());
LOG_VERBOSE("input truncated", {
{"n_ctx", slot.n_ctx},
{"n_keep", slot.params.n_keep},
{"n_left", n_left},
{"new_tokens", tokens_to_str(ctx, new_tokens.cbegin(), new_tokens.cend())},
LOG_INFO("input truncated", {
{"n_ctx", slot.n_ctx},
{"n_keep", slot.params.n_keep},
{"n_left", n_left},
{"n_shift", n_shift},
{"n_erase", n_erase},
});
slot.truncated = true;
prompt_tokens = new_tokens;
@@ -1704,7 +1743,7 @@ struct llama_server_context
slot.n_past -= 1;
}
slot.n_prompt_tokens_processed = slot.n_prompt_tokens - slot.n_past;
slot.n_prompt_tokens_processed = slot.n_prompt_tokens;
if (slot.ga_n != 1)
{
@@ -3149,26 +3188,33 @@ int main(int argc, char **argv) {
prompt = "";
}
json image_data;
if (body.count("image_data") != 0) {
image_data = body["image_data"];
}
else
{
image_data = "";
if (prompt.size() == 1) {
prompt = prompt[0];
}
// create and queue the task
const int task_id = llama.queue_tasks.get_new_id();
llama.queue_results.add_waiting_task_id(task_id);
llama.request_completion(task_id, { {"prompt", prompt}, { "n_predict", 0}, {"image_data", image_data} }, true, -1);
json responses;
{
const int id_task = llama.queue_tasks.get_new_id();
llama.queue_results.add_waiting_task_id(id_task);
llama.request_completion(id_task, {{"prompt", prompt}}, true, -1);
// get the result
task_result result = llama.queue_results.recv(task_id);
llama.queue_results.remove_waiting_task_id(task_id);
// get the result
task_result result = llama.queue_results.recv(id_task);
llama.queue_results.remove_waiting_task_id(id_task);
if (result.error) {
return res.set_content(result.result_json.dump(), "application/json; charset=utf-8");
}
// send the result
return res.set_content(result.result_json.dump(), "application/json; charset=utf-8");
responses = result.result_json.value("results", std::vector<json>{result.result_json});
json embeddings = json::array();
for (auto & elem : responses) {
embeddings.push_back(elem.at("embedding"));
}
// send the result
json embedding_res = json{{"embedding", embeddings}};
return res.set_content(embedding_res.dump(), "application/json; charset=utf-8");
}
});
// GG: if I put the main loop inside a thread, it crashes on the first request when build in Debug!?

View File

@@ -18,16 +18,16 @@ sign() {
fi
}
COMMON_DARWIN_DEFS="-DCMAKE_OSX_DEPLOYMENT_TARGET=11.3 -DLLAMA_METAL_MACOSX_VERSION_MIN=11.3 -DCMAKE_SYSTEM_NAME=Darwin -DLLAMA_METAL_EMBED_LIBRARY=on -DLLAMA_OPENMP=off"
COMMON_DARWIN_DEFS="-DBUILD_SHARED_LIBS=off -DCMAKE_OSX_DEPLOYMENT_TARGET=11.3 -DLLAMA_METAL_MACOSX_VERSION_MIN=11.3 -DCMAKE_SYSTEM_NAME=Darwin -DGGML_METAL_EMBED_LIBRARY=on -DGGML_OPENMP=off"
case "${GOARCH}" in
"amd64")
COMMON_CPU_DEFS="${COMMON_DARWIN_DEFS} -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DLLAMA_METAL=off -DLLAMA_NATIVE=off"
COMMON_CPU_DEFS="${COMMON_DARWIN_DEFS} -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DGGML_METAL=off -DGGML_NATIVE=off"
# Static build for linking into the Go binary
init_vars
CMAKE_TARGETS="--target llama --target ggml"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DBUILD_SHARED_LIBS=off -DLLAMA_BLAS=off -DLLAMA_ACCELERATE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_BLAS=off -DGGML_ACCELERATE=off -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}_static"
echo "Building static library"
build
@@ -37,7 +37,7 @@ case "${GOARCH}" in
# CPU first for the default library, set up as lowest common denominator for maximum compatibility (including Rosetta)
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=off -DLLAMA_BLAS=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_ACCELERATE=off -DGGML_BLAS=off -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}/cpu"
echo "Building LCD CPU"
build
@@ -49,7 +49,7 @@ case "${GOARCH}" in
# Approximately 400% faster than LCD on same CPU
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=off -DLLAMA_BLAS=off -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_ACCELERATE=off -DGGML_BLAS=off -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}/cpu_avx"
echo "Building AVX CPU"
build
@@ -61,7 +61,7 @@ case "${GOARCH}" in
# Approximately 10% faster than AVX on same CPU
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_ACCELERATE=on -DLLAMA_BLAS=off -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_F16C=on ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_ACCELERATE=on -DGGML_BLAS=off -DGGML_AVX=on -DGGML_AVX2=on -DGGML_AVX512=off -DGGML_FMA=on -DGGML_F16C=on ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}/cpu_avx2"
echo "Building AVX2 CPU"
EXTRA_LIBS="${EXTRA_LIBS} -framework Accelerate -framework Foundation"
@@ -75,14 +75,14 @@ case "${GOARCH}" in
# Static build for linking into the Go binary
init_vars
CMAKE_TARGETS="--target llama --target ggml"
CMAKE_DEFS="-DCMAKE_OSX_DEPLOYMENT_TARGET=11.3 -DLLAMA_BLAS=off -DCMAKE_SYSTEM_NAME=Darwin -DBUILD_SHARED_LIBS=off -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DLLAMA_METAL=off -DLLAMA_ACCELERATE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_DARWIN_DEFS} -DCMAKE_OSX_DEPLOYMENT_TARGET=11.3 -DCMAKE_SYSTEM_NAME=Darwin -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}_static"
echo "Building static library"
build
if [ -z "$OLLAMA_SKIP_METAL_GENERATE" ]; then
init_vars
CMAKE_DEFS="${COMMON_DARWIN_DEFS} -DLLAMA_ACCELERATE=on -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} -DLLAMA_METAL=on ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_DARWIN_DEFS} -DCMAKE_SYSTEM_PROCESSOR=${ARCH} -DCMAKE_OSX_ARCHITECTURES=${ARCH} ${CMAKE_DEFS}"
BUILD_DIR="../build/darwin/${ARCH}/metal"
EXTRA_LIBS="${EXTRA_LIBS} -framework Accelerate -framework Foundation -framework Metal -framework MetalKit -framework MetalPerformanceShaders"
build

View File

@@ -51,7 +51,7 @@ if [ -z "${CUDACXX}" ]; then
export CUDACXX=$(command -v nvcc)
fi
fi
COMMON_CMAKE_DEFS="-DCMAKE_POSITION_INDEPENDENT_CODE=on -DLLAMA_NATIVE=off -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off -DLLAMA_OPENMP=off"
COMMON_CMAKE_DEFS="-DBUILD_SHARED_LIBS=off -DCMAKE_POSITION_INDEPENDENT_CODE=on -DGGML_NATIVE=off -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_OPENMP=off"
source $(dirname $0)/gen_common.sh
init_vars
git_module_setup
@@ -64,7 +64,7 @@ if [ -z "${OLLAMA_SKIP_STATIC_GENERATE}" -o "${OLLAMA_CPU_TARGET}" = "static" ];
# Static build for linking into the Go binary
init_vars
CMAKE_TARGETS="--target llama --target ggml"
CMAKE_DEFS="-DBUILD_SHARED_LIBS=off -DLLAMA_NATIVE=off -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off -DLLAMA_OPENMP=off ${CMAKE_DEFS}"
CMAKE_DEFS="-DBUILD_SHARED_LIBS=off -DGGML_NATIVE=off -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off -DGGML_OPENMP=off ${CMAKE_DEFS}"
BUILD_DIR="../build/linux/${ARCH}_static"
echo "Building static library"
build
@@ -77,29 +77,29 @@ if [ -z "${OLLAMA_SKIP_CPU_GENERATE}" ]; then
if [ -n "${OLLAMA_CUSTOM_CPU_DEFS}" ]; then
init_vars
echo "OLLAMA_CUSTOM_CPU_DEFS=\"${OLLAMA_CUSTOM_CPU_DEFS}\""
CMAKE_DEFS="${OLLAMA_CUSTOM_CPU_DEFS} -DCMAKE_POSITION_INDEPENDENT_CODE=on ${CMAKE_DEFS}"
CMAKE_DEFS="${OLLAMA_CUSTOM_CPU_DEFS} -DBUILD_SHARED_LIBS=off -DCMAKE_POSITION_INDEPENDENT_CODE=on ${CMAKE_DEFS}"
BUILD_DIR="../build/linux/${ARCH}/cpu"
echo "Building custom CPU"
build
compress
else
# Darwin Rosetta x86 emulation does NOT support AVX, AVX2, AVX512
# -DLLAMA_AVX -- 2011 Intel Sandy Bridge & AMD Bulldozer
# -DLLAMA_F16C -- 2012 Intel Ivy Bridge & AMD 2011 Bulldozer (No significant improvement over just AVX)
# -DLLAMA_AVX2 -- 2013 Intel Haswell & 2015 AMD Excavator / 2017 AMD Zen
# -DLLAMA_FMA (FMA3) -- 2013 Intel Haswell & 2012 AMD Piledriver
# -DGGML_AVX -- 2011 Intel Sandy Bridge & AMD Bulldozer
# -DGGML_F16C -- 2012 Intel Ivy Bridge & AMD 2011 Bulldozer (No significant improvement over just AVX)
# -DGGML_AVX2 -- 2013 Intel Haswell & 2015 AMD Excavator / 2017 AMD Zen
# -DGGML_FMA (FMA3) -- 2013 Intel Haswell & 2012 AMD Piledriver
# Note: the following seem to yield slower results than AVX2 - ymmv
# -DLLAMA_AVX512 -- 2017 Intel Skylake and High End DeskTop (HEDT)
# -DLLAMA_AVX512_VBMI -- 2018 Intel Cannon Lake
# -DLLAMA_AVX512_VNNI -- 2021 Intel Alder Lake
# -DGGML_AVX512 -- 2017 Intel Skylake and High End DeskTop (HEDT)
# -DGGML_AVX512_VBMI -- 2018 Intel Cannon Lake
# -DGGML_AVX512_VNNI -- 2021 Intel Alder Lake
COMMON_CPU_DEFS="-DCMAKE_POSITION_INDEPENDENT_CODE=on -DLLAMA_NATIVE=off -DLLAMA_OPENMP=off"
COMMON_CPU_DEFS="-DBUILD_SHARED_LIBS=off -DCMAKE_POSITION_INDEPENDENT_CODE=on -DGGML_NATIVE=off -DGGML_OPENMP=off"
if [ -z "${OLLAMA_CPU_TARGET}" -o "${OLLAMA_CPU_TARGET}" = "cpu" ]; then
#
# CPU first for the default library, set up as lowest common denominator for maximum compatibility (including Rosetta)
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="../build/linux/${ARCH}/cpu"
echo "Building LCD CPU"
build
@@ -116,7 +116,7 @@ if [ -z "${OLLAMA_SKIP_CPU_GENERATE}" ]; then
# Approximately 400% faster than LCD on same CPU
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_FMA=off -DLLAMA_F16C=off ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_AVX=on -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_FMA=off -DGGML_F16C=off ${CMAKE_DEFS}"
BUILD_DIR="../build/linux/${ARCH}/cpu_avx"
echo "Building AVX CPU"
build
@@ -129,7 +129,7 @@ if [ -z "${OLLAMA_SKIP_CPU_GENERATE}" ]; then
# Approximately 10% faster than AVX on same CPU
#
init_vars
CMAKE_DEFS="${COMMON_CPU_DEFS} -DLLAMA_AVX=on -DLLAMA_AVX2=on -DLLAMA_AVX512=off -DLLAMA_FMA=on -DLLAMA_F16C=on ${CMAKE_DEFS}"
CMAKE_DEFS="${COMMON_CPU_DEFS} -DGGML_AVX=on -DGGML_AVX2=on -DGGML_AVX512=off -DGGML_FMA=on -DGGML_F16C=on ${CMAKE_DEFS}"
BUILD_DIR="../build/linux/${ARCH}/cpu_avx2"
echo "Building AVX2 CPU"
build
@@ -170,15 +170,15 @@ if [ -z "${OLLAMA_SKIP_CUDA_GENERATE}" -a -d "${CUDA_LIB_DIR}" ]; then
#
# CUDA compute < 6.0 lacks proper FP16 support on ARM.
# Disabling has minimal performance effect while maintaining compatibility.
ARM64_DEFS="-DLLAMA_AVX=off -DLLAMA_AVX2=off -DLLAMA_AVX512=off -DLLAMA_CUDA_F16=off"
ARM64_DEFS="-DGGML_AVX=off -DGGML_AVX2=off -DGGML_AVX512=off -DGGML_CUDA_F16=off"
fi
# Users building from source can tune the exact flags we pass to cmake for configuring llama.cpp
if [ -n "${OLLAMA_CUSTOM_CUDA_DEFS}" ]; then
echo "OLLAMA_CUSTOM_CUDA_DEFS=\"${OLLAMA_CUSTOM_CUDA_DEFS}\""
CMAKE_CUDA_DEFS="-DLLAMA_CUDA=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES} ${OLLAMA_CUSTOM_CUDA_DEFS}"
CMAKE_CUDA_DEFS="-DGGML_CUDA=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES} ${OLLAMA_CUSTOM_CUDA_DEFS}"
echo "Building custom CUDA GPU"
else
CMAKE_CUDA_DEFS="-DLLAMA_CUDA=on -DCMAKE_CUDA_FLAGS=-t8 -DLLAMA_CUDA_FORCE_MMQ=on -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES}"
CMAKE_CUDA_DEFS="-DGGML_CUDA=on -DCMAKE_CUDA_FLAGS=-t8 -DCMAKE_CUDA_ARCHITECTURES=${CMAKE_CUDA_ARCHITECTURES}"
fi
CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} ${ARM64_DEFS} ${CMAKE_CUDA_DEFS}"
BUILD_DIR="../build/linux/${ARCH}/cuda${CUDA_VARIANT}"
@@ -216,7 +216,7 @@ if [ -z "${OLLAMA_SKIP_ONEAPI_GENERATE}" -a -d "${ONEAPI_ROOT}" ]; then
init_vars
source ${ONEAPI_ROOT}/setvars.sh --force # set up environment variables for oneAPI
CC=icx
CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DLLAMA_SYCL=ON -DLLAMA_SYCL_F16=OFF"
CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx -DGGML_SYCL=ON -DGGML_SYCL_F16=OFF"
BUILD_DIR="../build/linux/${ARCH}/oneapi"
EXTRA_LIBS="-fsycl -Wl,-rpath,${ONEAPI_ROOT}/compiler/latest/lib,-rpath,${ONEAPI_ROOT}/mkl/latest/lib,-rpath,${ONEAPI_ROOT}/tbb/latest/lib,-rpath,${ONEAPI_ROOT}/compiler/latest/opt/oclfpga/linux64/lib -lOpenCL -lmkl_core -lmkl_sycl_blas -lmkl_intel_ilp64 -lmkl_tbb_thread -ltbb"
DEBUG_FLAGS="" # icx compiles with -O0 if we pass -g, so we must remove it
@@ -254,7 +254,7 @@ if [ -z "${OLLAMA_SKIP_ROCM_GENERATE}" -a -d "${ROCM_PATH}" ]; then
ROCM_VARIANT=_v$(ls ${ROCM_PATH}/lib/librocblas.so.*.*.????? | cut -f5 -d. || true)
fi
init_vars
CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} -DLLAMA_HIPBLAS=on -DCMAKE_C_COMPILER=$ROCM_PATH/llvm/bin/clang -DCMAKE_CXX_COMPILER=$ROCM_PATH/llvm/bin/clang++ -DAMDGPU_TARGETS=$(amdGPUs) -DGPU_TARGETS=$(amdGPUs)"
CMAKE_DEFS="${COMMON_CMAKE_DEFS} ${CMAKE_DEFS} -DGGML_HIPBLAS=on -DLLAMA_CUDA_NO_PEER_COPY=on -DCMAKE_C_COMPILER=$ROCM_PATH/llvm/bin/clang -DCMAKE_CXX_COMPILER=$ROCM_PATH/llvm/bin/clang++ -DAMDGPU_TARGETS=$(amdGPUs) -DGPU_TARGETS=$(amdGPUs)"
# Users building from source can tune the exact flags we pass to cmake for configuring llama.cpp
if [ -n "${OLLAMA_CUSTOM_ROCM_DEFS}" ]; then
echo "OLLAMA_CUSTOM_ROCM_DEFS=\"${OLLAMA_CUSTOM_ROCM_DEFS}\""

View File

@@ -6,18 +6,9 @@ function amdGPUs {
if ($env:AMDGPU_TARGETS) {
return $env:AMDGPU_TARGETS
}
# TODO - load from some common data file for linux + windows build consistency
# Current supported rocblas list from ROCm v6.1.2 on windows
# https://rocm.docs.amd.com/projects/install-on-windows/en/latest/reference/system-requirements.html#windows-supported-gpus
$GPU_LIST = @(
"gfx900"
"gfx906:xnack-"
"gfx908:xnack-"
"gfx90a:xnack+"
"gfx90a:xnack-"
"gfx940"
"gfx941"
"gfx942"
"gfx1010"
"gfx1012"
"gfx1030"
"gfx1100"
"gfx1101"
@@ -39,8 +30,8 @@ function init_vars {
}
$script:cmakeDefs = @(
"-DBUILD_SHARED_LIBS=on",
"-DLLAMA_NATIVE=off",
"-DLLAMA_OPENMP=off"
"-DGGML_NATIVE=off",
"-DGGML_OPENMP=off"
)
$script:commonCpuDefs = @("-DCMAKE_POSITION_INDEPENDENT_CODE=on")
$script:ARCH = $Env:PROCESSOR_ARCHITECTURE.ToLower()
@@ -182,9 +173,9 @@ function cleanup {
}
# -DLLAMA_AVX -- 2011 Intel Sandy Bridge & AMD Bulldozer
# -DLLAMA_AVX2 -- 2013 Intel Haswell & 2015 AMD Excavator / 2017 AMD Zen
# -DLLAMA_FMA (FMA3) -- 2013 Intel Haswell & 2012 AMD Piledriver
# -DGGML_AVX -- 2011 Intel Sandy Bridge & AMD Bulldozer
# -DGGML_AVX2 -- 2013 Intel Haswell & 2015 AMD Excavator / 2017 AMD Zen
# -DGGML_FMA (FMA3) -- 2013 Intel Haswell & 2012 AMD Piledriver
function build_static() {
@@ -204,13 +195,13 @@ function build_static() {
"-DCMAKE_C_COMPILER=gcc.exe",
"-DCMAKE_CXX_COMPILER=g++.exe",
"-DBUILD_SHARED_LIBS=off",
"-DLLAMA_NATIVE=off",
"-DLLAMA_AVX=off",
"-DLLAMA_AVX2=off",
"-DLLAMA_AVX512=off",
"-DLLAMA_F16C=off",
"-DLLAMA_FMA=off",
"-DLLAMA_OPENMP=off")
"-DGGML_NATIVE=off",
"-DGGML_AVX=off",
"-DGGML_AVX2=off",
"-DGGML_AVX512=off",
"-DGGML_F16C=off",
"-DGGML_FMA=off",
"-DGGML_OPENMP=off")
$script:buildDir="../build/windows/${script:ARCH}_static"
write-host "Building static library"
build
@@ -224,7 +215,7 @@ function build_cpu($gen_arch) {
if ((-not "${env:OLLAMA_SKIP_CPU_GENERATE}" ) -and ((-not "${env:OLLAMA_CPU_TARGET}") -or ("${env:OLLAMA_CPU_TARGET}" -eq "cpu"))) {
# remaining llama.cpp builds use MSVC
init_vars
$script:cmakeDefs = $script:commonCpuDefs + @("-A", $gen_arch, "-DLLAMA_AVX=off", "-DLLAMA_AVX2=off", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=off", "-DLLAMA_F16C=off") + $script:cmakeDefs
$script:cmakeDefs = $script:commonCpuDefs + @("-A", $gen_arch, "-DGGML_AVX=off", "-DGGML_AVX2=off", "-DGGML_AVX512=off", "-DGGML_FMA=off", "-DGGML_F16C=off") + $script:cmakeDefs
$script:buildDir="../build/windows/${script:ARCH}/cpu"
$script:distDir="$script:DIST_BASE\cpu"
write-host "Building LCD CPU"
@@ -239,7 +230,7 @@ function build_cpu($gen_arch) {
function build_cpu_avx() {
if ((-not "${env:OLLAMA_SKIP_CPU_GENERATE}" ) -and ((-not "${env:OLLAMA_CPU_TARGET}") -or ("${env:OLLAMA_CPU_TARGET}" -eq "cpu_avx"))) {
init_vars
$script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DLLAMA_AVX=on", "-DLLAMA_AVX2=off", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=off", "-DLLAMA_F16C=off") + $script:cmakeDefs
$script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DGGML_AVX=on", "-DGGML_AVX2=off", "-DGGML_AVX512=off", "-DGGML_FMA=off", "-DGGML_F16C=off") + $script:cmakeDefs
$script:buildDir="../build/windows/${script:ARCH}/cpu_avx"
$script:distDir="$script:DIST_BASE\cpu_avx"
write-host "Building AVX CPU"
@@ -254,7 +245,7 @@ function build_cpu_avx() {
function build_cpu_avx2() {
if ((-not "${env:OLLAMA_SKIP_CPU_GENERATE}" ) -and ((-not "${env:OLLAMA_CPU_TARGET}") -or ("${env:OLLAMA_CPU_TARGET}" -eq "cpu_avx2"))) {
init_vars
$script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DLLAMA_AVX=on", "-DLLAMA_AVX2=on", "-DLLAMA_AVX512=off", "-DLLAMA_FMA=on", "-DLLAMA_F16C=on") + $script:cmakeDefs
$script:cmakeDefs = $script:commonCpuDefs + @("-A", "x64", "-DGGML_AVX=on", "-DGGML_AVX2=on", "-DGGML_AVX512=off", "-DGGML_FMA=on", "-DGGML_F16C=on") + $script:cmakeDefs
$script:buildDir="../build/windows/${script:ARCH}/cpu_avx2"
$script:distDir="$script:DIST_BASE\cpu_avx2"
write-host "Building AVX2 CPU"
@@ -279,9 +270,9 @@ function build_cuda() {
$script:distDir="$script:DIST_BASE\cuda$script:CUDA_VARIANT"
$script:cmakeDefs += @(
"-A", "x64",
"-DLLAMA_CUDA=ON",
"-DLLAMA_AVX=on",
"-DLLAMA_AVX2=off",
"-DGGML_CUDA=ON",
"-DGGML_AVX=on",
"-DGGML_AVX2=off",
"-DCUDAToolkit_INCLUDE_DIR=$script:CUDA_INCLUDE_DIR",
"-DCMAKE_CUDA_FLAGS=-t8",
"-DCMAKE_CUDA_ARCHITECTURES=${script:CMAKE_CUDA_ARCHITECTURES}"
@@ -319,7 +310,7 @@ function build_oneapi() {
$script:distDir ="$script:DIST_BASE\oneapi$script:ONEAPI_VARIANT"
$script:cmakeDefs += @(
"-G", "MinGW Makefiles",
"-DLLAMA_SYCL=ON",
"-DGGML_SYCL=ON",
"-DCMAKE_C_COMPILER=icx",
"-DCMAKE_CXX_COMPILER=icx",
"-DCMAKE_BUILD_TYPE=Release"
@@ -365,10 +356,11 @@ function build_rocm() {
"-G", "Ninja",
"-DCMAKE_C_COMPILER=clang.exe",
"-DCMAKE_CXX_COMPILER=clang++.exe",
"-DLLAMA_HIPBLAS=on",
"-DGGML_HIPBLAS=on",
"-DLLAMA_CUDA_NO_PEER_COPY=on",
"-DHIP_PLATFORM=amd",
"-DLLAMA_AVX=on",
"-DLLAMA_AVX2=off",
"-DGGML_AVX=on",
"-DGGML_AVX2=off",
"-DCMAKE_POSITION_INDEPENDENT_CODE=on",
"-DAMDGPU_TARGETS=$(amdGPUs)",
"-DGPU_TARGETS=$(amdGPUs)"
@@ -394,7 +386,6 @@ function build_rocm() {
sign
install
# Assumes v5.7, may need adjustments for v6
rm -ea 0 -recurse -force -path "${script:SRC_DIR}\dist\windows-${script:ARCH}\rocm\"
md "${script:SRC_DIR}\dist\windows-${script:ARCH}\rocm\rocblas\library\" -ea 0 > $null
cp "${env:HIP_PATH}\bin\hipblas.dll" "${script:SRC_DIR}\dist\windows-${script:ARCH}\rocm\"

View File

@@ -366,9 +366,18 @@ func (llm GGML) GraphSize(context, batch uint64) (partialOffload, fullOffload ui
4*batch*(1+2*embedding+context*(1+heads))+embedding*(6*context*headsKV/heads+embedding*9/16),
)
}
case "gemma":
fullOffload = 4 * batch * (embedding + vocab)
partialOffload = 4*batch*(2*embedding+vocab+1) + embedding*vocab*105/128
case "gemma", "gemma2":
fullOffload = max(
4*batch*(embedding+vocab),
4*batch*(2+context+context*heads+2*embedding+2*embeddingHeadsK*heads),
)
partialOffload = max(
4*embedding*batch+embedding*vocab*105/128+4*vocab*batch,
4*batch*(2*embedding+1+2*embeddingHeadsK*heads+context+context*heads)+
4*embeddingHeadsK*context*8+
embedding*embeddingHeadsK*heads*9/16,
)
case "command-r":
fullOffload = max(
4*batch*(embedding+vocab),
@@ -415,6 +424,32 @@ func (llm GGML) GraphSize(context, batch uint64) (partialOffload, fullOffload ui
4*batch*(3*embedding+vocab)+embedding*vocab*105/128,
4*batch*(2*embedding+1+2*embeddingHeadsK*headsKV+context+context*headsKV)+4*embeddingHeadsK*context*headsKV+embedding*embeddingHeadsK*headsKV*9/16,
)
case "chatglm":
fullOffload = 4 * batch * (embedding + vocab)
partialOffload = 4*batch*(embedding+vocab) + embedding*vocab*105/128
if qkvBias, ok := layers["blk.0"]["attn_qkv.bias"]; ok {
fullOffload = max(
fullOffload,
4*batch*(2+
2*embedding+
context+
context*heads+
embeddingHeadsK*heads+
qkvBias.Shape[0]),
)
partialOffload = max(
partialOffload,
4*batch*(1+
2*embedding+
embeddingHeadsK*heads+
context+
context*heads)+
4*embeddingHeadsK*context+
4*context*embeddingHeadsK+
4*qkvBias.Shape[0],
)
}
}
return

View File

@@ -537,6 +537,7 @@ var ggufKVOrder = map[string][]string{
"tokenizer.ggml.add_bos_token",
"tokenizer.ggml.add_eos_token",
"tokenizer.chat_template",
"bert.pooling_type",
},
}

View File

@@ -1,12 +1,13 @@
package llm
// #cgo CFLAGS: -Illama.cpp
// #cgo darwin,arm64 LDFLAGS: ${SRCDIR}/build/darwin/arm64_static/libllama.a -lstdc++
// #cgo darwin,amd64 LDFLAGS: ${SRCDIR}/build/darwin/x86_64_static/libllama.a -lstdc++
// #cgo windows,amd64 LDFLAGS: ${SRCDIR}/build/windows/amd64_static/libllama.a -static -lstdc++
// #cgo windows,arm64 LDFLAGS: ${SRCDIR}/build/windows/arm64_static/libllama.a -static -lstdc++
// #cgo linux,amd64 LDFLAGS: ${SRCDIR}/build/linux/x86_64_static/libllama.a -lstdc++
// #cgo linux,arm64 LDFLAGS: ${SRCDIR}/build/linux/arm64_static/libllama.a -lstdc++
// #cgo CFLAGS: -Illama.cpp -Illama.cpp/include -Illama.cpp/ggml/include
// #cgo LDFLAGS: -lllama -lggml -lstdc++ -lpthread
// #cgo darwin,arm64 LDFLAGS: -L${SRCDIR}/build/darwin/arm64_static -L${SRCDIR}/build/darwin/arm64_static/src -L${SRCDIR}/build/darwin/arm64_static/ggml/src -framework Accelerate -framework Metal
// #cgo darwin,amd64 LDFLAGS: -L${SRCDIR}/build/darwin/x86_64_static -L${SRCDIR}/build/darwin/x86_64_static/src -L${SRCDIR}/build/darwin/x86_64_static/ggml/src
// #cgo windows,amd64 LDFLAGS: -static-libstdc++ -static-libgcc -static -L${SRCDIR}/build/windows/amd64_static -L${SRCDIR}/build/windows/amd64_static/src -L${SRCDIR}/build/windows/amd64_static/ggml/src
// #cgo windows,arm64 LDFLAGS: -static-libstdc++ -static-libgcc -static -L${SRCDIR}/build/windows/arm64_static -L${SRCDIR}/build/windows/arm64_static/src -L${SRCDIR}/build/windows/arm64_static/ggml/src
// #cgo linux,amd64 LDFLAGS: -L${SRCDIR}/build/linux/x86_64_static -L${SRCDIR}/build/linux/x86_64_static/src -L${SRCDIR}/build/linux/x86_64_static/ggml/src
// #cgo linux,arm64 LDFLAGS: -L${SRCDIR}/build/linux/arm64_static -L${SRCDIR}/build/linux/arm64_static/src -L${SRCDIR}/build/linux/arm64_static/ggml/src
// #include <stdlib.h>
// #include "llama.h"
import "C"
@@ -32,7 +33,7 @@ func Quantize(infile, outfile string, ftype fileType) error {
params.ftype = ftype.Value()
if rc := C.llama_model_quantize(cinfile, coutfile, &params); rc != 0 {
return fmt.Errorf("llama_model_quantize: %d", rc)
return fmt.Errorf("failed to quantize model. This model architecture may not be supported, or you may need to upgrade Ollama to the latest version")
}
return nil

View File

@@ -1,8 +1,8 @@
diff --git a/common/common.cpp b/common/common.cpp
index 73ff0e85..6adb1a92 100644
index 2c05a4d4..927f0e3d 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -2447,6 +2447,8 @@ struct llama_model_params llama_model_params_from_gpt_params(const gpt_params &
@@ -2093,6 +2093,8 @@ struct llama_model_params llama_model_params_from_gpt_params(const gpt_params &
mparams.use_mmap = params.use_mmap;
mparams.use_mlock = params.use_mlock;
mparams.check_tensors = params.check_tensors;
@@ -12,10 +12,10 @@ index 73ff0e85..6adb1a92 100644
mparams.kv_overrides = NULL;
} else {
diff --git a/common/common.h b/common/common.h
index 58ed72f4..0bb2605e 100644
index 65c0ef81..ebca2c77 100644
--- a/common/common.h
+++ b/common/common.h
@@ -180,6 +180,13 @@ struct gpt_params {
@@ -184,6 +184,13 @@ struct gpt_params {
std::string mmproj = ""; // path to multimodal projector
std::vector<std::string> image; // path to image file(s)
@@ -26,6 +26,6 @@ index 58ed72f4..0bb2605e 100644
+ // context pointer passed to the progress callback
+ void * progress_callback_user_data;
+
// server params
int32_t port = 8080; // server listens on this network port
int32_t timeout_read = 600; // http read timeout in seconds
// embedding
bool embedding = false; // get only sentence embedding
int32_t embd_normalize = 2; // normalisation for embendings (-1=none, 0=max absolute int16, 1=taxicab, 2=euclidean, >2=p-norm)

View File

@@ -1,17 +1,8 @@
From 544a2d2e646d39e878d87dfbb3398a356bc560ab Mon Sep 17 00:00:00 2001
From: Michael Yang <mxyng@pm.me>
Date: Thu, 23 May 2024 11:18:45 -0700
Subject: [PATCH] throw exception on load errors
---
llama.cpp | 25 ++++++++++++++++---------
1 file changed, 16 insertions(+), 9 deletions(-)
diff --git a/llama.cpp b/llama.cpp
index 15c66077..8ba90b6a 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -6346,7 +6346,7 @@ static int llama_model_load(const std::string & fname, llama_model & model, llam
diff --git a/src/llama.cpp b/src/llama.cpp
index 73f52435..58a00fb1 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -7241,7 +7241,7 @@ static int llama_model_load(const std::string & fname, llama_model & model, llam
}
} catch (const std::exception & err) {
LLAMA_LOG_ERROR("%s: error loading model: %s\n", __func__, err.what());
@@ -20,7 +11,7 @@ index 15c66077..8ba90b6a 100644
}
return 0;
@@ -15600,16 +15600,23 @@ struct llama_model * llama_load_model_from_file(
@@ -17564,16 +17564,23 @@ struct llama_model * llama_load_model_from_file(
}
model->rpc_servers.push_back(servers);
}
@@ -52,6 +43,3 @@ index 15c66077..8ba90b6a 100644
}
return model;
--
2.45.1

View File

@@ -1,7 +1,7 @@
diff --git a/ggml-metal.m b/ggml-metal.m
diff --git a/ggml/src/ggml-metal.m b/ggml/src/ggml-metal.m
index 0207b787..b5e9884b 100644
--- a/ggml-metal.m
+++ b/ggml-metal.m
--- a/ggml/src/ggml-metal.m
+++ b/ggml/src/ggml-metal.m
@@ -1396,27 +1396,23 @@ static enum ggml_status ggml_metal_graph_compute(
// to the matrix-vector kernel
int ne11_mm_min = 1;

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@@ -1,11 +1,11 @@
diff --git a/llama.cpp b/llama.cpp
index 61948751..4b72a293 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -4824,16 +4824,7 @@ static void llm_load_vocab(
// for now, only BPE models have pre-tokenizers
diff --git a/src/llama.cpp b/src/llama.cpp
index 2b9ace28..172640e2 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -5357,16 +5357,7 @@ static void llm_load_vocab(
if (vocab.type == LLAMA_VOCAB_TYPE_BPE) {
vocab.tokenizer_add_space_prefix = false;
vocab.tokenizer_clean_spaces = true;
- if (tokenizer_pre.empty()) {
- LLAMA_LOG_WARN("%s: missing pre-tokenizer type, using: 'default'\n", __func__);
- LLAMA_LOG_WARN("%s: \n", __func__);
@@ -20,13 +20,13 @@ index 61948751..4b72a293 100644
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
} else if (
tokenizer_pre == "llama3" ||
@@ -4888,7 +4879,8 @@ static void llm_load_vocab(
tokenizer_pre == "poro-chat") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_PORO;
@@ -5439,7 +5430,8 @@ static void llm_load_vocab(
tokenizer_pre == "jais") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_JAIS;
} else {
- throw std::runtime_error(format("unknown pre-tokenizer type: '%s'", tokenizer_pre.c_str()));
+ LLAMA_LOG_WARN("%s: missing or unrecognized pre-tokenizer type, using: 'default'\n", __func__);
+ vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
}
} else {
} else if (vocab.type == LLAMA_VOCAB_TYPE_SPM) {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;

View File

@@ -1,7 +1,7 @@
diff --git a/llama.cpp b/llama.cpp
diff --git a/src/llama.cpp b/src/llama.cpp
index 40d2ec2c..f34eb79a 100644
--- a/llama.cpp
+++ b/llama.cpp
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -6943,7 +6943,7 @@ static struct ggml_tensor * llm_build_kqv(
struct ggml_tensor * kq = ggml_mul_mat(ctx, k, q);
cb(kq, "kq", il);

View File

@@ -0,0 +1,45 @@
diff --git a/src/llama.cpp b/src/llama.cpp
index 1fe2b9f7..a43312a7 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -13689,7 +13689,7 @@ static size_t llama_output_reserve(llama_context & lctx, size_t n_outputs) {
const auto n_embd = hparams.n_embd;
// TODO: use a per-batch flag for logits presence instead
- const bool has_logits = !cparams.embeddings;
+ const bool has_logits = cparams.causal_attn;
const bool has_embd = lctx.is_encoding || (cparams.embeddings && (cparams.pooling_type == LLAMA_POOLING_TYPE_NONE));
const size_t logits_size = has_logits ? n_vocab*n_outputs_max : 0;
@@ -13959,17 +13959,25 @@ static int llama_decode_internal(
// no output
res = nullptr;
embd = nullptr;
- } else if (cparams.embeddings) {
- res = nullptr; // do not extract logits for embedding case
- embd = gf->nodes[gf->n_nodes - 1];
- if (strcmp(embd->name, "result_embd_pooled") != 0) {
- embd = gf->nodes[gf->n_nodes - 2];
+ }
+
+ if (cparams.embeddings) {
+ for (int i = gf->n_nodes - 1; i >= 0; --i) {
+ embd = gf->nodes[i];
+ if (strcmp(embd->name, "result_embd_pooled") == 0) {
+ break;
+ }
}
GGML_ASSERT(strcmp(embd->name, "result_embd_pooled") == 0 && "missing embeddings tensor");
- } else {
+ } else {
embd = nullptr; // do not extract embeddings when not needed
GGML_ASSERT(strcmp(res->name, "result_output") == 0 && "missing result_output tensor");
}
+
+ if (!cparams.causal_attn) {
+ res = nullptr; // do not extract logits when not needed
+ }
+
// LLAMA_LOG_INFO("graph build time: %.3f ms (%d nodes, %d leafs)\n", (ggml_time_us() - t_start_us)/1000.0, gf->n_nodes, gf->n_leafs);
ggml_backend_sched_alloc_graph(lctx.sched, gf);

View File

@@ -1,305 +0,0 @@
From 5cadb45f39d001ffbad95b690d6cf0abcb4a6d96 Mon Sep 17 00:00:00 2001
From: Ollama maintainers <hello@ollama.com>
Date: Wed, 26 Jun 2024 16:18:09 -0700
Subject: [PATCH] Architecture support
---
llama.cpp | 194 +++++++++++++++++++++++++++++++++++++++++++++++++++++-
1 file changed, 193 insertions(+), 1 deletion(-)
diff --git a/llama.cpp b/llama.cpp
index 61948751..3b4196f5 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -217,6 +217,7 @@ enum llm_arch {
LLM_ARCH_INTERNLM2,
LLM_ARCH_MINICPM,
LLM_ARCH_GEMMA,
+ LLM_ARCH_GEMMA2,
LLM_ARCH_STARCODER2,
LLM_ARCH_MAMBA,
LLM_ARCH_XVERSE,
@@ -255,6 +256,7 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
{ LLM_ARCH_INTERNLM2, "internlm2" },
{ LLM_ARCH_MINICPM, "minicpm" },
{ LLM_ARCH_GEMMA, "gemma" },
+ { LLM_ARCH_GEMMA2, "gemma2" },
{ LLM_ARCH_STARCODER2, "starcoder2" },
{ LLM_ARCH_MAMBA, "mamba" },
{ LLM_ARCH_XVERSE, "xverse" },
@@ -464,10 +466,12 @@ enum llm_tensor {
LLM_TENSOR_ATTN_NORM,
LLM_TENSOR_ATTN_NORM_2,
LLM_TENSOR_ATTN_OUT_NORM,
+ LLM_TENSOR_ATTN_POST_NORM,
LLM_TENSOR_ATTN_ROT_EMBD,
LLM_TENSOR_FFN_GATE_INP,
LLM_TENSOR_FFN_GATE_INP_SHEXP,
LLM_TENSOR_FFN_NORM,
+ LLM_TENSOR_FFN_POST_NORM,
LLM_TENSOR_FFN_GATE,
LLM_TENSOR_FFN_DOWN,
LLM_TENSOR_FFN_UP,
@@ -960,6 +964,24 @@ static const std::map<llm_arch, std::map<llm_tensor, std::string>> LLM_TENSOR_NA
{ LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },
},
},
+ {
+ LLM_ARCH_GEMMA2,
+ {
+ { LLM_TENSOR_TOKEN_EMBD, "token_embd" },
+ { LLM_TENSOR_OUTPUT_NORM, "output_norm" },
+ { LLM_TENSOR_ATTN_NORM, "blk.%d.attn_norm" },
+ { LLM_TENSOR_ATTN_Q, "blk.%d.attn_q" },
+ { LLM_TENSOR_ATTN_K, "blk.%d.attn_k" },
+ { LLM_TENSOR_ATTN_V, "blk.%d.attn_v" },
+ { LLM_TENSOR_ATTN_OUT, "blk.%d.attn_output" },
+ { LLM_TENSOR_ATTN_POST_NORM, "blk.%d.post_attention_norm" },
+ { LLM_TENSOR_FFN_NORM, "blk.%d.ffn_norm" },
+ { LLM_TENSOR_FFN_GATE, "blk.%d.ffn_gate" },
+ { LLM_TENSOR_FFN_DOWN, "blk.%d.ffn_down" },
+ { LLM_TENSOR_FFN_UP, "blk.%d.ffn_up" },
+ { LLM_TENSOR_FFN_POST_NORM, "blk.%d.post_ffw_norm" },
+ },
+ },
{
LLM_ARCH_STARCODER2,
{
@@ -1941,6 +1963,8 @@ enum e_model {
MODEL_8x22B,
MODEL_16x12B,
MODEL_10B_128x3_66B,
+ MODEL_9B,
+ MODEL_27B,
};
static const size_t kiB = 1024;
@@ -2114,6 +2138,7 @@ struct llama_layer {
struct ggml_tensor * attn_out_norm_b;
struct ggml_tensor * attn_q_a_norm;
struct ggml_tensor * attn_kv_a_norm;
+ struct ggml_tensor * attn_post_norm;
// attention
struct ggml_tensor * wq;
@@ -2136,6 +2161,7 @@ struct llama_layer {
// normalization
struct ggml_tensor * ffn_norm;
struct ggml_tensor * ffn_norm_b;
+ struct ggml_tensor * ffn_post_norm;
struct ggml_tensor * layer_out_norm;
struct ggml_tensor * layer_out_norm_b;
struct ggml_tensor * ffn_norm_exps;
@@ -4529,6 +4555,16 @@ static void llm_load_hparams(
}
} break;
case LLM_ARCH_GEMMA:
+ {
+ ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);
+
+ switch (hparams.n_layer) {
+ case 18: model.type = e_model::MODEL_9B; break;
+ case 28: model.type = e_model::MODEL_27B; break;
+ default: model.type = e_model::MODEL_UNKNOWN;
+ }
+ } break;
+ case LLM_ARCH_GEMMA2:
{
ml.get_key(LLM_KV_ATTENTION_LAYERNORM_RMS_EPS, hparams.f_norm_rms_eps);
@@ -6305,6 +6341,40 @@ static bool llm_load_tensors(
layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), { n_ff, n_embd});
}
} break;
+ case LLM_ARCH_GEMMA2:
+ {
+ model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
+
+ // output
+ model.output_norm = ml.create_tensor(ctx_output, tn(LLM_TENSOR_OUTPUT_NORM, "weight"), {n_embd});
+ model.output = ml.create_tensor(ctx_output, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, llama_model_loader::TENSOR_DUPLICATED); // same as tok_embd, duplicated to allow offloading
+
+ const int64_t n_ff = hparams.n_ff;
+ const int64_t n_embd_head_k = hparams.n_embd_head_k;
+ const int64_t n_embd_k_gqa = hparams.n_embd_k_gqa();
+ const int64_t n_embd_v_gqa = hparams.n_embd_v_gqa();
+
+ for (uint32_t i = 0; i < n_layer; ++i) {
+ ggml_context * ctx_layer = ctx_for_layer(i);
+ ggml_context * ctx_split = ctx_for_layer_split(i);
+
+ auto & layer = model.layers[i];
+
+ layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
+
+ layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q, "weight", i), {n_embd, n_embd_head_k * hparams.n_head});
+ layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K, "weight", i), {n_embd, n_embd_k_gqa});
+ layer.wv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V, "weight", i), {n_embd, n_embd_v_gqa});
+ layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd_head_k * hparams.n_head, n_embd});
+ layer.attn_post_norm = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_POST_NORM, "weight", i), {n_embd});
+
+ layer.ffn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_NORM, "weight", i), {n_embd});
+ layer.ffn_gate = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_GATE, "weight", i), {n_embd, n_ff});
+ layer.ffn_up = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_UP, "weight", i), {n_embd, n_ff});
+ layer.ffn_down = ml.create_tensor(ctx_split, tn(LLM_TENSOR_FFN_DOWN, "weight", i), { n_ff, n_embd});
+ layer.ffn_post_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_FFN_POST_NORM, "weight", i), {n_embd});
+ }
+ } break;
case LLM_ARCH_STARCODER2:
{
model.tok_embd = ml.create_tensor(ctx_input, tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab});
@@ -10614,6 +10684,123 @@ struct llm_build_context {
return gf;
}
+ struct ggml_cgraph * build_gemma2() {
+ struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
+
+ const int64_t n_embd_head_k = hparams.n_embd_head_k;
+
+ struct ggml_tensor * cur;
+ struct ggml_tensor * inpL;
+
+ inpL = llm_build_inp_embd(ctx0, lctx, hparams, batch, model.tok_embd, cb);
+
+ inpL = ggml_scale(ctx0, inpL, sqrtf(n_embd));
+ cb(inpL, "inp_scaled", -1);
+
+ // inp_pos - contains the positions
+ struct ggml_tensor * inp_pos = build_inp_pos();
+
+ // KQ_mask (mask for 1 head, it will be broadcasted to all heads)
+ struct ggml_tensor * KQ_mask = build_inp_KQ_mask();
+
+ for (int il = 0; il < n_layer; ++il) {
+ // norm
+ cur = llm_build_norm(ctx0, inpL, hparams,
+ model.layers[il].attn_norm, NULL,
+ LLM_NORM_RMS, cb, il);
+ cb(cur, "attn_norm", il);
+
+ // self-attention
+ {
+ // compute Q and K and RoPE them
+ struct ggml_tensor * Qcur = ggml_mul_mat(ctx0, model.layers[il].wq, cur);
+ cb(Qcur, "Qcur", il);
+
+ struct ggml_tensor * Kcur = ggml_mul_mat(ctx0, model.layers[il].wk, cur);
+ cb(Kcur, "Kcur", il);
+
+ struct ggml_tensor * Vcur = ggml_mul_mat(ctx0, model.layers[il].wv, cur);
+ cb(Vcur, "Vcur", il);
+
+ Qcur = ggml_rope_ext(
+ ctx0, ggml_reshape_3d(ctx0, Qcur, n_embd_head_k, n_head, n_tokens), inp_pos, nullptr,
+ n_embd_head_k, rope_type, n_ctx_orig, freq_base, freq_scale,
+ ext_factor, attn_factor, beta_fast, beta_slow);
+ cb(Qcur, "Qcur", il);
+
+ Qcur = ggml_scale(ctx0, Qcur, 1.0f / sqrtf(float(n_embd_head_k)));
+ cb(Qcur, "Qcur_scaled", il);
+
+ Kcur = ggml_rope_ext(
+ ctx0, ggml_reshape_3d(ctx0, Kcur, n_embd_head_k, n_head_kv, n_tokens), inp_pos, nullptr,
+ n_embd_head_k, rope_type, n_ctx_orig, freq_base, freq_scale,
+ ext_factor, attn_factor, beta_fast, beta_slow);
+ cb(Kcur, "Kcur", il);
+
+ cur = llm_build_kv(ctx0, model, hparams, cparams, kv_self, gf,
+ model.layers[il].wo, NULL,
+ Kcur, Vcur, Qcur, KQ_mask, n_tokens, kv_head, n_kv, 1.0f, cb, il);
+ }
+
+ if (il == n_layer - 1) {
+ // skip computing output for unused tokens
+ struct ggml_tensor * inp_out_ids = build_inp_out_ids();
+ cur = ggml_get_rows(ctx0, cur, inp_out_ids);
+ inpL = ggml_get_rows(ctx0, inpL, inp_out_ids);
+ }
+
+ cur = llm_build_norm(ctx0, cur, hparams,
+ model.layers[il].attn_post_norm, NULL,
+ LLM_NORM_RMS, cb, il);
+ cb(cur, "attn_post_norm", il);
+
+ struct ggml_tensor * sa_out = ggml_add(ctx0, cur, inpL);
+ cb(sa_out, "sa_out", il);
+
+ cur = llm_build_norm(ctx0, sa_out, hparams,
+ model.layers[il].ffn_norm, NULL,
+ LLM_NORM_RMS, cb, il);
+ cb(cur, "ffn_norm", il);
+
+ // feed-forward network
+ {
+ cur = llm_build_ffn(ctx0, cur,
+ model.layers[il].ffn_up, NULL,
+ model.layers[il].ffn_gate, NULL,
+ model.layers[il].ffn_down, NULL,
+ NULL,
+ LLM_FFN_GELU, LLM_FFN_PAR, cb, il);
+ cb(cur, "ffn_out", il);
+ }
+
+ cur = llm_build_norm(ctx0, cur, hparams,
+ model.layers[il].ffn_post_norm, NULL,
+ LLM_NORM_RMS, cb, -1);
+ cb(cur, "ffn_post_norm", -1);
+
+ cur = ggml_add(ctx0, cur, sa_out);
+ cb(cur, "l_out", il);
+
+ // input for next layer
+ inpL = cur;
+ }
+
+ cur = inpL;
+
+ cur = llm_build_norm(ctx0, cur, hparams,
+ model.output_norm, NULL,
+ LLM_NORM_RMS, cb, -1);
+ cb(cur, "result_norm", -1);
+
+ // lm_head
+ cur = ggml_mul_mat(ctx0, model.output, cur);
+ cb(cur, "result_output", -1);
+
+ ggml_build_forward_expand(gf, cur);
+
+ return gf;
+ }
+
struct ggml_cgraph * build_starcoder2() {
struct ggml_cgraph * gf = ggml_new_graph_custom(ctx0, LLAMA_MAX_NODES, false);
@@ -11847,6 +12034,10 @@ static struct ggml_cgraph * llama_build_graph(
{
result = llm.build_gemma();
} break;
+ case LLM_ARCH_GEMMA2:
+ {
+ result = llm.build_gemma2();
+ } break;
case LLM_ARCH_STARCODER2:
{
result = llm.build_starcoder2();
@@ -16671,6 +16862,7 @@ enum llama_rope_type llama_rope_type(const struct llama_model * model) {
case LLM_ARCH_PHI2:
case LLM_ARCH_PHI3:
case LLM_ARCH_GEMMA:
+ case LLM_ARCH_GEMMA2:
case LLM_ARCH_STARCODER2:
case LLM_ARCH_GPTNEOX:
return LLAMA_ROPE_TYPE_NEOX;
@@ -18551,7 +18743,7 @@ static int32_t llama_chat_apply_template_internal(
if (add_ass) {
ss << "<s>assistant\n";
}
- } else if (tmpl == "gemma" || tmpl.find("<start_of_turn>") != std::string::npos) {
+ } else if (tmpl == "gemma" || tmpl == "gemma2" || tmpl.find("<start_of_turn>") != std::string::npos) {
// google/gemma-7b-it
std::string system_prompt = "";
for (auto message : chat) {
--
2.45.2

View File

@@ -0,0 +1,42 @@
diff --git a/examples/llava/clip.cpp b/examples/llava/clip.cpp
index 95fbe3d0..5a02a6ec 100644
--- a/examples/llava/clip.cpp
+++ b/examples/llava/clip.cpp
@@ -32,6 +33,14 @@
#include <cinttypes>
#include <limits>
+#if defined(_WIN32)
+#define WIN32_LEAN_AND_MEAN
+#ifndef NOMINMAX
+ #define NOMINMAX
+#endif
+#include <windows.h>
+#endif
+
//#define CLIP_DEBUG_FUNCTIONS
// RGB uint8 image
@@ -1055,7 +1064,22 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) {
return nullptr;
}
+#ifdef _WIN32
+ int wlen = MultiByteToWideChar(CP_UTF8, 0, fname, -1, NULL, 0);
+ if (!wlen) {
+ return NULL;
+ }
+ wchar_t * wbuf = (wchar_t *) malloc(wlen * sizeof(wchar_t));
+ wlen = MultiByteToWideChar(CP_UTF8, 0, fname, -1, wbuf, wlen);
+ if (!wlen) {
+ free(wbuf);
+ return NULL;
+ }
+ auto fin = std::ifstream(wbuf, std::ios::binary);
+ free(wbuf);
+#else
auto fin = std::ifstream(fname, std::ios::binary);
+#endif
if (!fin) {
LOG_TEE("cannot open model file for loading tensors\n");
clip_free(new_clip);

View File

@@ -0,0 +1,60 @@
diff --git a/src/llama.cpp b/src/llama.cpp
index 721b8f4e..cfe7ac40 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -8420,14 +8420,14 @@ struct llm_build_context {
}
struct ggml_tensor * build_inp_mean() {
- lctx.inp_mean = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_tokens, n_tokens);
+ lctx.inp_mean = ggml_new_tensor_2d(ctx0, GGML_TYPE_F32, n_tokens, cparams.n_seq_max);
cb(lctx.inp_mean, "inp_mean", -1);
ggml_set_input(lctx.inp_mean);
return lctx.inp_mean;
}
struct ggml_tensor * build_inp_cls() {
- lctx.inp_cls = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, n_tokens);
+ lctx.inp_cls = ggml_new_tensor_1d(ctx0, GGML_TYPE_I32, cparams.n_seq_max);
cb(lctx.inp_cls, "inp_cls", -1);
ggml_set_input(lctx.inp_cls);
return lctx.inp_cls;
@@ -13847,19 +13847,16 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) {
GGML_ASSERT(ggml_backend_buffer_is_host(lctx.inp_mean->buffer));
float * data = (float *) lctx.inp_mean->data;
- memset(lctx.inp_mean->data, 0, n_tokens * n_tokens * ggml_element_size(lctx.inp_mean));
+ memset(lctx.inp_mean->data, 0, n_tokens * cparams.n_seq_max * ggml_element_size(lctx.inp_mean));
std::vector<uint64_t> sum(n_tokens, 0);
for (int i = 0; i < n_tokens; ++i) {
const llama_seq_id seq_id = batch.seq_id[i][0];
-
- GGML_ASSERT(seq_id < n_tokens && "seq_id cannot be larger than n_tokens with pooling_type == MEAN");
-
sum[seq_id] += 1;
}
- std::vector<float> div(n_tokens, 0.0f);
- for (int i = 0; i < n_tokens; ++i) {
+ std::vector<float> div(cparams.n_seq_max, 0.0f);
+ for (uint32_t i = 0; i < cparams.n_seq_max; ++i) {
const uint64_t s = sum[i];
if (s > 0) {
div[i] = 1.0f/float(s);
@@ -13879,14 +13876,11 @@ static void llama_set_inputs(llama_context & lctx, const llama_batch & batch) {
GGML_ASSERT(ggml_backend_buffer_is_host(lctx.inp_cls->buffer));
uint32_t * data = (uint32_t *) lctx.inp_cls->data;
- memset(lctx.inp_cls->data, 0, n_tokens * ggml_element_size(lctx.inp_cls));
+ memset(lctx.inp_cls->data, 0, cparams.n_seq_max * ggml_element_size(lctx.inp_cls));
for (int i = 0; i < n_tokens; ++i) {
const llama_seq_id seq_id = batch.seq_id[i][0];
const llama_pos pos = batch.pos[i];
-
- GGML_ASSERT(seq_id < n_tokens && "seq_id cannot be larger than n_tokens with pooling_type == CLS");
-
if (pos == 0) {
data[seq_id] = i;
}

View File

@@ -0,0 +1,43 @@
diff --git a/include/llama.h b/include/llama.h
index bb4b05ba..a92174e0 100644
--- a/include/llama.h
+++ b/include/llama.h
@@ -92,6 +92,7 @@ extern "C" {
LLAMA_VOCAB_PRE_TYPE_CHATGLM4 = 17,
LLAMA_VOCAB_PRE_TYPE_VIKING = 18,
LLAMA_VOCAB_PRE_TYPE_JAIS = 19,
+ LLAMA_VOCAB_PRE_TYPE_TEKKEN = 20,
};
// note: these values should be synchronized with ggml_rope
diff --git a/src/llama.cpp b/src/llama.cpp
index 18364976..435b6fe5 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -5429,6 +5429,12 @@ static void llm_load_vocab(
} else if (
tokenizer_pre == "jais") {
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_JAIS;
+ } else if (
+ tokenizer_pre == "tekken") {
+ vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_TEKKEN;
+ vocab.tokenizer_clean_spaces = false;
+ vocab.tokenizer_ignore_merges = true;
+ vocab.tokenizer_add_bos = true;
} else {
LLAMA_LOG_WARN("%s: missing or unrecognized pre-tokenizer type, using: 'default'\n", __func__);
vocab.type_pre = LLAMA_VOCAB_PRE_TYPE_DEFAULT;
@@ -15448,6 +15454,13 @@ struct llm_tokenizer_bpe {
" ?[^(\\s|.,!?…。,、।۔،)]+",
};
break;
+ case LLAMA_VOCAB_PRE_TYPE_TEKKEN:
+ // original regex from tokenizer.json
+ // "[^\\r\\n\\p{L}\\p{N}]?[\\p{Lu}\\p{Lt}\\p{Lm}\\p{Lo}\\p{M}]*[\\p{Ll}\\p{Lm}\\p{Lo}\\p{M}]+|[^\\r\\n\\p{L}\\p{N}]?[\\p{Lu}\\p{Lt}\\p{Lm}\\p{Lo}\\p{M}]+[\\p{Ll}\\p{Lm}\\p{Lo}\\p{M}]*|\\p{N}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n/]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+"
+ regex_exprs = {
+ "[^\\r\\n\\p{L}\\p{N}]?((?=[\\p{L}])([^a-z]))*((?=[\\p{L}])([^A-Z]))+|[^\\r\\n\\p{L}\\p{N}]?((?=[\\p{L}])([^a-z]))+((?=[\\p{L}])([^A-Z]))*|\\p{N}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n/]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
+ };
+ break;
default:
// default regex for BPE tokenization pre-processing
regex_exprs = {

View File

@@ -0,0 +1,19 @@
diff --git a/src/llama.cpp b/src/llama.cpp
index 2b9ace28..e60d3d8d 100644
--- a/src/llama.cpp
+++ b/src/llama.cpp
@@ -6052,10 +6052,10 @@ static bool llm_load_tensors(
layer.attn_norm = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_NORM, "weight", i), {n_embd});
- layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q, "weight", i), {n_embd, n_embd});
- layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K, "weight", i), {n_embd, n_embd_gqa});
- layer.wv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V, "weight", i), {n_embd, n_embd_gqa});
- layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd, n_embd});
+ layer.wq = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_Q, "weight", i), {n_embd, n_embd_head_k * n_head});
+ layer.wk = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_K, "weight", i), {n_embd, n_embd_k_gqa});
+ layer.wv = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_V, "weight", i), {n_embd, n_embd_v_gqa});
+ layer.wo = ml.create_tensor(ctx_split, tn(LLM_TENSOR_ATTN_OUT, "weight", i), {n_embd_head_k * n_head, n_embd});
// optional bias tensors
layer.bq = ml.create_tensor(ctx_layer, tn(LLM_TENSOR_ATTN_Q, "bias", i), {n_embd}, llama_model_loader::TENSOR_NOT_REQUIRED);

View File

@@ -38,7 +38,7 @@ func Init() error {
}
var variants []string
for v := range availableServers() {
for v := range getAvailableServers() {
variants = append(variants, v)
}
slog.Info(fmt.Sprintf("Dynamic LLM libraries %v", variants))
@@ -50,7 +50,7 @@ func Init() error {
// binary names may contain an optional variant separated by '_'
// For example, "ollama_rocm_v6" and "ollama_rocm_v5" or "ollama_cpu" and "ollama_cpu_avx2"
// Any library without a variant is the lowest common denominator
func availableServers() map[string]string {
func getAvailableServers() map[string]string {
payloadsDir, err := gpu.PayloadsDir()
if err != nil {
slog.Error("payload lookup error", "error", err)
@@ -80,7 +80,7 @@ func availableServers() map[string]string {
// TODO - switch to metadata based mapping
func serversForGpu(info gpu.GpuInfo) []string {
// glob workDir for files that start with ollama_
availableServers := availableServers()
availableServers := getAvailableServers()
requested := info.Library
if info.Variant != gpu.CPUCapabilityNone {
requested += "_" + info.Variant.String()
@@ -115,27 +115,29 @@ func serversForGpu(info gpu.GpuInfo) []string {
servers = append(servers, alt...)
}
// Load up the best CPU variant if not primary requested
if info.Library != "cpu" {
variant := gpu.GetCPUCapability()
// If no variant, then we fall back to default
// If we have a variant, try that if we find an exact match
// Attempting to run the wrong CPU instructions will panic the
// process
if variant != gpu.CPUCapabilityNone {
for cmp := range availableServers {
if cmp == "cpu_"+variant.String() {
servers = append(servers, cmp)
break
if !(runtime.GOOS == "darwin" && runtime.GOARCH == "arm64") {
// Load up the best CPU variant if not primary requested
if info.Library != "cpu" {
variant := gpu.GetCPUCapability()
// If no variant, then we fall back to default
// If we have a variant, try that if we find an exact match
// Attempting to run the wrong CPU instructions will panic the
// process
if variant != gpu.CPUCapabilityNone {
for cmp := range availableServers {
if cmp == "cpu_"+variant.String() {
servers = append(servers, cmp)
break
}
}
} else {
servers = append(servers, "cpu")
}
} else {
servers = append(servers, "cpu")
}
}
if len(servers) == 0 {
servers = []string{"cpu"}
if len(servers) == 0 {
servers = []string{"cpu"}
}
}
return servers
@@ -147,7 +149,7 @@ func serverForCpu() string {
return "metal"
}
variant := gpu.GetCPUCapability()
availableServers := availableServers()
availableServers := getAvailableServers()
if variant != gpu.CPUCapabilityNone {
for cmp := range availableServers {
if cmp == "cpu_"+variant.String() {

View File

@@ -33,7 +33,7 @@ type LlamaServer interface {
Ping(ctx context.Context) error
WaitUntilRunning(ctx context.Context) error
Completion(ctx context.Context, req CompletionRequest, fn func(CompletionResponse)) error
Embedding(ctx context.Context, prompt string) ([]float64, error)
Embed(ctx context.Context, input []string) ([][]float32, error)
Tokenize(ctx context.Context, content string) ([]int, error)
Detokenize(ctx context.Context, tokens []int) (string, error)
Close() error
@@ -82,12 +82,13 @@ func LoadModel(model string, maxArraySize int) (*GGML, error) {
// NewLlamaServer will run a server for the given GPUs
// The gpu list must be a single family.
func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, projectors []string, opts api.Options) (LlamaServer, error) {
func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, projectors []string, opts api.Options, numParallel int) (LlamaServer, error) {
var err error
var cpuRunner string
var estimate MemoryEstimate
var systemTotalMemory uint64
var systemFreeMemory uint64
var systemSwapFreeMemory uint64
systemMemInfo, err := gpu.GetCPUMem()
if err != nil {
@@ -95,7 +96,8 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
} else {
systemTotalMemory = systemMemInfo.TotalMemory
systemFreeMemory = systemMemInfo.FreeMemory
slog.Debug("system memory", "total", format.HumanBytes2(systemTotalMemory), "free", systemFreeMemory)
systemSwapFreeMemory = systemMemInfo.FreeSwap
slog.Debug("system memory", "total", format.HumanBytes2(systemTotalMemory), "free", format.HumanBytes2(systemFreeMemory), "free_swap", format.HumanBytes2(systemSwapFreeMemory))
}
// If the user wants zero GPU layers, reset the gpu list to be CPU/system ram info
@@ -122,6 +124,16 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
}
}
// On linux, over-allocating CPU memory will almost always result in an error
if runtime.GOOS == "linux" {
systemMemoryRequired := estimate.TotalSize - estimate.VRAMSize
available := systemFreeMemory + systemSwapFreeMemory
if systemMemoryRequired > available {
slog.Warn("model request too large for system", "requested", format.HumanBytes2(systemMemoryRequired), "available", available, "total", format.HumanBytes2(systemTotalMemory), "free", format.HumanBytes2(systemFreeMemory), "swap", format.HumanBytes2(systemSwapFreeMemory))
return nil, fmt.Errorf("model requires more system memory (%s) than is available (%s)", format.HumanBytes2(systemMemoryRequired), format.HumanBytes2(available))
}
}
estimate.log()
// Loop through potential servers
@@ -131,7 +143,20 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
return nil, errors.New("ollama supports only one lora adapter, but multiple were provided")
}
availableServers := availableServers()
availableServers := getAvailableServers()
if len(availableServers) == 0 {
if runtime.GOOS != "windows" {
slog.Warn("llama server binary disappeared, reinitializing payloads")
err = Init()
if err != nil {
slog.Warn("failed to reinitialize payloads", "error", err)
return nil, err
}
availableServers = getAvailableServers()
} else {
return nil, finalErr
}
}
var servers []string
if cpuRunner != "" {
servers = []string{cpuRunner}
@@ -166,8 +191,6 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
params = append(params, "--log-disable")
params = append(params, "--timeout", fmt.Sprintf("%d", 600))
if opts.NumGPU >= 0 {
params = append(params, "--n-gpu-layers", fmt.Sprintf("%d", opts.NumGPU))
}
@@ -210,7 +233,8 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
if g.Library == "metal" &&
uint64(opts.NumGPU) > 0 &&
uint64(opts.NumGPU) < ggml.KV().BlockCount()+1 {
opts.UseMMap = api.TriStateFalse
opts.UseMMap = new(bool)
*opts.UseMMap = false
}
}
@@ -220,9 +244,11 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
// Windows CUDA should not use mmap for best performance
// Linux with a model larger than free space, mmap leads to thrashing
if (runtime.GOOS == "windows" && gpus[0].Library == "cuda" && opts.UseMMap == api.TriStateUndefined) ||
(runtime.GOOS == "linux" && systemFreeMemory < estimate.TotalSize && opts.UseMMap == api.TriStateUndefined) ||
opts.UseMMap == api.TriStateFalse {
// For CPU loads we want the memory to be allocated, not FS cache
if (runtime.GOOS == "windows" && gpus[0].Library == "cuda" && opts.UseMMap == nil) ||
(runtime.GOOS == "linux" && systemFreeMemory < estimate.TotalSize && opts.UseMMap == nil) ||
(gpus[0].Library == "cpu" && opts.UseMMap == nil) ||
(opts.UseMMap != nil && !*opts.UseMMap) {
params = append(params, "--no-mmap")
}
@@ -234,25 +260,12 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
params = append(params, "--numa")
}
numParallel := envconfig.NumParallel
// TODO (jmorganca): multimodal models don't support parallel yet
// see https://github.com/ollama/ollama/issues/4165
if len(projectors) > 0 {
numParallel = 1
slog.Warn("multimodal models don't support parallel requests yet")
}
params = append(params, "--parallel", fmt.Sprintf("%d", numParallel))
if estimate.TensorSplit != "" {
params = append(params, "--tensor-split", estimate.TensorSplit)
}
if estimate.TensorSplit != "" {
params = append(params, "--tensor-split", estimate.TensorSplit)
}
for i := range len(servers) {
dir := availableServers[servers[i]]
if dir == "" {
@@ -372,8 +385,10 @@ func NewLlamaServer(gpus gpu.GpuInfoList, model string, ggml *GGML, adapters, pr
filteredEnv := []string{}
for _, ev := range s.cmd.Env {
if strings.HasPrefix(ev, "CUDA_") ||
strings.HasPrefix(ev, "ROCR_") ||
strings.HasPrefix(ev, "ROCM_") ||
strings.HasPrefix(ev, "HIP_") ||
strings.HasPrefix(ev, "GPU_") ||
strings.HasPrefix(ev, "HSA_") ||
strings.HasPrefix(ev, "GGML_") ||
strings.HasPrefix(ev, "PATH=") ||
@@ -569,6 +584,9 @@ func (s *llmServer) WaitUntilRunning(ctx context.Context) error {
if s.status != nil && s.status.LastErrMsg != "" {
msg = s.status.LastErrMsg
}
if strings.Contains(msg, "unknown model") {
return fmt.Errorf("this model is not supported by your version of Ollama. You may need to upgrade")
}
return fmt.Errorf("llama runner process has terminated: %v %s", err, msg)
default:
}
@@ -671,7 +689,7 @@ type CompletionRequest struct {
Prompt string
Format string
Images []ImageData
Options api.Options
Options *api.Options
}
type CompletionResponse struct {
@@ -691,10 +709,9 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
}
defer s.sem.Release(1)
// only allow maximum 10 "context shifts" to avoid infinite generation
// put an upper limit on num_predict to avoid the model running on forever
if req.Options.NumPredict < 0 || req.Options.NumPredict > 10*s.options.NumCtx {
req.Options.NumPredict = 10 * s.options.NumCtx
slog.Debug("setting token limit to 10x num_ctx", "num_ctx", s.options.NumCtx, "num_predict", req.Options.NumPredict)
}
request := map[string]any{
@@ -852,15 +869,15 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
return nil
}
type EmbeddingRequest struct {
Content string `json:"content"`
type EmbedRequest struct {
Content []string `json:"content"`
}
type EmbeddingResponse struct {
Embedding []float64 `json:"embedding"`
type EmbedResponse struct {
Embedding [][]float32 `json:"embedding"`
}
func (s *llmServer) Embedding(ctx context.Context, prompt string) ([]float64, error) {
func (s *llmServer) Embed(ctx context.Context, input []string) ([][]float32, error) {
if err := s.sem.Acquire(ctx, 1); err != nil {
slog.Error("Failed to acquire semaphore", "error", err)
return nil, err
@@ -875,7 +892,7 @@ func (s *llmServer) Embedding(ctx context.Context, prompt string) ([]float64, er
return nil, fmt.Errorf("unexpected server status: %s", status.ToString())
}
data, err := json.Marshal(TokenizeRequest{Content: prompt})
data, err := json.Marshal(EmbedRequest{Content: input})
if err != nil {
return nil, fmt.Errorf("error marshaling embed data: %w", err)
}
@@ -902,7 +919,7 @@ func (s *llmServer) Embedding(ctx context.Context, prompt string) ([]float64, er
return nil, fmt.Errorf("%s", body)
}
var embedding EmbeddingResponse
var embedding EmbedResponse
if err := json.Unmarshal(body, &embedding); err != nil {
return nil, fmt.Errorf("unmarshal tokenize response: %w", err)
}

View File

@@ -25,6 +25,7 @@ var errorPrefixes = []string{
"CUDA error",
"cudaMalloc failed",
"\"ERR\"",
"error loading model",
}
func (w *StatusWriter) Write(b []byte) (int, error) {

View File

@@ -3,15 +3,19 @@ package openai
import (
"bytes"
"encoding/base64"
"encoding/json"
"fmt"
"io"
"log/slog"
"math/rand"
"net/http"
"strings"
"time"
"github.com/gin-gonic/gin"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/types/model"
)
type Error struct {
@@ -26,8 +30,9 @@ type ErrorResponse struct {
}
type Message struct {
Role string `json:"role"`
Content string `json:"content"`
Role string `json:"role"`
Content any `json:"content"`
ToolCalls []ToolCall `json:"tool_calls,omitempty"`
}
type Choice struct {
@@ -42,6 +47,12 @@ type ChunkChoice struct {
FinishReason *string `json:"finish_reason"`
}
type CompleteChunkChoice struct {
Text string `json:"text"`
Index int `json:"index"`
FinishReason *string `json:"finish_reason"`
}
type Usage struct {
PromptTokens int `json:"prompt_tokens"`
CompletionTokens int `json:"completion_tokens"`
@@ -52,6 +63,11 @@ type ResponseFormat struct {
Type string `json:"type"`
}
type EmbedRequest struct {
Input any `json:"input"`
Model string `json:"model"`
}
type ChatCompletionRequest struct {
Model string `json:"model"`
Messages []Message `json:"messages"`
@@ -64,6 +80,7 @@ type ChatCompletionRequest struct {
PresencePenalty *float64 `json:"presence_penalty_penalty"`
TopP *float64 `json:"top_p"`
ResponseFormat *ResponseFormat `json:"response_format"`
Tools []api.Tool `json:"tools"`
}
type ChatCompletion struct {
@@ -85,6 +102,73 @@ type ChatCompletionChunk struct {
Choices []ChunkChoice `json:"choices"`
}
// TODO (https://github.com/ollama/ollama/issues/5259): support []string, []int and [][]int
type CompletionRequest struct {
Model string `json:"model"`
Prompt string `json:"prompt"`
FrequencyPenalty float32 `json:"frequency_penalty"`
MaxTokens *int `json:"max_tokens"`
PresencePenalty float32 `json:"presence_penalty"`
Seed *int `json:"seed"`
Stop any `json:"stop"`
Stream bool `json:"stream"`
Temperature *float32 `json:"temperature"`
TopP float32 `json:"top_p"`
Suffix string `json:"suffix"`
}
type Completion struct {
Id string `json:"id"`
Object string `json:"object"`
Created int64 `json:"created"`
Model string `json:"model"`
SystemFingerprint string `json:"system_fingerprint"`
Choices []CompleteChunkChoice `json:"choices"`
Usage Usage `json:"usage,omitempty"`
}
type CompletionChunk struct {
Id string `json:"id"`
Object string `json:"object"`
Created int64 `json:"created"`
Choices []CompleteChunkChoice `json:"choices"`
Model string `json:"model"`
SystemFingerprint string `json:"system_fingerprint"`
}
type ToolCall struct {
ID string `json:"id"`
Type string `json:"type"`
Function struct {
Name string `json:"name"`
Arguments string `json:"arguments"`
} `json:"function"`
}
type Model struct {
Id string `json:"id"`
Object string `json:"object"`
Created int64 `json:"created"`
OwnedBy string `json:"owned_by"`
}
type Embedding struct {
Object string `json:"object"`
Embedding []float32 `json:"embedding"`
Index int `json:"index"`
}
type ListCompletion struct {
Object string `json:"object"`
Data []Model `json:"data"`
}
type EmbeddingList struct {
Object string `json:"object"`
Data []Embedding `json:"data"`
Model string `json:"model"`
}
func NewError(code int, message string) ErrorResponse {
var etype string
switch code {
@@ -99,7 +183,31 @@ func NewError(code int, message string) ErrorResponse {
return ErrorResponse{Error{Type: etype, Message: message}}
}
func toolCallId() string {
const letterBytes = "abcdefghijklmnopqrstuvwxyz0123456789"
b := make([]byte, 8)
for i := range b {
b[i] = letterBytes[rand.Intn(len(letterBytes))]
}
return "call_" + strings.ToLower(string(b))
}
func toChatCompletion(id string, r api.ChatResponse) ChatCompletion {
toolCalls := make([]ToolCall, len(r.Message.ToolCalls))
for i, tc := range r.Message.ToolCalls {
toolCalls[i].ID = toolCallId()
toolCalls[i].Type = "function"
toolCalls[i].Function.Name = tc.Function.Name
args, err := json.Marshal(tc.Function.Arguments)
if err != nil {
slog.Error("could not marshall function arguments to json", "error", err)
continue
}
toolCalls[i].Function.Arguments = string(args)
}
return ChatCompletion{
Id: id,
Object: "chat.completion",
@@ -108,7 +216,7 @@ func toChatCompletion(id string, r api.ChatResponse) ChatCompletion {
SystemFingerprint: "fp_ollama",
Choices: []Choice{{
Index: 0,
Message: Message{Role: r.Message.Role, Content: r.Message.Content},
Message: Message{Role: r.Message.Role, Content: r.Message.Content, ToolCalls: toolCalls},
FinishReason: func(reason string) *string {
if len(reason) > 0 {
return &reason
@@ -117,7 +225,6 @@ func toChatCompletion(id string, r api.ChatResponse) ChatCompletion {
}(r.DoneReason),
}},
Usage: Usage{
// TODO: ollama returns 0 for prompt eval if the prompt was cached, but openai returns the actual count
PromptTokens: r.PromptEvalCount,
CompletionTokens: r.EvalCount,
TotalTokens: r.PromptEvalCount + r.EvalCount,
@@ -145,10 +252,169 @@ func toChunk(id string, r api.ChatResponse) ChatCompletionChunk {
}
}
func fromRequest(r ChatCompletionRequest) api.ChatRequest {
func toCompletion(id string, r api.GenerateResponse) Completion {
return Completion{
Id: id,
Object: "text_completion",
Created: r.CreatedAt.Unix(),
Model: r.Model,
SystemFingerprint: "fp_ollama",
Choices: []CompleteChunkChoice{{
Text: r.Response,
Index: 0,
FinishReason: func(reason string) *string {
if len(reason) > 0 {
return &reason
}
return nil
}(r.DoneReason),
}},
Usage: Usage{
PromptTokens: r.PromptEvalCount,
CompletionTokens: r.EvalCount,
TotalTokens: r.PromptEvalCount + r.EvalCount,
},
}
}
func toCompleteChunk(id string, r api.GenerateResponse) CompletionChunk {
return CompletionChunk{
Id: id,
Object: "text_completion",
Created: time.Now().Unix(),
Model: r.Model,
SystemFingerprint: "fp_ollama",
Choices: []CompleteChunkChoice{{
Text: r.Response,
Index: 0,
FinishReason: func(reason string) *string {
if len(reason) > 0 {
return &reason
}
return nil
}(r.DoneReason),
}},
}
}
func toListCompletion(r api.ListResponse) ListCompletion {
var data []Model
for _, m := range r.Models {
data = append(data, Model{
Id: m.Name,
Object: "model",
Created: m.ModifiedAt.Unix(),
OwnedBy: model.ParseName(m.Name).Namespace,
})
}
return ListCompletion{
Object: "list",
Data: data,
}
}
func toEmbeddingList(model string, r api.EmbedResponse) EmbeddingList {
if r.Embeddings != nil {
var data []Embedding
for i, e := range r.Embeddings {
data = append(data, Embedding{
Object: "embedding",
Embedding: e,
Index: i,
})
}
return EmbeddingList{
Object: "list",
Data: data,
Model: model,
}
}
return EmbeddingList{}
}
func toModel(r api.ShowResponse, m string) Model {
return Model{
Id: m,
Object: "model",
Created: r.ModifiedAt.Unix(),
OwnedBy: model.ParseName(m).Namespace,
}
}
func fromChatRequest(r ChatCompletionRequest) (*api.ChatRequest, error) {
var messages []api.Message
for _, msg := range r.Messages {
messages = append(messages, api.Message{Role: msg.Role, Content: msg.Content})
switch content := msg.Content.(type) {
case string:
messages = append(messages, api.Message{Role: msg.Role, Content: content})
case []any:
for _, c := range content {
data, ok := c.(map[string]any)
if !ok {
return nil, fmt.Errorf("invalid message format")
}
switch data["type"] {
case "text":
text, ok := data["text"].(string)
if !ok {
return nil, fmt.Errorf("invalid message format")
}
messages = append(messages, api.Message{Role: msg.Role, Content: text})
case "image_url":
var url string
if urlMap, ok := data["image_url"].(map[string]any); ok {
if url, ok = urlMap["url"].(string); !ok {
return nil, fmt.Errorf("invalid message format")
}
} else {
if url, ok = data["image_url"].(string); !ok {
return nil, fmt.Errorf("invalid message format")
}
}
types := []string{"jpeg", "jpg", "png"}
valid := false
for _, t := range types {
prefix := "data:image/" + t + ";base64,"
if strings.HasPrefix(url, prefix) {
url = strings.TrimPrefix(url, prefix)
valid = true
break
}
}
if !valid {
return nil, fmt.Errorf("invalid image input")
}
img, err := base64.StdEncoding.DecodeString(url)
if err != nil {
return nil, fmt.Errorf("invalid message format")
}
messages = append(messages, api.Message{Role: msg.Role, Images: []api.ImageData{img}})
default:
return nil, fmt.Errorf("invalid message format")
}
}
default:
if msg.ToolCalls == nil {
return nil, fmt.Errorf("invalid message content type: %T", content)
}
toolCalls := make([]api.ToolCall, len(msg.ToolCalls))
for i, tc := range msg.ToolCalls {
toolCalls[i].Function.Name = tc.Function.Name
err := json.Unmarshal([]byte(tc.Function.Arguments), &toolCalls[i].Function.Arguments)
if err != nil {
return nil, fmt.Errorf("invalid tool call arguments")
}
}
messages = append(messages, api.Message{Role: msg.Role, ToolCalls: toolCalls})
}
}
options := make(map[string]interface{})
@@ -156,7 +422,7 @@ func fromRequest(r ChatCompletionRequest) api.ChatRequest {
switch stop := r.Stop.(type) {
case string:
options["stop"] = []string{stop}
case []interface{}:
case []any:
var stops []string
for _, s := range stop {
if str, ok := s.(string); ok {
@@ -199,22 +465,98 @@ func fromRequest(r ChatCompletionRequest) api.ChatRequest {
format = "json"
}
return api.ChatRequest{
return &api.ChatRequest{
Model: r.Model,
Messages: messages,
Format: format,
Options: options,
Stream: &r.Stream,
}
Tools: r.Tools,
}, nil
}
type writer struct {
stream bool
id string
func fromCompleteRequest(r CompletionRequest) (api.GenerateRequest, error) {
options := make(map[string]any)
switch stop := r.Stop.(type) {
case string:
options["stop"] = []string{stop}
case []any:
var stops []string
for _, s := range stop {
if str, ok := s.(string); ok {
stops = append(stops, str)
} else {
return api.GenerateRequest{}, fmt.Errorf("invalid type for 'stop' field: %T", s)
}
}
options["stop"] = stops
}
if r.MaxTokens != nil {
options["num_predict"] = *r.MaxTokens
}
if r.Temperature != nil {
options["temperature"] = *r.Temperature * 2.0
} else {
options["temperature"] = 1.0
}
if r.Seed != nil {
options["seed"] = *r.Seed
}
options["frequency_penalty"] = r.FrequencyPenalty * 2.0
options["presence_penalty"] = r.PresencePenalty * 2.0
if r.TopP != 0.0 {
options["top_p"] = r.TopP
} else {
options["top_p"] = 1.0
}
return api.GenerateRequest{
Model: r.Model,
Prompt: r.Prompt,
Options: options,
Stream: &r.Stream,
Suffix: r.Suffix,
}, nil
}
type BaseWriter struct {
gin.ResponseWriter
}
func (w *writer) writeError(code int, data []byte) (int, error) {
type ChatWriter struct {
stream bool
id string
BaseWriter
}
type CompleteWriter struct {
stream bool
id string
BaseWriter
}
type ListWriter struct {
BaseWriter
}
type RetrieveWriter struct {
BaseWriter
model string
}
type EmbedWriter struct {
BaseWriter
model string
}
func (w *BaseWriter) writeError(code int, data []byte) (int, error) {
var serr api.StatusError
err := json.Unmarshal(data, &serr)
if err != nil {
@@ -230,7 +572,7 @@ func (w *writer) writeError(code int, data []byte) (int, error) {
return len(data), nil
}
func (w *writer) writeResponse(data []byte) (int, error) {
func (w *ChatWriter) writeResponse(data []byte) (int, error) {
var chatResponse api.ChatResponse
err := json.Unmarshal(data, &chatResponse)
if err != nil {
@@ -270,7 +612,7 @@ func (w *writer) writeResponse(data []byte) (int, error) {
return len(data), nil
}
func (w *writer) Write(data []byte) (int, error) {
func (w *ChatWriter) Write(data []byte) (int, error) {
code := w.ResponseWriter.Status()
if code != http.StatusOK {
return w.writeError(code, data)
@@ -279,7 +621,244 @@ func (w *writer) Write(data []byte) (int, error) {
return w.writeResponse(data)
}
func Middleware() gin.HandlerFunc {
func (w *CompleteWriter) writeResponse(data []byte) (int, error) {
var generateResponse api.GenerateResponse
err := json.Unmarshal(data, &generateResponse)
if err != nil {
return 0, err
}
// completion chunk
if w.stream {
d, err := json.Marshal(toCompleteChunk(w.id, generateResponse))
if err != nil {
return 0, err
}
w.ResponseWriter.Header().Set("Content-Type", "text/event-stream")
_, err = w.ResponseWriter.Write([]byte(fmt.Sprintf("data: %s\n\n", d)))
if err != nil {
return 0, err
}
if generateResponse.Done {
_, err = w.ResponseWriter.Write([]byte("data: [DONE]\n\n"))
if err != nil {
return 0, err
}
}
return len(data), nil
}
// completion
w.ResponseWriter.Header().Set("Content-Type", "application/json")
err = json.NewEncoder(w.ResponseWriter).Encode(toCompletion(w.id, generateResponse))
if err != nil {
return 0, err
}
return len(data), nil
}
func (w *CompleteWriter) Write(data []byte) (int, error) {
code := w.ResponseWriter.Status()
if code != http.StatusOK {
return w.writeError(code, data)
}
return w.writeResponse(data)
}
func (w *ListWriter) writeResponse(data []byte) (int, error) {
var listResponse api.ListResponse
err := json.Unmarshal(data, &listResponse)
if err != nil {
return 0, err
}
w.ResponseWriter.Header().Set("Content-Type", "application/json")
err = json.NewEncoder(w.ResponseWriter).Encode(toListCompletion(listResponse))
if err != nil {
return 0, err
}
return len(data), nil
}
func (w *ListWriter) Write(data []byte) (int, error) {
code := w.ResponseWriter.Status()
if code != http.StatusOK {
return w.writeError(code, data)
}
return w.writeResponse(data)
}
func (w *RetrieveWriter) writeResponse(data []byte) (int, error) {
var showResponse api.ShowResponse
err := json.Unmarshal(data, &showResponse)
if err != nil {
return 0, err
}
// retrieve completion
w.ResponseWriter.Header().Set("Content-Type", "application/json")
err = json.NewEncoder(w.ResponseWriter).Encode(toModel(showResponse, w.model))
if err != nil {
return 0, err
}
return len(data), nil
}
func (w *RetrieveWriter) Write(data []byte) (int, error) {
code := w.ResponseWriter.Status()
if code != http.StatusOK {
return w.writeError(code, data)
}
return w.writeResponse(data)
}
func (w *EmbedWriter) writeResponse(data []byte) (int, error) {
var embedResponse api.EmbedResponse
err := json.Unmarshal(data, &embedResponse)
if err != nil {
return 0, err
}
w.ResponseWriter.Header().Set("Content-Type", "application/json")
err = json.NewEncoder(w.ResponseWriter).Encode(toEmbeddingList(w.model, embedResponse))
if err != nil {
return 0, err
}
return len(data), nil
}
func (w *EmbedWriter) Write(data []byte) (int, error) {
code := w.ResponseWriter.Status()
if code != http.StatusOK {
return w.writeError(code, data)
}
return w.writeResponse(data)
}
func ListMiddleware() gin.HandlerFunc {
return func(c *gin.Context) {
w := &ListWriter{
BaseWriter: BaseWriter{ResponseWriter: c.Writer},
}
c.Writer = w
c.Next()
}
}
func RetrieveMiddleware() gin.HandlerFunc {
return func(c *gin.Context) {
var b bytes.Buffer
if err := json.NewEncoder(&b).Encode(api.ShowRequest{Name: c.Param("model")}); err != nil {
c.AbortWithStatusJSON(http.StatusInternalServerError, NewError(http.StatusInternalServerError, err.Error()))
return
}
c.Request.Body = io.NopCloser(&b)
// response writer
w := &RetrieveWriter{
BaseWriter: BaseWriter{ResponseWriter: c.Writer},
model: c.Param("model"),
}
c.Writer = w
c.Next()
}
}
func CompletionsMiddleware() gin.HandlerFunc {
return func(c *gin.Context) {
var req CompletionRequest
err := c.ShouldBindJSON(&req)
if err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, NewError(http.StatusBadRequest, err.Error()))
return
}
var b bytes.Buffer
genReq, err := fromCompleteRequest(req)
if err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, NewError(http.StatusBadRequest, err.Error()))
return
}
if err := json.NewEncoder(&b).Encode(genReq); err != nil {
c.AbortWithStatusJSON(http.StatusInternalServerError, NewError(http.StatusInternalServerError, err.Error()))
return
}
c.Request.Body = io.NopCloser(&b)
w := &CompleteWriter{
BaseWriter: BaseWriter{ResponseWriter: c.Writer},
stream: req.Stream,
id: fmt.Sprintf("cmpl-%d", rand.Intn(999)),
}
c.Writer = w
c.Next()
}
}
func EmbeddingsMiddleware() gin.HandlerFunc {
return func(c *gin.Context) {
var req EmbedRequest
err := c.ShouldBindJSON(&req)
if err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, NewError(http.StatusBadRequest, err.Error()))
return
}
if req.Input == "" {
req.Input = []string{""}
}
if req.Input == nil {
c.AbortWithStatusJSON(http.StatusBadRequest, NewError(http.StatusBadRequest, "invalid input"))
return
}
if v, ok := req.Input.([]any); ok && len(v) == 0 {
c.AbortWithStatusJSON(http.StatusBadRequest, NewError(http.StatusBadRequest, "invalid input"))
return
}
var b bytes.Buffer
if err := json.NewEncoder(&b).Encode(api.EmbedRequest{Model: req.Model, Input: req.Input}); err != nil {
c.AbortWithStatusJSON(http.StatusInternalServerError, NewError(http.StatusInternalServerError, err.Error()))
return
}
c.Request.Body = io.NopCloser(&b)
w := &EmbedWriter{
BaseWriter: BaseWriter{ResponseWriter: c.Writer},
model: req.Model,
}
c.Writer = w
c.Next()
}
}
func ChatMiddleware() gin.HandlerFunc {
return func(c *gin.Context) {
var req ChatCompletionRequest
err := c.ShouldBindJSON(&req)
@@ -294,17 +873,24 @@ func Middleware() gin.HandlerFunc {
}
var b bytes.Buffer
if err := json.NewEncoder(&b).Encode(fromRequest(req)); err != nil {
chatReq, err := fromChatRequest(req)
if err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, NewError(http.StatusBadRequest, err.Error()))
return
}
if err := json.NewEncoder(&b).Encode(chatReq); err != nil {
c.AbortWithStatusJSON(http.StatusInternalServerError, NewError(http.StatusInternalServerError, err.Error()))
return
}
c.Request.Body = io.NopCloser(&b)
w := &writer{
ResponseWriter: c.Writer,
stream: req.Stream,
id: fmt.Sprintf("chatcmpl-%d", rand.Intn(999)),
w := &ChatWriter{
BaseWriter: BaseWriter{ResponseWriter: c.Writer},
stream: req.Stream,
id: fmt.Sprintf("chatcmpl-%d", rand.Intn(999)),
}
c.Writer = w

496
openai/openai_test.go Normal file
View File

@@ -0,0 +1,496 @@
package openai
import (
"bytes"
"encoding/base64"
"encoding/json"
"io"
"net/http"
"net/http/httptest"
"strings"
"testing"
"time"
"github.com/gin-gonic/gin"
"github.com/ollama/ollama/api"
"github.com/stretchr/testify/assert"
)
const prefix = `data:image/jpeg;base64,`
const image = `iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNk+A8AAQUBAScY42YAAAAASUVORK5CYII=`
const imageURL = prefix + image
func prepareRequest(req *http.Request, body any) {
bodyBytes, _ := json.Marshal(body)
req.Body = io.NopCloser(bytes.NewReader(bodyBytes))
req.Header.Set("Content-Type", "application/json")
}
func captureRequestMiddleware(capturedRequest any) gin.HandlerFunc {
return func(c *gin.Context) {
bodyBytes, _ := io.ReadAll(c.Request.Body)
c.Request.Body = io.NopCloser(bytes.NewReader(bodyBytes))
err := json.Unmarshal(bodyBytes, capturedRequest)
if err != nil {
c.AbortWithStatusJSON(http.StatusInternalServerError, "failed to unmarshal request")
}
c.Next()
}
}
func TestChatMiddleware(t *testing.T) {
type testCase struct {
Name string
Setup func(t *testing.T, req *http.Request)
Expected func(t *testing.T, req *api.ChatRequest, resp *httptest.ResponseRecorder)
}
var capturedRequest *api.ChatRequest
testCases := []testCase{
{
Name: "chat handler",
Setup: func(t *testing.T, req *http.Request) {
body := ChatCompletionRequest{
Model: "test-model",
Messages: []Message{{Role: "user", Content: "Hello"}},
}
prepareRequest(req, body)
},
Expected: func(t *testing.T, req *api.ChatRequest, resp *httptest.ResponseRecorder) {
if resp.Code != http.StatusOK {
t.Fatalf("expected 200, got %d", resp.Code)
}
if req.Messages[0].Role != "user" {
t.Fatalf("expected 'user', got %s", req.Messages[0].Role)
}
if req.Messages[0].Content != "Hello" {
t.Fatalf("expected 'Hello', got %s", req.Messages[0].Content)
}
},
},
{
Name: "chat handler with image content",
Setup: func(t *testing.T, req *http.Request) {
body := ChatCompletionRequest{
Model: "test-model",
Messages: []Message{
{
Role: "user", Content: []map[string]any{
{"type": "text", "text": "Hello"},
{"type": "image_url", "image_url": map[string]string{"url": imageURL}},
},
},
},
}
prepareRequest(req, body)
},
Expected: func(t *testing.T, req *api.ChatRequest, resp *httptest.ResponseRecorder) {
if resp.Code != http.StatusOK {
t.Fatalf("expected 200, got %d", resp.Code)
}
if req.Messages[0].Role != "user" {
t.Fatalf("expected 'user', got %s", req.Messages[0].Role)
}
if req.Messages[0].Content != "Hello" {
t.Fatalf("expected 'Hello', got %s", req.Messages[0].Content)
}
img, _ := base64.StdEncoding.DecodeString(imageURL[len(prefix):])
if req.Messages[1].Role != "user" {
t.Fatalf("expected 'user', got %s", req.Messages[1].Role)
}
if !bytes.Equal(req.Messages[1].Images[0], img) {
t.Fatalf("expected image encoding, got %s", req.Messages[1].Images[0])
}
},
},
{
Name: "chat handler with tools",
Setup: func(t *testing.T, req *http.Request) {
body := ChatCompletionRequest{
Model: "test-model",
Messages: []Message{
{Role: "user", Content: "What's the weather like in Paris Today?"},
{Role: "assistant", ToolCalls: []ToolCall{{
ID: "id",
Type: "function",
Function: struct {
Name string `json:"name"`
Arguments string `json:"arguments"`
}{
Name: "get_current_weather",
Arguments: "{\"location\": \"Paris, France\", \"format\": \"celsius\"}",
},
}}},
},
}
prepareRequest(req, body)
},
Expected: func(t *testing.T, req *api.ChatRequest, resp *httptest.ResponseRecorder) {
if resp.Code != 200 {
t.Fatalf("expected 200, got %d", resp.Code)
}
if req.Messages[0].Content != "What's the weather like in Paris Today?" {
t.Fatalf("expected What's the weather like in Paris Today?, got %s", req.Messages[0].Content)
}
if req.Messages[1].ToolCalls[0].Function.Arguments["location"] != "Paris, France" {
t.Fatalf("expected 'Paris, France', got %v", req.Messages[1].ToolCalls[0].Function.Arguments["location"])
}
if req.Messages[1].ToolCalls[0].Function.Arguments["format"] != "celsius" {
t.Fatalf("expected celsius, got %v", req.Messages[1].ToolCalls[0].Function.Arguments["format"])
}
},
},
{
Name: "chat handler error forwarding",
Setup: func(t *testing.T, req *http.Request) {
body := ChatCompletionRequest{
Model: "test-model",
Messages: []Message{{Role: "user", Content: 2}},
}
prepareRequest(req, body)
},
Expected: func(t *testing.T, req *api.ChatRequest, resp *httptest.ResponseRecorder) {
if resp.Code != http.StatusBadRequest {
t.Fatalf("expected 400, got %d", resp.Code)
}
if !strings.Contains(resp.Body.String(), "invalid message content type") {
t.Fatalf("error was not forwarded")
}
},
},
}
endpoint := func(c *gin.Context) {
c.Status(http.StatusOK)
}
gin.SetMode(gin.TestMode)
router := gin.New()
router.Use(ChatMiddleware(), captureRequestMiddleware(&capturedRequest))
router.Handle(http.MethodPost, "/api/chat", endpoint)
for _, tc := range testCases {
t.Run(tc.Name, func(t *testing.T) {
req, _ := http.NewRequest(http.MethodPost, "/api/chat", nil)
tc.Setup(t, req)
resp := httptest.NewRecorder()
router.ServeHTTP(resp, req)
tc.Expected(t, capturedRequest, resp)
capturedRequest = nil
})
}
}
func TestCompletionsMiddleware(t *testing.T) {
type testCase struct {
Name string
Setup func(t *testing.T, req *http.Request)
Expected func(t *testing.T, req *api.GenerateRequest, resp *httptest.ResponseRecorder)
}
var capturedRequest *api.GenerateRequest
testCases := []testCase{
{
Name: "completions handler",
Setup: func(t *testing.T, req *http.Request) {
temp := float32(0.8)
body := CompletionRequest{
Model: "test-model",
Prompt: "Hello",
Temperature: &temp,
Stop: []string{"\n", "stop"},
Suffix: "suffix",
}
prepareRequest(req, body)
},
Expected: func(t *testing.T, req *api.GenerateRequest, resp *httptest.ResponseRecorder) {
if req.Prompt != "Hello" {
t.Fatalf("expected 'Hello', got %s", req.Prompt)
}
if req.Options["temperature"] != 1.6 {
t.Fatalf("expected 1.6, got %f", req.Options["temperature"])
}
stopTokens, ok := req.Options["stop"].([]any)
if !ok {
t.Fatalf("expected stop tokens to be a list")
}
if stopTokens[0] != "\n" || stopTokens[1] != "stop" {
t.Fatalf("expected ['\\n', 'stop'], got %v", stopTokens)
}
if req.Suffix != "suffix" {
t.Fatalf("expected 'suffix', got %s", req.Suffix)
}
},
},
{
Name: "completions handler error forwarding",
Setup: func(t *testing.T, req *http.Request) {
body := CompletionRequest{
Model: "test-model",
Prompt: "Hello",
Temperature: nil,
Stop: []int{1, 2},
Suffix: "suffix",
}
prepareRequest(req, body)
},
Expected: func(t *testing.T, req *api.GenerateRequest, resp *httptest.ResponseRecorder) {
if resp.Code != http.StatusBadRequest {
t.Fatalf("expected 400, got %d", resp.Code)
}
if !strings.Contains(resp.Body.String(), "invalid type for 'stop' field") {
t.Fatalf("error was not forwarded")
}
},
},
}
endpoint := func(c *gin.Context) {
c.Status(http.StatusOK)
}
gin.SetMode(gin.TestMode)
router := gin.New()
router.Use(CompletionsMiddleware(), captureRequestMiddleware(&capturedRequest))
router.Handle(http.MethodPost, "/api/generate", endpoint)
for _, tc := range testCases {
t.Run(tc.Name, func(t *testing.T) {
req, _ := http.NewRequest(http.MethodPost, "/api/generate", nil)
tc.Setup(t, req)
resp := httptest.NewRecorder()
router.ServeHTTP(resp, req)
tc.Expected(t, capturedRequest, resp)
capturedRequest = nil
})
}
}
func TestEmbeddingsMiddleware(t *testing.T) {
type testCase struct {
Name string
Setup func(t *testing.T, req *http.Request)
Expected func(t *testing.T, req *api.EmbedRequest, resp *httptest.ResponseRecorder)
}
var capturedRequest *api.EmbedRequest
testCases := []testCase{
{
Name: "embed handler single input",
Setup: func(t *testing.T, req *http.Request) {
body := EmbedRequest{
Input: "Hello",
Model: "test-model",
}
prepareRequest(req, body)
},
Expected: func(t *testing.T, req *api.EmbedRequest, resp *httptest.ResponseRecorder) {
if req.Input != "Hello" {
t.Fatalf("expected 'Hello', got %s", req.Input)
}
if req.Model != "test-model" {
t.Fatalf("expected 'test-model', got %s", req.Model)
}
},
},
{
Name: "embed handler batch input",
Setup: func(t *testing.T, req *http.Request) {
body := EmbedRequest{
Input: []string{"Hello", "World"},
Model: "test-model",
}
prepareRequest(req, body)
},
Expected: func(t *testing.T, req *api.EmbedRequest, resp *httptest.ResponseRecorder) {
input, ok := req.Input.([]any)
if !ok {
t.Fatalf("expected input to be a list")
}
if input[0].(string) != "Hello" {
t.Fatalf("expected 'Hello', got %s", input[0])
}
if input[1].(string) != "World" {
t.Fatalf("expected 'World', got %s", input[1])
}
if req.Model != "test-model" {
t.Fatalf("expected 'test-model', got %s", req.Model)
}
},
},
{
Name: "embed handler error forwarding",
Setup: func(t *testing.T, req *http.Request) {
body := EmbedRequest{
Model: "test-model",
}
prepareRequest(req, body)
},
Expected: func(t *testing.T, req *api.EmbedRequest, resp *httptest.ResponseRecorder) {
if resp.Code != http.StatusBadRequest {
t.Fatalf("expected 400, got %d", resp.Code)
}
if !strings.Contains(resp.Body.String(), "invalid input") {
t.Fatalf("error was not forwarded")
}
},
},
}
endpoint := func(c *gin.Context) {
c.Status(http.StatusOK)
}
gin.SetMode(gin.TestMode)
router := gin.New()
router.Use(EmbeddingsMiddleware(), captureRequestMiddleware(&capturedRequest))
router.Handle(http.MethodPost, "/api/embed", endpoint)
for _, tc := range testCases {
t.Run(tc.Name, func(t *testing.T) {
req, _ := http.NewRequest(http.MethodPost, "/api/embed", nil)
tc.Setup(t, req)
resp := httptest.NewRecorder()
router.ServeHTTP(resp, req)
tc.Expected(t, capturedRequest, resp)
capturedRequest = nil
})
}
}
func TestMiddlewareResponses(t *testing.T) {
type testCase struct {
Name string
Method string
Path string
TestPath string
Handler func() gin.HandlerFunc
Endpoint func(c *gin.Context)
Setup func(t *testing.T, req *http.Request)
Expected func(t *testing.T, resp *httptest.ResponseRecorder)
}
testCases := []testCase{
{
Name: "list handler",
Method: http.MethodGet,
Path: "/api/tags",
TestPath: "/api/tags",
Handler: ListMiddleware,
Endpoint: func(c *gin.Context) {
c.JSON(http.StatusOK, api.ListResponse{
Models: []api.ListModelResponse{
{
Name: "Test Model",
},
},
})
},
Expected: func(t *testing.T, resp *httptest.ResponseRecorder) {
var listResp ListCompletion
if err := json.NewDecoder(resp.Body).Decode(&listResp); err != nil {
t.Fatal(err)
}
if listResp.Object != "list" {
t.Fatalf("expected list, got %s", listResp.Object)
}
if len(listResp.Data) != 1 {
t.Fatalf("expected 1, got %d", len(listResp.Data))
}
if listResp.Data[0].Id != "Test Model" {
t.Fatalf("expected Test Model, got %s", listResp.Data[0].Id)
}
},
},
{
Name: "retrieve model",
Method: http.MethodGet,
Path: "/api/show/:model",
TestPath: "/api/show/test-model",
Handler: RetrieveMiddleware,
Endpoint: func(c *gin.Context) {
c.JSON(http.StatusOK, api.ShowResponse{
ModifiedAt: time.Date(2024, 6, 17, 13, 45, 0, 0, time.UTC),
})
},
Expected: func(t *testing.T, resp *httptest.ResponseRecorder) {
var retrieveResp Model
if err := json.NewDecoder(resp.Body).Decode(&retrieveResp); err != nil {
t.Fatal(err)
}
if retrieveResp.Object != "model" {
t.Fatalf("Expected object to be model, got %s", retrieveResp.Object)
}
if retrieveResp.Id != "test-model" {
t.Fatalf("Expected id to be test-model, got %s", retrieveResp.Id)
}
},
},
}
gin.SetMode(gin.TestMode)
router := gin.New()
for _, tc := range testCases {
t.Run(tc.Name, func(t *testing.T) {
router = gin.New()
router.Use(tc.Handler())
router.Handle(tc.Method, tc.Path, tc.Endpoint)
req, _ := http.NewRequest(tc.Method, tc.TestPath, nil)
if tc.Setup != nil {
tc.Setup(t, req)
}
resp := httptest.NewRecorder()
router.ServeHTTP(resp, req)
assert.Equal(t, http.StatusOK, resp.Code)
tc.Expected(t, resp)
})
}
}

View File

@@ -124,7 +124,7 @@ func ParseFile(r io.Reader) (*File, error) {
case stateComment, stateNil:
// pass
case stateValue:
s, ok := unquote(b.String())
s, ok := unquote(strings.TrimSpace(b.String()))
if !ok || isSpace(r) {
if _, err := b.WriteRune(r); err != nil {
return nil, err
@@ -158,7 +158,7 @@ func ParseFile(r io.Reader) (*File, error) {
case stateComment, stateNil:
// pass; nothing to flush
case stateValue:
s, ok := unquote(b.String())
s, ok := unquote(strings.TrimSpace(b.String()))
if !ok {
return nil, io.ErrUnexpectedEOF
}

View File

@@ -22,7 +22,13 @@ ADAPTER adapter1
LICENSE MIT
PARAMETER param1 value1
PARAMETER param2 value2
TEMPLATE template1
TEMPLATE """{{ if .System }}<|start_header_id|>system<|end_header_id|>
{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>
{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>
{{ .Response }}<|eot_id|>"""
`
reader := strings.NewReader(input)
@@ -36,7 +42,40 @@ TEMPLATE template1
{Name: "license", Args: "MIT"},
{Name: "param1", Args: "value1"},
{Name: "param2", Args: "value2"},
{Name: "template", Args: "template1"},
{Name: "template", Args: "{{ if .System }}<|start_header_id|>system<|end_header_id|>\n\n{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>\n\n{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>\n\n{{ .Response }}<|eot_id|>"},
}
assert.Equal(t, expectedCommands, modelfile.Commands)
}
func TestParseFileTrimSpace(t *testing.T) {
input := `
FROM " model 1"
ADAPTER adapter3
LICENSE "MIT "
PARAMETER param1 value1
PARAMETER param2 value2
TEMPLATE """ {{ if .System }}<|start_header_id|>system<|end_header_id|>
{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>
{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>
{{ .Response }}<|eot_id|> """
`
reader := strings.NewReader(input)
modelfile, err := ParseFile(reader)
require.NoError(t, err)
expectedCommands := []Command{
{Name: "model", Args: " model 1"},
{Name: "adapter", Args: "adapter3"},
{Name: "license", Args: "MIT "},
{Name: "param1", Args: "value1"},
{Name: "param2", Args: "value2"},
{Name: "template", Args: " {{ if .System }}<|start_header_id|>system<|end_header_id|>\n\n{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>\n\n{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>\n\n{{ .Response }}<|eot_id|> "},
}
assert.Equal(t, expectedCommands, modelfile.Commands)
@@ -48,6 +87,26 @@ func TestParseFileFrom(t *testing.T) {
expected []Command
err error
}{
{
"FROM \"FOO BAR \"",
[]Command{{Name: "model", Args: "FOO BAR "}},
nil,
},
{
"FROM \"FOO BAR\"\nPARAMETER param1 value1",
[]Command{{Name: "model", Args: "FOO BAR"}, {Name: "param1", Args: "value1"}},
nil,
},
{
"FROM FOOO BAR ",
[]Command{{Name: "model", Args: "FOOO BAR"}},
nil,
},
{
"FROM /what/is/the path ",
[]Command{{Name: "model", Args: "/what/is/the path"}},
nil,
},
{
"FROM foo",
[]Command{{Name: "model", Args: "foo"}},
@@ -86,6 +145,11 @@ func TestParseFileFrom(t *testing.T) {
[]Command{{Name: "param1", Args: "value1"}, {Name: "model", Args: "foo"}},
nil,
},
{
"PARAMETER what the \nFROM lemons make lemonade ",
[]Command{{Name: "what", Args: "the"}, {Name: "model", Args: "lemons make lemonade"}},
nil,
},
}
for _, c := range cases {
@@ -399,7 +463,7 @@ func TestParseFileParameters(t *testing.T) {
"mirostat_eta 1.0": {"mirostat_eta", "1.0"},
"penalize_newline true": {"penalize_newline", "true"},
"stop ### User:": {"stop", "### User:"},
"stop ### User: ": {"stop", "### User: "},
"stop ### User: ": {"stop", "### User:"},
"stop \"### User:\"": {"stop", "### User:"},
"stop \"### User: \"": {"stop", "### User: "},
"stop \"\"\"### User:\"\"\"": {"stop", "### User:"},

View File

@@ -107,9 +107,12 @@ function gatherDependencies() {
# TODO - this varies based on host build system and MSVC version - drive from dumpbin output
# currently works for Win11 + MSVC 2019 + Cuda V11
cp "${env:VCToolsRedistDir}\x64\Microsoft.VC*.CRT\msvcp140.dll" "${script:DEPS_DIR}\ollama_runners\"
cp "${env:VCToolsRedistDir}\x64\Microsoft.VC*.CRT\msvcp140*.dll" "${script:DEPS_DIR}\ollama_runners\"
cp "${env:VCToolsRedistDir}\x64\Microsoft.VC*.CRT\vcruntime140.dll" "${script:DEPS_DIR}\ollama_runners\"
cp "${env:VCToolsRedistDir}\x64\Microsoft.VC*.CRT\vcruntime140_1.dll" "${script:DEPS_DIR}\ollama_runners\"
foreach ($part in $("runtime", "stdio", "filesystem", "math", "convert", "heap", "string", "time", "locale", "environment")) {
cp "$env:VCToolsRedistDir\..\..\..\Tools\Llvm\x64\bin\api-ms-win-crt-${part}*.dll" "${script:DEPS_DIR}\ollama_runners\"
}
cp "${script:SRC_DIR}\app\ollama_welcome.ps1" "${script:SRC_DIR}\dist\"

View File

@@ -6,10 +6,21 @@ set -ex
MACHINE=$(uname -m)
if grep -i "centos" /etc/system-release >/dev/null; then
# As of 7/1/2024 mirrorlist.centos.org has been taken offline, so adjust accordingly
sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
# Centos 7 derivatives have too old of a git version to run our generate script
# uninstall and ignore failures
yum remove -y git
yum -y install epel-release centos-release-scl
# The release packages reinstate the mirrors, undo that again
sed -i s/mirror.centos.org/vault.centos.org/g /etc/yum.repos.d/*.repo
sed -i s/^#.*baseurl=http/baseurl=http/g /etc/yum.repos.d/*.repo
sed -i s/^mirrorlist=http/#mirrorlist=http/g /etc/yum.repos.d/*.repo
yum -y install dnf
if [ "${MACHINE}" = "x86_64" ]; then
yum -y install https://repo.ius.io/ius-release-el7.rpm

View File

@@ -28,11 +28,27 @@ import (
"github.com/ollama/ollama/format"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/parser"
"github.com/ollama/ollama/template"
"github.com/ollama/ollama/types/errtypes"
"github.com/ollama/ollama/types/model"
"github.com/ollama/ollama/version"
)
var (
errCapabilities = errors.New("does not support")
errCapabilityCompletion = errors.New("completion")
errCapabilityTools = errors.New("tools")
errCapabilityInsert = errors.New("insert")
)
type Capability string
const (
CapabilityCompletion = Capability("completion")
CapabilityTools = Capability("tools")
CapabilityInsert = Capability("insert")
)
type registryOptions struct {
Insecure bool
Username string
@@ -48,16 +64,59 @@ type Model struct {
ParentModel string
AdapterPaths []string
ProjectorPaths []string
Template string
System string
License []string
Digest string
Options map[string]interface{}
Messages []Message
Template *template.Template
}
func (m *Model) IsEmbedding() bool {
return slices.Contains(m.Config.ModelFamilies, "bert") || slices.Contains(m.Config.ModelFamilies, "nomic-bert")
// CheckCapabilities checks if the model has the specified capabilities returning an error describing
// any missing or unknown capabilities
func (m *Model) CheckCapabilities(caps ...Capability) error {
var errs []error
for _, cap := range caps {
switch cap {
case CapabilityCompletion:
f, err := os.Open(m.ModelPath)
if err != nil {
slog.Error("couldn't open model file", "error", err)
continue
}
defer f.Close()
// TODO(mxyng): decode the GGML into model to avoid doing this multiple times
ggml, _, err := llm.DecodeGGML(f, 0)
if err != nil {
slog.Error("couldn't decode ggml", "error", err)
continue
}
if _, ok := ggml.KV()[fmt.Sprintf("%s.pooling_type", ggml.KV().Architecture())]; ok {
errs = append(errs, errCapabilityCompletion)
}
case CapabilityTools:
if !slices.Contains(m.Template.Vars(), "tools") {
errs = append(errs, errCapabilityTools)
}
case CapabilityInsert:
vars := m.Template.Vars()
if !slices.Contains(vars, "suffix") {
errs = append(errs, errCapabilityInsert)
}
default:
slog.Error("unknown capability", "capability", cap)
return fmt.Errorf("unknown capability: %s", cap)
}
}
if err := errors.Join(errs...); err != nil {
return fmt.Errorf("%w %w", errCapabilities, errors.Join(errs...))
}
return nil
}
func (m *Model) String() string {
@@ -82,10 +141,10 @@ func (m *Model) String() string {
})
}
if m.Template != "" {
if m.Template != nil {
modelfile.Commands = append(modelfile.Commands, parser.Command{
Name: "template",
Args: m.Template,
Args: m.Template.String(),
})
}
@@ -135,13 +194,6 @@ type Message struct {
Content string `json:"content"`
}
type ManifestV2 struct {
SchemaVersion int `json:"schemaVersion"`
MediaType string `json:"mediaType"`
Config *Layer `json:"config"`
Layers []*Layer `json:"layers"`
}
type ConfigV2 struct {
ModelFormat string `json:"model_format"`
ModelFamily string `json:"model_family"`
@@ -160,7 +212,7 @@ type RootFS struct {
DiffIDs []string `json:"diff_ids"`
}
func GetManifest(mp ModelPath) (*ManifestV2, string, error) {
func GetManifest(mp ModelPath) (*Manifest, string, error) {
fp, err := mp.GetManifestPath()
if err != nil {
return nil, "", err
@@ -170,7 +222,7 @@ func GetManifest(mp ModelPath) (*ManifestV2, string, error) {
return nil, "", err
}
var manifest *ManifestV2
var manifest *Manifest
bts, err := os.ReadFile(fp)
if err != nil {
@@ -198,8 +250,7 @@ func GetModel(name string) (*Model, error) {
Name: mp.GetFullTagname(),
ShortName: mp.GetShortTagname(),
Digest: digest,
Template: "{{ .Prompt }}",
License: []string{},
Template: template.DefaultTemplate,
}
filename, err := GetBlobsPath(manifest.Config.Digest)
@@ -235,13 +286,17 @@ func GetModel(name string) (*Model, error) {
model.AdapterPaths = append(model.AdapterPaths, filename)
case "application/vnd.ollama.image.projector":
model.ProjectorPaths = append(model.ProjectorPaths, filename)
case "application/vnd.ollama.image.template":
case "application/vnd.ollama.image.prompt",
"application/vnd.ollama.image.template":
bts, err := os.ReadFile(filename)
if err != nil {
return nil, err
}
model.Template = string(bts)
model.Template, err = template.Parse(string(bts))
if err != nil {
return nil, err
}
case "application/vnd.ollama.image.system":
bts, err := os.ReadFile(filename)
if err != nil {
@@ -249,13 +304,6 @@ func GetModel(name string) (*Model, error) {
}
model.System = string(bts)
case "application/vnd.ollama.image.prompt":
bts, err := os.ReadFile(filename)
if err != nil {
return nil, err
}
model.Template = string(bts)
case "application/vnd.ollama.image.params":
params, err := os.Open(filename)
if err != nil {
@@ -444,6 +492,12 @@ func CreateModel(ctx context.Context, name model.Name, modelFileDir, quantizatio
layers = append(layers, baseLayer.Layer)
}
case "license", "template", "system":
if c.Name == "template" {
if _, err := template.Parse(c.Args); err != nil {
return fmt.Errorf("%w: %s", errBadTemplate, err)
}
}
if c.Name != "license" {
// replace
layers = slices.DeleteFunc(layers, func(layer *Layer) bool {
@@ -822,7 +876,7 @@ func PushModel(ctx context.Context, name string, regOpts *registryOptions, fn fu
func PullModel(ctx context.Context, name string, regOpts *registryOptions, fn func(api.ProgressResponse)) error {
mp := ParseModelPath(name)
var manifest *ManifestV2
var manifest *Manifest
var err error
var noprune string
@@ -929,7 +983,7 @@ func PullModel(ctx context.Context, name string, regOpts *registryOptions, fn fu
return nil
}
func pullModelManifest(ctx context.Context, mp ModelPath, regOpts *registryOptions) (*ManifestV2, error) {
func pullModelManifest(ctx context.Context, mp ModelPath, regOpts *registryOptions) (*Manifest, error) {
requestURL := mp.BaseURL().JoinPath("v2", mp.GetNamespaceRepository(), "manifests", mp.Tag)
headers := make(http.Header)
@@ -940,7 +994,7 @@ func pullModelManifest(ctx context.Context, mp ModelPath, regOpts *registryOptio
}
defer resp.Body.Close()
var m *ManifestV2
var m *Manifest
if err := json.NewDecoder(resp.Body).Decode(&m); err != nil {
return nil, err
}

View File

@@ -14,7 +14,10 @@ import (
)
type Manifest struct {
ManifestV2
SchemaVersion int `json:"schemaVersion"`
MediaType string `json:"mediaType"`
Config *Layer `json:"config"`
Layers []*Layer `json:"layers"`
filepath string
fi os.FileInfo
@@ -66,7 +69,7 @@ func ParseNamedManifest(n model.Name) (*Manifest, error) {
p := filepath.Join(manifests, n.Filepath())
var m ManifestV2
var m Manifest
f, err := os.Open(p)
if err != nil {
return nil, err
@@ -83,12 +86,11 @@ func ParseNamedManifest(n model.Name) (*Manifest, error) {
return nil, err
}
return &Manifest{
ManifestV2: m,
filepath: p,
fi: fi,
digest: fmt.Sprintf("%x", sha256sum.Sum(nil)),
}, nil
m.filepath = p
m.fi = fi
m.digest = fmt.Sprintf("%x", sha256sum.Sum(nil))
return &m, nil
}
func WriteManifest(name model.Name, config *Layer, layers []*Layer) error {
@@ -108,7 +110,7 @@ func WriteManifest(name model.Name, config *Layer, layers []*Layer) error {
}
defer f.Close()
m := ManifestV2{
m := Manifest{
SchemaVersion: 2,
MediaType: "application/vnd.docker.distribution.manifest.v2+json",
Config: config,

View File

@@ -25,7 +25,7 @@ func createManifest(t *testing.T, path, name string) {
}
defer f.Close()
if err := json.NewEncoder(f).Encode(ManifestV2{}); err != nil {
if err := json.NewEncoder(f).Encode(Manifest{}); err != nil {
t.Fatal(err)
}
}

View File

@@ -4,6 +4,7 @@ import (
"archive/zip"
"bytes"
"context"
"encoding/json"
"errors"
"fmt"
"io"
@@ -11,12 +12,14 @@ import (
"net/http"
"os"
"path/filepath"
"slices"
"strings"
"text/template/parse"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/convert"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/templates"
"github.com/ollama/ollama/template"
"github.com/ollama/ollama/types/model"
)
@@ -91,12 +94,11 @@ func extractFromZipFile(p string, file *os.File, fn func(api.ProgressResponse))
fn(api.ProgressResponse{Status: "unpacking model metadata"})
for _, f := range r.File {
n := filepath.Join(p, f.Name)
if !strings.HasPrefix(n, p) {
slog.Warn("skipped extracting file outside of context", "name", f.Name)
continue
if !filepath.IsLocal(f.Name) {
return fmt.Errorf("%w: %s", zip.ErrInsecurePath, f.Name)
}
n := filepath.Join(p, f.Name)
if err := os.MkdirAll(filepath.Dir(n), 0o750); err != nil {
return err
}
@@ -258,7 +260,7 @@ func parseFromFile(ctx context.Context, file *os.File, digest string, fn func(ap
func detectChatTemplate(layers []*layerGGML) ([]*layerGGML, error) {
for _, layer := range layers {
if s := layer.GGML.KV().ChatTemplate(); s != "" {
if t, err := templates.NamedTemplate(s); err != nil {
if t, err := template.Named(s); err != nil {
slog.Debug("template detection", "error", err)
} else {
tmpl, err := NewLayer(t.Reader(), "application/vnd.ollama.image.template")
@@ -291,3 +293,92 @@ func detectContentType(r io.Reader) (string, error) {
return "unknown", nil
}
// parseToolCalls attempts to parse a JSON string into a slice of ToolCalls.
// mxyng: this only really works if the input contains tool calls in some JSON format
func (m *Model) parseToolCalls(s string) ([]api.ToolCall, bool) {
// create a subtree from the node that ranges over .ToolCalls
tmpl := m.Template.Subtree(func(n parse.Node) bool {
if t, ok := n.(*parse.RangeNode); ok {
return slices.Contains(template.Identifiers(t.Pipe), "ToolCalls")
}
return false
})
if tmpl == nil {
return nil, false
}
var b bytes.Buffer
if err := tmpl.Execute(&b, map[string][]api.ToolCall{
"ToolCalls": {
{
Function: api.ToolCallFunction{
Name: "@@name@@",
Arguments: api.ToolCallFunctionArguments{
"@@argument@@": 1,
},
},
},
},
}); err != nil {
return nil, false
}
var kv map[string]any
// execute the subtree with placeholders to identify the keys
// trim any commands that might exist in the template
if err := json.Unmarshal(bytes.TrimSuffix(b.Bytes(), []byte(",")), &kv); err != nil {
return nil, false
}
// find the keys that correspond to the name and arguments fields
var name, arguments string
for k, v := range kv {
switch v.(type) {
case string:
name = k
case map[string]any:
arguments = k
}
}
var objs []map[string]any
for offset := 0; offset < len(s); {
var obj map[string]any
decoder := json.NewDecoder(strings.NewReader(s[offset:]))
if err := decoder.Decode(&obj); errors.Is(err, io.EOF) || errors.Is(err, io.ErrUnexpectedEOF) {
break
} else if syntax := &(json.SyntaxError{}); errors.As(err, &syntax) {
// skip over any syntax errors
offset += int(syntax.Offset)
} else if unmarshalType := &(json.UnmarshalTypeError{}); errors.As(err, &unmarshalType) {
// skip over any unmarshalable types
offset += int(unmarshalType.Offset)
} else if err != nil {
slog.Error("parseToolCalls", "error", err)
return nil, false
} else {
offset += int(decoder.InputOffset())
objs = append(objs, obj)
}
}
var toolCalls []api.ToolCall
for _, kv := range objs {
var call api.ToolCall
for k, v := range kv {
switch k {
case name:
call.Function.Name = v.(string)
case arguments:
call.Function.Arguments = v.(map[string]any)
}
}
toolCalls = append(toolCalls, call)
}
return toolCalls, len(toolCalls) > 0
}

View File

@@ -3,13 +3,19 @@ package server
import (
"archive/zip"
"bytes"
"encoding/json"
"errors"
"fmt"
"io"
"os"
"path/filepath"
"slices"
"strings"
"testing"
"github.com/google/go-cmp/cmp"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/template"
)
func createZipFile(t *testing.T, name string) *os.File {
@@ -39,13 +45,31 @@ func TestExtractFromZipFile(t *testing.T) {
cases := []struct {
name string
expect []string
err error
}{
{
name: "good",
expect: []string{"good"},
},
{
name: filepath.Join("..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "bad"),
name: strings.Join([]string{"path", "..", "to", "good"}, string(os.PathSeparator)),
expect: []string{filepath.Join("to", "good")},
},
{
name: strings.Join([]string{"path", "..", "to", "..", "good"}, string(os.PathSeparator)),
expect: []string{"good"},
},
{
name: strings.Join([]string{"path", "to", "..", "..", "good"}, string(os.PathSeparator)),
expect: []string{"good"},
},
{
name: strings.Join([]string{"..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "..", "bad"}, string(os.PathSeparator)),
err: zip.ErrInsecurePath,
},
{
name: strings.Join([]string{"path", "..", "..", "to", "bad"}, string(os.PathSeparator)),
err: zip.ErrInsecurePath,
},
}
@@ -55,7 +79,7 @@ func TestExtractFromZipFile(t *testing.T) {
defer f.Close()
tempDir := t.TempDir()
if err := extractFromZipFile(tempDir, f, func(api.ProgressResponse) {}); err != nil {
if err := extractFromZipFile(tempDir, f, func(api.ProgressResponse) {}); !errors.Is(err, tt.err) {
t.Fatal(err)
}
@@ -90,3 +114,122 @@ func TestExtractFromZipFile(t *testing.T) {
})
}
}
func readFile(t *testing.T, base, name string) *bytes.Buffer {
t.Helper()
bts, err := os.ReadFile(filepath.Join(base, name))
if err != nil {
t.Fatal(err)
}
return bytes.NewBuffer(bts)
}
func TestExecuteWithTools(t *testing.T) {
p := filepath.Join("testdata", "tools")
cases := []struct {
model string
output string
ok bool
}{
{"mistral", `[TOOL_CALLS] [{"name": "get_current_weather", "arguments": {"format":"fahrenheit","location":"San Francisco, CA"}},{"name": "get_current_weather", "arguments": {"format":"celsius","location":"Toronto, Canada"}}]`, true},
{"mistral", `[TOOL_CALLS] [{"name": "get_current_weather", "arguments": {"format":"fahrenheit","location":"San Francisco, CA"}},{"name": "get_current_weather", "arguments": {"format":"celsius","location":"Toronto, Canada"}}]
The temperature in San Francisco, CA is 70°F and in Toronto, Canada is 20°C.`, true},
{"mistral", `I'm not aware of that information. However, I can suggest searching for the weather using the "get_current_weather" function:
[{"name": "get_current_weather", "arguments": {"format":"fahrenheit","location":"San Francisco, CA"}},{"name": "get_current_weather", "arguments": {"format":"celsius","location":"Toronto, Canada"}}]`, true},
{"mistral", " The weather in San Francisco, CA is 70°F and in Toronto, Canada is 20°C.", false},
{"command-r-plus", "Action: ```json" + `
[
{
"tool_name": "get_current_weather",
"parameters": {
"format": "fahrenheit",
"location": "San Francisco, CA"
}
},
{
"tool_name": "get_current_weather",
"parameters": {
"format": "celsius",
"location": "Toronto, Canada"
}
}
]
` + "```", true},
{"command-r-plus", " The weather in San Francisco, CA is 70°F and in Toronto, Canada is 20°C.", false},
{"firefunction", ` functools[{"name": "get_current_weather", "arguments": {"format":"fahrenheit","location":"San Francisco, CA"}},{"name": "get_current_weather", "arguments": {"format":"celsius","location":"Toronto, Canada"}}]`, true},
{"firefunction", " The weather in San Francisco, CA is 70°F and in Toronto, Canada is 20°C.", false},
{"llama3-groq-tool-use", `<tool_call>
{"name": "get_current_weather", "arguments": {"format":"fahrenheit","location":"San Francisco, CA"}}
{"name": "get_current_weather", "arguments": {"format":"celsius","location":"Toronto, Canada"}}
</tool_call>`, true},
}
var tools []api.Tool
if err := json.Unmarshal(readFile(t, p, "tools.json").Bytes(), &tools); err != nil {
t.Fatal(err)
}
var messages []api.Message
if err := json.Unmarshal(readFile(t, p, "messages.json").Bytes(), &messages); err != nil {
t.Fatal(err)
}
calls := []api.ToolCall{
{
Function: api.ToolCallFunction{
Name: "get_current_weather",
Arguments: api.ToolCallFunctionArguments{
"format": "fahrenheit",
"location": "San Francisco, CA",
},
},
},
{
Function: api.ToolCallFunction{
Name: "get_current_weather",
Arguments: api.ToolCallFunctionArguments{
"format": "celsius",
"location": "Toronto, Canada",
},
},
},
}
for _, tt := range cases {
t.Run(tt.model, func(t *testing.T) {
tmpl, err := template.Parse(readFile(t, p, fmt.Sprintf("%s.gotmpl", tt.model)).String())
if err != nil {
t.Fatal(err)
}
t.Run("template", func(t *testing.T) {
var actual bytes.Buffer
if err := tmpl.Execute(&actual, template.Values{Tools: tools, Messages: messages}); err != nil {
t.Fatal(err)
}
if diff := cmp.Diff(actual.String(), readFile(t, p, fmt.Sprintf("%s.out", tt.model)).String()); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
t.Run("parse", func(t *testing.T) {
m := &Model{Template: tmpl}
actual, ok := m.parseToolCalls(tt.output)
if ok != tt.ok {
t.Fatalf("expected %t, got %t", tt.ok, ok)
}
if tt.ok {
if diff := cmp.Diff(actual, calls); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
}
})
})
}
}

View File

@@ -103,18 +103,9 @@ func (mp ModelPath) GetShortTagname() string {
return fmt.Sprintf("%s/%s/%s:%s", mp.Registry, mp.Namespace, mp.Repository, mp.Tag)
}
// modelsDir returns the value of the OLLAMA_MODELS environment variable or the user's home directory if OLLAMA_MODELS is not set.
// The models directory is where Ollama stores its model files and manifests.
func modelsDir() (string, error) {
return envconfig.ModelsDir, nil
}
// GetManifestPath returns the path to the manifest file for the given model path, it is up to the caller to create the directory if it does not exist.
func (mp ModelPath) GetManifestPath() (string, error) {
dir, err := modelsDir()
if err != nil {
return "", err
}
dir := envconfig.ModelsDir
return filepath.Join(dir, "manifests", mp.Registry, mp.Namespace, mp.Repository, mp.Tag), nil
}
@@ -127,10 +118,7 @@ func (mp ModelPath) BaseURL() *url.URL {
}
func GetManifestPath() (string, error) {
dir, err := modelsDir()
if err != nil {
return "", err
}
dir := envconfig.ModelsDir
path := filepath.Join(dir, "manifests")
if err := os.MkdirAll(path, 0o755); err != nil {
@@ -141,10 +129,7 @@ func GetManifestPath() (string, error) {
}
func GetBlobsPath(digest string) (string, error) {
dir, err := modelsDir()
if err != nil {
return "", err
}
dir := envconfig.ModelsDir
// only accept actual sha256 digests
pattern := "^sha256[:-][0-9a-fA-F]{64}$"

View File

@@ -1,221 +1,74 @@
package server
import (
"fmt"
"bytes"
"context"
"log/slog"
"strings"
"text/template"
"text/template/parse"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/template"
)
// isResponseNode checks if the node contains .Response
func isResponseNode(node *parse.ActionNode) bool {
for _, cmd := range node.Pipe.Cmds {
for _, arg := range cmd.Args {
if fieldNode, ok := arg.(*parse.FieldNode); ok && len(fieldNode.Ident) > 0 {
if fieldNode.Ident[0] == "Response" {
return true
}
type tokenizeFunc func(context.Context, string) ([]int, error)
// chatPrompt accepts a list of messages and returns the prompt and images that should be used for the next chat turn.
// chatPrompt truncates any messages that exceed the context window of the model, making sure to always include 1) the
// latest message and 2) system messages
func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.Options, msgs []api.Message, tools []api.Tool) (prompt string, images []llm.ImageData, _ error) {
var system []api.Message
// always include the last message
n := len(msgs) - 1
// in reverse, find all messages that fit into context window
for i := n - 1; i >= 0; i-- {
system = make([]api.Message, 0)
for j := range i {
if msgs[j].Role == "system" {
system = append(system, msgs[j])
}
}
}
return false
}
// formatTemplateForResponse formats the template AST to:
// 1. remove all nodes after the first .Response (if generate=true)
// 2. add a .Response node to the end if it doesn't exist
// TODO(jmorganca): this should recursively cut the template before the first .Response
func formatTemplateForResponse(tmpl *template.Template, generate bool) {
var found bool
for i, node := range tmpl.Tree.Root.Nodes {
if actionNode, ok := node.(*parse.ActionNode); ok {
if isResponseNode(actionNode) {
found = true
if generate {
tmpl.Tree.Root.Nodes = tmpl.Tree.Root.Nodes[:i+1]
break
}
}
var b bytes.Buffer
if err := m.Template.Execute(&b, template.Values{Messages: append(system, msgs[i:]...), Tools: tools}); err != nil {
return "", nil, err
}
}
if !found {
// add the response node if it doesn't exist
responseFieldNode := &parse.FieldNode{NodeType: parse.NodeField, Ident: []string{"Response"}}
responsePipeNode := &parse.PipeNode{NodeType: parse.NodePipe, Cmds: []*parse.CommandNode{{NodeType: parse.NodeCommand, Args: []parse.Node{responseFieldNode}}}}
responseActionNode := &parse.ActionNode{NodeType: parse.NodeAction, Pipe: responsePipeNode}
tmpl.Tree.Root.Nodes = append(tmpl.Tree.Root.Nodes, responseActionNode)
}
}
// Prompt renders a prompt from a template. If generate is set to true,
// the response and parts of the template following it are not rendered
func Prompt(tmpl, system, prompt, response string, generate bool) (string, error) {
parsed, err := template.New("").Option("missingkey=zero").Parse(tmpl)
if err != nil {
return "", err
}
formatTemplateForResponse(parsed, generate)
vars := map[string]any{
"System": system,
"Prompt": prompt,
"Response": response,
}
var sb strings.Builder
if err := parsed.Execute(&sb, vars); err != nil {
return "", err
}
return sb.String(), nil
}
func countTokens(tmpl string, system string, prompt string, response string, encode func(string) ([]int, error)) (int, error) {
rendered, err := Prompt(tmpl, system, prompt, response, false)
if err != nil {
return 0, err
}
tokens, err := encode(rendered)
if err != nil {
slog.Error("failed to encode prompt", "err", err)
return 0, err
}
return len(tokens), err
}
// ChatPrompt builds up a prompt from a series of messages, truncating based on context window size
func ChatPrompt(tmpl string, messages []api.Message, window int, encode func(string) ([]int, error)) (string, error) {
type prompt struct {
System string
Prompt string
Response string
images []int
tokens int
}
var p prompt
// iterate through messages to build up {system,user,response} prompts
var imgId int
var prompts []prompt
for _, msg := range messages {
switch strings.ToLower(msg.Role) {
case "system":
if p.System != "" || p.Prompt != "" || p.Response != "" {
prompts = append(prompts, p)
p = prompt{}
}
p.System = msg.Content
case "user":
if p.Prompt != "" || p.Response != "" {
prompts = append(prompts, p)
p = prompt{}
}
var sb strings.Builder
for range msg.Images {
fmt.Fprintf(&sb, "[img-%d] ", imgId)
p.images = append(p.images, imgId)
imgId += 1
}
sb.WriteString(msg.Content)
p.Prompt = sb.String()
case "assistant":
if p.Response != "" {
prompts = append(prompts, p)
p = prompt{}
}
p.Response = msg.Content
default:
return "", fmt.Errorf("invalid role: %s, role must be one of [system, user, assistant]", msg.Role)
}
}
// add final prompt
if p.System != "" || p.Prompt != "" || p.Response != "" {
prompts = append(prompts, p)
}
// calculate token lengths for each prompt, estimating 768 tokens per images
for i, p := range prompts {
tokens, err := countTokens(tmpl, p.System, p.Prompt, p.Response, encode)
s, err := tokenize(ctx, b.String())
if err != nil {
return "", err
return "", nil, err
}
prompts[i].tokens = tokens + len(prompts[i].images)*768
}
// truncate images and prompts starting from the beginning of the list
// until either one prompt remains or the total tokens fits the context window
// TODO (jmorganca): this doesn't account for the context window room required for the response
for {
var required int
for _, p := range prompts {
required += p.tokens
c := len(s)
if m.ProjectorPaths != nil {
for _, m := range msgs[i:] {
// images are represented as 768 sized embeddings
// TODO: get embedding length from project metadata
c += 768 * len(m.Images)
}
}
required += 1 // for bos token
if required <= window {
slog.Debug("prompt now fits in context window", "required", required, "window", window)
if c > opts.NumCtx {
slog.Debug("truncating input messages which exceed context length", "truncated", len(msgs[i:]))
break
} else {
n = i
}
prompt := &prompts[0]
if len(prompt.images) > 1 {
img := prompt.images[0]
slog.Debug("prompt longer than context window, removing image", "id", img, "required", required, "window", window)
prompt.images = prompt.images[1:]
prompt.Prompt = strings.Replace(prompt.Prompt, fmt.Sprintf(" [img-%d]", img), "", 1)
prompt.tokens -= 768
continue
}
if len(prompts) > 1 {
slog.Debug("required tokens longer than context window, removing first prompt", "prompt", prompts[0].tokens, "required", required, "window", window)
system := prompt.System
prompts = prompts[1:]
if system != "" && prompts[0].System == "" {
prompts[0].System = system
tokens, err := countTokens(tmpl, prompts[0].System, prompts[0].Prompt, prompts[0].Response, encode)
if err != nil {
return "", err
}
prompts[0].tokens = tokens + len(prompts[0].images)*768
}
continue
}
// stop truncating if there's only one prompt left
break
}
var sb strings.Builder
for i, p := range prompts {
// last prompt should leave the response unrendered (for completion)
rendered, err := Prompt(tmpl, p.System, p.Prompt, p.Response, i == len(prompts)-1)
if err != nil {
return "", err
}
sb.WriteString(rendered)
// truncate any messages that do not fit into the context window
var b bytes.Buffer
if err := m.Template.Execute(&b, template.Values{Messages: append(system, msgs[n:]...), Tools: tools}); err != nil {
return "", nil, err
}
return sb.String(), nil
for _, m := range msgs[n:] {
for _, i := range m.Images {
images = append(images, llm.ImageData{
ID: len(images),
Data: i,
})
}
}
return b.String(), images, nil
}

View File

@@ -1,204 +1,209 @@
package server
import (
"strings"
"bytes"
"context"
"testing"
"github.com/google/go-cmp/cmp"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/template"
)
func TestPrompt(t *testing.T) {
tests := []struct {
name string
template string
system string
prompt string
response string
generate bool
want string
}{
{
name: "simple prompt",
template: "[INST] {{ .System }} {{ .Prompt }} [/INST]",
system: "You are a Wizard.",
prompt: "What are the potion ingredients?",
want: "[INST] You are a Wizard. What are the potion ingredients? [/INST]",
},
{
name: "implicit response",
template: "[INST] {{ .System }} {{ .Prompt }} [/INST]",
system: "You are a Wizard.",
prompt: "What are the potion ingredients?",
response: "I don't know.",
want: "[INST] You are a Wizard. What are the potion ingredients? [/INST]I don't know.",
},
{
name: "response",
template: "[INST] {{ .System }} {{ .Prompt }} [/INST] {{ .Response }}",
system: "You are a Wizard.",
prompt: "What are the potion ingredients?",
response: "I don't know.",
want: "[INST] You are a Wizard. What are the potion ingredients? [/INST] I don't know.",
},
{
name: "cut",
template: "<system>{{ .System }}</system><user>{{ .Prompt }}</user><assistant>{{ .Response }}</assistant>",
system: "You are a Wizard.",
prompt: "What are the potion ingredients?",
response: "I don't know.",
generate: true,
want: "<system>You are a Wizard.</system><user>What are the potion ingredients?</user><assistant>I don't know.",
},
{
name: "nocut",
template: "<system>{{ .System }}</system><user>{{ .Prompt }}</user><assistant>{{ .Response }}</assistant>",
system: "You are a Wizard.",
prompt: "What are the potion ingredients?",
response: "I don't know.",
want: "<system>You are a Wizard.</system><user>What are the potion ingredients?</user><assistant>I don't know.</assistant>",
},
}
for _, tc := range tests {
t.Run(tc.name, func(t *testing.T) {
got, err := Prompt(tc.template, tc.system, tc.prompt, tc.response, tc.generate)
if err != nil {
t.Errorf("error = %v", err)
}
if got != tc.want {
t.Errorf("got = %v, want %v", got, tc.want)
}
})
}
}
func TestChatPrompt(t *testing.T) {
tests := []struct {
name string
template string
messages []api.Message
window int
want string
type expect struct {
prompt string
images [][]byte
}
cases := []struct {
name string
limit int
msgs []api.Message
expect
}{
{
name: "simple prompt",
template: "[INST] {{ .Prompt }} [/INST]",
messages: []api.Message{
{Role: "user", Content: "Hello"},
name: "messages",
limit: 64,
msgs: []api.Message{
{Role: "user", Content: "You're a test, Harry!"},
{Role: "assistant", Content: "I-I'm a what?"},
{Role: "user", Content: "A test. And a thumping good one at that, I'd wager."},
},
expect: expect{
prompt: "You're a test, Harry! I-I'm a what? A test. And a thumping good one at that, I'd wager. ",
},
window: 1024,
want: "[INST] Hello [/INST]",
},
{
name: "with system message",
template: "[INST] {{ if .System }}<<SYS>>{{ .System }}<</SYS>> {{ end }}{{ .Prompt }} [/INST]",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "Hello"},
name: "truncate messages",
limit: 1,
msgs: []api.Message{
{Role: "user", Content: "You're a test, Harry!"},
{Role: "assistant", Content: "I-I'm a what?"},
{Role: "user", Content: "A test. And a thumping good one at that, I'd wager."},
},
expect: expect{
prompt: "A test. And a thumping good one at that, I'd wager. ",
},
window: 1024,
want: "[INST] <<SYS>>You are a Wizard.<</SYS>> Hello [/INST]",
},
{
name: "with response",
template: "[INST] {{ if .System }}<<SYS>>{{ .System }}<</SYS>> {{ end }}{{ .Prompt }} [/INST] {{ .Response }}",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "Hello"},
{Role: "assistant", Content: "I am?"},
name: "truncate messages with image",
limit: 64,
msgs: []api.Message{
{Role: "user", Content: "You're a test, Harry!"},
{Role: "assistant", Content: "I-I'm a what?"},
{Role: "user", Content: "A test. And a thumping good one at that, I'd wager.", Images: []api.ImageData{[]byte("something")}},
},
expect: expect{
prompt: "[img-0] A test. And a thumping good one at that, I'd wager. ",
images: [][]byte{
[]byte("something"),
},
},
window: 1024,
want: "[INST] <<SYS>>You are a Wizard.<</SYS>> Hello [/INST] I am?",
},
{
name: "with implicit response",
template: "[INST] {{ if .System }}<<SYS>>{{ .System }}<</SYS>> {{ end }}{{ .Prompt }} [/INST]",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "Hello"},
{Role: "assistant", Content: "I am?"},
name: "truncate messages with images",
limit: 64,
msgs: []api.Message{
{Role: "user", Content: "You're a test, Harry!", Images: []api.ImageData{[]byte("something")}},
{Role: "assistant", Content: "I-I'm a what?"},
{Role: "user", Content: "A test. And a thumping good one at that, I'd wager.", Images: []api.ImageData{[]byte("somethingelse")}},
},
expect: expect{
prompt: "[img-0] A test. And a thumping good one at that, I'd wager. ",
images: [][]byte{
[]byte("somethingelse"),
},
},
window: 1024,
want: "[INST] <<SYS>>You are a Wizard.<</SYS>> Hello [/INST]I am?",
},
{
name: "with conversation",
template: "[INST] {{ if .System }}<<SYS>>{{ .System }}<</SYS>> {{ end }}{{ .Prompt }} [/INST] {{ .Response }} ",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "What are the potion ingredients?"},
{Role: "assistant", Content: "sugar"},
{Role: "user", Content: "Anything else?"},
name: "messages with images",
limit: 2048,
msgs: []api.Message{
{Role: "user", Content: "You're a test, Harry!", Images: []api.ImageData{[]byte("something")}},
{Role: "assistant", Content: "I-I'm a what?"},
{Role: "user", Content: "A test. And a thumping good one at that, I'd wager.", Images: []api.ImageData{[]byte("somethingelse")}},
},
expect: expect{
prompt: "[img-0] You're a test, Harry! I-I'm a what? [img-1] A test. And a thumping good one at that, I'd wager. ",
images: [][]byte{
[]byte("something"),
[]byte("somethingelse"),
},
},
window: 1024,
want: "[INST] <<SYS>>You are a Wizard.<</SYS>> What are the potion ingredients? [/INST] sugar [INST] Anything else? [/INST] ",
},
{
name: "with truncation",
template: "{{ .System }} {{ .Prompt }} {{ .Response }} ",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "Hello"},
{Role: "assistant", Content: "I am?"},
{Role: "user", Content: "Why is the sky blue?"},
{Role: "assistant", Content: "The sky is blue from rayleigh scattering"},
name: "message with image tag",
limit: 2048,
msgs: []api.Message{
{Role: "user", Content: "You're a test, Harry! [img]", Images: []api.ImageData{[]byte("something")}},
{Role: "assistant", Content: "I-I'm a what?"},
{Role: "user", Content: "A test. And a thumping good one at that, I'd wager.", Images: []api.ImageData{[]byte("somethingelse")}},
},
expect: expect{
prompt: "You're a test, Harry! [img-0] I-I'm a what? [img-1] A test. And a thumping good one at that, I'd wager. ",
images: [][]byte{
[]byte("something"),
[]byte("somethingelse"),
},
},
window: 10,
want: "You are a Wizard. Why is the sky blue? The sky is blue from rayleigh scattering",
},
{
name: "images",
template: "{{ .System }} {{ .Prompt }}",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "Hello", Images: []api.ImageData{[]byte("base64")}},
name: "messages with interleaved images",
limit: 2048,
msgs: []api.Message{
{Role: "user", Content: "You're a test, Harry!"},
{Role: "user", Images: []api.ImageData{[]byte("something")}},
{Role: "user", Images: []api.ImageData{[]byte("somethingelse")}},
{Role: "assistant", Content: "I-I'm a what?"},
{Role: "user", Content: "A test. And a thumping good one at that, I'd wager."},
},
expect: expect{
prompt: "You're a test, Harry!\n\n[img-0]\n\n[img-1] I-I'm a what? A test. And a thumping good one at that, I'd wager. ",
images: [][]byte{
[]byte("something"),
[]byte("somethingelse"),
},
},
window: 1024,
want: "You are a Wizard. [img-0] Hello",
},
{
name: "images truncated",
template: "{{ .System }} {{ .Prompt }}",
messages: []api.Message{
{Role: "system", Content: "You are a Wizard."},
{Role: "user", Content: "Hello", Images: []api.ImageData{[]byte("img1"), []byte("img2")}},
name: "truncate message with interleaved images",
limit: 1024,
msgs: []api.Message{
{Role: "user", Content: "You're a test, Harry!"},
{Role: "user", Images: []api.ImageData{[]byte("something")}},
{Role: "user", Images: []api.ImageData{[]byte("somethingelse")}},
{Role: "assistant", Content: "I-I'm a what?"},
{Role: "user", Content: "A test. And a thumping good one at that, I'd wager."},
},
expect: expect{
prompt: "[img-0] I-I'm a what? A test. And a thumping good one at that, I'd wager. ",
images: [][]byte{
[]byte("somethingelse"),
},
},
window: 1024,
want: "You are a Wizard. [img-0] [img-1] Hello",
},
{
name: "empty list",
template: "{{ .System }} {{ .Prompt }}",
messages: []api.Message{},
window: 1024,
want: "",
name: "message with system prompt",
limit: 2048,
msgs: []api.Message{
{Role: "system", Content: "You are the Test Who Lived."},
{Role: "user", Content: "You're a test, Harry!"},
{Role: "assistant", Content: "I-I'm a what?"},
{Role: "user", Content: "A test. And a thumping good one at that, I'd wager."},
},
expect: expect{
prompt: "You are the Test Who Lived. You're a test, Harry! I-I'm a what? A test. And a thumping good one at that, I'd wager. ",
},
},
{
name: "empty prompt",
template: "[INST] {{ if .System }}<<SYS>>{{ .System }}<</SYS>> {{ end }}{{ .Prompt }} [/INST] {{ .Response }} ",
messages: []api.Message{
{Role: "user", Content: ""},
name: "out of order system",
limit: 2048,
msgs: []api.Message{
{Role: "user", Content: "You're a test, Harry!"},
{Role: "assistant", Content: "I-I'm a what?"},
{Role: "system", Content: "You are the Test Who Lived."},
{Role: "user", Content: "A test. And a thumping good one at that, I'd wager."},
},
expect: expect{
prompt: "You're a test, Harry! I-I'm a what? You are the Test Who Lived. A test. And a thumping good one at that, I'd wager. ",
},
window: 1024,
want: "",
},
}
encode := func(s string) ([]int, error) {
words := strings.Fields(s)
return make([]int, len(words)), nil
tmpl, err := template.Parse(`
{{- if .System }}{{ .System }} {{ end }}
{{- if .Prompt }}{{ .Prompt }} {{ end }}
{{- if .Response }}{{ .Response }} {{ end }}`)
if err != nil {
t.Fatal(err)
}
for _, tc := range tests {
t.Run(tc.name, func(t *testing.T) {
got, err := ChatPrompt(tc.template, tc.messages, tc.window, encode)
for _, tt := range cases {
t.Run(tt.name, func(t *testing.T) {
model := Model{Template: tmpl, ProjectorPaths: []string{"vision"}}
opts := api.Options{Runner: api.Runner{NumCtx: tt.limit}}
prompt, images, err := chatPrompt(context.TODO(), &model, mockRunner{}.Tokenize, &opts, tt.msgs, nil)
if err != nil {
t.Errorf("error = %v", err)
t.Fatal(err)
}
if got != tc.want {
t.Errorf("got: %q, want: %q", got, tc.want)
if diff := cmp.Diff(prompt, tt.prompt); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
if len(images) != len(tt.images) {
t.Fatalf("expected %d images, got %d", len(tt.images), len(images))
}
for i := range images {
if images[i].ID != i {
t.Errorf("expected ID %d, got %d", i, images[i].ID)
}
if !bytes.Equal(images[i].Data, tt.images[i]) {
t.Errorf("expected %q, got %q", tt.images[i], images[i])
}
}
})
}

View File

@@ -1,13 +1,13 @@
package server
import (
"bytes"
"cmp"
"context"
"encoding/json"
"errors"
"fmt"
"io"
"io/fs"
"log/slog"
"math"
"net"
@@ -17,7 +17,6 @@ import (
"os/signal"
"path/filepath"
"slices"
"strconv"
"strings"
"syscall"
"time"
@@ -31,6 +30,7 @@ import (
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/openai"
"github.com/ollama/ollama/parser"
"github.com/ollama/ollama/template"
"github.com/ollama/ollama/types/errtypes"
"github.com/ollama/ollama/types/model"
"github.com/ollama/ollama/version"
@@ -55,7 +55,8 @@ func init() {
gin.SetMode(mode)
}
var defaultSessionDuration = 5 * time.Minute
var errRequired = errors.New("is required")
var errBadTemplate = errors.New("template error")
func modelOptions(model *Model, requestOpts map[string]interface{}) (api.Options, error) {
opts := api.DefaultOptions()
@@ -70,277 +71,220 @@ func modelOptions(model *Model, requestOpts map[string]interface{}) (api.Options
return opts, nil
}
func isSupportedImageType(image []byte) bool {
contentType := http.DetectContentType(image)
allowedTypes := []string{"image/jpeg", "image/jpg", "image/png"}
return slices.Contains(allowedTypes, contentType)
// scheduleRunner schedules a runner after validating inputs such as capabilities and model options.
// It returns the allocated runner, model instance, and consolidated options if successful and error otherwise.
func (s *Server) scheduleRunner(ctx context.Context, name string, caps []Capability, requestOpts map[string]any, keepAlive *api.Duration) (llm.LlamaServer, *Model, *api.Options, error) {
if name == "" {
return nil, nil, nil, fmt.Errorf("model %w", errRequired)
}
model, err := GetModel(name)
if err != nil {
return nil, nil, nil, err
}
if err := model.CheckCapabilities(caps...); err != nil {
return nil, nil, nil, fmt.Errorf("%s %w", name, err)
}
opts, err := modelOptions(model, requestOpts)
if err != nil {
return nil, nil, nil, err
}
runnerCh, errCh := s.sched.GetRunner(ctx, model, opts, keepAlive)
var runner *runnerRef
select {
case runner = <-runnerCh:
case err = <-errCh:
return nil, nil, nil, err
}
return runner.llama, model, &opts, nil
}
func (s *Server) GenerateHandler(c *gin.Context) {
checkpointStart := time.Now()
var req api.GenerateRequest
err := c.ShouldBindJSON(&req)
switch {
case errors.Is(err, io.EOF):
if err := c.ShouldBindJSON(&req); errors.Is(err, io.EOF) {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "missing request body"})
return
case err != nil:
} else if err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": err.Error()})
return
}
// validate the request
switch {
case req.Model == "":
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "model is required"})
if req.Format != "" && req.Format != "json" {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "format must be empty or \"json\""})
return
case len(req.Format) > 0 && req.Format != "json":
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "format must be json"})
return
case req.Raw && (req.Template != "" || req.System != "" || len(req.Context) > 0):
} else if req.Raw && (req.Template != "" || req.System != "" || len(req.Context) > 0) {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "raw mode does not support template, system, or context"})
return
}
for _, img := range req.Images {
if !isSupportedImageType(img) {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "unsupported image format"})
return
}
caps := []Capability{CapabilityCompletion}
if req.Suffix != "" {
caps = append(caps, CapabilityInsert)
}
model, err := GetModel(req.Model)
if err != nil {
var pErr *fs.PathError
if errors.As(err, &pErr) {
c.JSON(http.StatusNotFound, gin.H{"error": fmt.Sprintf("model '%s' not found, try pulling it first", req.Model)})
return
}
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
r, m, opts, err := s.scheduleRunner(c.Request.Context(), req.Model, caps, req.Options, req.KeepAlive)
if errors.Is(err, errCapabilityCompletion) {
c.JSON(http.StatusBadRequest, gin.H{"error": fmt.Sprintf("%q does not support generate", req.Model)})
return
} else if err != nil {
handleScheduleError(c, req.Model, err)
return
}
if model.IsEmbedding() {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "embedding models do not support generate"})
return
}
checkpointLoaded := time.Now()
opts, err := modelOptions(model, req.Options)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
var sessionDuration time.Duration
if req.KeepAlive == nil {
sessionDuration = getDefaultSessionDuration()
} else {
sessionDuration = req.KeepAlive.Duration
}
rCh, eCh := s.sched.GetRunner(c.Request.Context(), model, opts, sessionDuration)
var runner *runnerRef
select {
case runner = <-rCh:
case err = <-eCh:
handleErrorResponse(c, err)
return
}
// an empty request loads the model
// note: for a short while template was used in lieu
// of `raw` mode so we need to check for it too
if req.Prompt == "" && req.Template == "" && req.System == "" {
if req.Prompt == "" {
c.JSON(http.StatusOK, api.GenerateResponse{
CreatedAt: time.Now().UTC(),
Model: req.Model,
CreatedAt: time.Now().UTC(),
Done: true,
DoneReason: "load",
})
return
}
checkpointLoaded := time.Now()
images := make([]llm.ImageData, len(req.Images))
for i := range req.Images {
images[i] = llm.ImageData{ID: i, Data: req.Images[i]}
}
var prompt string
switch {
case req.Raw:
prompt = req.Prompt
case req.Prompt != "":
if req.Template == "" {
req.Template = model.Template
prompt := req.Prompt
if !req.Raw {
tmpl := m.Template
if req.Template != "" {
tmpl, err = template.Parse(req.Template)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
}
if req.System == "" {
req.System = model.System
}
slog.Debug("generate handler", "prompt", req.Prompt)
slog.Debug("generate handler", "template", req.Template)
slog.Debug("generate handler", "system", req.System)
var sb strings.Builder
for i := range req.Images {
fmt.Fprintf(&sb, "[img-%d] ", i)
}
sb.WriteString(req.Prompt)
p, err := Prompt(req.Template, req.System, sb.String(), "", true)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
sb.Reset()
var b bytes.Buffer
if req.Context != nil {
prev, err := runner.llama.Detokenize(c.Request.Context(), req.Context)
s, err := r.Detokenize(c.Request.Context(), req.Context)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
sb.WriteString(prev)
b.WriteString(s)
}
sb.WriteString(p)
prompt = sb.String()
}
slog.Debug("generate handler", "prompt", prompt)
ch := make(chan any)
var generated strings.Builder
go func() {
defer close(ch)
fn := func(r llm.CompletionResponse) {
// Build up the full response
if _, err := generated.WriteString(r.Content); err != nil {
ch <- gin.H{"error": err.Error()}
return
var values template.Values
if req.Suffix != "" {
values.Prompt = prompt
values.Suffix = req.Suffix
} else {
var msgs []api.Message
if req.System != "" {
msgs = append(msgs, api.Message{Role: "system", Content: req.System})
} else if m.System != "" {
msgs = append(msgs, api.Message{Role: "system", Content: m.System})
}
resp := api.GenerateResponse{
for _, i := range images {
msgs = append(msgs, api.Message{Role: "user", Content: fmt.Sprintf("[img-%d]", i.ID)})
}
values.Messages = append(msgs, api.Message{Role: "user", Content: req.Prompt})
}
if err := tmpl.Execute(&b, values); err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
prompt = b.String()
}
slog.Debug("generate request", "prompt", prompt, "images", images)
ch := make(chan any)
go func() {
// TODO (jmorganca): avoid building the response twice both here and below
var sb strings.Builder
defer close(ch)
if err := r.Completion(c.Request.Context(), llm.CompletionRequest{
Prompt: prompt,
Images: images,
Format: req.Format,
Options: opts,
}, func(cr llm.CompletionResponse) {
res := api.GenerateResponse{
Model: req.Model,
CreatedAt: time.Now().UTC(),
Done: r.Done,
Response: r.Content,
DoneReason: r.DoneReason,
Response: cr.Content,
Done: cr.Done,
DoneReason: cr.DoneReason,
Metrics: api.Metrics{
PromptEvalCount: r.PromptEvalCount,
PromptEvalDuration: r.PromptEvalDuration,
EvalCount: r.EvalCount,
EvalDuration: r.EvalDuration,
PromptEvalCount: cr.PromptEvalCount,
PromptEvalDuration: cr.PromptEvalDuration,
EvalCount: cr.EvalCount,
EvalDuration: cr.EvalDuration,
},
}
if r.Done {
resp.TotalDuration = time.Since(checkpointStart)
resp.LoadDuration = checkpointLoaded.Sub(checkpointStart)
if _, err := sb.WriteString(cr.Content); err != nil {
ch <- gin.H{"error": err.Error()}
}
if cr.Done {
res.TotalDuration = time.Since(checkpointStart)
res.LoadDuration = checkpointLoaded.Sub(checkpointStart)
if !req.Raw {
p, err := Prompt(req.Template, req.System, req.Prompt, generated.String(), false)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
// TODO (jmorganca): encode() should not strip special tokens
tokens, err := runner.llama.Tokenize(c.Request.Context(), p)
tokens, err := r.Tokenize(c.Request.Context(), prompt+sb.String())
if err != nil {
ch <- gin.H{"error": err.Error()}
return
}
resp.Context = append(req.Context, tokens...)
res.Context = append(req.Context, tokens...)
}
}
ch <- resp
}
var images []llm.ImageData
for i := range req.Images {
images = append(images, llm.ImageData{
ID: i,
Data: req.Images[i],
})
}
// Start prediction
req := llm.CompletionRequest{
Prompt: prompt,
Format: req.Format,
Images: images,
Options: opts,
}
if err := runner.llama.Completion(c.Request.Context(), req, fn); err != nil {
ch <- res
}); err != nil {
ch <- gin.H{"error": err.Error()}
}
}()
if req.Stream != nil && !*req.Stream {
// Accumulate responses into the final response
var final api.GenerateResponse
var r api.GenerateResponse
var sb strings.Builder
for resp := range ch {
switch r := resp.(type) {
for rr := range ch {
switch t := rr.(type) {
case api.GenerateResponse:
sb.WriteString(r.Response)
final = r
sb.WriteString(t.Response)
r = t
case gin.H:
if errorMsg, ok := r["error"].(string); ok {
c.JSON(http.StatusInternalServerError, gin.H{"error": errorMsg})
return
} else {
c.JSON(http.StatusInternalServerError, gin.H{"error": "unexpected error format in response"})
return
msg, ok := t["error"].(string)
if !ok {
msg = "unexpected error format in response"
}
c.JSON(http.StatusInternalServerError, gin.H{"error": msg})
return
default:
c.JSON(http.StatusInternalServerError, gin.H{"error": "unexpected error"})
c.JSON(http.StatusInternalServerError, gin.H{"error": "unexpected response"})
return
}
}
final.Response = sb.String()
c.JSON(http.StatusOK, final)
r.Response = sb.String()
c.JSON(http.StatusOK, r)
return
}
streamResponse(c, ch)
}
func getDefaultSessionDuration() time.Duration {
if envconfig.KeepAlive != "" {
v, err := strconv.Atoi(envconfig.KeepAlive)
if err != nil {
d, err := time.ParseDuration(envconfig.KeepAlive)
if err != nil {
return defaultSessionDuration
}
if d < 0 {
return time.Duration(math.MaxInt64)
}
return d
}
d := time.Duration(v) * time.Second
if d < 0 {
return time.Duration(math.MaxInt64)
}
return d
}
return defaultSessionDuration
}
func (s *Server) EmbeddingsHandler(c *gin.Context) {
var req api.EmbeddingRequest
func (s *Server) EmbedHandler(c *gin.Context) {
var req api.EmbedRequest
err := c.ShouldBindJSON(&req)
switch {
case errors.Is(err, io.EOF):
@@ -351,41 +295,122 @@ func (s *Server) EmbeddingsHandler(c *gin.Context) {
return
}
if req.Model == "" {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "model is required"})
truncate := true
if req.Truncate != nil && !*req.Truncate {
truncate = false
}
var input []string
switch i := req.Input.(type) {
case string:
if len(i) > 0 {
input = append(input, i)
}
case []any:
for _, v := range i {
if _, ok := v.(string); !ok {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "invalid input type"})
return
}
input = append(input, v.(string))
}
default:
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "invalid input type"})
return
}
model, err := GetModel(req.Model)
if len(input) == 0 {
c.JSON(http.StatusOK, api.EmbedResponse{Model: req.Model, Embeddings: [][]float32{}})
return
}
r, m, opts, err := s.scheduleRunner(c.Request.Context(), req.Model, []Capability{}, req.Options, req.KeepAlive)
if err != nil {
var pErr *fs.PathError
if errors.As(err, &pErr) {
c.JSON(http.StatusNotFound, gin.H{"error": fmt.Sprintf("model '%s' not found, try pulling it first", req.Model)})
handleScheduleError(c, req.Model, err)
return
}
kvData, err := getKVData(m.ModelPath, false)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
for i, s := range input {
tokens, err := r.Tokenize(c.Request.Context(), s)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
opts, err := modelOptions(model, req.Options)
ctxLen := min(opts.NumCtx, int(kvData.ContextLength()))
if len(tokens) > ctxLen {
if !truncate {
c.JSON(http.StatusBadRequest, gin.H{"error": "input length exceeds maximum context length"})
return
}
tokens = tokens[:ctxLen]
s, err = r.Detokenize(c.Request.Context(), tokens)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
}
input[i] = s
}
embeddings, err := r.Embed(c.Request.Context(), input)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
slog.Error("embedding generation failed", "error", err)
c.JSON(http.StatusInternalServerError, gin.H{"error": "failed to generate embedding"})
return
}
var sessionDuration time.Duration
if req.KeepAlive == nil {
sessionDuration = getDefaultSessionDuration()
} else {
sessionDuration = req.KeepAlive.Duration
for i, e := range embeddings {
embeddings[i] = normalize(e)
}
rCh, eCh := s.sched.GetRunner(c.Request.Context(), model, opts, sessionDuration)
var runner *runnerRef
select {
case runner = <-rCh:
case err = <-eCh:
handleErrorResponse(c, err)
resp := api.EmbedResponse{
Model: req.Model,
Embeddings: embeddings,
}
c.JSON(http.StatusOK, resp)
}
func normalize(vec []float32) []float32 {
var sum float32
for _, v := range vec {
sum += v * v
}
norm := float32(0.0)
if sum > 0 {
norm = float32(1.0 / math.Sqrt(float64(sum)))
}
for i := range vec {
vec[i] *= norm
}
return vec
}
func (s *Server) EmbeddingsHandler(c *gin.Context) {
var req api.EmbeddingRequest
if err := c.ShouldBindJSON(&req); errors.Is(err, io.EOF) {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "missing request body"})
return
} else if err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": err.Error()})
return
}
r, _, _, err := s.scheduleRunner(c.Request.Context(), req.Model, []Capability{}, req.Options, req.KeepAlive)
if err != nil {
handleScheduleError(c, req.Model, err)
return
}
@@ -395,13 +420,20 @@ func (s *Server) EmbeddingsHandler(c *gin.Context) {
return
}
embedding, err := runner.llama.Embedding(c.Request.Context(), req.Prompt)
embeddings, err := r.Embed(c.Request.Context(), []string{req.Prompt})
if err != nil {
slog.Info(fmt.Sprintf("embedding generation failed: %v", err))
c.JSON(http.StatusInternalServerError, gin.H{"error": "failed to generate embedding"})
return
}
embedding := make([]float64, len(embeddings[0]))
for i, v := range embeddings[0] {
embedding[i] = float64(v)
}
resp := api.EmbeddingResponse{
Embedding: embedding,
}
@@ -578,8 +610,11 @@ func (s *Server) CreateModelHandler(c *gin.Context) {
quantization := cmp.Or(r.Quantize, r.Quantization)
if err := CreateModel(ctx, name, filepath.Dir(r.Path), strings.ToUpper(quantization), f, fn); err != nil {
if errors.Is(err, errBadTemplate) {
ch <- gin.H{"error": err.Error(), "status": http.StatusBadRequest}
}
ch <- gin.H{"error": err.Error()}
}
}
}()
if r.Stream != nil && !*r.Stream {
@@ -679,13 +714,9 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
m.System = req.System
}
if req.Template != "" {
m.Template = req.Template
}
msgs := make([]api.Message, 0)
for _, msg := range m.Messages {
msgs = append(msgs, api.Message{Role: msg.Role, Content: msg.Content})
msgs := make([]api.Message, len(m.Messages))
for i, msg := range m.Messages {
msgs[i] = api.Message{Role: msg.Role, Content: msg.Content}
}
n := model.ParseName(req.Model)
@@ -701,7 +732,7 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
resp := &api.ShowResponse{
License: strings.Join(m.License, "\n"),
System: m.System,
Template: m.Template,
Template: m.Template.String(),
Details: modelDetails,
Messages: msgs,
ModifiedAt: manifest.fi.ModTime(),
@@ -1028,6 +1059,7 @@ func (s *Server) GenerateRoutes() http.Handler {
r.POST("/api/pull", s.PullModelHandler)
r.POST("/api/generate", s.GenerateHandler)
r.POST("/api/chat", s.ChatHandler)
r.POST("/api/embed", s.EmbedHandler)
r.POST("/api/embeddings", s.EmbeddingsHandler)
r.POST("/api/create", s.CreateModelHandler)
r.POST("/api/push", s.PushModelHandler)
@@ -1039,7 +1071,11 @@ func (s *Server) GenerateRoutes() http.Handler {
r.GET("/api/ps", s.ProcessHandler)
// Compatibility endpoints
r.POST("/v1/chat/completions", openai.Middleware(), s.ChatHandler)
r.POST("/v1/chat/completions", openai.ChatMiddleware(), s.ChatHandler)
r.POST("/v1/completions", openai.CompletionsMiddleware(), s.GenerateHandler)
r.POST("/v1/embeddings", openai.EmbeddingsMiddleware(), s.EmbedHandler)
r.GET("/v1/models", openai.ListMiddleware(), s.ListModelsHandler)
r.GET("/v1/models/:model", openai.RetrieveMiddleware(), s.ShowModelHandler)
for _, method := range []string{http.MethodGet, http.MethodHead} {
r.Handle(method, "/", func(c *gin.Context) {
@@ -1164,11 +1200,15 @@ func waitForStream(c *gin.Context, ch chan interface{}) {
return
}
case gin.H:
status, ok := r["status"].(int)
if !ok {
status = http.StatusInternalServerError
}
if errorMsg, ok := r["error"].(string); ok {
c.JSON(http.StatusInternalServerError, gin.H{"error": errorMsg})
c.JSON(status, gin.H{"error": errorMsg})
return
} else {
c.JSON(http.StatusInternalServerError, gin.H{"error": "unexpected error format in progress response"})
c.JSON(status, gin.H{"error": "unexpected error format in progress response"})
return
}
default:
@@ -1237,142 +1277,75 @@ func (s *Server) ProcessHandler(c *gin.Context) {
models = append(models, mr)
}
slices.SortStableFunc(models, func(i, j api.ProcessModelResponse) int {
// longest duration remaining listed first
return cmp.Compare(j.ExpiresAt.Unix(), i.ExpiresAt.Unix())
})
c.JSON(http.StatusOK, api.ProcessResponse{Models: models})
}
// ChatPrompt builds up a prompt from a series of messages for the currently `loaded` model
func chatPrompt(ctx context.Context, runner *runnerRef, template string, messages []api.Message, numCtx int) (string, error) {
encode := func(s string) ([]int, error) {
return runner.llama.Tokenize(ctx, s)
}
prompt, err := ChatPrompt(template, messages, numCtx, encode)
if err != nil {
return "", err
}
return prompt, nil
}
func (s *Server) ChatHandler(c *gin.Context) {
checkpointStart := time.Now()
var req api.ChatRequest
err := c.ShouldBindJSON(&req)
switch {
case errors.Is(err, io.EOF):
if err := c.ShouldBindJSON(&req); errors.Is(err, io.EOF) {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "missing request body"})
return
case err != nil:
} else if err != nil {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": err.Error()})
return
}
// validate the request
switch {
case req.Model == "":
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "model is required"})
return
case len(req.Format) > 0 && req.Format != "json":
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "format must be json"})
return
caps := []Capability{CapabilityCompletion}
if len(req.Tools) > 0 {
caps = append(caps, CapabilityTools)
}
model, err := GetModel(req.Model)
if err != nil {
var pErr *fs.PathError
if errors.As(err, &pErr) {
c.JSON(http.StatusNotFound, gin.H{"error": fmt.Sprintf("model '%s' not found, try pulling it first", req.Model)})
return
}
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
r, m, opts, err := s.scheduleRunner(c.Request.Context(), req.Model, caps, req.Options, req.KeepAlive)
if errors.Is(err, errCapabilityCompletion) {
c.JSON(http.StatusBadRequest, gin.H{"error": fmt.Sprintf("%q does not support chat", req.Model)})
return
}
if model.IsEmbedding() {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "embedding models do not support chat"})
return
}
opts, err := modelOptions(model, req.Options)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
var sessionDuration time.Duration
if req.KeepAlive == nil {
sessionDuration = getDefaultSessionDuration()
} else {
sessionDuration = req.KeepAlive.Duration
}
rCh, eCh := s.sched.GetRunner(c.Request.Context(), model, opts, sessionDuration)
var runner *runnerRef
select {
case runner = <-rCh:
case err = <-eCh:
handleErrorResponse(c, err)
} else if err != nil {
handleScheduleError(c, req.Model, err)
return
}
checkpointLoaded := time.Now()
// if the first message is not a system message, then add the model's default system message
if len(req.Messages) > 0 && req.Messages[0].Role != "system" {
req.Messages = append([]api.Message{
{
Role: "system",
Content: model.System,
},
}, req.Messages...)
}
prompt, err := chatPrompt(c.Request.Context(), runner, model.Template, req.Messages, opts.NumCtx)
if err != nil {
c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
return
}
// an empty request loads the model
if len(req.Messages) == 0 || prompt == "" {
resp := api.ChatResponse{
CreatedAt: time.Now().UTC(),
if len(req.Messages) == 0 {
c.JSON(http.StatusOK, api.ChatResponse{
Model: req.Model,
CreatedAt: time.Now().UTC(),
Message: api.Message{Role: "assistant"},
Done: true,
DoneReason: "load",
Message: api.Message{Role: "assistant"},
}
c.JSON(http.StatusOK, resp)
})
return
}
// only send images that are in the prompt
var i int
var images []llm.ImageData
for _, m := range req.Messages {
for _, img := range m.Images {
if !isSupportedImageType(img) {
c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "unsupported image format"})
return
}
if strings.Contains(prompt, fmt.Sprintf("[img-%d]", i)) {
images = append(images, llm.ImageData{Data: img, ID: i})
}
i += 1
}
if req.Messages[0].Role != "system" && m.System != "" {
req.Messages = append([]api.Message{{Role: "system", Content: m.System}}, req.Messages...)
}
slog.Debug("chat handler", "prompt", prompt, "images", len(images))
prompt, images, err := chatPrompt(c.Request.Context(), m, r.Tokenize, opts, req.Messages, req.Tools)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
slog.Debug("chat request", "images", len(images), "prompt", prompt)
ch := make(chan any)
go func() {
defer close(ch)
fn := func(r llm.CompletionResponse) {
resp := api.ChatResponse{
if err := r.Completion(c.Request.Context(), llm.CompletionRequest{
Prompt: prompt,
Images: images,
Format: req.Format,
Options: opts,
}, func(r llm.CompletionResponse) {
res := api.ChatResponse{
Model: req.Model,
CreatedAt: time.Now().UTC(),
Message: api.Message{Role: "assistant", Content: r.Content},
@@ -1387,62 +1360,65 @@ func (s *Server) ChatHandler(c *gin.Context) {
}
if r.Done {
resp.TotalDuration = time.Since(checkpointStart)
resp.LoadDuration = checkpointLoaded.Sub(checkpointStart)
res.TotalDuration = time.Since(checkpointStart)
res.LoadDuration = checkpointLoaded.Sub(checkpointStart)
}
ch <- resp
}
if err := runner.llama.Completion(c.Request.Context(), llm.CompletionRequest{
Prompt: prompt,
Format: req.Format,
Images: images,
Options: opts,
}, fn); err != nil {
ch <- res
}); err != nil {
ch <- gin.H{"error": err.Error()}
}
}()
if req.Stream != nil && !*req.Stream {
// Accumulate responses into the final response
var final api.ChatResponse
var resp api.ChatResponse
var sb strings.Builder
for resp := range ch {
switch r := resp.(type) {
for rr := range ch {
switch t := rr.(type) {
case api.ChatResponse:
sb.WriteString(r.Message.Content)
final = r
sb.WriteString(t.Message.Content)
resp = t
case gin.H:
if errorMsg, ok := r["error"].(string); ok {
c.JSON(http.StatusInternalServerError, gin.H{"error": errorMsg})
return
} else {
c.JSON(http.StatusInternalServerError, gin.H{"error": "unexpected error format in response"})
return
msg, ok := t["error"].(string)
if !ok {
msg = "unexpected error format in response"
}
c.JSON(http.StatusInternalServerError, gin.H{"error": msg})
return
default:
c.JSON(http.StatusInternalServerError, gin.H{"error": "unexpected error"})
c.JSON(http.StatusInternalServerError, gin.H{"error": "unexpected response"})
return
}
}
final.Message = api.Message{Role: "assistant", Content: sb.String()}
c.JSON(http.StatusOK, final)
resp.Message.Content = sb.String()
if len(req.Tools) > 0 {
if toolCalls, ok := m.parseToolCalls(sb.String()); ok {
resp.Message.ToolCalls = toolCalls
resp.Message.Content = ""
}
}
c.JSON(http.StatusOK, resp)
return
}
streamResponse(c, ch)
}
func handleErrorResponse(c *gin.Context, err error) {
if errors.Is(err, context.Canceled) {
func handleScheduleError(c *gin.Context, name string, err error) {
switch {
case errors.Is(err, errCapabilities), errors.Is(err, errRequired):
c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
case errors.Is(err, context.Canceled):
c.JSON(499, gin.H{"error": "request canceled"})
return
}
if errors.Is(err, ErrMaxQueue) {
case errors.Is(err, ErrMaxQueue):
c.JSON(http.StatusServiceUnavailable, gin.H{"error": err.Error()})
return
case errors.Is(err, os.ErrNotExist):
c.JSON(http.StatusNotFound, gin.H{"error": fmt.Sprintf("model %q not found, try pulling it first", name)})
default:
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
}
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
}

View File

@@ -85,6 +85,8 @@ func checkFileExists(t *testing.T, p string, expect []string) {
}
func TestCreateFromBin(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
envconfig.LoadConfig()
@@ -111,6 +113,8 @@ func TestCreateFromBin(t *testing.T) {
}
func TestCreateFromModel(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
envconfig.LoadConfig()
@@ -152,6 +156,8 @@ func TestCreateFromModel(t *testing.T) {
}
func TestCreateRemovesLayers(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
envconfig.LoadConfig()
@@ -199,6 +205,8 @@ func TestCreateRemovesLayers(t *testing.T) {
}
func TestCreateUnsetsSystem(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
envconfig.LoadConfig()
@@ -255,6 +263,8 @@ func TestCreateUnsetsSystem(t *testing.T) {
}
func TestCreateMergeParameters(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
envconfig.LoadConfig()
@@ -358,6 +368,8 @@ func TestCreateMergeParameters(t *testing.T) {
}
func TestCreateReplacesMessages(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
envconfig.LoadConfig()
@@ -434,6 +446,8 @@ func TestCreateReplacesMessages(t *testing.T) {
}
func TestCreateTemplateSystem(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
envconfig.LoadConfig()
@@ -477,9 +491,47 @@ func TestCreateTemplateSystem(t *testing.T) {
if string(system) != "Say bye!" {
t.Errorf("expected \"Say bye!\", actual %s", system)
}
t.Run("incomplete template", func(t *testing.T) {
w := createRequest(t, s.CreateModelHandler, api.CreateRequest{
Name: "test",
Modelfile: fmt.Sprintf("FROM %s\nTEMPLATE {{ .Prompt", createBinFile(t, nil, nil)),
Stream: &stream,
})
if w.Code != http.StatusBadRequest {
t.Fatalf("expected status code 400, actual %d", w.Code)
}
})
t.Run("template with unclosed if", func(t *testing.T) {
w := createRequest(t, s.CreateModelHandler, api.CreateRequest{
Name: "test",
Modelfile: fmt.Sprintf("FROM %s\nTEMPLATE {{ if .Prompt }}", createBinFile(t, nil, nil)),
Stream: &stream,
})
if w.Code != http.StatusBadRequest {
t.Fatalf("expected status code 400, actual %d", w.Code)
}
})
t.Run("template with undefined function", func(t *testing.T) {
w := createRequest(t, s.CreateModelHandler, api.CreateRequest{
Name: "test",
Modelfile: fmt.Sprintf("FROM %s\nTEMPLATE {{ Prompt }}", createBinFile(t, nil, nil)),
Stream: &stream,
})
if w.Code != http.StatusBadRequest {
t.Fatalf("expected status code 400, actual %d", w.Code)
}
})
}
func TestCreateLicenses(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
envconfig.LoadConfig()
@@ -526,6 +578,8 @@ func TestCreateLicenses(t *testing.T) {
}
func TestCreateDetectTemplate(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
envconfig.LoadConfig()
@@ -545,9 +599,9 @@ func TestCreateDetectTemplate(t *testing.T) {
}
checkFileExists(t, filepath.Join(p, "blobs", "*"), []string{
filepath.Join(p, "blobs", "sha256-2f8e594e6f34b1b4d36a246628eeb3365ce442303d656f1fcc69e821722acea0"),
filepath.Join(p, "blobs", "sha256-542b217f179c7825eeb5bca3c77d2b75ed05bafbd3451d9188891a60a85337c6"),
filepath.Join(p, "blobs", "sha256-553c4a3f747b3d22a4946875f1cc8ed011c2930d83f864a0c7265f9ec0a20413"),
filepath.Join(p, "blobs", "sha256-c608dc615584cd20d9d830363dabf8a4783ae5d34245c3d8c115edb3bc7b28e4"),
filepath.Join(p, "blobs", "sha256-f836ee110db21567f826332e4cedd746c06d10664fd5a9ea3659e3683a944510"),
})
})

View File

@@ -8,12 +8,15 @@ import (
"path/filepath"
"testing"
"github.com/gin-gonic/gin"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/types/model"
)
func TestDelete(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
envconfig.LoadConfig()
@@ -77,6 +80,8 @@ func TestDelete(t *testing.T) {
}
func TestDeleteDuplicateLayers(t *testing.T) {
gin.SetMode(gin.TestMode)
p := t.TempDir()
t.Setenv("OLLAMA_MODELS", p)
var s Server

View File

@@ -0,0 +1,714 @@
package server
import (
"bytes"
"context"
"encoding/json"
"fmt"
"io"
"net/http"
"strings"
"testing"
"time"
"github.com/gin-gonic/gin"
"github.com/google/go-cmp/cmp"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/gpu"
"github.com/ollama/ollama/llm"
)
type mockRunner struct {
llm.LlamaServer
// CompletionRequest is only valid until the next call to Completion
llm.CompletionRequest
llm.CompletionResponse
}
func (m *mockRunner) Completion(_ context.Context, r llm.CompletionRequest, fn func(r llm.CompletionResponse)) error {
m.CompletionRequest = r
fn(m.CompletionResponse)
return nil
}
func (mockRunner) Tokenize(_ context.Context, s string) (tokens []int, err error) {
for range strings.Fields(s) {
tokens = append(tokens, len(tokens))
}
return
}
func newMockServer(mock *mockRunner) func(gpu.GpuInfoList, string, *llm.GGML, []string, []string, api.Options, int) (llm.LlamaServer, error) {
return func(gpus gpu.GpuInfoList, model string, ggml *llm.GGML, projectors, system []string, opts api.Options, numParallel int) (llm.LlamaServer, error) {
return mock, nil
}
}
func TestGenerateChat(t *testing.T) {
gin.SetMode(gin.TestMode)
mock := mockRunner{
CompletionResponse: llm.CompletionResponse{
Done: true,
DoneReason: "stop",
PromptEvalCount: 1,
PromptEvalDuration: 1,
EvalCount: 1,
EvalDuration: 1,
},
}
s := Server{
sched: &Scheduler{
pendingReqCh: make(chan *LlmRequest, 1),
finishedReqCh: make(chan *LlmRequest, 1),
expiredCh: make(chan *runnerRef, 1),
unloadedCh: make(chan any, 1),
loaded: make(map[string]*runnerRef),
newServerFn: newMockServer(&mock),
getGpuFn: gpu.GetGPUInfo,
getCpuFn: gpu.GetCPUInfo,
reschedDelay: 250 * time.Millisecond,
loadFn: func(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList, numParallel int) {
// add small delay to simulate loading
time.Sleep(time.Millisecond)
req.successCh <- &runnerRef{
llama: &mock,
}
},
},
}
go s.sched.Run(context.TODO())
w := createRequest(t, s.CreateModelHandler, api.CreateRequest{
Model: "test",
Modelfile: fmt.Sprintf(`FROM %s
TEMPLATE """
{{- if .System }}System: {{ .System }} {{ end }}
{{- if .Prompt }}User: {{ .Prompt }} {{ end }}
{{- if .Response }}Assistant: {{ .Response }} {{ end }}"""
`, createBinFile(t, llm.KV{
"general.architecture": "llama",
"llama.block_count": uint32(1),
"llama.context_length": uint32(8192),
"llama.embedding_length": uint32(4096),
"llama.attention.head_count": uint32(32),
"llama.attention.head_count_kv": uint32(8),
"tokenizer.ggml.tokens": []string{""},
"tokenizer.ggml.scores": []float32{0},
"tokenizer.ggml.token_type": []int32{0},
}, []llm.Tensor{
{Name: "token_embd.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.attn_norm.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.ffn_down.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.ffn_gate.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.ffn_up.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.ffn_norm.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.attn_k.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.attn_output.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.attn_q.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.attn_v.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "output.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
})),
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
t.Run("missing body", func(t *testing.T) {
w := createRequest(t, s.ChatHandler, nil)
if w.Code != http.StatusBadRequest {
t.Errorf("expected status 400, got %d", w.Code)
}
if diff := cmp.Diff(w.Body.String(), `{"error":"model is required"}`); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
t.Run("missing model", func(t *testing.T) {
w := createRequest(t, s.ChatHandler, api.ChatRequest{})
if w.Code != http.StatusBadRequest {
t.Errorf("expected status 400, got %d", w.Code)
}
if diff := cmp.Diff(w.Body.String(), `{"error":"model is required"}`); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
t.Run("missing capabilities chat", func(t *testing.T) {
w := createRequest(t, s.CreateModelHandler, api.CreateRequest{
Model: "bert",
Modelfile: fmt.Sprintf("FROM %s", createBinFile(t, llm.KV{
"general.architecture": "bert",
"bert.pooling_type": uint32(0),
}, []llm.Tensor{})),
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
w = createRequest(t, s.ChatHandler, api.ChatRequest{
Model: "bert",
})
if w.Code != http.StatusBadRequest {
t.Errorf("expected status 400, got %d", w.Code)
}
if diff := cmp.Diff(w.Body.String(), `{"error":"\"bert\" does not support chat"}`); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
t.Run("load model", func(t *testing.T) {
w := createRequest(t, s.ChatHandler, api.ChatRequest{
Model: "test",
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
var actual api.ChatResponse
if err := json.NewDecoder(w.Body).Decode(&actual); err != nil {
t.Fatal(err)
}
if actual.Model != "test" {
t.Errorf("expected model test, got %s", actual.Model)
}
if !actual.Done {
t.Errorf("expected done true, got false")
}
if actual.DoneReason != "load" {
t.Errorf("expected done reason load, got %s", actual.DoneReason)
}
})
checkChatResponse := func(t *testing.T, body io.Reader, model, content string) {
t.Helper()
var actual api.ChatResponse
if err := json.NewDecoder(body).Decode(&actual); err != nil {
t.Fatal(err)
}
if actual.Model != model {
t.Errorf("expected model test, got %s", actual.Model)
}
if !actual.Done {
t.Errorf("expected done false, got true")
}
if actual.DoneReason != "stop" {
t.Errorf("expected done reason stop, got %s", actual.DoneReason)
}
if diff := cmp.Diff(actual.Message, api.Message{
Role: "assistant",
Content: content,
}); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
if actual.PromptEvalCount == 0 {
t.Errorf("expected prompt eval count > 0, got 0")
}
if actual.PromptEvalDuration == 0 {
t.Errorf("expected prompt eval duration > 0, got 0")
}
if actual.EvalCount == 0 {
t.Errorf("expected eval count > 0, got 0")
}
if actual.EvalDuration == 0 {
t.Errorf("expected eval duration > 0, got 0")
}
if actual.LoadDuration == 0 {
t.Errorf("expected load duration > 0, got 0")
}
if actual.TotalDuration == 0 {
t.Errorf("expected total duration > 0, got 0")
}
}
mock.CompletionResponse.Content = "Hi!"
t.Run("messages", func(t *testing.T) {
w := createRequest(t, s.ChatHandler, api.ChatRequest{
Model: "test",
Messages: []api.Message{
{Role: "user", Content: "Hello!"},
},
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "User: Hello! "); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
checkChatResponse(t, w.Body, "test", "Hi!")
})
w = createRequest(t, s.CreateModelHandler, api.CreateRequest{
Model: "test-system",
Modelfile: "FROM test\nSYSTEM You are a helpful assistant.",
})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
t.Run("messages with model system", func(t *testing.T) {
w := createRequest(t, s.ChatHandler, api.ChatRequest{
Model: "test-system",
Messages: []api.Message{
{Role: "user", Content: "Hello!"},
},
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "System: You are a helpful assistant. User: Hello! "); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
checkChatResponse(t, w.Body, "test-system", "Hi!")
})
mock.CompletionResponse.Content = "Abra kadabra!"
t.Run("messages with system", func(t *testing.T) {
w := createRequest(t, s.ChatHandler, api.ChatRequest{
Model: "test-system",
Messages: []api.Message{
{Role: "system", Content: "You can perform magic tricks."},
{Role: "user", Content: "Hello!"},
},
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "System: You can perform magic tricks. User: Hello! "); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
checkChatResponse(t, w.Body, "test-system", "Abra kadabra!")
})
t.Run("messages with interleaved system", func(t *testing.T) {
w := createRequest(t, s.ChatHandler, api.ChatRequest{
Model: "test-system",
Messages: []api.Message{
{Role: "user", Content: "Hello!"},
{Role: "assistant", Content: "I can help you with that."},
{Role: "system", Content: "You can perform magic tricks."},
{Role: "user", Content: "Help me write tests."},
},
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "System: You are a helpful assistant. User: Hello! Assistant: I can help you with that. System: You can perform magic tricks. User: Help me write tests. "); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
checkChatResponse(t, w.Body, "test-system", "Abra kadabra!")
})
}
func TestGenerate(t *testing.T) {
gin.SetMode(gin.TestMode)
mock := mockRunner{
CompletionResponse: llm.CompletionResponse{
Done: true,
DoneReason: "stop",
PromptEvalCount: 1,
PromptEvalDuration: 1,
EvalCount: 1,
EvalDuration: 1,
},
}
s := Server{
sched: &Scheduler{
pendingReqCh: make(chan *LlmRequest, 1),
finishedReqCh: make(chan *LlmRequest, 1),
expiredCh: make(chan *runnerRef, 1),
unloadedCh: make(chan any, 1),
loaded: make(map[string]*runnerRef),
newServerFn: newMockServer(&mock),
getGpuFn: gpu.GetGPUInfo,
getCpuFn: gpu.GetCPUInfo,
reschedDelay: 250 * time.Millisecond,
loadFn: func(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList, numParallel int) {
// add small delay to simulate loading
time.Sleep(time.Millisecond)
req.successCh <- &runnerRef{
llama: &mock,
}
},
},
}
go s.sched.Run(context.TODO())
w := createRequest(t, s.CreateModelHandler, api.CreateRequest{
Model: "test",
Modelfile: fmt.Sprintf(`FROM %s
TEMPLATE """
{{- if .System }}System: {{ .System }} {{ end }}
{{- if .Prompt }}User: {{ .Prompt }} {{ end }}
{{- if .Response }}Assistant: {{ .Response }} {{ end }}"""
`, createBinFile(t, llm.KV{
"general.architecture": "llama",
"llama.block_count": uint32(1),
"llama.context_length": uint32(8192),
"llama.embedding_length": uint32(4096),
"llama.attention.head_count": uint32(32),
"llama.attention.head_count_kv": uint32(8),
"tokenizer.ggml.tokens": []string{""},
"tokenizer.ggml.scores": []float32{0},
"tokenizer.ggml.token_type": []int32{0},
}, []llm.Tensor{
{Name: "token_embd.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.attn_norm.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.ffn_down.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.ffn_gate.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.ffn_up.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.ffn_norm.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.attn_k.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.attn_output.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.attn_q.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "blk.0.attn_v.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
{Name: "output.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
})),
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
t.Run("missing body", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, nil)
if w.Code != http.StatusBadRequest {
t.Errorf("expected status 400, got %d", w.Code)
}
if diff := cmp.Diff(w.Body.String(), `{"error":"model is required"}`); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
t.Run("missing model", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, api.GenerateRequest{})
if w.Code != http.StatusBadRequest {
t.Errorf("expected status 400, got %d", w.Code)
}
if diff := cmp.Diff(w.Body.String(), `{"error":"model is required"}`); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
t.Run("missing capabilities generate", func(t *testing.T) {
w := createRequest(t, s.CreateModelHandler, api.CreateRequest{
Model: "bert",
Modelfile: fmt.Sprintf("FROM %s", createBinFile(t, llm.KV{
"general.architecture": "bert",
"bert.pooling_type": uint32(0),
}, []llm.Tensor{})),
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
w = createRequest(t, s.GenerateHandler, api.GenerateRequest{
Model: "bert",
})
if w.Code != http.StatusBadRequest {
t.Errorf("expected status 400, got %d", w.Code)
}
if diff := cmp.Diff(w.Body.String(), `{"error":"\"bert\" does not support generate"}`); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
t.Run("missing capabilities suffix", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
Model: "test",
Prompt: "def add(",
Suffix: " return c",
})
if w.Code != http.StatusBadRequest {
t.Errorf("expected status 400, got %d", w.Code)
}
if diff := cmp.Diff(w.Body.String(), `{"error":"test does not support insert"}`); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
t.Run("load model", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
Model: "test",
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
var actual api.GenerateResponse
if err := json.NewDecoder(w.Body).Decode(&actual); err != nil {
t.Fatal(err)
}
if actual.Model != "test" {
t.Errorf("expected model test, got %s", actual.Model)
}
if !actual.Done {
t.Errorf("expected done true, got false")
}
if actual.DoneReason != "load" {
t.Errorf("expected done reason load, got %s", actual.DoneReason)
}
})
checkGenerateResponse := func(t *testing.T, body io.Reader, model, content string) {
t.Helper()
var actual api.GenerateResponse
if err := json.NewDecoder(body).Decode(&actual); err != nil {
t.Fatal(err)
}
if actual.Model != model {
t.Errorf("expected model test, got %s", actual.Model)
}
if !actual.Done {
t.Errorf("expected done false, got true")
}
if actual.DoneReason != "stop" {
t.Errorf("expected done reason stop, got %s", actual.DoneReason)
}
if actual.Response != content {
t.Errorf("expected response %s, got %s", content, actual.Response)
}
if actual.Context == nil {
t.Errorf("expected context not nil")
}
if actual.PromptEvalCount == 0 {
t.Errorf("expected prompt eval count > 0, got 0")
}
if actual.PromptEvalDuration == 0 {
t.Errorf("expected prompt eval duration > 0, got 0")
}
if actual.EvalCount == 0 {
t.Errorf("expected eval count > 0, got 0")
}
if actual.EvalDuration == 0 {
t.Errorf("expected eval duration > 0, got 0")
}
if actual.LoadDuration == 0 {
t.Errorf("expected load duration > 0, got 0")
}
if actual.TotalDuration == 0 {
t.Errorf("expected total duration > 0, got 0")
}
}
mock.CompletionResponse.Content = "Hi!"
t.Run("prompt", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
Model: "test",
Prompt: "Hello!",
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "User: Hello! "); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
checkGenerateResponse(t, w.Body, "test", "Hi!")
})
w = createRequest(t, s.CreateModelHandler, api.CreateRequest{
Model: "test-system",
Modelfile: "FROM test\nSYSTEM You are a helpful assistant.",
})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
t.Run("prompt with model system", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
Model: "test-system",
Prompt: "Hello!",
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "System: You are a helpful assistant. User: Hello! "); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
checkGenerateResponse(t, w.Body, "test-system", "Hi!")
})
mock.CompletionResponse.Content = "Abra kadabra!"
t.Run("prompt with system", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
Model: "test-system",
Prompt: "Hello!",
System: "You can perform magic tricks.",
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "System: You can perform magic tricks. User: Hello! "); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
checkGenerateResponse(t, w.Body, "test-system", "Abra kadabra!")
})
t.Run("prompt with template", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
Model: "test-system",
Prompt: "Help me write tests.",
System: "You can perform magic tricks.",
Template: `{{- if .System }}{{ .System }} {{ end }}
{{- if .Prompt }}### USER {{ .Prompt }} {{ end }}
{{- if .Response }}### ASSISTANT {{ .Response }} {{ end }}`,
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "You can perform magic tricks. ### USER Help me write tests. "); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
checkGenerateResponse(t, w.Body, "test-system", "Abra kadabra!")
})
w = createRequest(t, s.CreateModelHandler, api.CreateRequest{
Model: "test-suffix",
Modelfile: `FROM test
TEMPLATE """{{- if .Suffix }}<PRE> {{ .Prompt }} <SUF>{{ .Suffix }} <MID>
{{- else }}{{ .Prompt }}
{{- end }}"""`,
})
if w.Code != http.StatusOK {
t.Fatalf("expected status 200, got %d", w.Code)
}
t.Run("prompt with suffix", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
Model: "test-suffix",
Prompt: "def add(",
Suffix: " return c",
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "<PRE> def add( <SUF> return c <MID>"); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
t.Run("prompt without suffix", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
Model: "test-suffix",
Prompt: "def add(",
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "def add("); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
t.Run("raw", func(t *testing.T) {
w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
Model: "test-system",
Prompt: "Help me write tests.",
Raw: true,
Stream: &stream,
})
if w.Code != http.StatusOK {
t.Errorf("expected status 200, got %d", w.Code)
}
if diff := cmp.Diff(mock.CompletionRequest.Prompt, "Help me write tests."); diff != "" {
t.Errorf("mismatch (-got +want):\n%s", diff)
}
})
}

View File

@@ -7,11 +7,14 @@ import (
"slices"
"testing"
"github.com/gin-gonic/gin"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/envconfig"
)
func TestList(t *testing.T) {
gin.SetMode(gin.TestMode)
t.Setenv("OLLAMA_MODELS", t.TempDir())
envconfig.LoadConfig()

View File

@@ -7,6 +7,7 @@ import (
"encoding/json"
"fmt"
"io"
"math"
"net/http"
"net/http/httptest"
"os"
@@ -20,6 +21,7 @@ import (
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/envconfig"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/openai"
"github.com/ollama/ollama/parser"
"github.com/ollama/ollama/types/model"
"github.com/ollama/ollama/version"
@@ -105,6 +107,24 @@ func Test_Routes(t *testing.T) {
assert.Empty(t, len(modelList.Models))
},
},
{
Name: "openai empty list",
Method: http.MethodGet,
Path: "/v1/models",
Expected: func(t *testing.T, resp *http.Response) {
contentType := resp.Header.Get("Content-Type")
assert.Equal(t, "application/json", contentType)
body, err := io.ReadAll(resp.Body)
require.NoError(t, err)
var modelList openai.ListCompletion
err = json.Unmarshal(body, &modelList)
require.NoError(t, err)
assert.Equal(t, "list", modelList.Object)
assert.Empty(t, modelList.Data)
},
},
{
Name: "Tags Handler (yes tags)",
Method: http.MethodGet,
@@ -128,6 +148,25 @@ func Test_Routes(t *testing.T) {
assert.Equal(t, "test-model:latest", modelList.Models[0].Name)
},
},
{
Name: "openai list models with tags",
Method: http.MethodGet,
Path: "/v1/models",
Expected: func(t *testing.T, resp *http.Response) {
contentType := resp.Header.Get("Content-Type")
assert.Equal(t, "application/json", contentType)
body, err := io.ReadAll(resp.Body)
require.NoError(t, err)
var modelList openai.ListCompletion
err = json.Unmarshal(body, &modelList)
require.NoError(t, err)
assert.Len(t, modelList.Data, 1)
assert.Equal(t, "test-model:latest", modelList.Data[0].Id)
assert.Equal(t, "library", modelList.Data[0].OwnedBy)
},
},
{
Name: "Create Model Handler",
Method: http.MethodPost,
@@ -216,6 +255,95 @@ func Test_Routes(t *testing.T) {
assert.InDelta(t, 0, showResp.ModelInfo["general.parameter_count"], 1e-9, "Parameter count should be 0")
},
},
{
Name: "openai retrieve model handler",
Method: http.MethodGet,
Path: "/v1/models/show-model",
Expected: func(t *testing.T, resp *http.Response) {
contentType := resp.Header.Get("Content-Type")
assert.Equal(t, "application/json", contentType)
body, err := io.ReadAll(resp.Body)
require.NoError(t, err)
var retrieveResp api.RetrieveModelResponse
err = json.Unmarshal(body, &retrieveResp)
require.NoError(t, err)
assert.Equal(t, "show-model", retrieveResp.Id)
assert.Equal(t, "library", retrieveResp.OwnedBy)
},
},
{
Name: "Embed Handler Empty Input",
Method: http.MethodPost,
Path: "/api/embed",
Setup: func(t *testing.T, req *http.Request) {
embedReq := api.EmbedRequest{
Model: "t-bone",
Input: "",
}
jsonData, err := json.Marshal(embedReq)
require.NoError(t, err)
req.Body = io.NopCloser(bytes.NewReader(jsonData))
},
Expected: func(t *testing.T, resp *http.Response) {
contentType := resp.Header.Get("Content-Type")
if contentType != "application/json; charset=utf-8" {
t.Fatalf("expected content type application/json; charset=utf-8, got %s", contentType)
}
body, err := io.ReadAll(resp.Body)
if err != nil {
t.Fatal(err)
}
var embedResp api.EmbedResponse
err = json.Unmarshal(body, &embedResp)
if err != nil {
t.Fatal(err)
}
if embedResp.Model != "t-bone" {
t.Fatalf("expected model t-bone, got %s", embedResp.Model)
}
if embedResp.Embeddings == nil {
t.Fatalf("expected embeddings to not be nil, got %v", embedResp.Embeddings)
}
if len(embedResp.Embeddings) != 0 {
t.Fatalf("expected embeddings to be empty, got %v", embedResp.Embeddings)
}
},
},
{
Name: "Embed Handler Invalid Input",
Method: http.MethodPost,
Path: "/api/embed",
Setup: func(t *testing.T, req *http.Request) {
embedReq := api.EmbedRequest{
Model: "t-bone",
Input: 2,
}
jsonData, err := json.Marshal(embedReq)
require.NoError(t, err)
req.Body = io.NopCloser(bytes.NewReader(jsonData))
},
Expected: func(t *testing.T, resp *http.Response) {
contentType := resp.Header.Get("Content-Type")
if contentType != "application/json; charset=utf-8" {
t.Fatalf("expected content type application/json; charset=utf-8, got %s", contentType)
}
_, err := io.ReadAll(resp.Body)
if err != nil {
t.Fatal(err)
}
if resp.StatusCode != http.StatusBadRequest {
t.Fatalf("expected status code 400, got %d", resp.StatusCode)
}
},
},
}
t.Setenv("OLLAMA_MODELS", t.TempDir())
@@ -364,3 +492,38 @@ func TestShow(t *testing.T) {
t.Fatal("Expected projector architecture to be 'clip', but got", resp.ProjectorInfo["general.architecture"])
}
}
func TestNormalize(t *testing.T) {
type testCase struct {
input []float32
}
testCases := []testCase{
{input: []float32{1}},
{input: []float32{0, 1, 2, 3}},
{input: []float32{0.1, 0.2, 0.3}},
{input: []float32{-0.1, 0.2, 0.3, -0.4}},
{input: []float32{0, 0, 0}},
}
isNormalized := func(vec []float32) (res bool) {
sum := 0.0
for _, v := range vec {
sum += float64(v * v)
}
if math.Abs(sum-1) > 1e-6 {
return sum == 0
} else {
return true
}
}
for _, tc := range testCases {
t.Run("", func(t *testing.T) {
normalized := normalize(tc.input)
if !isNormalized(normalized) {
t.Errorf("Vector %v is not normalized", tc.input)
}
})
}
}

View File

@@ -23,7 +23,8 @@ type LlmRequest struct {
ctx context.Context //nolint:containedctx
model *Model
opts api.Options
sessionDuration time.Duration
origNumCtx int // Track the initial ctx request
sessionDuration *api.Duration
successCh chan *runnerRef
errCh chan error
schedAttempts uint
@@ -38,13 +39,23 @@ type Scheduler struct {
loaded map[string]*runnerRef
loadedMu sync.Mutex
loadFn func(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList)
newServerFn func(gpus gpu.GpuInfoList, model string, ggml *llm.GGML, adapters []string, projectors []string, opts api.Options) (llm.LlamaServer, error)
loadFn func(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList, numParallel int)
newServerFn func(gpus gpu.GpuInfoList, model string, ggml *llm.GGML, adapters []string, projectors []string, opts api.Options, numParallel int) (llm.LlamaServer, error)
getGpuFn func() gpu.GpuInfoList
getCpuFn func() gpu.GpuInfoList
reschedDelay time.Duration
}
// Default automatic value for number of models we allow per GPU
// Model will still need to fit in VRAM, but loading many small models
// on a large GPU can cause stalling
var defaultModelsPerGPU = 3
// Default automatic value for parallel setting
// Model will still need to fit in VRAM. If this setting wont fit
// we'll back off down to 1 to try to get it to fit
var defaultParallel = 4
var ErrMaxQueue = fmt.Errorf("server busy, please try again. maximum pending requests exceeded")
func InitScheduler(ctx context.Context) *Scheduler {
@@ -64,14 +75,11 @@ func InitScheduler(ctx context.Context) *Scheduler {
}
// context must be canceled to decrement ref count and release the runner
func (s *Scheduler) GetRunner(c context.Context, model *Model, opts api.Options, sessionDuration time.Duration) (chan *runnerRef, chan error) {
// allocate a large enough kv cache for all parallel requests
func (s *Scheduler) GetRunner(c context.Context, model *Model, opts api.Options, sessionDuration *api.Duration) (chan *runnerRef, chan error) {
if opts.NumCtx < 4 {
opts.NumCtx = 4
}
opts.NumCtx *= envconfig.NumParallel
req := &LlmRequest{
ctx: c,
model: model,
@@ -110,11 +118,21 @@ func (s *Scheduler) processPending(ctx context.Context) {
case pending := <-s.pendingReqCh:
// Block other requests until we get this pending request running
pending.schedAttempts++
if pending.origNumCtx == 0 {
pending.origNumCtx = pending.opts.NumCtx
}
if pending.ctx.Err() != nil {
slog.Debug("pending request cancelled or timed out, skipping scheduling")
continue
}
numParallel := envconfig.NumParallel
// TODO (jmorganca): multimodal models don't support parallel yet
// see https://github.com/ollama/ollama/issues/4165
if len(pending.model.ProjectorPaths) > 0 && numParallel != 1 {
numParallel = 1
slog.Warn("multimodal models don't support parallel requests yet")
}
for {
var runnerToExpire *runnerRef
@@ -143,6 +161,26 @@ func (s *Scheduler) processPending(ctx context.Context) {
gpus = s.getGpuFn()
}
if envconfig.MaxRunners <= 0 {
// No user specified MaxRunners, so figure out what automatic setting to use
// If all GPUs have reliable free memory reporting, defaultModelsPerGPU * the number of GPUs
// if any GPU has unreliable free memory reporting, 1x the number of GPUs
allReliable := true
for _, gpu := range gpus {
if gpu.UnreliableFreeMemory {
allReliable = false
break
}
}
if allReliable {
envconfig.MaxRunners = defaultModelsPerGPU * len(gpus)
slog.Debug("updating default concurrency", "OLLAMA_MAX_LOADED_MODELS", envconfig.MaxRunners, "gpu_count", len(gpus))
} else {
slog.Info("one or more GPUs detected that are unable to accurately report free memory - disabling default concurrency")
envconfig.MaxRunners = len(gpus)
}
}
// Load model for fitting
ggml, err := llm.LoadModel(pending.model.ModelPath, 0)
if err != nil {
@@ -152,26 +190,33 @@ func (s *Scheduler) processPending(ctx context.Context) {
// Evaluate if the model will fit in the available system memory, or if we should unload a model first
if len(gpus) == 1 && gpus[0].Library == "cpu" {
// simplifying assumption of defaultParallel when in CPU mode
if numParallel <= 0 {
numParallel = defaultParallel
}
pending.opts.NumCtx = pending.origNumCtx * numParallel
if loadedCount == 0 {
slog.Debug("cpu mode with first model, loading")
s.loadFn(pending, ggml, gpus)
s.loadFn(pending, ggml, gpus, numParallel)
break
}
runnerToExpire = s.maybeFindCPURunnerToUnload(pending, ggml, gpus)
if runnerToExpire == nil {
slog.Debug("cpu mode with available system memory or first model, loading")
s.loadFn(pending, ggml, gpus)
s.loadFn(pending, ggml, gpus, numParallel)
break
}
// else we need to expire a runner
} else if loadedCount == 0 {
// No models loaded. Load the model but prefer the best fit.
slog.Debug("loading first model", "model", pending.model.ModelPath)
g := pickBestFitGPUs(pending, ggml, gpus)
g := pickBestFitGPUs(pending, ggml, gpus, &numParallel)
if g != nil {
gpus = g
}
s.loadFn(pending, ggml, gpus)
s.loadFn(pending, ggml, gpus, numParallel)
break
}
@@ -186,10 +231,10 @@ func (s *Scheduler) processPending(ctx context.Context) {
// Update free memory from currently loaded models
s.updateFreeSpace(availGpus)
fitGpus := pickBestFitGPUs(pending, ggml, availGpus)
fitGpus := pickBestFitGPUs(pending, ggml, availGpus, &numParallel)
if fitGpus != nil {
slog.Debug("new model fits with existing models, loading")
s.loadFn(pending, ggml, fitGpus)
s.loadFn(pending, ggml, fitGpus, numParallel)
break
}
@@ -341,7 +386,9 @@ func (pending *LlmRequest) useLoadedRunner(runner *runnerRef, finished chan *Llm
runner.expireTimer.Stop()
runner.expireTimer = nil
}
runner.sessionDuration = pending.sessionDuration
if pending.sessionDuration != nil {
runner.sessionDuration = pending.sessionDuration.Duration
}
pending.successCh <- runner
go func() {
<-pending.ctx.Done()
@@ -350,8 +397,15 @@ func (pending *LlmRequest) useLoadedRunner(runner *runnerRef, finished chan *Llm
}()
}
func (s *Scheduler) load(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList) {
llama, err := s.newServerFn(gpus, req.model.ModelPath, ggml, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts)
func (s *Scheduler) load(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList, numParallel int) {
if numParallel < 1 {
numParallel = 1
}
sessionDuration := envconfig.KeepAlive
if req.sessionDuration != nil {
sessionDuration = req.sessionDuration.Duration
}
llama, err := s.newServerFn(gpus, req.model.ModelPath, ggml, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts, numParallel)
if err != nil {
// some older models are not compatible with newer versions of llama.cpp
// show a generalized compatibility error until there is a better way to
@@ -368,13 +422,14 @@ func (s *Scheduler) load(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList)
modelPath: req.model.ModelPath,
llama: llama,
Options: &req.opts,
sessionDuration: req.sessionDuration,
sessionDuration: sessionDuration,
gpus: gpus,
estimatedVRAM: llama.EstimatedVRAM(),
estimatedTotal: llama.EstimatedTotal(),
loading: true,
refCount: 1,
}
runner.numParallel = numParallel
runner.refMu.Lock()
s.loadedMu.Lock()
@@ -483,8 +538,9 @@ type runnerRef struct {
expireTimer *time.Timer
expiresAt time.Time
model *Model
modelPath string
model *Model
modelPath string
numParallel int
*api.Options
}
@@ -525,6 +581,9 @@ func (runner *runnerRef) needsReload(ctx context.Context, req *LlmRequest) bool
optsNew.NumGPU = -1
}
// Normalize the NumCtx for parallelism
optsExisting.NumCtx = optsExisting.NumCtx / runner.numParallel
ctx, cancel := context.WithTimeout(ctx, timeout)
defer cancel()
if !reflect.DeepEqual(runner.model.AdapterPaths, req.model.AdapterPaths) || // have the adapters changed?
@@ -611,22 +670,38 @@ func (a ByDuration) Less(i, j int) bool {
// pickBestFitGPUs will try to find the optimal placement of the model in the available GPUs where the model fully fits
// If the model can not be fit fully within the available GPU(s) nil is returned
func pickBestFitGPUs(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList) gpu.GpuInfoList {
// If numParallel is <= 0, this will attempt try to optimize parallism based on available VRAM, and adjust
// opts.NumCtx accordingly
func pickBestFitGPUs(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList, numParallel *int) gpu.GpuInfoList {
var estimatedVRAM uint64
var numParallelToTry []int
if *numParallel <= 0 {
// If no specific parallel setting was provided, try larger then smaller, always end with 1
numParallelToTry = append(numParallelToTry, defaultParallel, 1)
} else {
numParallelToTry = []int{*numParallel}
}
for _, gl := range gpus.ByLibrary() {
var ok bool
sgl := append(make(gpu.GpuInfoList, 0, len(gl)), gl...)
// TODO - potentially sort by performance capability, existing models loaded, etc.
// TODO - Eliminate any GPUs that already have envconfig.MaxRunners loaded on them
// Note: at present, this will favor more VRAM over faster GPU speed in mixed setups
sort.Sort(sort.Reverse(gpu.ByFreeMemory(sgl)))
// First attempt to fit the model into a single GPU
if !envconfig.SchedSpread {
for _, g := range sgl {
if ok, estimatedVRAM = llm.PredictServerFit([]gpu.GpuInfo{g}, ggml, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts); ok {
slog.Debug("new model will fit in available VRAM in single GPU, loading", "model", req.model.ModelPath, "gpu", g.ID, "available", g.FreeMemory, "required", format.HumanBytes2(estimatedVRAM))
return []gpu.GpuInfo{g}
for _, p := range numParallelToTry {
req.opts.NumCtx = req.origNumCtx * p
if !envconfig.SchedSpread {
for _, g := range sgl {
if ok, estimatedVRAM = llm.PredictServerFit([]gpu.GpuInfo{g}, ggml, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts); ok {
slog.Info("new model will fit in available VRAM in single GPU, loading", "model", req.model.ModelPath, "gpu", g.ID, "parallel", p, "available", g.FreeMemory, "required", format.HumanBytes2(estimatedVRAM))
*numParallel = p
return []gpu.GpuInfo{g}
}
}
}
}
@@ -636,9 +711,13 @@ func pickBestFitGPUs(req *LlmRequest, ggml *llm.GGML, gpus gpu.GpuInfoList) gpu.
// - try subsets of GPUs instead of just falling back to 1 or all in a family
// Now try all the GPUs
if ok, estimatedVRAM = llm.PredictServerFit(sgl, ggml, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts); ok {
slog.Debug("new model will fit in available VRAM, loading", "model", req.model.ModelPath, "library", sgl[0].Library, "required", format.HumanBytes2(estimatedVRAM))
return sgl
for _, p := range numParallelToTry {
req.opts.NumCtx = req.origNumCtx * p
if ok, estimatedVRAM = llm.PredictServerFit(sgl, ggml, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts); ok {
slog.Info("new model will fit in available VRAM, loading", "model", req.model.ModelPath, "library", sgl[0].Library, "parallel", p, "required", format.HumanBytes2(estimatedVRAM))
*numParallel = p
return sgl
}
}
}
return nil

View File

@@ -7,6 +7,7 @@ import (
"fmt"
"log/slog"
"os"
"runtime"
"testing"
"time"
@@ -44,14 +45,14 @@ func TestLoad(t *testing.T) {
opts: api.DefaultOptions(),
successCh: make(chan *runnerRef, 1),
errCh: make(chan error, 1),
sessionDuration: 2,
sessionDuration: &api.Duration{Duration: 2 * time.Second},
}
// Fail to load model first
s.newServerFn = func(gpus gpu.GpuInfoList, model string, ggml *llm.GGML, adapters []string, projectors []string, opts api.Options) (llm.LlamaServer, error) {
s.newServerFn = func(gpus gpu.GpuInfoList, model string, ggml *llm.GGML, adapters []string, projectors []string, opts api.Options, numParallel int) (llm.LlamaServer, error) {
return nil, fmt.Errorf("something failed to load model blah")
}
gpus := gpu.GpuInfoList{}
s.load(req, ggml, gpus)
s.load(req, ggml, gpus, 0)
require.Empty(t, req.successCh)
require.Len(t, req.errCh, 1)
s.loadedMu.Lock()
@@ -61,10 +62,10 @@ func TestLoad(t *testing.T) {
require.Contains(t, err.Error(), "this model may be incompatible")
server := &mockLlm{estimatedVRAM: 10, estimatedVRAMByGPU: map[string]uint64{}}
s.newServerFn = func(gpus gpu.GpuInfoList, model string, ggml *llm.GGML, adapters []string, projectors []string, opts api.Options) (llm.LlamaServer, error) {
s.newServerFn = func(gpus gpu.GpuInfoList, model string, ggml *llm.GGML, adapters []string, projectors []string, opts api.Options, numParallel int) (llm.LlamaServer, error) {
return server, nil
}
s.load(req, ggml, gpus)
s.load(req, ggml, gpus, 0)
select {
case err := <-req.errCh:
require.NoError(t, err)
@@ -78,12 +79,12 @@ func TestLoad(t *testing.T) {
req.model.ModelPath = "dummy_model_path"
server.waitResp = fmt.Errorf("wait failure")
s.load(req, ggml, gpus)
s.load(req, ggml, gpus, 0)
select {
case err := <-req.errCh:
require.Contains(t, err.Error(), "wait failure")
case resp := <-req.successCh:
t.Errorf("unexpected success %v", resp)
t.Fatalf("unexpected success %v", resp)
}
s.loadedMu.Lock()
runner := s.loaded["dummy_model_path"]
@@ -94,7 +95,7 @@ func TestLoad(t *testing.T) {
require.Len(t, s.expiredCh, 1)
}
type bundle struct {
type reqBundle struct {
ctx context.Context //nolint:containedctx
ctxDone func()
srv *mockLlm
@@ -102,13 +103,13 @@ type bundle struct {
ggml *llm.GGML
}
func (scenario *bundle) newServer(gpus gpu.GpuInfoList, model string, ggml *llm.GGML, adapters []string, projectors []string, opts api.Options) (llm.LlamaServer, error) {
func (scenario *reqBundle) newServer(gpus gpu.GpuInfoList, model string, ggml *llm.GGML, adapters []string, projectors []string, opts api.Options, numParallel int) (llm.LlamaServer, error) {
return scenario.srv, nil
}
func newScenario(t *testing.T, ctx context.Context, modelName string, estimatedVRAM uint64) *bundle {
scenario := &bundle{}
scenario.ctx, scenario.ctxDone = context.WithCancel(ctx)
func newScenarioRequest(t *testing.T, ctx context.Context, modelName string, estimatedVRAM uint64, duration *api.Duration) *reqBundle {
b := &reqBundle{}
b.ctx, b.ctxDone = context.WithCancel(ctx)
t.Helper()
f, err := os.CreateTemp(t.TempDir(), modelName)
@@ -135,208 +136,279 @@ func newScenario(t *testing.T, ctx context.Context, modelName string, estimatedV
fname := f.Name()
model := &Model{Name: modelName, ModelPath: fname}
scenario.ggml, err = llm.LoadModel(model.ModelPath, 0)
b.ggml, err = llm.LoadModel(model.ModelPath, 0)
require.NoError(t, err)
scenario.req = &LlmRequest{
ctx: scenario.ctx,
if duration == nil {
duration = &api.Duration{Duration: 5 * time.Millisecond}
}
b.req = &LlmRequest{
ctx: b.ctx,
model: model,
opts: api.DefaultOptions(),
sessionDuration: 5 * time.Millisecond,
sessionDuration: duration,
successCh: make(chan *runnerRef, 1),
errCh: make(chan error, 1),
}
scenario.srv = &mockLlm{estimatedVRAM: estimatedVRAM, estimatedVRAMByGPU: map[string]uint64{"": estimatedVRAM}}
return scenario
b.srv = &mockLlm{estimatedVRAM: estimatedVRAM, estimatedVRAMByGPU: map[string]uint64{"": estimatedVRAM}}
return b
}
func TestRequests(t *testing.T) {
ctx, done := context.WithTimeout(context.Background(), 10*time.Second)
func getGpuFn() gpu.GpuInfoList {
g := gpu.GpuInfo{Library: "metal"}
g.TotalMemory = 24 * format.GigaByte
g.FreeMemory = 12 * format.GigaByte
return []gpu.GpuInfo{g}
}
func getCpuFn() gpu.GpuInfoList {
g := gpu.GpuInfo{Library: "cpu"}
g.TotalMemory = 32 * format.GigaByte
g.FreeMemory = 26 * format.GigaByte
return []gpu.GpuInfo{g}
}
func TestRequestsSameModelSameRequest(t *testing.T) {
ctx, done := context.WithTimeout(context.Background(), 500*time.Millisecond)
defer done()
// Same model, same request
scenario1a := newScenario(t, ctx, "ollama-model-1", 10)
scenario1a.req.sessionDuration = 5 * time.Millisecond
scenario1b := newScenario(t, ctx, "ollama-model-1", 11)
scenario1b.req.model = scenario1a.req.model
scenario1b.ggml = scenario1a.ggml
scenario1b.req.sessionDuration = 0
// simple reload of same model
scenario2a := newScenario(t, ctx, "ollama-model-1", 20)
tmpModel := *scenario1a.req.model
scenario2a.req.model = &tmpModel
scenario2a.ggml = scenario1a.ggml
scenario2a.req.sessionDuration = 5 * time.Millisecond
// Multiple loaded models
scenario3a := newScenario(t, ctx, "ollama-model-3a", 1*format.GigaByte)
scenario3b := newScenario(t, ctx, "ollama-model-3b", 24*format.GigaByte)
scenario3c := newScenario(t, ctx, "ollama-model-4a", 30)
scenario3c.req.opts.NumGPU = 0 // CPU load, will be allowed
scenario3d := newScenario(t, ctx, "ollama-model-3c", 30) // Needs prior unloaded
s := InitScheduler(ctx)
s.getGpuFn = func() gpu.GpuInfoList {
g := gpu.GpuInfo{Library: "metal"}
g.TotalMemory = 24 * format.GigaByte
g.FreeMemory = 12 * format.GigaByte
return []gpu.GpuInfo{g}
}
s.getCpuFn = func() gpu.GpuInfoList {
g := gpu.GpuInfo{Library: "cpu"}
g.TotalMemory = 32 * format.GigaByte
g.FreeMemory = 26 * format.GigaByte
return []gpu.GpuInfo{g}
}
s.newServerFn = scenario1a.newServer
slog.Info("scenario1a")
s.pendingReqCh <- scenario1a.req
s.getGpuFn = getGpuFn
s.getCpuFn = getCpuFn
a := newScenarioRequest(t, ctx, "ollama-model-1", 10, &api.Duration{Duration: 5 * time.Millisecond})
b := newScenarioRequest(t, ctx, "ollama-model-1", 11, &api.Duration{Duration: 0})
b.req.model = a.req.model
b.ggml = a.ggml
s.newServerFn = a.newServer
slog.Info("a")
s.pendingReqCh <- a.req
require.Len(t, s.pendingReqCh, 1)
s.Run(ctx)
select {
case resp := <-scenario1a.req.successCh:
require.Equal(t, resp.llama, scenario1a.srv)
case resp := <-a.req.successCh:
require.Equal(t, resp.llama, a.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, scenario1a.req.errCh)
require.Empty(t, a.req.errCh)
case err := <-a.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Errorf("timeout")
t.Fatal("timeout")
}
// Same runner as first request due to not needing a reload
s.newServerFn = scenario1b.newServer
slog.Info("scenario1b")
s.pendingReqCh <- scenario1b.req
s.newServerFn = b.newServer
slog.Info("b")
s.pendingReqCh <- b.req
select {
case resp := <-scenario1b.req.successCh:
require.Equal(t, resp.llama, scenario1a.srv)
case resp := <-b.req.successCh:
require.Equal(t, resp.llama, a.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, scenario1b.req.errCh)
require.Empty(t, b.req.errCh)
case err := <-b.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Errorf("timeout")
t.Fatal("timeout")
}
}
func TestRequestsSimpleReloadSameModel(t *testing.T) {
ctx, done := context.WithTimeout(context.Background(), 500*time.Millisecond)
defer done()
s := InitScheduler(ctx)
s.getGpuFn = getGpuFn
s.getCpuFn = getCpuFn
a := newScenarioRequest(t, ctx, "ollama-model-1", 10, &api.Duration{Duration: 5 * time.Millisecond})
b := newScenarioRequest(t, ctx, "ollama-model-1", 20, &api.Duration{Duration: 5 * time.Millisecond})
tmpModel := *a.req.model
b.req.model = &tmpModel
b.ggml = a.ggml
s.newServerFn = a.newServer
slog.Info("a")
s.pendingReqCh <- a.req
require.Len(t, s.pendingReqCh, 1)
s.Run(ctx)
select {
case resp := <-a.req.successCh:
require.Equal(t, resp.llama, a.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, a.req.errCh)
case err := <-a.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Fatal("timeout")
}
// Trigger a reload
s.newServerFn = scenario2a.newServer
scenario2a.req.model.AdapterPaths = []string{"new"}
slog.Info("scenario2a")
s.pendingReqCh <- scenario2a.req
s.newServerFn = b.newServer
b.req.model.AdapterPaths = []string{"new"}
slog.Info("b")
s.pendingReqCh <- b.req
// finish first two requests, so model can reload
time.Sleep(1 * time.Millisecond)
scenario1a.ctxDone()
scenario1b.ctxDone()
a.ctxDone()
select {
case resp := <-scenario2a.req.successCh:
require.Equal(t, resp.llama, scenario2a.srv)
case resp := <-b.req.successCh:
require.Equal(t, resp.llama, b.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, scenario2a.req.errCh)
require.Empty(t, b.req.errCh)
case err := <-b.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Errorf("timeout")
t.Fatal("timeout")
}
}
func TestRequestsMultipleLoadedModels(t *testing.T) {
ctx, done := context.WithTimeout(context.Background(), 500*time.Millisecond)
defer done()
s := InitScheduler(ctx)
s.getGpuFn = getGpuFn
s.getCpuFn = getCpuFn
// Multiple loaded models
a := newScenarioRequest(t, ctx, "ollama-model-3a", 1*format.GigaByte, nil)
b := newScenarioRequest(t, ctx, "ollama-model-3b", 24*format.GigaByte, nil)
c := newScenarioRequest(t, ctx, "ollama-model-4a", 30, nil)
c.req.opts.NumGPU = 0 // CPU load, will be allowed
d := newScenarioRequest(t, ctx, "ollama-model-3c", 30, nil) // Needs prior unloaded
envconfig.MaxRunners = 1
s.newServerFn = scenario3a.newServer
slog.Info("scenario3a")
s.pendingReqCh <- scenario3a.req
// finish prior request, so new model can load
time.Sleep(1 * time.Millisecond)
scenario2a.ctxDone()
s.newServerFn = a.newServer
slog.Info("a")
s.pendingReqCh <- a.req
s.Run(ctx)
select {
case resp := <-scenario3a.req.successCh:
require.Equal(t, resp.llama, scenario3a.srv)
case resp := <-a.req.successCh:
require.Equal(t, resp.llama, a.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, scenario3a.req.errCh)
require.Empty(t, a.req.errCh)
case err := <-a.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Errorf("timeout")
t.Fatal("timeout")
}
s.loadedMu.Lock()
require.Len(t, s.loaded, 1)
s.loadedMu.Unlock()
envconfig.MaxRunners = 0
s.newServerFn = scenario3b.newServer
slog.Info("scenario3b")
s.pendingReqCh <- scenario3b.req
s.newServerFn = b.newServer
slog.Info("b")
s.pendingReqCh <- b.req
select {
case resp := <-scenario3b.req.successCh:
require.Equal(t, resp.llama, scenario3b.srv)
case resp := <-b.req.successCh:
require.Equal(t, resp.llama, b.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, scenario3b.req.errCh)
require.Empty(t, b.req.errCh)
case err := <-b.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Errorf("timeout")
t.Fatal("timeout")
}
s.loadedMu.Lock()
require.Len(t, s.loaded, 2)
s.loadedMu.Unlock()
// This is a CPU load with NumGPU = 0 so it should load
s.newServerFn = scenario3c.newServer
slog.Info("scenario3c")
s.pendingReqCh <- scenario3c.req
s.newServerFn = c.newServer
slog.Info("c")
s.pendingReqCh <- c.req
select {
case resp := <-scenario3c.req.successCh:
require.Equal(t, resp.llama, scenario3c.srv)
case resp := <-c.req.successCh:
require.Equal(t, resp.llama, c.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, scenario3c.req.errCh)
require.Empty(t, c.req.errCh)
case err := <-c.req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Errorf("timeout")
t.Fatal("timeout")
}
s.loadedMu.Lock()
require.Len(t, s.loaded, 3)
s.loadedMu.Unlock()
// Try to load a model that wont fit
s.newServerFn = scenario3d.newServer
slog.Info("scenario3d")
s.newServerFn = d.newServer
slog.Info("d")
s.loadedMu.Lock()
require.Len(t, s.loaded, 3)
s.loadedMu.Unlock()
scenario3a.ctxDone() // Won't help since this one isn't big enough to make room
a.ctxDone() // Won't help since this one isn't big enough to make room
time.Sleep(2 * time.Millisecond)
s.pendingReqCh <- scenario3d.req
s.pendingReqCh <- d.req
// finish prior request, so new model can load
time.Sleep(6 * time.Millisecond)
s.loadedMu.Lock()
require.Len(t, s.loaded, 2)
s.loadedMu.Unlock()
scenario3b.ctxDone()
b.ctxDone()
select {
case resp := <-scenario3d.req.successCh:
require.Equal(t, resp.llama, scenario3d.srv)
case resp := <-d.req.successCh:
require.Equal(t, resp.llama, d.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, scenario3d.req.errCh)
require.Empty(t, d.req.errCh)
case <-ctx.Done():
t.Errorf("timeout")
t.Fatal("timeout")
}
s.loadedMu.Lock()
require.Len(t, s.loaded, 2)
s.loadedMu.Unlock()
}
func TestRequestsModelTooBigForSystem(t *testing.T) {
ctx, done := context.WithTimeout(context.Background(), 500*time.Millisecond)
defer done()
s := InitScheduler(ctx)
s.getGpuFn = func() gpu.GpuInfoList {
g := gpu.GpuInfo{Library: "metal"}
g.TotalMemory = 4 * format.MebiByte
g.FreeMemory = 3 * format.MebiByte
return []gpu.GpuInfo{g}
}
s.getCpuFn = func() gpu.GpuInfoList {
g := gpu.GpuInfo{Library: "cpu"}
g.TotalMemory = 4 * format.MebiByte
g.FreeMemory = 2 * format.MebiByte
return []gpu.GpuInfo{g}
}
a := newScenarioRequest(t, ctx, "ollama-model-1", 10, &api.Duration{Duration: 5 * time.Millisecond})
s.newServerFn = a.newServer
slog.Info("a")
s.pendingReqCh <- a.req
require.Len(t, s.pendingReqCh, 1)
s.Run(ctx)
select {
case <-a.req.successCh:
if runtime.GOOS == "linux" {
t.Fatal("request should have been rejected with out of space")
}
// else - Darwin and Windows don't reject right now
case err := <-a.req.errCh:
require.Contains(t, err.Error(), "too large")
case <-ctx.Done():
t.Fatal("timeout")
}
}
func TestGetRunner(t *testing.T) {
ctx, done := context.WithTimeout(context.Background(), 100*time.Millisecond)
defer done()
scenario1a := newScenario(t, ctx, "ollama-model-1a", 10)
scenario1a.req.sessionDuration = 0
scenario1b := newScenario(t, ctx, "ollama-model-1b", 10)
scenario1b.req.sessionDuration = 0
scenario1c := newScenario(t, ctx, "ollama-model-1c", 10)
scenario1c.req.sessionDuration = 0
a := newScenarioRequest(t, ctx, "ollama-model-1a", 10, &api.Duration{Duration: 2 * time.Millisecond})
b := newScenarioRequest(t, ctx, "ollama-model-1b", 10, &api.Duration{Duration: 2 * time.Millisecond})
c := newScenarioRequest(t, ctx, "ollama-model-1c", 10, &api.Duration{Duration: 2 * time.Millisecond})
envconfig.MaxQueuedRequests = 1
s := InitScheduler(ctx)
s.getGpuFn = func() gpu.GpuInfoList {
g := gpu.GpuInfo{Library: "metal"}
g.TotalMemory = 24 * format.GigaByte
g.FreeMemory = 12 * format.GigaByte
return []gpu.GpuInfo{g}
}
s.newServerFn = scenario1a.newServer
slog.Info("scenario1a")
successCh1a, errCh1a := s.GetRunner(scenario1a.ctx, scenario1a.req.model, scenario1a.req.opts, scenario1a.req.sessionDuration)
s.getGpuFn = getGpuFn
s.getCpuFn = getCpuFn
s.newServerFn = a.newServer
slog.Info("a")
successCh1a, errCh1a := s.GetRunner(a.ctx, a.req.model, a.req.opts, a.req.sessionDuration)
require.Len(t, s.pendingReqCh, 1)
slog.Info("scenario1b")
successCh1b, errCh1b := s.GetRunner(scenario1b.ctx, scenario1b.req.model, scenario1b.req.opts, scenario1b.req.sessionDuration)
slog.Info("b")
successCh1b, errCh1b := s.GetRunner(b.ctx, b.req.model, b.req.opts, b.req.sessionDuration)
require.Len(t, s.pendingReqCh, 1)
require.Empty(t, successCh1b)
require.Len(t, errCh1b, 1)
@@ -345,22 +417,24 @@ func TestGetRunner(t *testing.T) {
s.Run(ctx)
select {
case resp := <-successCh1a:
require.Equal(t, resp.llama, scenario1a.srv)
require.Equal(t, resp.llama, a.srv)
require.Empty(t, s.pendingReqCh)
require.Empty(t, errCh1a)
case err := <-errCh1a:
t.Fatal(err.Error())
case <-ctx.Done():
t.Errorf("timeout")
t.Fatal("timeout")
}
scenario1a.ctxDone()
a.ctxDone() // Set "a" model to idle so it can unload
s.loadedMu.Lock()
require.Len(t, s.loaded, 1)
s.loadedMu.Unlock()
scenario1c.req.model.ModelPath = "bad path"
slog.Info("scenario1c")
successCh1c, errCh1c := s.GetRunner(scenario1c.ctx, scenario1c.req.model, scenario1c.req.opts, scenario1c.req.sessionDuration)
c.req.model.ModelPath = "bad path"
slog.Info("c")
successCh1c, errCh1c := s.GetRunner(c.ctx, c.req.model, c.req.opts, c.req.sessionDuration)
// Starts in pending channel, then should be quickly processsed to return an error
time.Sleep(5 * time.Millisecond)
time.Sleep(20 * time.Millisecond) // Long enough for the "a" model to expire and unload
require.Empty(t, successCh1c)
s.loadedMu.Lock()
require.Empty(t, s.loaded)
@@ -368,7 +442,7 @@ func TestGetRunner(t *testing.T) {
require.Len(t, errCh1c, 1)
err = <-errCh1c
require.Contains(t, err.Error(), "bad path")
scenario1b.ctxDone()
b.ctxDone()
}
// TODO - add one scenario that triggers the bogus finished event with positive ref count
@@ -377,7 +451,7 @@ func TestPrematureExpired(t *testing.T) {
defer done()
// Same model, same request
scenario1a := newScenario(t, ctx, "ollama-model-1a", 10)
scenario1a := newScenarioRequest(t, ctx, "ollama-model-1a", 10, nil)
s := InitScheduler(ctx)
s.getGpuFn = func() gpu.GpuInfoList {
g := gpu.GpuInfo{Library: "metal"}
@@ -399,10 +473,12 @@ func TestPrematureExpired(t *testing.T) {
s.loadedMu.Unlock()
slog.Info("sending premature expired event now")
s.expiredCh <- resp // Shouldn't happen in real life, but make sure its safe
case err := <-errCh1a:
t.Fatal(err.Error())
case <-ctx.Done():
t.Errorf("timeout")
t.Fatal("timeout")
}
time.Sleep(scenario1a.req.sessionDuration)
time.Sleep(scenario1a.req.sessionDuration.Duration)
scenario1a.ctxDone()
time.Sleep(20 * time.Millisecond)
require.LessOrEqual(t, len(s.finishedReqCh), 1)
@@ -423,19 +499,21 @@ func TestUseLoadedRunner(t *testing.T) {
ctx: ctx,
opts: api.DefaultOptions(),
successCh: make(chan *runnerRef, 1),
sessionDuration: 2,
sessionDuration: &api.Duration{Duration: 2},
}
finished := make(chan *LlmRequest)
llm1 := &mockLlm{estimatedVRAMByGPU: map[string]uint64{}}
r1 := &runnerRef{llama: llm1, sessionDuration: 1}
r1 := &runnerRef{llama: llm1, sessionDuration: 1, numParallel: 1}
req.useLoadedRunner(r1, finished)
require.Equal(t, uint(1), r1.refCount)
require.Equal(t, time.Duration(2), r1.sessionDuration)
select {
case success := <-req.successCh:
require.Equal(t, r1, success)
case err := <-req.errCh:
t.Fatal(err.Error())
case <-ctx.Done():
t.Errorf("timeout")
t.Fatal("timeout")
}
done()
fin := <-finished
@@ -461,8 +539,8 @@ func TestUpdateFreeSpace(t *testing.T) {
gpus[1].FreeMemory = 1900
llm1 := &mockLlm{estimatedVRAMByGPU: map[string]uint64{"1": 50, "2": 50}}
llm2 := &mockLlm{estimatedVRAMByGPU: map[string]uint64{"1": 125, "2": 75}}
r1 := &runnerRef{llama: llm1, gpus: gpus}
r2 := &runnerRef{llama: llm2, gpus: gpus}
r1 := &runnerRef{llama: llm1, gpus: gpus, numParallel: 1}
r2 := &runnerRef{llama: llm2, gpus: gpus, numParallel: 1}
s := InitScheduler(ctx)
s.loadedMu.Lock()
@@ -513,8 +591,8 @@ func TestFindRunnerToUnload(t *testing.T) {
ctx, done := context.WithTimeout(context.Background(), 100*time.Millisecond)
defer done()
r1 := &runnerRef{refCount: 1, sessionDuration: 1}
r2 := &runnerRef{sessionDuration: 2}
r1 := &runnerRef{refCount: 1, sessionDuration: 1, numParallel: 1}
r2 := &runnerRef{sessionDuration: 2, numParallel: 1}
s := InitScheduler(ctx)
s.loadedMu.Lock()
@@ -536,9 +614,13 @@ func TestNeedsReload(t *testing.T) {
llm := &mockLlm{estimatedVRAMByGPU: map[string]uint64{}}
do := api.DefaultOptions()
runner := &runnerRef{
model: &Model{AdapterPaths: []string{"adapter1"}, ProjectorPaths: []string{"projector1"}},
Options: &do,
llama: llm,
model: &Model{
AdapterPaths: []string{"adapter1"},
ProjectorPaths: []string{"projector1"},
},
Options: &do,
llama: llm,
numParallel: 1,
}
req := &LlmRequest{
model: &Model{
@@ -581,8 +663,8 @@ func TestUnloadAllRunners(t *testing.T) {
s := InitScheduler(ctx)
s.unloadAllRunners()
r1 := &runnerRef{llama: llm1}
r2 := &runnerRef{llama: llm2}
r1 := &runnerRef{llama: llm1, numParallel: 1}
r2 := &runnerRef{llama: llm2, numParallel: 1}
s.loadedMu.Lock()
s.loaded["a"] = r1
@@ -596,20 +678,37 @@ func TestUnloadAllRunners(t *testing.T) {
func TestUnload(t *testing.T) {
llm1 := &mockLlm{estimatedVRAMByGPU: map[string]uint64{}}
r1 := &runnerRef{llama: llm1}
r2 := &runnerRef{model: &Model{AdapterPaths: []string{"A"}}}
r1 := &runnerRef{llama: llm1, numParallel: 1}
r2 := &runnerRef{model: &Model{AdapterPaths: []string{"A"}}, numParallel: 1}
r1.unload()
require.True(t, llm1.closeCalled)
r2.unload()
require.Nil(t, r2.model)
}
func TestAlreadyCanceled(t *testing.T) {
ctx, done := context.WithTimeout(context.Background(), 500*time.Millisecond)
defer done()
dctx, done2 := context.WithCancel(ctx)
done2()
scenario1a := newScenarioRequest(t, dctx, "ollama-model-1", 10, &api.Duration{Duration: 0})
s := InitScheduler(ctx)
slog.Info("scenario1a")
s.pendingReqCh <- scenario1a.req
require.Len(t, s.pendingReqCh, 1)
s.Run(ctx)
time.Sleep(5 * time.Millisecond)
require.Empty(t, s.pendingReqCh)
require.Empty(t, scenario1a.req.errCh)
require.Empty(t, scenario1a.req.successCh)
}
type mockLlm struct {
pingResp error
waitResp error
completionResp error
embeddingResp []float64
embeddingRespErr error
embedResp [][]float32
embedRespErr error
tokenizeResp []int
tokenizeRespErr error
detokenizeResp string
@@ -626,8 +725,8 @@ func (s *mockLlm) WaitUntilRunning(ctx context.Context) error { return s.waitRes
func (s *mockLlm) Completion(ctx context.Context, req llm.CompletionRequest, fn func(llm.CompletionResponse)) error {
return s.completionResp
}
func (s *mockLlm) Embedding(ctx context.Context, prompt string) ([]float64, error) {
return s.embeddingResp, s.embeddingRespErr
func (s *mockLlm) Embed(ctx context.Context, input []string) ([][]float32, error) {
return s.embedResp, s.embedRespErr
}
func (s *mockLlm) Tokenize(ctx context.Context, content string) ([]int, error) {
return s.tokenizeResp, s.tokenizeRespErr

View File

@@ -0,0 +1,67 @@
{{- if or .Tools .System }}<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>
{{- if .Tools }}# Safety Preamble
The instructions in this section override those in the task description and style guide sections. Don't answer questions that are harmful or immoral.
# System Preamble
## Basic Rules
You are a powerful conversational AI trained by Cohere to help people. You are augmented by a number of tools, and your job is to use and consume the output of these tools to best help the user. You will see a conversation history between yourself and a user, ending with an utterance from the user. You will then see a specific instruction instructing you what kind of response to generate. When you answer the user's requests, you cite your sources in your answers, according to those instructions.
{{ if .System }}# User Preamble
{{ .System }}
{{- end }}
## Available Tools
Here is a list of tools that you have available to you:
{{- range .Tools }}
```python
def {{ .Function.Name }}(
{{- range $name, $property := .Function.Parameters.Properties }}{{ $name }}: {{ $property.Type }}, {{ end }}) -> List[Dict]:
"""{{ .Function.Description }}
{{- if .Function.Parameters.Properties }}
Args:
{{- range $name, $property := .Function.Parameters.Properties }}
{{ $name }} ({{ $property.Type }}): {{ $property.Description }}
{{- end }}
{{- end }}
"""
pass
```
{{- end }}
{{- else if .System }}{{ .System }}
{{- end }}<|END_OF_TURN_TOKEN|>
{{- end }}
{{- range .Messages }}
{{- if eq .Role "system" }}
{{- continue }}
{{- end }}<|START_OF_TURN_TOKEN|>
{{- if eq .Role "user" }}<|USER_TOKEN|>{{ .Content }}
{{- else if eq .Role "assistant" }}<|CHATBOT_TOKEN|>
{{- if .Content }}{{ .Content }}
{{- else if .ToolCalls }}
Action: ```json
[
{{- range .ToolCalls }}
{
"tool_name": "{{ .Function.Name }}",
"parameters": {{ .Function.Arguments }}
}
{{- end }}
]```
{{ continue }}
{{ end }}
{{- else if eq .Role "tool" }}<|SYSTEM_TOKEN|><results>
{{ .Content }}</results>
{{- end }}<|END_OF_TURN_TOKEN|>
{{- end }}
{{- if .Tools }}<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>Write 'Action:' followed by a json-formatted list of actions that you want to perform in order to produce a good response to the user's last input. You can use any of the supplied tools any number of times, but you should aim to execute the minimum number of necessary actions for the input. You should use the `directly-answer` tool if calling the other tools is unnecessary. The list of actions you want to call should be formatted as a list of json objects, for example:
```json
[
{
"tool_name": title of the tool in the specification,
"parameters": a dict of parameters to input into the tool as they are defined in the specs, or {} if it takes no parameters
}
]```
{{- end }}<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>

View File

@@ -0,0 +1,39 @@
<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|># Safety Preamble
The instructions in this section override those in the task description and style guide sections. Don't answer questions that are harmful or immoral.
# System Preamble
## Basic Rules
You are a powerful conversational AI trained by Cohere to help people. You are augmented by a number of tools, and your job is to use and consume the output of these tools to best help the user. You will see a conversation history between yourself and a user, ending with an utterance from the user. You will then see a specific instruction instructing you what kind of response to generate. When you answer the user's requests, you cite your sources in your answers, according to those instructions.
# User Preamble
You are a knowledgable assistant. You can answer questions and perform tasks.
## Available Tools
Here is a list of tools that you have available to you:
```python
def get_current_weather(format: string, location: string, ) -> List[Dict]:
"""Get the current weather
Args:
format (string): The temperature unit to use. Infer this from the users location.
location (string): The city and state, e.g. San Francisco, CA
"""
pass
```<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|USER_TOKEN|>What's the weather like today in Paris?<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>
Action: ```json
[
{
"tool_name": "get_current_weather",
"parameters": {"format":"celsius","location":"Paris, France"}
}
]```
<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|><results>
22</results><|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>The current temperature in Paris, France is 22 degrees Celsius.<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|USER_TOKEN|>What's the weather like today in San Francisco and Toronto?<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>Write 'Action:' followed by a json-formatted list of actions that you want to perform in order to produce a good response to the user's last input. You can use any of the supplied tools any number of times, but you should aim to execute the minimum number of necessary actions for the input. You should use the `directly-answer` tool if calling the other tools is unnecessary. The list of actions you want to call should be formatted as a list of json objects, for example:
```json
[
{
"tool_name": title of the tool in the specification,
"parameters": a dict of parameters to input into the tool as they are defined in the specs, or {} if it takes no parameters
}
]```<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>

View File

@@ -0,0 +1,31 @@
{{- if or .System .Tools }}<|start_header_id|>system<|end_header_id|>
{{- if .System }}
{{ .System }}
{{- end }}
In addition to plain text responses, you can chose to call one or more of the provided functions.
Use the following rule to decide when to call a function:
* if the response can be generated from your internal knowledge (e.g., as in the case of queries like "What is the capital of Poland?"), do so
* if you need external information that can be obtained by calling one or more of the provided functions, generate a function calls
If you decide to call functions:
* prefix function calls with functools marker (no closing marker required)
* all function calls should be generated in a single JSON list formatted as functools[{"name": [function name], "arguments": [function arguments as JSON]}, ...]
* follow the provided JSON schema. Do not hallucinate arguments or values. Do to blindly copy values from the provided samples
* respect the argument type formatting. E.g., if the type if number and format is float, write value 7 as 7.0
* make sure you pick the right functions that match the user intent
Available functions as JSON spec:
{{- if .Tools }}
{{ .Tools }}
{{- end }}<|eot_id|>
{{- end }}
{{- range .Messages }}<|start_header_id|>
{{- if or (eq .Role "user") (eq .Role "assistant") (eq .Role "tool") }}{{ .Role }}
{{- end }}<|end_header_id|>
{{- if .Content }}{{ .Content }}
{{- else if .ToolCalls }} functools[
{{- range .ToolCalls }}{{ "{" }}"name": "{{ .Function.Name }}", "arguments": {{ .Function.Arguments }}{{ "}" }}
{{- end }}]
{{- end }}<|eot_id|>
{{- end }}<|start_header_id|>assistant<|end_header_id|>

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<|start_header_id|>system<|end_header_id|>
You are a knowledgable assistant. You can answer questions and perform tasks.
In addition to plain text responses, you can chose to call one or more of the provided functions.
Use the following rule to decide when to call a function:
* if the response can be generated from your internal knowledge (e.g., as in the case of queries like "What is the capital of Poland?"), do so
* if you need external information that can be obtained by calling one or more of the provided functions, generate a function calls
If you decide to call functions:
* prefix function calls with functools marker (no closing marker required)
* all function calls should be generated in a single JSON list formatted as functools[{"name": [function name], "arguments": [function arguments as JSON]}, ...]
* follow the provided JSON schema. Do not hallucinate arguments or values. Do to blindly copy values from the provided samples
* respect the argument type formatting. E.g., if the type if number and format is float, write value 7 as 7.0
* make sure you pick the right functions that match the user intent
Available functions as JSON spec:
[{"type":"function","function":{"name":"get_current_weather","description":"Get the current weather","parameters":{"type":"object","required":["location","format"],"properties":{"format":{"type":"string","description":"The temperature unit to use. Infer this from the users location.","enum":["celsius","fahrenheit"]},"location":{"type":"string","description":"The city and state, e.g. San Francisco, CA"}}}}}]<|eot_id|><|start_header_id|><|end_header_id|>You are a knowledgable assistant. You can answer questions and perform tasks.<|eot_id|><|start_header_id|>user<|end_header_id|>What's the weather like today in Paris?<|eot_id|><|start_header_id|>assistant<|end_header_id|> functools[{"name": "get_current_weather", "arguments": {"format":"celsius","location":"Paris, France"}}]<|eot_id|><|start_header_id|>tool<|end_header_id|>22<|eot_id|><|start_header_id|>assistant<|end_header_id|>The current temperature in Paris, France is 22 degrees Celsius.<|eot_id|><|start_header_id|>user<|end_header_id|>What's the weather like today in San Francisco and Toronto?<|eot_id|><|start_header_id|>assistant<|end_header_id|>

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{{- if .Messages }}
{{- if or .System .Tools }}<|start_header_id|>system<|end_header_id|>
{{ .System }}
{{- if .Tools }} You are provided with function signatures within <tools></tools> XML tags. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. For each function call return a json object with function name and arguments within <tool_call></tool_call> XML tags as follows:
<tool_call>
{"name": <function-name>,"arguments": <args-dict>}
</tool_call>
Here are the available tools:
<tools>
{{- range .Tools }} {{ .Function }}
{{- end }} </tools>
{{- end }}
{{- end }}<|eot_id|>
{{- range .Messages }}
{{- if ne .Role "system" }}<|start_header_id|>{{ .Role }}<|end_header_id|>
{{ if eq .Role "user" }}{{ .Content }}
{{- else if eq .Role "assistant" }}
{{- if .Content }}{{ .Content }}
{{- else if .ToolCalls }}<tool_call>
{{ range .ToolCalls }}{"name": "{{ .Function.Name }}", "arguments": {{ .Function.Arguments }}}
{{- end }}
</tool_call>
{{- end }}
{{- else if eq .Role "tool" }}<tool_response>
{{ .Content }}
</tool_response>
{{- end }}<|eot_id|>
{{- end }}
{{- end }}<|start_header_id|>assistant<|end_header_id|>
{{ else }}
{{ if .System }}<|start_header_id|>system<|end_header_id|>
{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>
{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>
{{ end }}{{ .Response }}
{{- if .Response }}<|eot_id|>
{{- end }}

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<|start_header_id|>system<|end_header_id|>
You are a knowledgable assistant. You can answer questions and perform tasks. You are provided with function signatures within <tools></tools> XML tags. You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions. For each function call return a json object with function name and arguments within <tool_call></tool_call> XML tags as follows:
<tool_call>
{"name": <function-name>,"arguments": <args-dict>}
</tool_call>
Here are the available tools:
<tools> {"name":"get_current_weather","description":"Get the current weather","parameters":{"type":"object","required":["location","format"],"properties":{"format":{"type":"string","description":"The temperature unit to use. Infer this from the users location.","enum":["celsius","fahrenheit"]},"location":{"type":"string","description":"The city and state, e.g. San Francisco, CA"}}}} </tools><|eot_id|><|start_header_id|>user<|end_header_id|>
What's the weather like today in Paris?<|eot_id|><|start_header_id|>assistant<|end_header_id|>
<tool_call>
{"name": "get_current_weather", "arguments": {"format":"celsius","location":"Paris, France"}}
</tool_call><|eot_id|><|start_header_id|>tool<|end_header_id|>
<tool_response>
22
</tool_response><|eot_id|><|start_header_id|>assistant<|end_header_id|>
The current temperature in Paris, France is 22 degrees Celsius.<|eot_id|><|start_header_id|>user<|end_header_id|>
What's the weather like today in San Francisco and Toronto?<|eot_id|><|start_header_id|>assistant<|end_header_id|>

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server/testdata/tools/messages.json vendored Normal file
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[
{
"role": "system",
"content": "You are a knowledgable assistant. You can answer questions and perform tasks."
},
{
"role": "user",
"content": "What's the weather like today in Paris?"
},
{
"role": "assistant",
"tool_calls": [
{
"id": "89a1e453-0bce-4de3-a456-c54bed09c520",
"type": "function",
"function": {
"name": "get_current_weather",
"arguments": {
"location": "Paris, France",
"format": "celsius"
}
}
}
]
},
{
"role": "tool",
"tool_call_id": "89a1e453-0bce-4de3-a456-c54bed09c520",
"content": "22"
},
{
"role": "assistant",
"content": "The current temperature in Paris, France is 22 degrees Celsius."
},
{
"role": "user",
"content": "What's the weather like today in San Francisco and Toronto?"
}
]

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{{- range $index, $_ := .Messages }}
{{- if eq .Role "user" }}
{{- if and (eq (len (slice $.Messages $index)) 1) $.Tools }}[AVAILABLE_TOOLS] {{ $.Tools }}[/AVAILABLE_TOOLS]
{{- end }}[INST] {{ if and (eq (len (slice $.Messages $index)) 1) $.System }}{{ $.System }}
{{ end }}{{ .Content }}[/INST]
{{- else if eq .Role "assistant" }}
{{- if .Content }} {{ .Content }}</s>
{{- else if .ToolCalls }}[TOOL_CALLS] [
{{- range .ToolCalls }}{"name": "{{ .Function.Name }}", "arguments": {{ .Function.Arguments }}}
{{- end }}]</s>
{{- end }}
{{- else if eq .Role "tool" }}[TOOL_RESULTS] {"content": {{ .Content }}}[/TOOL_RESULTS]
{{- end }}
{{- end }}

3
server/testdata/tools/mistral.out vendored Normal file
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[INST] What's the weather like today in Paris?[/INST][TOOL_CALLS] [{"name": "get_current_weather", "arguments": {"format":"celsius","location":"Paris, France"}}]</s>[TOOL_RESULTS] {"content": 22}[/TOOL_RESULTS] The current temperature in Paris, France is 22 degrees Celsius.</s>[AVAILABLE_TOOLS] [{"type":"function","function":{"name":"get_current_weather","description":"Get the current weather","parameters":{"type":"object","required":["location","format"],"properties":{"format":{"type":"string","description":"The temperature unit to use. Infer this from the users location.","enum":["celsius","fahrenheit"]},"location":{"type":"string","description":"The city and state, e.g. San Francisco, CA"}}}}}][/AVAILABLE_TOOLS][INST] You are a knowledgable assistant. You can answer questions and perform tasks.
What's the weather like today in San Francisco and Toronto?[/INST]

30
server/testdata/tools/tools.json vendored Normal file
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[
{
"type": "function",
"function": {
"name": "get_current_weather",
"description": "Get the current weather",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA"
},
"format": {
"type": "string",
"enum": [
"celsius",
"fahrenheit"
],
"description": "The temperature unit to use. Infer this from the users location."
}
},
"required": [
"location",
"format"
]
}
}
}
]

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@@ -4,4 +4,5 @@
{{ .Prompt }}
{{ end }}### Response:
{{ .Response }}
{{ .Response }}

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@@ -3,4 +3,4 @@
{{ end }}{{ if .Prompt }}<|im_start|>user
{{ .Prompt }}<|im_end|>
{{ end }}<|im_start|>assistant
{{ .Response }}<|im_end|>
{{ .Response }}<|im_end|>

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@@ -2,4 +2,5 @@
{{ end }}{{ if .Prompt }}User: {{ .Prompt }}
{{ end }}Assistant: <|begin_of_text|>{{ .Response }}
{{ end }}Assistant: {{ .Response }}

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{{ if .System }}Source: system
{{ .System }} <step> {{ end }}Source: user
{{ .Prompt }} <step> Source: assistant
{{- if not .Response }}
Destination: user
{{- end }}
{{ .Response }} <step>

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{{ if .System }}System: {{ .System }}
{{ end }}{{ if .Prompt }}User:
{{ .Prompt }}
{{ end }}Falcon:
{{ .Response }}

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<start_of_turn>user
{{ if .System }}{{ .System }}
{{ end }}{{ .Prompt }}<end_of_turn>
<start_of_turn>model
{{ .Response }}<end_of_turn>

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@@ -1,9 +1,9 @@
{{ if .System }}
System:
{{ if .System }}System:
{{ .System }}
{{ end }}{{ if .Prompt }}Question:
{{ .Prompt }}
{{ end }}Answer:
{{ .Response }}
{{ .Response }}

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[INST] <<SYS>>
{{- if .System }}
{{ .System }}
{{ end }}<</SYS>>
{{ .Prompt }} [/INST] {{ .Response }}</s><s>

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