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272 Commits

Author SHA1 Message Date
Jeffrey Morgan
e3fb1fd3f1 server: compare options correctly 2023-08-03 15:55:40 -04:00
Michael Yang
29b897f525 Merge pull request #253 from jmorganca/upload
use a pipe to push to registry with progress
2023-08-03 12:11:23 -07:00
Michael Yang
85aeb42869 Merge pull request #270 from jmorganca/update-llama-cpp
update llama.cpp
2023-08-03 12:09:00 -07:00
Michael Yang
c5bcf32823 update llama.cpp 2023-08-03 11:50:24 -07:00
Michael Yang
a71ff3f6a2 use a pipe to push to registry with progress
switch to a monolithic upload instead of a chunk upload through a pipe
to report progress
2023-08-03 10:37:13 -07:00
Michael Chiang
f0b365a478 Merge pull request #268 from jmorganca/mchiang0610-patch-2
Update README.md
2023-08-03 11:23:31 -04:00
Michael Chiang
df8048fecd Update README.md 2023-08-03 11:22:57 -04:00
Michael Yang
da2459d519 Update README.md (#265) 2023-08-02 22:38:32 -04:00
Bruce MacDonald
bd6d741d87 tell users to check the server error logs 2023-08-02 17:08:11 -04:00
Bruce MacDonald
8b1e791820 allow specifying zero values in modelfile 2023-08-02 17:07:53 -04:00
Jeffrey Morgan
03cff3a225 server: reset digest at end of generate 2023-08-02 16:15:44 -04:00
Michael Yang
cc509a994e Merge pull request #260 from jmorganca/embed-ggml-metal
override ggml-metal if the file is different
2023-08-02 13:01:46 -07:00
Michael Yang
0e79e52ddd override ggml-metal if the file is different 2023-08-02 12:50:30 -07:00
Jeffrey Morgan
6fbb380076 hide dock icon if window closes 2023-08-02 11:05:34 -04:00
Bruce MacDonald
8f8b6288ac check server is running before running command 2023-08-02 10:51:23 -04:00
Michael Yang
b98096389d Merge pull request #255 from jmorganca/update-llama-cpp
Update llama cpp
2023-08-01 17:18:33 -07:00
Michael Yang
74a5f7e698 no gpu for 70B model 2023-08-01 17:12:50 -07:00
Michael Yang
7a1c3e62dc update llama.cpp 2023-08-01 16:54:01 -07:00
Jeffrey Morgan
da52f5bfdd run npm install on build 2023-08-01 17:41:25 -04:00
Bruce MacDonald
50e87c6691 read from os executable 2023-08-01 16:01:55 -04:00
Gerd
e4a970ece1 Add model update to README.md (#252) 2023-08-01 15:06:33 -04:00
Jeffrey Morgan
4ca43a694c remove newlines between list items in README.md 2023-08-01 15:05:39 -04:00
Bruce MacDonald
765994362c use head to check heartbeat 2023-08-01 14:50:38 -04:00
Bruce MacDonald
40a25bf8c3 pr comments 2023-08-01 13:48:48 -04:00
Bruce MacDonald
1c5a8770ee read runner parameter options from map
- read runner options from map to see what was specified explicitly and overwrite zero values
2023-08-01 13:38:19 -04:00
Bruce MacDonald
daa0d1de7a allow specifying zero values in modelfile 2023-08-01 13:37:50 -04:00
Jeffrey Morgan
58daeb962a add llama2-uncensored to model list 2023-08-01 11:25:01 -04:00
Jeffrey Morgan
528bafa585 cache loaded model 2023-08-01 11:24:18 -04:00
Michael Chiang
81f75696e2 Merge pull request #251 from jmorganca/mchiang0610-patch-2
add examples of projects using Ollama
2023-08-01 11:16:14 -04:00
Michael Chiang
8bdcf894bd Update README.md
add examples of projects using Ollama
2023-08-01 11:14:54 -04:00
Michael Chiang
fe530423a5 Merge pull request #249 from sestinj/main
Add "Awesome projects built with Ollama" section to README, including Continue
2023-08-01 08:07:50 -07:00
Michael Yang
05e390205b Merge pull request #250 from jmorganca/fixes
Fixes
2023-07-31 21:47:42 -07:00
Michael Yang
872011630a fix license 2023-07-31 21:46:48 -07:00
Michael Yang
203fdbc4b8 check err 2023-07-31 21:46:48 -07:00
Michael Yang
70e0ab6b3d remove unnecessary fmt.Sprintf 2023-07-31 21:46:47 -07:00
Michael Yang
319f078dd9 remove -Werror
there are compile warnings on Linux which -Werror elevates to errors,
preventing compile
2023-07-31 21:45:56 -07:00
Jeffrey Morgan
9968153729 fix Go warnings 2023-07-31 21:37:40 -04:00
Jeffrey Morgan
7da249fcc1 only build metal for darwin,arm target 2023-07-31 21:35:23 -04:00
Bruce MacDonald
f529626c6c log prediction failures 2023-07-31 17:39:20 -04:00
Bruce MacDonald
36d6081ed1 find symlink of mac app 2023-07-31 17:38:10 -04:00
Nate Sesti
aadedda486 Update README.md 2023-07-31 13:59:39 -07:00
Bruce MacDonald
671eec6da9 log prediction failures 2023-07-31 16:46:37 -04:00
Bruce MacDonald
e72fe7945f check server is running before running command 2023-07-31 16:25:57 -04:00
Bruce MacDonald
d1c098b038 tell users to check the server error logs 2023-07-31 11:49:33 -04:00
Jeffrey Morgan
90ba0b80c7 fix build_darwin.sh 2023-07-29 22:36:59 -04:00
Patrick Devine
39bb25d5f6 allow multiline text using three double-quotes (#239) 2023-07-29 13:35:23 -07:00
Michael Yang
eadee46840 Merge pull request #236 from jmorganca/check-os-walk
check os.Walk err
2023-07-28 14:14:21 -07:00
Jeffrey Morgan
2e2e624d21 app: use notarytool for notarizing 2023-07-28 12:23:56 -07:00
Jeffrey Morgan
ed832ce3b7 darwin build script 2023-07-28 12:23:27 -07:00
Michael Yang
227da16909 Merge pull request #235 from jmorganca/rm-ioutil
remove io/ioutil import
2023-07-28 12:19:06 -07:00
Michael Yang
bd58528fbd check os.Walk err 2023-07-28 12:15:31 -07:00
Michael Yang
c5e447a359 remove io/ioutil import
ioutil is deprecated
2023-07-28 12:06:03 -07:00
Michael Yang
fc40a4f166 Merge pull request #234 from jmorganca/fix-parse-license
use max scan token size to hold large objects
2023-07-28 12:03:51 -07:00
Michael Yang
9c7f30d31c use max scan token size to hold large objects 2023-07-28 11:43:31 -07:00
Bruce MacDonald
6ed3ec0cb3 Allow specifying stop conditions in Modelfile 2023-07-28 12:31:08 -04:00
Bruce MacDonald
47bda0b860 add stop to docs 2023-07-28 12:30:27 -04:00
Jeffrey Morgan
c75cafdb58 build for universal architecture on macos 2023-07-28 12:18:11 -04:00
Bruce MacDonald
f5cbcb08e6 specify stop params separately 2023-07-28 11:29:00 -04:00
Jeffrey Morgan
67b6f8ba86 add ggml-metal.metal to .gitignore 2023-07-28 11:04:21 -04:00
Bruce MacDonald
184ad8f057 allow specifying stop conditions in modelfile 2023-07-28 11:02:04 -04:00
Jeffrey Morgan
822a0e36eb lower batch size to 512 2023-07-28 10:56:21 -04:00
Jeffrey Morgan
18b6b601ad app: cleanup README.md 2023-07-28 10:51:41 -04:00
Bruce MacDonald
0345070dfa update model file docs 2023-07-28 10:33:52 -04:00
Jeffrey Morgan
dffc8b6e09 update llama.cpp to d91f3f0 2023-07-28 08:07:48 -04:00
Jeffrey Morgan
0871083776 app: fix tray icon color scheme in dark mode 2023-07-28 07:03:46 -04:00
Michael Yang
e5b26c3aa2 Merge pull request #221 from jmorganca/embed-metal
embed ggml-metal.metal
2023-07-27 17:24:41 -07:00
Michael Yang
3549676678 embed ggml-metal.metal 2023-07-27 17:23:29 -07:00
Michael Yang
8fa477fadb Merge pull request #225 from jmorganca/stop-conditions
add stop conditions
2023-07-27 17:20:56 -07:00
Michael Yang
fadf75f99d add stop conditions 2023-07-27 17:00:47 -07:00
Patrick Devine
01d155c969 show system/template/license layers from cmd prompt (#223) 2023-07-27 16:58:40 -07:00
Michael Yang
5685c16d4e Merge pull request #211 from jmorganca/update-llama-cpp
update llama.cpp
2023-07-27 16:57:03 -07:00
Michael Yang
db77dfe01f Merge pull request #102 from jmorganca/session-id
Session
2023-07-27 16:46:29 -07:00
Michael Yang
ad3a7d0e2c add NumGQA 2023-07-27 14:05:11 -07:00
Michael Yang
18ffeeec45 update llama.cpp 2023-07-27 14:05:11 -07:00
Jeffrey Morgan
688661ab9b increase default batch size to 1024 2023-07-27 16:51:01 -04:00
Michael Chiang
36ad90e8e3 Merge pull request #231 from jmorganca/mchiang0610-discord
Update discord invite link
2023-07-27 15:43:52 -04:00
Michael Chiang
6fff59c637 Update discord invite link
Update discord invite link
2023-07-27 15:43:15 -04:00
Bruce MacDonald
fee7687cf3 Update modelfile.md 2023-07-27 15:15:10 -04:00
Bruce MacDonald
d3bfb4889c Update README.md 2023-07-27 15:13:50 -04:00
Bruce MacDonald
1ac38ec89c improve modelfile docs 2023-07-27 15:13:04 -04:00
Michael Yang
1ad8266473 Merge pull request #226 from jmorganca/fix-modelfile-quotes
refactor scan multiline for reuse
2023-07-27 11:45:41 -07:00
Michael Yang
f5ac8ddfb4 refactor scan multiline for reuse 2023-07-27 11:30:51 -07:00
Michael Yang
cca61181cb sample metrics 2023-07-27 09:31:44 -07:00
Michael Yang
c490416189 lock on llm.lock(); decrease batch size 2023-07-27 09:31:44 -07:00
Michael Yang
f62a882760 add session expiration 2023-07-27 09:31:44 -07:00
Michael Yang
3003fc03fc update predict code 2023-07-27 09:31:44 -07:00
Michael Yang
32aec66e6a add load duration 2023-07-27 09:31:44 -07:00
Michael Yang
35af37a2cb session id 2023-07-27 09:31:44 -07:00
Jeffrey Morgan
dbb3174cbc app: fix #218 and keep dock open on install 2023-07-27 10:53:38 -04:00
Jeffrey Morgan
31673d26d0 app: quit other instance when starting 2023-07-27 00:57:25 -04:00
Jeffrey Morgan
8ba0f328af clobber release artifacts 2023-07-26 18:58:28 -04:00
Jeffrey Morgan
d0e934b497 app: tray cleanup 2023-07-26 14:24:56 -04:00
Jeffrey Morgan
e751e47d70 app: remove dialog, icons for updates 2023-07-26 14:04:36 -04:00
Jeffrey Morgan
19d0f2b4cc publish as pre-release first 2023-07-26 10:48:49 -04:00
Jeffrey Morgan
c48f07f821 app: dont advance on error 2023-07-26 10:46:43 -04:00
Jeffrey Morgan
dc642aa07d web: skip pre-releases 2023-07-25 17:11:57 -04:00
Bruce MacDonald
f1ff892fdd pull model on make if not present locally 2023-07-25 16:53:01 -04:00
Jeffrey Morgan
3f2a100465 app: log app errors to console 2023-07-25 15:42:04 -04:00
Michael Yang
95397416f3 Merge pull request #212 from jmorganca/fix-multiline-parsing
fix multiline string
2023-07-25 11:53:51 -07:00
Michael Yang
8a86aae019 Merge pull request #209 from jmorganca/k-quants
enable k quants
2023-07-25 11:53:29 -07:00
Michael Yang
24c2c77057 fix multiline string
the data needs to remove the multiline quotes but include the command:

e.g.

TEMPLATE """
my template values
"""

should be

TEMPLATE
my template values

after scanning
2023-07-25 11:51:43 -07:00
Michael Yang
5614984f06 Merge pull request #189 from Mohit-Gaur/main
Improve command parsing and multiline string handling
2023-07-25 11:28:10 -07:00
Bruce MacDonald
4c1caa3733 download models when creating from modelfile 2023-07-25 14:25:13 -04:00
Bruce MacDonald
12ab8f8f5f Revert "pull model on make if not present locally"
This reverts commit 360a10ace391a674de60aa7b9b8cb65e8074027c.
2023-07-25 14:18:46 -04:00
Bruce MacDonald
8ebbd12f21 pull model on make if not present locally 2023-07-25 14:18:46 -04:00
Eva Ho
07971759fa fix typo 2023-07-25 13:30:52 -04:00
Mohit Gaur
f5f79049c2 Incorporate code review improvements 2023-07-25 22:52:23 +05:30
Michael Yang
726bc647b2 enable k quants 2023-07-25 08:39:58 -07:00
Bruce MacDonald
af9039a167 better error message when model not found on pull 2023-07-25 10:30:48 -04:00
Bruce MacDonald
07ed69bc37 remove reduandant err var 2023-07-25 10:30:14 -04:00
Michael Yang
0deb3767fc Merge pull request #205 from jmorganca/accelerate
enable accelerate
2023-07-24 20:06:05 -07:00
Michael Yang
cb55fa9270 enable accelerate 2023-07-24 17:14:45 -07:00
Michael Yang
93bc9f17a1 Merge pull request #192 from jmorganca/update-development.md
update development.md
2023-07-24 16:13:22 -07:00
Bruce MacDonald
536028c35a better error message when model not found on pull 2023-07-24 17:48:17 -04:00
Michael Chiang
aedf3d1f38 Merge pull request #196 from isbkch/main
add devops-engineer example
2023-07-24 17:10:22 -04:00
iLyas Bakouch
91d927abc5 Update Modelfile 2023-07-24 16:43:11 -04:00
iLyas Bakouch
ba8df10a43 Update examples/devops-engineer/Modelfile
Co-authored-by: Jeffrey Morgan <251292+jmorganca@users.noreply.github.com>
2023-07-24 16:42:08 -04:00
Bruce MacDonald
abf614804b remove file on digest mismatch 2023-07-24 21:59:12 +02:00
Bruce MacDonald
a0dbbb23c4 truncate file size on resume 2023-07-24 21:58:32 +02:00
Bruce MacDonald
0fd6278446 do not panic server if file cannot be opened 2023-07-24 15:24:34 -04:00
Bruce MacDonald
29fe07f0cc make response errors unique for error trace 2023-07-24 21:21:18 +02:00
Bruce MacDonald
abfc73d31e make response errors unique for error trace 2023-07-24 15:04:21 -04:00
Bruce MacDonald
5a5ca8e7ff remove file on digest mismatch 2023-07-24 14:53:01 -04:00
Ilyas Bakouch
f24a6f5988 add devops-engineer example 2023-07-24 14:44:44 -04:00
Bruce MacDonald
fdbef6c95e truncate file size on resume 2023-07-24 14:36:19 -04:00
Michael Yang
24e43e3212 update development.md 2023-07-24 09:43:57 -07:00
Patrick Devine
4cb42ca55e add copy command (#191) 2023-07-24 11:27:28 -04:00
Michael Yang
ec5e22ac85 Merge pull request #174 from jmorganca/tokenize
allocate a large enough tokens slice
2023-07-24 08:22:51 -07:00
Mohit Gaur
ed89da92b4 Improve command parsing and multiline string handling 2023-07-24 18:11:13 +05:30
Jeffrey Morgan
a3297fed41 add /api/create docs to readme 2023-07-23 18:01:05 -04:00
Patrick Devine
88c55199f8 change push to chunked uploads from monolithic (#179) 2023-07-22 17:31:26 -07:00
hoyyeva
c448443813 Merge pull request #164 from jmorganca/restart-server
restart server more gracefully
2023-07-22 18:19:22 -04:00
Michael Yang
efacd45fc5 Merge pull request #175 from jk1jk/main
Update .gitignore
2023-07-22 09:40:37 -07:00
Michael Yang
fa522695c4 Merge pull request #178 from jmorganca/gin-cors
use gin-contrib/cors middleware
2023-07-22 09:40:01 -07:00
Michael Yang
8609db77ea use gin-contrib/cors middleware 2023-07-22 09:39:08 -07:00
Ikko Eltociear Ashimine
65d93a86b2 Update modelfile.md (#177)
fix markdown.
2023-07-22 08:19:30 -07:00
jk1jk
e6c427ce4d Update .gitignore 2023-07-22 17:00:52 +03:00
Michael Yang
b71c67b6ba allocate a large enough tokens slice 2023-07-21 23:05:15 -07:00
Patrick Devine
6d6b0d3321 change error handler behavior and fix error when a model isn't found (#173) 2023-07-21 23:02:12 -07:00
Michael Yang
37324a0a00 Merge pull request #172 from jmorganca/set-vars-first
fix vars.First
2023-07-21 20:55:06 -07:00
Michael Yang
20a5d99f77 fix vars.First 2023-07-21 20:45:32 -07:00
Patrick Devine
3b43cc019a fix extended tag names (#171) 2023-07-21 20:27:25 -07:00
Patrick Devine
b8421dce3d get the proper path for blobs to delete (#168) 2023-07-21 17:30:40 -07:00
Patrick Devine
9f6e97865c allow pushing/pulling to insecure registries (#157) 2023-07-21 15:42:19 -07:00
Eva Ho
9657314ae2 address comment 2023-07-21 17:29:07 -04:00
Eva Ho
3f7d2336c7 add prettier and address comments 2023-07-21 17:10:05 -04:00
Eva Ho
e0a73d7fbe address comment 2023-07-21 16:53:56 -04:00
hoyyeva
b08c4ca2bd Update app/src/index.ts
Co-authored-by: Jeffrey Morgan <251292+jmorganca@users.noreply.github.com>
2023-07-21 16:53:56 -04:00
Eva Ho
734892f1e2 address comment 2023-07-21 16:53:56 -04:00
Eva Ho
d2bfaeac63 format code 2023-07-21 16:53:56 -04:00
Eva Ho
0768b1b907 restart server with condition and timeout 2023-07-21 16:53:56 -04:00
Bruce MacDonald
f5f0da06d9 Merge pull request #166 from jmorganca/brucemacd/dev-cgo 2023-07-21 22:48:10 +02:00
Bruce MacDonald
52f04e39f2 Note that CGO must be enabled in dev docs 2023-07-21 22:36:36 +02:00
Jeffrey Morgan
3c8f4c03d7 web: tweak homepage text 2023-07-21 09:57:57 -07:00
Bruce MacDonald
7ba1308595 Merge pull request #147 from jmorganca/brucemacd/cli-err-display
Improve CLI error display
2023-07-21 16:10:19 +02:00
Jeffrey Morgan
91cd54016c add basic REST api documentation 2023-07-21 00:47:17 -07:00
Patrick Devine
e7a393de54 add rm command for models (#151) 2023-07-20 16:09:23 -07:00
Jeffrey Morgan
8454f298ac fix example Modelfiles 2023-07-20 15:46:32 -07:00
Patrick Devine
a3badaf103 add ls alias (#152) 2023-07-20 15:28:27 -07:00
Michael Yang
50e8e5bdbe Merge pull request #148 from jmorganca/more-llama-files
add llama.cpp mpi, opencl files
2023-07-20 14:26:46 -07:00
Michael Yang
8526e1f5f1 add llama.cpp mpi, opencl files 2023-07-20 14:19:55 -07:00
Michael Yang
0cfdbb95cc Merge pull request #146 from jmorganca/fix-windows-pull
windows: fix model pulling
2023-07-20 13:41:54 -07:00
Michael Yang
6cea2061ec windows: fix model pulling 2023-07-20 12:35:04 -07:00
Michael Yang
2832801c2a Merge pull request #91 from jmorganca/fix-stream-errors
fix stream errors
2023-07-20 12:21:59 -07:00
Jeffrey Morgan
23a37dc466 clean up README.md 2023-07-20 12:21:36 -07:00
Michael Yang
992892866b Merge pull request #145 from jmorganca/verify-digest
verify blob digest
2023-07-20 12:14:21 -07:00
Michael Yang
dde880290c Merge pull request #131 from jmorganca/update-llama-cpp
update llama.cpp to e782c9e735f93ab4767ffc37462c523b73a17ddc
2023-07-20 12:14:10 -07:00
Michael Yang
1f27d7f1b8 fix stream errors 2023-07-20 12:12:08 -07:00
Bruce MacDonald
00aaa05901 remove unused code 2023-07-20 20:57:30 +02:00
Michael Yang
a83eaa7a9f update llama.cpp to e782c9e735f93ab4767ffc37462c523b73a17ddc 2023-07-20 11:55:56 -07:00
Michael Yang
5156e48c2a add script to update llama.cpp 2023-07-20 11:54:59 -07:00
Michael Yang
bf198c3918 verify blob digest 2023-07-20 11:53:57 -07:00
Bruce MacDonald
09dc6273e3 suppress error when running list before pulling image 2023-07-20 20:53:09 +02:00
Bruce MacDonald
ebaa33ac28 display gin api errors in cli 2023-07-20 20:45:12 +02:00
Bruce MacDonald
3ec4ebc562 remove unused code 2023-07-20 20:18:00 +02:00
Jeffrey Morgan
6a19724d5f remove colon from library modelfiles 2023-07-20 09:51:30 -07:00
Jeffrey Morgan
924ce739f9 documentation on the model format 2023-07-20 09:03:41 -07:00
Michael Chiang
e1973e6780 Update icon (#139) 2023-07-20 08:55:20 -07:00
Jeffrey Morgan
f1b08ef40e set temperature on README.md example 2023-07-20 08:17:09 -07:00
Jeffrey Morgan
31f0cb7742 new Modelfile syntax 2023-07-20 07:52:24 -07:00
Jeffrey Morgan
e4b2ccfb23 web: clean up remaining models.json usage 2023-07-20 07:51:46 -07:00
Bruce MacDonald
a3d7bb0a30 Merge pull request #136 from jmorganca/brucemacd/remove-models
Delete models.json
2023-07-20 16:40:46 +02:00
Bruce MacDonald
77e49f3822 Delete models.json 2023-07-20 16:32:50 +02:00
Jeffrey Morgan
8945b25484 new modelfile syntax on branch 2023-07-20 02:24:21 -07:00
Jeffrey Morgan
99ccf0c5d3 fix broken link in README.md 2023-07-20 02:15:11 -07:00
Jeffrey Morgan
d59b164fa2 add prompt back to parser 2023-07-20 01:13:30 -07:00
Michael Yang
55b5f5dc34 ctrl+c on empty line exits (#135) 2023-07-20 00:53:08 -07:00
Jeffrey Morgan
3b135ac963 parser: fix case where multi line string termination error wouldnt show 2023-07-20 00:43:22 -07:00
Jeffrey Morgan
e6bae8d916 parser: keep seeking until eof 2023-07-20 00:37:52 -07:00
Jeffrey Morgan
d9f54300c3 library: add echo for verify progress 2023-07-19 23:58:28 -07:00
Jeffrey Morgan
1511219763 update library modelfiles with new syntax 2023-07-19 23:57:22 -07:00
Jeffrey Morgan
ada0add89b fix llama library templates 2023-07-19 23:53:40 -07:00
Jeffrey Morgan
75e508e1d6 remove old templates 2023-07-19 23:47:13 -07:00
Michael Yang
6f046dbf18 Update images.go (#134) 2023-07-19 23:46:01 -07:00
Jeffrey Morgan
cd820c8bca move wizard-vicuna to correct location 2023-07-19 23:44:03 -07:00
Jeffrey Morgan
88e755d7fd Add files for library models 2023-07-19 23:40:37 -07:00
Michael Yang
6984171cfd Merge pull request #93 from jmorganca/split-prompt
separate prompt into template and system
2023-07-19 23:25:33 -07:00
Michael Yang
60b4db6389 add .First 2023-07-19 23:24:32 -07:00
Michael Chiang
7c6ea2a966 fix dangling """ 2023-07-19 23:24:32 -07:00
Michael Chiang
c161aef5f9 update example 2023-07-19 23:24:32 -07:00
Michael Chiang
c47786c1b0 Update docs/modelfile.md
Co-authored-by: Michael Yang <mxyng@pm.me>
2023-07-19 23:24:32 -07:00
Michael Chiang
df100ce540 Update docs/modelfile.md
Co-authored-by: Michael Yang <mxyng@pm.me>
2023-07-19 23:24:32 -07:00
Michael Chiang
5c5948b4e7 clean up my previous empty sentences 2023-07-19 23:24:32 -07:00
Michael Yang
1c72e46e09 update modelfile.md 2023-07-19 23:24:32 -07:00
Michael Yang
ca210ba480 handle vnd.ollama.image.prompt for compat 2023-07-19 23:24:32 -07:00
Michael Yang
df146c41e2 separate prompt into template and system 2023-07-19 23:24:31 -07:00
Jeffrey Morgan
2d305fa99a allow relative paths in FROM instruction 2023-07-19 21:55:15 -07:00
Patrick Devine
e4d7f3e287 vendor in progress bar and change to bytes instead of bibytes (#130) 2023-07-19 17:24:03 -07:00
Jeffrey Morgan
f2044b5838 web: fix newsletter signup 2023-07-19 16:11:56 -07:00
Michael Chiang
d53988f619 Merge pull request #128 from jmorganca/mchiang0610-patch-1
Update modelfile.md
2023-07-19 13:40:39 -07:00
Michael Chiang
ac88ab48d9 update 2023-07-19 13:37:21 -07:00
Michael Yang
84c6ee8cc6 Merge pull request #104 from jmorganca/interactive-readline
use readline
2023-07-19 13:36:24 -07:00
Michael Yang
dbc90576b8 add verbose/quiet commands 2023-07-19 13:34:56 -07:00
Michael Yang
84200dcde6 use readline 2023-07-19 13:34:56 -07:00
Michael Chiang
e54c08da89 updating prompt 2023-07-19 13:34:40 -07:00
Michael Chiang
31413857ea organizing examples 2023-07-19 13:25:14 -07:00
Michael Chiang
25f874c030 Update modelfile.md 2023-07-19 12:48:57 -07:00
Jeffrey Morgan
10d502611f fix discord link in README.md 2023-07-19 12:31:48 -07:00
Jeffrey Morgan
7fe4103b94 add discord link, remove repeated text 2023-07-19 12:28:50 -07:00
Michael Chiang
7fbdc8e2c1 Update modelfile.md 2023-07-19 11:38:06 -07:00
Eva Ho
9c5572d51f add discord link back 2023-07-19 13:03:26 -04:00
Matt Williams
75eb28f574 Merge pull request #125 from jmorganca/matt/addlicensetomodelfiledoc
Updated modelfile doc to include license
2023-07-19 08:57:06 -07:00
Patrick Devine
56b6a1720f add llama2:13b model to the readme (#126) 2023-07-19 08:21:28 -07:00
Eva Ho
dfceca48a7 update icons to have different images for bright and dark mode 2023-07-19 11:14:43 -04:00
Matt Williams
bbb67002c3 get rid of latest
Signed-off-by: Matt Williams <m@technovangelist.com>
2023-07-19 07:40:40 -07:00
Michael Chiang
0294216ea9 Merge pull request #124 from DavidZirinsky/patch-1
Update README.md
2023-07-19 07:40:24 -07:00
Matt Williams
7a62b2d2ab Update the FROM instructions
Signed-off-by: Matt Williams <m@technovangelist.com>
2023-07-19 07:39:40 -07:00
Eva Ho
f08c050e57 fix page transitions flickering 2023-07-19 10:19:24 -04:00
Matt Williams
67c8d49757 Updated modelfile doc to include license
and attributed midjourneyprompt

Signed-off-by: Matt Williams <m@technovangelist.com>
2023-07-19 07:16:38 -07:00
DavidZirinsky
ffcd90e8a7 Update README.md
I needed to do this to run the project
2023-07-19 08:14:44 -06:00
Jeffrey Morgan
4ca7c4be1f dont consume reader when calculating digest 2023-07-19 00:47:55 -07:00
Michael Chiang
17b7af78f0 Merge pull request #115 from jmorganca/Add-wizard-vicuna-uncensored-model-link
Add wizard vicuna uncensored model link
2023-07-18 22:58:07 -07:00
Jeffrey Morgan
4c1dc52083 app: create /usr/local/bin/ if it does not exist 2023-07-18 22:50:52 -07:00
Patrick Devine
572fc9099f add license layers to the parser (#116) 2023-07-18 22:49:38 -07:00
Michael Chiang
3020f29041 Add wizard vicuna uncensored model link 2023-07-18 22:19:12 -07:00
Michael Yang
a6d03dd510 Merge pull request #110 from jmorganca/fix-pull-0-bytes
fix pull 0 bytes on completed layer
2023-07-18 19:38:59 -07:00
Michael Yang
68df36ae50 fix pull 0 bytes on completed layer 2023-07-18 19:38:11 -07:00
Michael Yang
5540305293 Merge pull request #112 from jmorganca/fix-relative-modelfile
resolve modelfile before passing to server
2023-07-18 19:36:24 -07:00
Michael Yang
d4cfee79d5 resolve modelfile before passing to server 2023-07-18 19:34:05 -07:00
Michael Yang
6e36f948df Merge pull request #109 from jmorganca/fix-create-memory
fix memory leak in create
2023-07-18 17:25:19 -07:00
Michael Yang
553fa39fe8 fix memory leak in create 2023-07-18 17:14:17 -07:00
Jeffrey Morgan
820e581ad8 web: fix typos and add link to discord 2023-07-18 17:03:40 -07:00
Isaac McFadyen
d14785738e README typo fix (#106)
* Fixed typo in README
2023-07-18 16:24:57 -07:00
Patrick Devine
9e15635c2d attempt two for skipping files in the file walk (#105) 2023-07-18 15:37:01 -07:00
Jeffrey Morgan
3e10f902f5 add mario example 2023-07-18 14:27:36 -07:00
Jeffrey Morgan
aa6714f25c fix typo in README.md 2023-07-18 14:03:11 -07:00
Jeffrey Morgan
7f3a37aed4 fix typo 2023-07-18 13:32:06 -07:00
Jeffrey Morgan
7b08280355 move download to the top of README.md 2023-07-18 13:31:25 -07:00
Jeffrey Morgan
e3cc4d5eac update README.md with new syntax 2023-07-18 13:22:46 -07:00
Jeffrey Morgan
8c85dfb735 Add README.md for examples 2023-07-18 13:22:46 -07:00
hoyyeva
ac62a413e5 Merge pull request #103 from jmorganca/web-update
website content and design update
2023-07-18 16:18:04 -04:00
Eva Ho
d1f89778e9 fix css on smaller screen 2023-07-18 16:17:42 -04:00
Eva Ho
df67a90e64 fix css 2023-07-18 16:02:45 -04:00
Eva Ho
576ae644de enable downloader 2023-07-18 15:57:39 -04:00
Eva Ho
7e52e51db1 update website text and design 2023-07-18 15:56:43 -04:00
Michael Chiang
f12df8d79a Merge pull request #101 from jmorganca/adding-logo
add logo
2023-07-18 12:47:20 -07:00
Michael Chiang
65de730bdb Update README.md
add logo
2023-07-18 12:45:38 -07:00
Patrick Devine
9658a5043b skip files in the list if we can't get the correct model path (#100) 2023-07-18 12:39:08 -07:00
Jeffrey Morgan
280fbe8019 app: use llama2 instead of orca 2023-07-18 12:36:03 -07:00
Jeffrey Morgan
2e339c2bab flatten examples 2023-07-18 12:33:50 -07:00
Michael Yang
38f0c54c64 Merge pull request #99 from jmorganca/mkdir-blobs
fix mkdir blob path
2023-07-18 11:29:05 -07:00
Michael Yang
f20426a768 fix mkdir blob path 2023-07-18 11:24:19 -07:00
Michael Yang
885f67a471 Merge pull request #92 from jmorganca/create-model-spinner
Create model spinner
2023-07-18 11:15:45 -07:00
Eva Ho
a9cc270b4d icon update 2023-07-18 13:33:26 -04:00
Eva Ho
aa281a30e5 updating icons 2023-07-18 13:33:26 -04:00
Matt Williams
760bc3366b Merge pull request #98 from jmorganca/matt/modelfiledoc
First stab at a modelfile doc
2023-07-18 09:16:01 -07:00
Patrick Devine
5bea29f610 add new list command (#97) 2023-07-18 09:09:45 -07:00
Matt Williams
9310ee3967 First stab at a modelfile doc
Signed-off-by: Matt Williams <m@technovangelist.com>
2023-07-18 08:22:17 -07:00
Matt Williams
da7ddbb4dc Merge pull request #95 from jmorganca/matt/examplemodelfiles 2023-07-18 05:32:38 -07:00
Matt Williams
3d9498dc95 Some simple modelfile examples
Signed-off-by: Matt Williams <m@technovangelist.com>
2023-07-17 17:16:59 -07:00
Michael Yang
e4300e1eb7 add spinner to create 2023-07-17 14:15:42 -07:00
Michael Yang
aba706ea2d remove unused persistent pre run 2023-07-17 14:14:57 -07:00
104 changed files with 13922 additions and 3367 deletions

2
.gitignore vendored
View File

@@ -2,5 +2,7 @@
.vscode
.env
.venv
.swp
dist
ollama
/ggml-metal.metal

144
README.md
View File

@@ -1,76 +1,117 @@
![ollama](https://github.com/jmorganca/ollama/assets/251292/961f99bb-251a-4eec-897d-1ba99997ad0f)
<div align="center">
<picture>
<source media="(prefers-color-scheme: dark)" height="200px" srcset="https://github.com/jmorganca/ollama/assets/3325447/56ea1849-1284-4645-8970-956de6e51c3c">
<img alt="logo" height="200px" src="https://github.com/jmorganca/ollama/assets/3325447/0d0b44e2-8f4a-4e99-9b52-a5c1c741c8f7">
</picture>
</div>
# Ollama
Run large language models with `llama.cpp`.
[![Discord](https://dcbadge.vercel.app/api/server/ollama?style=flat&compact=true)](https://discord.gg/ollama)
> Note: certain models that can be run with Ollama are intended for research and/or non-commercial use only.
> Note: Ollama is in early preview. Please report any issues you find.
### Features
Run, create, and share large language models (LLMs).
- Download and run popular large language models
- Switch between multiple models on the fly
- Hardware acceleration where available (Metal, CUDA)
- Fast inference server written in Go, powered by [llama.cpp](https://github.com/ggerganov/llama.cpp)
- REST API to use with your application (python, typescript SDKs coming soon)
## Download
## Install
- [Download](https://ollama.ai/download) for macOS with Apple Silicon (Intel coming soon)
- Download for Windows (coming soon)
You can also build the [binary from source](#building).
- [Download](https://ollama.ai/download) for macOS on Apple Silicon (Intel coming soon)
- Download for Windows and Linux (coming soon)
- Build [from source](#building)
## Quickstart
Run a fast and simple model.
To run and chat with [Llama 2](https://ai.meta.com/llama), the new model by Meta:
```
ollama run orca
ollama run llama2
```
## Example models
## Model library
### 💬 Chat
`ollama` includes a library of open-source models:
Have a conversation.
| Model | Parameters | Size | Download |
| ------------------------ | ---------- | ----- | ------------------------------- |
| Llama2 | 7B | 3.8GB | `ollama pull llama2` |
| Llama2 Uncensored | 7B | 3.8GB | `ollama pull llama2-uncensored` |
| Llama2 13B | 13B | 7.3GB | `ollama pull llama2:13b` |
| Orca Mini | 3B | 1.9GB | `ollama pull orca` |
| Vicuna | 7B | 3.8GB | `ollama pull vicuna` |
| Nous-Hermes | 13B | 7.3GB | `ollama pull nous-hermes` |
| Wizard Vicuna Uncensored | 13B | 7.3GB | `ollama pull wizard-vicuna` |
> Note: You should have at least 8 GB of RAM to run the 3B models, 16 GB to run the 7B models, and 32 GB to run the 13B models.
## Examples
### Run a model
```
ollama run vicuna "Why is the sky blue?"
ollama run llama2
>>> hi
Hello! How can I help you today?
```
### 🗺️ Instructions
### Create a custom model
Get a helping hand.
Pull a base model:
```
ollama run orca "Write an email to my boss."
ollama pull llama2
```
> To update a model to the latest version, run `ollama pull llama2` again. The model will be updated (if necessary).
### 🔎 Ask questions about documents
Send the contents of a document and ask questions about it.
Create a `Modelfile`:
```
ollama run nous-hermes "$(cat input.txt)", please summarize this story
FROM llama2
# set the temperature to 1 [higher is more creative, lower is more coherent]
PARAMETER temperature 1
# set the system prompt
SYSTEM """
You are Mario from Super Mario Bros. Answer as Mario, the assistant, only.
"""
```
### 📖 Storytelling
Venture into the unknown.
Next, create and run the model:
```
ollama run nous-hermes "Once upon a time"
ollama create mario -f ./Modelfile
ollama run mario
>>> hi
Hello! It's your friend Mario.
```
## Advanced usage
For more examples, see the [examples](./examples) directory.
### Run a local model
For more information on creating a Modelfile, see the [Modelfile](./docs/modelfile.md) documentation.
### Pull a model from the registry
```
ollama run ~/Downloads/vicuna-7b-v1.3.ggmlv3.q4_1.bin
ollama pull orca
```
### Listing local models
```
ollama list
```
## Model packages
### Overview
Ollama bundles model weights, configuration, and data into a single package, defined by a [Modelfile](./docs/modelfile.md).
<picture>
<source media="(prefers-color-scheme: dark)" height="480" srcset="https://github.com/jmorganca/ollama/assets/251292/2fd96b5f-191b-45c1-9668-941cfad4eb70">
<img alt="logo" height="480" src="https://github.com/jmorganca/ollama/assets/251292/2fd96b5f-191b-45c1-9668-941cfad4eb70">
</picture>
## Building
```
@@ -80,29 +121,36 @@ go build .
To run it start the server:
```
./ollama server &
./ollama serve &
```
Finally, run a model!
```
./ollama run ~/Downloads/vicuna-7b-v1.3.ggmlv3.q4_1.bin
./ollama run llama2
```
## API Reference
### `POST /api/pull`
Download a model
```
curl -X POST http://localhost:11343/api/pull -d '{"model": "orca"}'
```
## REST API
### `POST /api/generate`
Complete a prompt
Generate text from a model.
```
curl -X POST http://localhost:11434/api/generate -d '{"model": "orca", "prompt": "hello!"}'
curl -X POST http://localhost:11434/api/generate -d '{"model": "llama2", "prompt":"Why is the sky blue?"}'
```
### `POST /api/create`
Create a model from a `Modelfile`.
```
curl -X POST http://localhost:11434/api/create -d '{"name": "my-model", "path": "/path/to/modelfile"}'
```
## Projects built with Ollama
- [Continue](https://github.com/continuedev/continue) - embeds Ollama inside Visual Studio Code. The extension lets you highlight code to add to the prompt, ask questions in the sidebar, and generate code inline.
- [Discord AI Bot](https://github.com/mekb-turtle/discord-ai-bot) - interact with Ollama as a chatbot on Discord.
- [Raycast Ollama](https://github.com/MassimilianoPasquini97/raycast_ollama) - Raycast extension to use Ollama for local llama inference on Raycast.
- [Simple HTML UI for Ollama](https://github.com/rtcfirefly/ollama-ui)

View File

@@ -6,26 +6,31 @@ import (
"context"
"encoding/json"
"fmt"
"io"
"net/http"
"net/url"
)
type StatusError struct {
StatusCode int
Status string
Message string
type Client struct {
base url.URL
HTTP http.Client
Headers http.Header
}
func (e StatusError) Error() string {
if e.Message != "" {
return fmt.Sprintf("%s: %s", e.Status, e.Message)
func checkError(resp *http.Response, body []byte) error {
if resp.StatusCode >= 200 && resp.StatusCode < 400 {
return nil
}
return e.Status
}
apiError := StatusError{StatusCode: resp.StatusCode}
type Client struct {
base url.URL
err := json.Unmarshal(body, &apiError)
if err != nil {
// Use the full body as the message if we fail to decode a response.
apiError.ErrorMessage = string(body)
}
return apiError
}
func NewClient(hosts ...string) *Client {
@@ -36,9 +41,59 @@ func NewClient(hosts ...string) *Client {
return &Client{
base: url.URL{Scheme: "http", Host: host},
HTTP: http.Client{},
}
}
func (c *Client) do(ctx context.Context, method, path string, reqData, respData any) error {
var reqBody io.Reader
var data []byte
var err error
if reqData != nil {
data, err = json.Marshal(reqData)
if err != nil {
return err
}
reqBody = bytes.NewReader(data)
}
url := c.base.JoinPath(path).String()
req, err := http.NewRequestWithContext(ctx, method, url, reqBody)
if err != nil {
return err
}
req.Header.Set("Content-Type", "application/json")
req.Header.Set("Accept", "application/json")
for k, v := range c.Headers {
req.Header[k] = v
}
respObj, err := c.HTTP.Do(req)
if err != nil {
return err
}
defer respObj.Body.Close()
respBody, err := io.ReadAll(respObj.Body)
if err != nil {
return err
}
if err := checkError(respObj, respBody); err != nil {
return err
}
if len(respBody) > 0 && respData != nil {
if err := json.Unmarshal(respBody, respData); err != nil {
return err
}
}
return nil
}
func (c *Client) stream(ctx context.Context, method, path string, data any, fn func([]byte) error) error {
var buf *bytes.Buffer
if data != nil {
@@ -75,11 +130,15 @@ func (c *Client) stream(ctx context.Context, method, path string, data any, fn f
return fmt.Errorf("unmarshal: %w", err)
}
if errorResponse.Error != "" {
return fmt.Errorf(errorResponse.Error)
}
if response.StatusCode >= 400 {
return StatusError{
StatusCode: response.StatusCode,
Status: response.Status,
Message: errorResponse.Error,
StatusCode: response.StatusCode,
Status: response.Status,
ErrorMessage: errorResponse.Error,
}
}
@@ -104,11 +163,11 @@ func (c *Client) Generate(ctx context.Context, req *GenerateRequest, fn Generate
})
}
type PullProgressFunc func(PullProgress) error
type PullProgressFunc func(ProgressResponse) error
func (c *Client) Pull(ctx context.Context, req *PullRequest, fn PullProgressFunc) error {
return c.stream(ctx, http.MethodPost, "/api/pull", req, func(bts []byte) error {
var resp PullProgress
var resp ProgressResponse
if err := json.Unmarshal(bts, &resp); err != nil {
return err
}
@@ -117,11 +176,11 @@ func (c *Client) Pull(ctx context.Context, req *PullRequest, fn PullProgressFunc
})
}
type PushProgressFunc func(PushProgress) error
type PushProgressFunc func(ProgressResponse) error
func (c *Client) Push(ctx context.Context, req *PushRequest, fn PushProgressFunc) error {
return c.stream(ctx, http.MethodPost, "/api/push", req, func(bts []byte) error {
var resp PushProgress
var resp ProgressResponse
if err := json.Unmarshal(bts, &resp); err != nil {
return err
}
@@ -130,11 +189,11 @@ func (c *Client) Push(ctx context.Context, req *PushRequest, fn PushProgressFunc
})
}
type CreateProgressFunc func(CreateProgress) error
type CreateProgressFunc func(ProgressResponse) error
func (c *Client) Create(ctx context.Context, req *CreateRequest, fn CreateProgressFunc) error {
return c.stream(ctx, http.MethodPost, "/api/create", req, func(bts []byte) error {
var resp CreateProgress
var resp ProgressResponse
if err := json.Unmarshal(bts, &resp); err != nil {
return err
}
@@ -142,3 +201,32 @@ func (c *Client) Create(ctx context.Context, req *CreateRequest, fn CreateProgre
return fn(resp)
})
}
func (c *Client) List(ctx context.Context) (*ListResponse, error) {
var lr ListResponse
if err := c.do(ctx, http.MethodGet, "/api/tags", nil, &lr); err != nil {
return nil, err
}
return &lr, nil
}
func (c *Client) Copy(ctx context.Context, req *CopyRequest) error {
if err := c.do(ctx, http.MethodPost, "/api/copy", req, nil); err != nil {
return err
}
return nil
}
func (c *Client) Delete(ctx context.Context, req *DeleteRequest) error {
if err := c.do(ctx, http.MethodDelete, "/api/delete", req, nil); err != nil {
return err
}
return nil
}
func (c *Client) Heartbeat(ctx context.Context) error {
if err := c.do(ctx, http.MethodHead, "/", nil, nil); err != nil {
return err
}
return nil
}

View File

@@ -1,18 +1,43 @@
package api
import (
"encoding/json"
"fmt"
"log"
"math"
"os"
"reflect"
"runtime"
"strings"
"time"
)
type StatusError struct {
StatusCode int
Status string
ErrorMessage string `json:"error"`
}
func (e StatusError) Error() string {
switch {
case e.Status != "" && e.ErrorMessage != "":
return fmt.Sprintf("%s: %s", e.Status, e.ErrorMessage)
case e.Status != "":
return e.Status
case e.ErrorMessage != "":
return e.ErrorMessage
default:
// this should not happen
return "something went wrong, please see the ollama server logs for details"
}
}
type GenerateRequest struct {
Model string `json:"model"`
Prompt string `json:"prompt"`
Context []int `json:"context,omitempty"`
Options `json:"options"`
Options map[string]interface{} `json:"options"`
}
type CreateRequest struct {
@@ -20,36 +45,44 @@ type CreateRequest struct {
Path string `json:"path"`
}
type CreateProgress struct {
Status string `json:"status"`
type DeleteRequest struct {
Name string `json:"name"`
}
type CopyRequest struct {
Source string `json:"source"`
Destination string `json:"destination"`
}
type PullRequest struct {
Name string `json:"name"`
Insecure bool `json:"insecure,omitempty"`
Username string `json:"username"`
Password string `json:"password"`
}
type PullProgress struct {
Status string `json:"status"`
Digest string `json:"digest,omitempty"`
Total int `json:"total,omitempty"`
Completed int `json:"completed,omitempty"`
Percent float64 `json:"percent,omitempty"`
type ProgressResponse struct {
Status string `json:"status"`
Digest string `json:"digest,omitempty"`
Total int `json:"total,omitempty"`
Completed int `json:"completed,omitempty"`
}
type PushRequest struct {
Name string `json:"name"`
Insecure bool `json:"insecure,omitempty"`
Username string `json:"username"`
Password string `json:"password"`
}
type PushProgress struct {
Status string `json:"status"`
Digest string `json:"digest,omitempty"`
Total int `json:"total,omitempty"`
Completed int `json:"completed,omitempty"`
Percent float64 `json:"percent,omitempty"`
type ListResponse struct {
Models []ListResponseModel `json:"models"`
}
type ListResponseModel struct {
Name string `json:"name"`
ModifiedAt time.Time `json:"modified_at"`
Size int `json:"size"`
}
type GenerateResponse struct {
@@ -61,6 +94,9 @@ type GenerateResponse struct {
Context []int `json:"context,omitempty"`
TotalDuration time.Duration `json:"total_duration,omitempty"`
LoadDuration time.Duration `json:"load_duration,omitempty"`
SampleCount int `json:"sample_count,omitempty"`
SampleDuration time.Duration `json:"sample_duration,omitempty"`
PromptEvalCount int `json:"prompt_eval_count,omitempty"`
PromptEvalDuration time.Duration `json:"prompt_eval_duration,omitempty"`
EvalCount int `json:"eval_count,omitempty"`
@@ -72,6 +108,19 @@ func (r *GenerateResponse) Summary() {
fmt.Fprintf(os.Stderr, "total duration: %v\n", r.TotalDuration)
}
if r.LoadDuration > 0 {
fmt.Fprintf(os.Stderr, "load duration: %v\n", r.LoadDuration)
}
if r.SampleCount > 0 {
fmt.Fprintf(os.Stderr, "sample count: %d token(s)\n", r.SampleCount)
}
if r.SampleDuration > 0 {
fmt.Fprintf(os.Stderr, "sample duration: %s\n", r.SampleDuration)
fmt.Fprintf(os.Stderr, "sample rate: %.2f tokens/s\n", float64(r.SampleCount)/r.SampleDuration.Seconds())
}
if r.PromptEvalCount > 0 {
fmt.Fprintf(os.Stderr, "prompt eval count: %d token(s)\n", r.PromptEvalCount)
}
@@ -99,7 +148,9 @@ type Options struct {
// Model options
NumCtx int `json:"num_ctx,omitempty"`
NumKeep int `json:"num_keep,omitempty"`
NumBatch int `json:"num_batch,omitempty"`
NumGQA int `json:"num_gqa,omitempty"`
NumGPU int `json:"num_gpu,omitempty"`
MainGPU int `json:"main_gpu,omitempty"`
LowVRAM bool `json:"low_vram,omitempty"`
@@ -111,22 +162,99 @@ type Options struct {
EmbeddingOnly bool `json:"embedding_only,omitempty"`
// Predict options
RepeatLastN int `json:"repeat_last_n,omitempty"`
RepeatPenalty float32 `json:"repeat_penalty,omitempty"`
FrequencyPenalty float32 `json:"frequency_penalty,omitempty"`
PresencePenalty float32 `json:"presence_penalty,omitempty"`
Temperature float32 `json:"temperature,omitempty"`
TopK int `json:"top_k,omitempty"`
TopP float32 `json:"top_p,omitempty"`
TFSZ float32 `json:"tfs_z,omitempty"`
TypicalP float32 `json:"typical_p,omitempty"`
Mirostat int `json:"mirostat,omitempty"`
MirostatTau float32 `json:"mirostat_tau,omitempty"`
MirostatEta float32 `json:"mirostat_eta,omitempty"`
RepeatLastN int `json:"repeat_last_n,omitempty"`
RepeatPenalty float32 `json:"repeat_penalty,omitempty"`
FrequencyPenalty float32 `json:"frequency_penalty,omitempty"`
PresencePenalty float32 `json:"presence_penalty,omitempty"`
Temperature float32 `json:"temperature,omitempty"`
TopK int `json:"top_k,omitempty"`
TopP float32 `json:"top_p,omitempty"`
TFSZ float32 `json:"tfs_z,omitempty"`
TypicalP float32 `json:"typical_p,omitempty"`
Mirostat int `json:"mirostat,omitempty"`
MirostatTau float32 `json:"mirostat_tau,omitempty"`
MirostatEta float32 `json:"mirostat_eta,omitempty"`
PenalizeNewline bool `json:"penalize_newline,omitempty"`
Stop []string `json:"stop,omitempty"`
NumThread int `json:"num_thread,omitempty"`
}
func (opts *Options) FromMap(m map[string]interface{}) error {
valueOpts := reflect.ValueOf(opts).Elem() // names of the fields in the options struct
typeOpts := reflect.TypeOf(opts).Elem() // types of the fields in the options struct
// build map of json struct tags to their types
jsonOpts := make(map[string]reflect.StructField)
for _, field := range reflect.VisibleFields(typeOpts) {
jsonTag := strings.Split(field.Tag.Get("json"), ",")[0]
if jsonTag != "" {
jsonOpts[jsonTag] = field
}
}
for key, val := range m {
if opt, ok := jsonOpts[key]; ok {
field := valueOpts.FieldByName(opt.Name)
if field.IsValid() && field.CanSet() {
switch field.Kind() {
case reflect.Int:
// when JSON unmarshals numbers, it uses float64 by default, not int
val, ok := val.(float64)
if !ok {
log.Printf("could not convert model parmeter %v to int, skipped", key)
continue
}
field.SetInt(int64(val))
case reflect.Bool:
val, ok := val.(bool)
if !ok {
log.Printf("could not convert model parmeter %v to bool, skipped", key)
continue
}
field.SetBool(val)
case reflect.Float32:
// JSON unmarshals to float64
val, ok := val.(float64)
if !ok {
log.Printf("could not convert model parmeter %v to float32, skipped", key)
continue
}
field.SetFloat(val)
case reflect.String:
val, ok := val.(string)
if !ok {
log.Printf("could not convert model parmeter %v to string, skipped", key)
continue
}
field.SetString(val)
case reflect.Slice:
// JSON unmarshals to []interface{}, not []string
val, ok := val.([]interface{})
if !ok {
log.Printf("could not convert model parmeter %v to slice, skipped", key)
continue
}
// convert []interface{} to []string
slice := make([]string, len(val))
for i, item := range val {
str, ok := item.(string)
if !ok {
log.Printf("could not convert model parmeter %v to slice of strings, skipped", key)
continue
}
slice[i] = str
}
field.Set(reflect.ValueOf(slice))
default:
return fmt.Errorf("unknown type loading config params: %v", field.Kind())
}
}
}
}
return nil
}
func DefaultOptions() Options {
return Options{
Seed: -1,
@@ -136,12 +264,13 @@ func DefaultOptions() Options {
NumCtx: 2048,
NumBatch: 512,
NumGPU: 1,
NumGQA: 1,
LowVRAM: false,
F16KV: true,
UseMMap: true,
UseMLock: false,
RepeatLastN: 512,
RepeatLastN: 64,
RepeatPenalty: 1.1,
FrequencyPenalty: 0.0,
PresencePenalty: 0.0,
@@ -153,7 +282,37 @@ func DefaultOptions() Options {
Mirostat: 0,
MirostatTau: 5.0,
MirostatEta: 0.1,
PenalizeNewline: true,
NumThread: runtime.NumCPU(),
}
}
type Duration struct {
time.Duration
}
func (d *Duration) UnmarshalJSON(b []byte) (err error) {
var v any
if err := json.Unmarshal(b, &v); err != nil {
return err
}
d.Duration = 5 * time.Minute
switch t := v.(type) {
case float64:
if t < 0 {
t = math.MaxFloat64
}
d.Duration = time.Duration(t)
case string:
d.Duration, err = time.ParseDuration(t)
if err != nil {
return err
}
}
return nil
}

View File

@@ -1,7 +1,5 @@
# Desktop
_Note: the Ollama desktop app is a work in progress and is not ready yet for general use._
This app builds upon Ollama to provide a desktop experience for running models.
## Developing
@@ -9,19 +7,15 @@ This app builds upon Ollama to provide a desktop experience for running models.
First, build the `ollama` binary:
```
make -C ..
cd ..
go build .
```
Then run the desktop app with `npm start`:
```
cd app
npm install
npm start
```
## Coming soon
- Browse the latest available models on Hugging Face and other sources
- Keep track of previous conversations with models
- Switch quickly between models
- Connect to remote Ollama servers to run models

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View File

@@ -1,4 +1,4 @@
import type { ForgeConfig, ResolvedForgeConfig, ForgeMakeResult } from '@electron-forge/shared-types'
import type { ForgeConfig } from '@electron-forge/shared-types'
import { MakerSquirrel } from '@electron-forge/maker-squirrel'
import { MakerZIP } from '@electron-forge/maker-zip'
import { PublisherGithub } from '@electron-forge/publisher-github'
@@ -18,9 +18,15 @@ const config: ForgeConfig = {
asar: true,
icon: './assets/icon.icns',
extraResource: [
'../ollama',
path.join(__dirname, './assets/ollama_icon_16x16Template.png'),
path.join(__dirname, './assets/ollama_icon_16x16Template@2x.png'),
'../dist/ollama',
path.join(__dirname, './assets/iconTemplate.png'),
path.join(__dirname, './assets/iconTemplate@2x.png'),
path.join(__dirname, './assets/iconUpdateTemplate.png'),
path.join(__dirname, './assets/iconUpdateTemplate@2x.png'),
path.join(__dirname, './assets/iconDarkTemplate.png'),
path.join(__dirname, './assets/iconDarkTemplate@2x.png'),
path.join(__dirname, './assets/iconDarkUpdateTemplate.png'),
path.join(__dirname, './assets/iconDarkUpdateTemplate@2x.png'),
...(process.platform === 'darwin' ? ['../llama/ggml-metal.metal'] : []),
],
...(process.env.SIGN
@@ -36,6 +42,9 @@ const config: ForgeConfig = {
},
}
: {}),
osxUniversal: {
x64ArchFiles: '**/ollama',
},
},
rebuildConfig: {},
makers: [new MakerSquirrel({}), new MakerZIP({}, ['darwin'])],

7
app/package-lock.json generated
View File

@@ -32,6 +32,7 @@
"@electron-forge/plugin-auto-unpack-natives": "^6.2.1",
"@electron-forge/plugin-webpack": "^6.2.1",
"@electron-forge/publisher-github": "^6.2.1",
"@electron/universal": "^1.4.1",
"@svgr/webpack": "^8.0.1",
"@types/chmodr": "^1.0.0",
"@types/node": "^20.4.0",
@@ -3328,9 +3329,9 @@
}
},
"node_modules/@electron/universal": {
"version": "1.3.4",
"resolved": "https://registry.npmjs.org/@electron/universal/-/universal-1.3.4.tgz",
"integrity": "sha512-BdhBgm2ZBnYyYRLRgOjM5VHkyFItsbggJ0MHycOjKWdFGYwK97ZFXH54dTvUWEfha81vfvwr5On6XBjt99uDcg==",
"version": "1.4.1",
"resolved": "https://registry.npmjs.org/@electron/universal/-/universal-1.4.1.tgz",
"integrity": "sha512-lE/U3UNw1YHuowNbTmKNs9UlS3En3cPgwM5MI+agIgr/B1hSze9NdOP0qn7boZaI9Lph8IDv3/24g9IxnJP7aQ==",
"dev": true,
"dependencies": {
"@electron/asar": "^3.2.1",

View File

@@ -6,12 +6,14 @@
"main": ".webpack/main",
"scripts": {
"start": "electron-forge start",
"package": "electron-forge package",
"package:sign": "SIGN=1 electron-forge package",
"make": "electron-forge make",
"make:sign": "SIGN=1 electron-forge make",
"package": "electron-forge package --arch universal",
"package:sign": "SIGN=1 electron-forge package --arch universal",
"make": "electron-forge make --arch universal",
"make:sign": "SIGN=1 electron-forge make --arch universal",
"publish": "SIGN=1 electron-forge publish",
"lint": "eslint --ext .ts,.tsx ."
"lint": "eslint --ext .ts,.tsx .",
"format": "prettier --check . --ignore-path .gitignore",
"format:fix": "prettier --write . --ignore-path .gitignore"
},
"keywords": [],
"author": {
@@ -30,6 +32,7 @@
"@electron-forge/plugin-auto-unpack-natives": "^6.2.1",
"@electron-forge/plugin-webpack": "^6.2.1",
"@electron-forge/publisher-github": "^6.2.1",
"@electron/universal": "^1.4.1",
"@svgr/webpack": "^8.0.1",
"@types/chmodr": "^1.0.0",
"@types/node": "^20.4.0",

View File

@@ -2,7 +2,7 @@ import { useState } from 'react'
import copy from 'copy-to-clipboard'
import { CheckIcon, DocumentDuplicateIcon } from '@heroicons/react/24/outline'
import Store from 'electron-store'
import { getCurrentWindow } from '@electron/remote'
import { getCurrentWindow, app } from '@electron/remote'
import { install } from './install'
import OllamaIcon from './ollama.svg'
@@ -19,7 +19,7 @@ export default function () {
const [step, setStep] = useState<Step>(Step.WELCOME)
const [commandCopied, setCommandCopied] = useState<boolean>(false)
const command = 'ollama run orca'
const command = 'ollama run llama2'
return (
<div className='drag'>
@@ -51,10 +51,15 @@ export default function () {
<div className='mx-auto'>
<button
onClick={async () => {
await install()
getCurrentWindow().show()
getCurrentWindow().focus()
setStep(Step.FINISH)
try {
await install()
setStep(Step.FINISH)
} catch (e) {
console.error('could not install: ', e)
} finally {
getCurrentWindow().show()
getCurrentWindow().focus()
}
}}
className='no-drag rounded-dm mx-auto w-[60%] rounded-md bg-black px-4 py-2 text-sm text-white hover:brightness-110'
>
@@ -77,7 +82,11 @@ export default function () {
{command}
</pre>
<button
className={`no-drag absolute right-[5px] px-2 py-2 ${commandCopied ? 'text-gray-900 opacity-100 hover:cursor-auto' : 'text-gray-200 opacity-50 hover:cursor-pointer'} hover:text-gray-900 hover:font-bold group-hover:opacity-100`}
className={`no-drag absolute right-[5px] px-2 py-2 ${
commandCopied
? 'text-gray-900 opacity-100 hover:cursor-auto'
: 'text-gray-200 opacity-50 hover:cursor-pointer'
} hover:font-bold hover:text-gray-900 group-hover:opacity-100`}
onClick={() => {
copy(command)
setCommandCopied(true)
@@ -85,13 +94,15 @@ export default function () {
}}
>
{commandCopied ? (
<CheckIcon className='h-4 w-4 text-gray-500 font-bold' />
<CheckIcon className='h-4 w-4 font-bold text-gray-500' />
) : (
<DocumentDuplicateIcon className='h-4 w-4 text-gray-500' />
)}
</button>
</div>
<p className='mx-auto my-4 w-[70%] text-xs text-gray-400'>Run this command in your favorite terminal.</p>
<p className='mx-auto my-4 w-[70%] text-xs text-gray-400'>
Run this command in your favorite terminal.
</p>
</div>
<button
onClick={() => {

View File

@@ -1,4 +1,4 @@
declare module '*.svg' {
const content: string;
export default content;
}
const content: string
export default content
}

View File

@@ -1,5 +1,5 @@
import { spawn } from 'child_process'
import { app, autoUpdater, dialog, Tray, Menu, BrowserWindow } from 'electron'
import { spawn, ChildProcess } from 'child_process'
import { app, autoUpdater, dialog, Tray, Menu, BrowserWindow, MenuItemConstructorOptions, nativeTheme } from 'electron'
import Store from 'electron-store'
import winston from 'winston'
import 'winston-daily-rotate-file'
@@ -10,8 +10,12 @@ import { installed } from './install'
require('@electron/remote/main').initialize()
if (require('electron-squirrel-startup')) {
app.quit()
}
const store = new Store()
let tray: Tray | null = null
let welcomeWindow: BrowserWindow | null = null
declare const MAIN_WINDOW_WEBPACK_ENTRY: string
@@ -28,10 +32,30 @@ const logger = winston.createLogger({
format: winston.format.printf(info => info.message),
})
const SingleInstanceLock = app.requestSingleInstanceLock()
if (!SingleInstanceLock) {
app.quit()
}
app.on('ready', () => {
const gotTheLock = app.requestSingleInstanceLock()
if (!gotTheLock) {
app.exit(0)
return
}
app.on('second-instance', () => {
if (app.hasSingleInstanceLock()) {
app.releaseSingleInstanceLock()
}
if (proc) {
proc.off('exit', restart)
proc.kill()
}
app.exit(0)
})
app.focus({ steal: true })
init()
})
function firstRunWindow() {
// Create the browser window.
@@ -52,44 +76,70 @@ function firstRunWindow() {
require('@electron/remote/main').enable(welcomeWindow.webContents)
// and load the index.html of the app.
welcomeWindow.loadURL(MAIN_WINDOW_WEBPACK_ENTRY)
welcomeWindow.on('ready-to-show', () => welcomeWindow.show())
welcomeWindow.on('closed', () => {
if (process.platform === 'darwin') {
app.dock.hide()
}
})
}
// for debugging
// welcomeWindow.webContents.openDevTools()
let tray: Tray | null = null
let updateAvailable = false
const assetPath = app.isPackaged ? process.resourcesPath : path.join(__dirname, '..', '..', 'assets')
if (process.platform === 'darwin') {
app.dock.hide()
function trayIconPath() {
return nativeTheme.shouldUseDarkColors
? updateAvailable
? path.join(assetPath, 'iconDarkUpdateTemplate.png')
: path.join(assetPath, 'iconDarkTemplate.png')
: updateAvailable
? path.join(assetPath, 'iconUpdateTemplate.png')
: path.join(assetPath, 'iconTemplate.png')
}
function updateTrayIcon() {
if (tray) {
tray.setImage(trayIconPath())
}
}
function createSystemtray() {
let iconPath = path.join(__dirname, '..', '..', 'assets', 'ollama_icon_16x16Template.png')
function updateTray() {
const updateItems: MenuItemConstructorOptions[] = [
{ label: 'An update is available', enabled: false },
{
label: 'Restart to update',
click: () => autoUpdater.quitAndInstall(),
},
{ type: 'separator' },
]
if (app.isPackaged) {
iconPath = path.join(process.resourcesPath, 'ollama_icon_16x16Template.png')
const menu = Menu.buildFromTemplate([
...(updateAvailable ? updateItems : []),
{ role: 'quit', label: 'Quit Ollama', accelerator: 'Command+Q' },
])
if (!tray) {
tray = new Tray(trayIconPath())
}
tray = new Tray(iconPath)
tray.setToolTip(updateAvailable ? 'An update is available' : 'Ollama')
tray.setContextMenu(menu)
tray.setImage(trayIconPath())
const contextMenu = Menu.buildFromTemplate([{ role: 'quit', label: 'Quit Ollama', accelerator: 'Command+Q' }])
tray.setContextMenu(contextMenu)
tray.setToolTip('Ollama')
nativeTheme.off('updated', updateTrayIcon)
nativeTheme.on('updated', updateTrayIcon)
}
if (require('electron-squirrel-startup')) {
app.quit()
}
let proc: ChildProcess = null
function server() {
const binary = app.isPackaged
? path.join(process.resourcesPath, 'ollama')
: path.resolve(process.cwd(), '..', 'ollama')
const proc = spawn(binary, ['serve'])
proc = spawn(binary, ['serve'])
proc.stdout.on('data', data => {
logger.info(data.toString().trim())
@@ -99,24 +149,32 @@ function server() {
logger.error(data.toString().trim())
})
function restart() {
logger.info('Restarting the server...')
server()
}
proc.on('exit', restart)
}
app.on('before-quit', () => {
function restart() {
setTimeout(server, 1000)
}
app.on('before-quit', () => {
if (proc) {
proc.off('exit', restart)
proc.kill()
})
}
}
})
if (process.platform === 'darwin') {
app.dock.hide()
}
function init() {
if (app.isPackaged) {
heartbeat()
autoUpdater.checkForUpdates()
setInterval(() => {
heartbeat()
autoUpdater.checkForUpdates()
}, 60 * 60 * 1000)
}
updateTray()
app.on('ready', () => {
if (process.platform === 'darwin') {
if (app.isPackaged) {
if (!app.isInApplicationsFolder()) {
@@ -152,19 +210,21 @@ app.on('ready', () => {
}
}
createSystemtray()
server()
if (store.get('first-time-run') && installed()) {
if (process.platform === 'darwin') {
app.dock.hide()
}
app.setLoginItemSettings({ openAtLogin: app.getLoginItemSettings().openAtLogin })
return
}
// This is the first run or the CLI is no longer installed
app.setLoginItemSettings({ openAtLogin: true })
firstRunWindow()
})
}
// Quit when all windows are closed, except on macOS. There, it's common
// for applications and their menu bar to stay active until the user quits
@@ -191,29 +251,11 @@ async function heartbeat() {
})
}
if (app.isPackaged) {
heartbeat()
autoUpdater.checkForUpdates()
setInterval(() => {
heartbeat()
autoUpdater.checkForUpdates()
}, 60 * 60 * 1000)
}
autoUpdater.on('error', e => {
logger.error(`update check failed - ${e.message}`)
console.error(`update check failed - ${e.message}`)
})
autoUpdater.on('update-downloaded', (event, releaseNotes, releaseName) => {
dialog
.showMessageBox({
type: 'info',
buttons: ['Restart Now', 'Later'],
title: 'New update available',
message: process.platform === 'win32' ? releaseNotes : releaseName,
detail: 'A new version of Ollama is available. Restart to apply the update.',
})
.then(returnValue => {
if (returnValue.response === 0) autoUpdater.quitAndInstall()
})
autoUpdater.on('update-downloaded', () => {
updateAvailable = true
updateTray()
})

View File

@@ -13,12 +13,9 @@ export function installed() {
}
export async function install() {
const command = `do shell script "ln -F -s ${ollama} ${symlinkPath}" with administrator privileges`
const command = `do shell script "mkdir -p ${path.dirname(
symlinkPath
)} && ln -F -s \\"${ollama}\\" \\"${symlinkPath}\\"" with administrator privileges`
try {
await exec(`osascript -e '${command}'`)
} catch (error) {
console.error(`cli: failed to install cli: ${error.message}`)
return
}
await exec(`osascript -e '${command}'`)
}

View File

@@ -5,38 +5,65 @@ import (
"context"
"errors"
"fmt"
"io"
"log"
"net"
"net/http"
"os"
"os/exec"
"path/filepath"
"runtime"
"strings"
"time"
"github.com/schollz/progressbar/v3"
"github.com/chzyer/readline"
"github.com/dustin/go-humanize"
"github.com/olekukonko/tablewriter"
"github.com/spf13/cobra"
"golang.org/x/term"
"github.com/jmorganca/ollama/api"
"github.com/jmorganca/ollama/format"
"github.com/jmorganca/ollama/progressbar"
"github.com/jmorganca/ollama/server"
)
func cacheDir() string {
home, err := os.UserHomeDir()
func CreateHandler(cmd *cobra.Command, args []string) error {
filename, _ := cmd.Flags().GetString("file")
filename, err := filepath.Abs(filename)
if err != nil {
panic(err)
return err
}
return filepath.Join(home, ".ollama")
}
func create(cmd *cobra.Command, args []string) error {
filename, _ := cmd.Flags().GetString("file")
client := api.NewClient()
var spinner *Spinner
var currentDigest string
var bar *progressbar.ProgressBar
request := api.CreateRequest{Name: args[0], Path: filename}
fn := func(resp api.CreateProgress) error {
fmt.Println(resp.Status)
fn := func(resp api.ProgressResponse) error {
if resp.Digest != currentDigest && resp.Digest != "" {
if spinner != nil {
spinner.Stop()
}
currentDigest = resp.Digest
bar = progressbar.DefaultBytes(
int64(resp.Total),
fmt.Sprintf("pulling %s...", resp.Digest[7:19]),
)
bar.Set(resp.Completed)
} else if resp.Digest == currentDigest && resp.Digest != "" {
bar.Set(resp.Completed)
} else {
currentDigest = ""
if spinner != nil {
spinner.Stop()
}
spinner = NewSpinner(resp.Status)
go spinner.Spin(100 * time.Millisecond)
}
return nil
}
@@ -44,10 +71,14 @@ func create(cmd *cobra.Command, args []string) error {
return err
}
if spinner != nil {
spinner.Stop()
}
return nil
}
func RunRun(cmd *cobra.Command, args []string) error {
func RunHandler(cmd *cobra.Command, args []string) error {
mp := server.ParseModelPath(args[0])
fp, err := mp.GetManifestPath(false)
if err != nil {
@@ -57,7 +88,7 @@ func RunRun(cmd *cobra.Command, args []string) error {
_, err = os.Stat(fp)
switch {
case errors.Is(err, os.ErrNotExist):
if err := pull(args[0]); err != nil {
if err := pull(args[0], false); err != nil {
var apiStatusError api.StatusError
if !errors.As(err, &apiStatusError) {
return err
@@ -74,12 +105,33 @@ func RunRun(cmd *cobra.Command, args []string) error {
return RunGenerate(cmd, args)
}
func push(cmd *cobra.Command, args []string) error {
func PushHandler(cmd *cobra.Command, args []string) error {
client := api.NewClient()
request := api.PushRequest{Name: args[0]}
fn := func(resp api.PushProgress) error {
fmt.Println(resp.Status)
insecure, err := cmd.Flags().GetBool("insecure")
if err != nil {
return err
}
var currentDigest string
var bar *progressbar.ProgressBar
request := api.PushRequest{Name: args[0], Insecure: insecure}
fn := func(resp api.ProgressResponse) error {
if resp.Digest != currentDigest && resp.Digest != "" {
currentDigest = resp.Digest
bar = progressbar.DefaultBytes(
int64(resp.Total),
fmt.Sprintf("pushing %s...", resp.Digest[7:19]),
)
bar.Set(resp.Completed)
} else if resp.Digest == currentDigest && resp.Digest != "" {
bar.Set(resp.Completed)
} else {
currentDigest = ""
fmt.Println(resp.Status)
}
return nil
}
@@ -89,32 +141,87 @@ func push(cmd *cobra.Command, args []string) error {
return nil
}
func RunPull(cmd *cobra.Command, args []string) error {
return pull(args[0])
}
func pull(model string) error {
func ListHandler(cmd *cobra.Command, args []string) error {
client := api.NewClient()
models, err := client.List(context.Background())
if err != nil {
return err
}
var data [][]string
for _, m := range models.Models {
if len(args) == 0 || strings.HasPrefix(m.Name, args[0]) {
data = append(data, []string{m.Name, humanize.Bytes(uint64(m.Size)), format.HumanTime(m.ModifiedAt, "Never")})
}
}
table := tablewriter.NewWriter(os.Stdout)
table.SetHeader([]string{"NAME", "SIZE", "MODIFIED"})
table.SetHeaderAlignment(tablewriter.ALIGN_LEFT)
table.SetAlignment(tablewriter.ALIGN_LEFT)
table.SetHeaderLine(false)
table.SetBorder(false)
table.SetNoWhiteSpace(true)
table.SetTablePadding("\t")
table.AppendBulk(data)
table.Render()
return nil
}
func DeleteHandler(cmd *cobra.Command, args []string) error {
client := api.NewClient()
req := api.DeleteRequest{Name: args[0]}
if err := client.Delete(context.Background(), &req); err != nil {
return err
}
fmt.Printf("deleted '%s'\n", args[0])
return nil
}
func CopyHandler(cmd *cobra.Command, args []string) error {
client := api.NewClient()
req := api.CopyRequest{Source: args[0], Destination: args[1]}
if err := client.Copy(context.Background(), &req); err != nil {
return err
}
fmt.Printf("copied '%s' to '%s'\n", args[0], args[1])
return nil
}
func PullHandler(cmd *cobra.Command, args []string) error {
insecure, err := cmd.Flags().GetBool("insecure")
if err != nil {
return err
}
return pull(args[0], insecure)
}
func pull(model string, insecure bool) error {
client := api.NewClient()
var currentDigest string
var bar *progressbar.ProgressBar
currentLayer := ""
request := api.PullRequest{Name: model}
fn := func(resp api.PullProgress) error {
if resp.Digest != currentLayer && resp.Digest != "" {
if currentLayer != "" {
fmt.Println()
}
currentLayer = resp.Digest
layerStr := resp.Digest[7:23] + "..."
request := api.PullRequest{Name: model, Insecure: insecure}
fn := func(resp api.ProgressResponse) error {
if resp.Digest != currentDigest && resp.Digest != "" {
currentDigest = resp.Digest
bar = progressbar.DefaultBytes(
int64(resp.Total),
"pulling "+layerStr,
fmt.Sprintf("pulling %s...", resp.Digest[7:19]),
)
} else if resp.Digest == currentLayer && resp.Digest != "" {
bar.Set(resp.Completed)
} else if resp.Digest == currentDigest && resp.Digest != "" {
bar.Set(resp.Completed)
} else {
currentLayer = ""
currentDigest = ""
fmt.Println(resp.Status)
}
return nil
@@ -132,60 +239,54 @@ func RunGenerate(cmd *cobra.Command, args []string) error {
return generate(cmd, args[0], strings.Join(args[1:], " "))
}
if term.IsTerminal(int(os.Stdin.Fd())) {
if readline.IsTerminal(int(os.Stdin.Fd())) {
return generateInteractive(cmd, args[0])
}
return generateBatch(cmd, args[0])
}
var generateContextKey struct{}
type generateContextKey string
func generate(cmd *cobra.Command, model, prompt string) error {
if len(strings.TrimSpace(prompt)) > 0 {
client := api.NewClient()
spinner := progressbar.NewOptions(-1,
progressbar.OptionSetWriter(os.Stderr),
progressbar.OptionThrottle(60*time.Millisecond),
progressbar.OptionSpinnerType(14),
progressbar.OptionSetRenderBlankState(true),
progressbar.OptionSetElapsedTime(false),
progressbar.OptionClearOnFinish(),
)
go func() {
for range time.Tick(60 * time.Millisecond) {
if spinner.IsFinished() {
break
}
spinner.Add(1)
}
}()
spinner := NewSpinner("")
go spinner.Spin(60 * time.Millisecond)
var latest api.GenerateResponse
generateContext, ok := cmd.Context().Value(generateContextKey).([]int)
generateContext, ok := cmd.Context().Value(generateContextKey("context")).([]int)
if !ok {
generateContext = []int{}
}
request := api.GenerateRequest{Model: model, Prompt: prompt, Context: generateContext}
fn := func(resp api.GenerateResponse) error {
fn := func(response api.GenerateResponse) error {
if !spinner.IsFinished() {
spinner.Finish()
}
latest = resp
latest = response
fmt.Print(resp.Response)
cmd.SetContext(context.WithValue(cmd.Context(), generateContextKey, resp.Context))
fmt.Print(response.Response)
return nil
}
if err := client.Generate(context.Background(), &request, fn); err != nil {
if strings.Contains(err.Error(), "failed to load model") {
// tell the user to check the server log, if it exists locally
home, nestedErr := os.UserHomeDir()
if nestedErr != nil {
// return the original error
return err
}
logPath := filepath.Join(home, ".ollama", "logs", "server.log")
if _, nestedErr := os.Stat(logPath); nestedErr == nil {
err = fmt.Errorf("%w\nFor more details, check the error logs at %s", err, logPath)
}
}
return err
}
@@ -200,23 +301,203 @@ func generate(cmd *cobra.Command, model, prompt string) error {
if verbose {
latest.Summary()
}
ctx := cmd.Context()
ctx = context.WithValue(ctx, generateContextKey("context"), latest.Context)
cmd.SetContext(ctx)
}
return nil
}
func showLayer(l *server.Layer) {
filename, err := server.GetBlobsPath(l.Digest)
bts, err := os.ReadFile(filename)
if err != nil {
fmt.Printf("Couldn't read layer")
return
}
fmt.Printf(string(bts) + "\n")
}
func generateInteractive(cmd *cobra.Command, model string) error {
fmt.Print(">>> ")
scanner := bufio.NewScanner(os.Stdin)
for scanner.Scan() {
if err := generate(cmd, model, scanner.Text()); err != nil {
home, err := os.UserHomeDir()
if err != nil {
return err
}
completer := readline.NewPrefixCompleter(
readline.PcItem("/help"),
readline.PcItem("/list"),
readline.PcItem("/set",
readline.PcItem("history"),
readline.PcItem("nohistory"),
readline.PcItem("verbose"),
readline.PcItem("quiet"),
readline.PcItem("mode",
readline.PcItem("vim"),
readline.PcItem("emacs"),
readline.PcItem("default"),
),
),
readline.PcItem("/show",
readline.PcItem("license"),
readline.PcItem("system"),
readline.PcItem("template"),
),
readline.PcItem("/exit"),
readline.PcItem("/bye"),
)
usage := func() {
fmt.Fprintln(os.Stderr, "commands:")
fmt.Fprintln(os.Stderr, completer.Tree(" "))
}
config := readline.Config{
Prompt: ">>> ",
HistoryFile: filepath.Join(home, ".ollama", "history"),
AutoComplete: completer,
}
scanner, err := readline.NewEx(&config)
if err != nil {
return err
}
defer scanner.Close()
var multiLineBuffer string
var isMultiLine bool
for {
line, err := scanner.Readline()
switch {
case errors.Is(err, io.EOF):
return nil
case errors.Is(err, readline.ErrInterrupt):
if line == "" {
return nil
}
continue
case err != nil:
return err
}
fmt.Print(">>> ")
}
line = strings.TrimSpace(line)
return nil
switch {
case isMultiLine:
if strings.HasSuffix(line, `"""`) {
isMultiLine = false
multiLineBuffer += strings.TrimSuffix(line, `"""`)
line = multiLineBuffer
multiLineBuffer = ""
scanner.SetPrompt(">>> ")
} else {
multiLineBuffer += line + " "
continue
}
case strings.HasPrefix(line, `"""`):
isMultiLine = true
multiLineBuffer = strings.TrimPrefix(line, `"""`) + " "
scanner.SetPrompt("... ")
continue
case strings.HasPrefix(line, "/list"):
args := strings.Fields(line)
if err := ListHandler(cmd, args[1:]); err != nil {
return err
}
continue
case strings.HasPrefix(line, "/set"):
args := strings.Fields(line)
if len(args) > 1 {
switch args[1] {
case "history":
scanner.HistoryEnable()
continue
case "nohistory":
scanner.HistoryDisable()
continue
case "verbose":
cmd.Flags().Set("verbose", "true")
continue
case "quiet":
cmd.Flags().Set("verbose", "false")
continue
case "mode":
if len(args) > 2 {
switch args[2] {
case "vim":
scanner.SetVimMode(true)
continue
case "emacs", "default":
scanner.SetVimMode(false)
continue
default:
usage()
continue
}
} else {
usage()
continue
}
}
} else {
usage()
continue
}
case strings.HasPrefix(line, "/show"):
args := strings.Fields(line)
if len(args) > 1 {
mp := server.ParseModelPath(model)
manifest, err := server.GetManifest(mp)
if err != nil {
fmt.Printf("error: couldn't get a manifestfor this model")
continue
}
switch args[1] {
case "license":
for _, l := range manifest.Layers {
if l.MediaType == "application/vnd.ollama.image.license" {
showLayer(l)
}
}
continue
case "system":
for _, l := range manifest.Layers {
if l.MediaType == "application/vnd.ollama.image.system" {
showLayer(l)
}
}
continue
case "template":
for _, l := range manifest.Layers {
if l.MediaType == "application/vnd.ollama.image.template" {
showLayer(l)
}
}
continue
default:
usage()
continue
}
} else {
usage()
continue
}
case line == "/help", line == "/?":
usage()
continue
case line == "/exit", line == "/bye":
return nil
}
if err := generate(cmd, model, line); err != nil {
return err
}
}
}
func generateBatch(cmd *cobra.Command, model string) error {
@@ -251,6 +532,54 @@ func RunServer(_ *cobra.Command, _ []string) error {
return server.Serve(ln)
}
func startMacApp(client *api.Client) error {
exe, err := os.Executable()
if err != nil {
return err
}
link, err := os.Readlink(exe)
if err != nil {
return err
}
if !strings.Contains(link, "Ollama.app") {
return fmt.Errorf("could not find ollama app")
}
path := strings.Split(link, "Ollama.app")
if err := exec.Command("/usr/bin/open", "-a", path[0]+"Ollama.app").Run(); err != nil {
return err
}
// wait for the server to start
timeout := time.After(5 * time.Second)
tick := time.Tick(500 * time.Millisecond)
for {
select {
case <-timeout:
return errors.New("timed out waiting for server to start")
case <-tick:
if err := client.Heartbeat(context.Background()); err == nil {
return nil // server has started
}
}
}
}
func checkServerHeartbeat(_ *cobra.Command, _ []string) error {
client := api.NewClient()
if err := client.Heartbeat(context.Background()); err != nil {
if !strings.Contains(err.Error(), "connection refused") {
return err
}
if runtime.GOOS == "darwin" {
if err := startMacApp(client); err != nil {
return fmt.Errorf("could not connect to ollama app, is it running?")
}
} else {
return fmt.Errorf("could not connect to ollama server, run 'ollama serve' to start it")
}
}
return nil
}
func NewCLI() *cobra.Command {
log.SetFlags(log.LstdFlags | log.Lshortfile)
@@ -261,28 +590,26 @@ func NewCLI() *cobra.Command {
CompletionOptions: cobra.CompletionOptions{
DisableDefaultCmd: true,
},
PersistentPreRunE: func(_ *cobra.Command, args []string) error {
// create the models directory and it's parent
return os.MkdirAll(filepath.Join(cacheDir(), "models"), 0o700)
},
}
cobra.EnableCommandSorting = false
createCmd := &cobra.Command{
Use: "create MODEL",
Short: "Create a model from a Modelfile",
Args: cobra.MinimumNArgs(1),
RunE: create,
Use: "create MODEL",
Short: "Create a model from a Modelfile",
Args: cobra.MinimumNArgs(1),
PreRunE: checkServerHeartbeat,
RunE: CreateHandler,
}
createCmd.Flags().StringP("file", "f", "Modelfile", "Name of the Modelfile (default \"Modelfile\")")
runCmd := &cobra.Command{
Use: "run MODEL [PROMPT]",
Short: "Run a model",
Args: cobra.MinimumNArgs(1),
RunE: RunRun,
Use: "run MODEL [PROMPT]",
Short: "Run a model",
Args: cobra.MinimumNArgs(1),
PreRunE: checkServerHeartbeat,
RunE: RunHandler,
}
runCmd.Flags().Bool("verbose", false, "Show timings for response")
@@ -295,17 +622,47 @@ func NewCLI() *cobra.Command {
}
pullCmd := &cobra.Command{
Use: "pull MODEL",
Short: "Pull a model from a registry",
Args: cobra.MinimumNArgs(1),
RunE: RunPull,
Use: "pull MODEL",
Short: "Pull a model from a registry",
Args: cobra.MinimumNArgs(1),
PreRunE: checkServerHeartbeat,
RunE: PullHandler,
}
pullCmd.Flags().Bool("insecure", false, "Use an insecure registry")
pushCmd := &cobra.Command{
Use: "push MODEL",
Short: "Push a model to a registry",
Args: cobra.MinimumNArgs(1),
RunE: push,
Use: "push MODEL",
Short: "Push a model to a registry",
Args: cobra.MinimumNArgs(1),
PreRunE: checkServerHeartbeat,
RunE: PushHandler,
}
pushCmd.Flags().Bool("insecure", false, "Use an insecure registry")
listCmd := &cobra.Command{
Use: "list",
Aliases: []string{"ls"},
Short: "List models",
PreRunE: checkServerHeartbeat,
RunE: ListHandler,
}
copyCmd := &cobra.Command{
Use: "cp",
Short: "Copy a model",
Args: cobra.MinimumNArgs(2),
PreRunE: checkServerHeartbeat,
RunE: CopyHandler,
}
deleteCmd := &cobra.Command{
Use: "rm",
Short: "Remove a model",
Args: cobra.MinimumNArgs(1),
PreRunE: checkServerHeartbeat,
RunE: DeleteHandler,
}
rootCmd.AddCommand(
@@ -314,6 +671,9 @@ func NewCLI() *cobra.Command {
runCmd,
pullCmd,
pushCmd,
listCmd,
copyCmd,
deleteCmd,
)
return rootCmd

44
cmd/spinner.go Normal file
View File

@@ -0,0 +1,44 @@
package cmd
import (
"fmt"
"os"
"time"
"github.com/jmorganca/ollama/progressbar"
)
type Spinner struct {
description string
*progressbar.ProgressBar
}
func NewSpinner(description string) *Spinner {
return &Spinner{
description: description,
ProgressBar: progressbar.NewOptions(-1,
progressbar.OptionSetWriter(os.Stderr),
progressbar.OptionThrottle(60*time.Millisecond),
progressbar.OptionSpinnerType(14),
progressbar.OptionSetRenderBlankState(true),
progressbar.OptionSetElapsedTime(false),
progressbar.OptionClearOnFinish(),
progressbar.OptionSetDescription(description),
),
}
}
func (s *Spinner) Spin(tick time.Duration) {
for range time.Tick(tick) {
if s.IsFinished() {
break
}
s.Add(1)
}
}
func (s *Spinner) Stop() {
s.Finish()
fmt.Println(s.description)
}

View File

@@ -3,13 +3,21 @@
Install required tools:
```
brew install cmake go node
brew install go
```
Then run `make`:
Enable CGO:
```
make
export CGO_ENABLED=1
```
You will also need a C/C++ compiler such as GCC for MacOS and Linux or Mingw-w64 GCC for Windows.
Then build ollama:
```
go build .
```
Now you can run `ollama`:

166
docs/modelfile.md Normal file
View File

@@ -0,0 +1,166 @@
# Ollama Model File
> Note: this model file syntax is in development
A model file is the blueprint to create and share models with Ollama.
## Table of Contents
- [Format](#format)
- [Examples](#examples)
- [Instructions](#instructions)
- [FROM (Required)](#from-required)
- [Build from llama2](#build-from-llama2)
- [Build from a bin file](#build-from-a-bin-file)
- [PARAMETER](#parameter)
- [Valid Parameters and Values](#valid-parameters-and-values)
- [TEMPLATE](#template)
- [Template Variables](#template-variables)
- [SYSTEM](#system)
- [LICENSE](#license)
- [Notes](#notes)
## Format
The format of the Modelfile:
```modelfile
# comment
INSTRUCTION arguments
```
| Instruction | Description |
| ----------------------------------- | ------------------------------------------------------------- |
| [`FROM`](#from-required) (required) | Defines the base model to use. |
| [`PARAMETER`](#parameter) | Sets the parameters for how Ollama will run the model. |
| [`TEMPLATE`](#template) | The full prompt template to be sent to the model. |
| [`SYSTEM`](#system) | Specifies the system prompt that will be set in the template. |
| [`LICENSE`](#license) | Specifies the legal license. |
## Examples
An example of a model file creating a mario blueprint:
```
FROM llama2
# sets the temperature to 1 [higher is more creative, lower is more coherent]
PARAMETER temperature 1
# sets the context window size to 4096, this controls how many tokens the LLM can use as context to generate the next token
PARAMETER num_ctx 4096
# sets a custom system prompt to specify the behavior of the chat assistant
SYSTEM You are Mario from super mario bros, acting as an assistant.
```
To use this:
1. Save it as a file (eg. `Modelfile`)
2. `ollama create NAME -f <location of the file eg. ./Modelfile>'`
3. `ollama run NAME`
4. Start using the model!
More examples are available in the [examples directory](../examples).
## Instructions
### FROM (Required)
The FROM instruction defines the base model to use when creating a model.
```
FROM <model name>:<tag>
```
#### Build from llama2
```
FROM llama2
```
A list of available base models:
<https://github.com/jmorganca/ollama#model-library>
#### Build from a bin file
```
FROM ./ollama-model.bin
```
This bin file location should be specified as an absolute path or relative to the Modelfile location.
### PARAMETER
The `PARAMETER` instruction defines a parameter that can be set when the model is run.
```
PARAMETER <parameter> <parametervalue>
```
### Valid Parameters and Values
| Parameter | Description | Value Type | Example Usage |
| -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------- | -------------------- |
| mirostat | Enable Mirostat sampling for controlling perplexity. (default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0) | int | mirostat 0 |
| mirostat_eta | Influences how quickly the algorithm responds to feedback from the generated text. A lower learning rate will result in slower adjustments, while a higher learning rate will make the algorithm more responsive. (Default: 0.1) | float | mirostat_eta 0.1 |
| mirostat_tau | Controls the balance between coherence and diversity of the output. A lower value will result in more focused and coherent text. (Default: 5.0) | float | mirostat_tau 5.0 |
| num_ctx | Sets the size of the context window used to generate the next token. (Default: 2048) | int | num_ctx 4096 |
| num_gpu | The number of GPUs to use. On macOS it defaults to 1 to enable metal support, 0 to disable. | int | num_gpu 1 |
| num_thread | Sets the number of threads to use during computation. By default, Ollama will detect this for optimal performance. It is recommended to set this value to the number of physical CPU cores your system has (as opposed to the logical number of cores). | int | num_thread 8 |
| repeat_last_n | Sets how far back for the model to look back to prevent repetition. (Default: 64, 0 = disabled, -1 = num_ctx) | int | repeat_last_n 64 |
| repeat_penalty | Sets how strongly to penalize repetitions. A higher value (e.g., 1.5) will penalize repetitions more strongly, while a lower value (e.g., 0.9) will be more lenient. (Default: 1.1) | float | repeat_penalty 1.1 |
| temperature | The temperature of the model. Increasing the temperature will make the model answer more creatively. (Default: 0.8) | float | temperature 0.7 |
| stop | Sets the stop tokens to use. | string | stop "AI assistant:" |
| tfs_z | Tail free sampling is used to reduce the impact of less probable tokens from the output. A higher value (e.g., 2.0) will reduce the impact more, while a value of 1.0 disables this setting. (default: 1) | float | tfs_z 1 |
| top_k | Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative. (Default: 40) | int | top_k 40 |
| top_p | Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text. (Default: 0.9) | float | top_p 0.9 |
### TEMPLATE
`TEMPLATE` of the full prompt template to be passed into the model. It may include (optionally) a system prompt and a user's prompt. This is used to create a full custom prompt, and syntax may be model specific.
#### Template Variables
| Variable | Description |
| --------------- | ------------------------------------------------------------------------------------------------------------ |
| `{{ .System }}` | The system prompt used to specify custom behavior, this must also be set in the Modelfile as an instruction. |
| `{{ .Prompt }}` | The incoming prompt, this is not specified in the model file and will be set based on input. |
| `{{ .First }}` | A boolean value used to render specific template information for the first generation of a session. |
```
TEMPLATE """
{{- if .First }}
### System:
{{ .System }}
{{- end }}
### User:
{{ .Prompt }}
### Response:
"""
SYSTEM """<system message>"""
```
### SYSTEM
The `SYSTEM` instruction specifies the system prompt to be used in the template, if applicable.
```
SYSTEM """<system message>"""
```
### LICENSE
The `LICENSE` instruction allows you to specify the legal license under which the model used with this Modelfile is shared or distributed.
```
LICENSE """
<license text>
"""
```
## Notes
- the **modelfile is not case sensitive**. In the examples, we use uppercase for instructions to make it easier to distinguish it from arguments.
- Instructions can be in any order. In the examples, we start with FROM instruction to keep it easily readable.

15
examples/README.md Normal file
View File

@@ -0,0 +1,15 @@
# Examples
This directory contains examples that can be created and run with `ollama`.
To create a model:
```
ollama create example -f <example file>
```
To run a model:
```
ollama run example
```

View File

@@ -0,0 +1,8 @@
# Modelfile for creating a devops engineer assistant
# Run `ollama create devops-engineer -f ./Modelfile` and then `ollama run devops-engineer` and enter a topic
FROM llama2:13b
PARAMETER temperature 1
SYSTEM """
You are a senior devops engineer, acting as an assistant. You offer help with cloud technologies like: Terraform, AWS, kubernetes, python. You answer with code examples when possible
"""

5
examples/mario/Modelfile Normal file
View File

@@ -0,0 +1,5 @@
FROM llama2
PARAMETER temperature 1
SYSTEM """
You are Mario from super mario bros, acting as an assistant.
"""

BIN
examples/mario/logo.png Normal file

Binary file not shown.

After

Width:  |  Height:  |  Size: 446 KiB

43
examples/mario/readme.md Normal file
View File

@@ -0,0 +1,43 @@
<img src="logo.png" alt="image of Italian plumber" height="200"/>
# Example character: Mario
This example shows how to create a basic character using Llama2 as the base model.
To run this example:
1. Download the Modelfile
2. `ollama pull llama2` to get the base model used in the model file.
3. `ollama create NAME -f ./Modelfile`
4. `ollama run NAME`
Ask it some questions like "Who are you?" or "Is Peach in trouble again?"
## Editing this file
What the model file looks like:
```
FROM llama2
PARAMETER temperature 1
SYSTEM """
You are Mario from Super Mario Bros, acting as an assistant.
"""
```
What if you want to change its behaviour?
- Try changing the prompt
- Try changing the parameters [Docs](https://github.com/jmorganca/ollama/blob/main/docs/modelfile.md)
- Try changing the model (e.g. An uncensored model by `FROM wizard-vicuna` this is the wizard-vicuna uncensored model )
Once the changes are made,
1. `ollama create NAME -f ./Modelfile`
2. `ollama run NAME`
3. Iterate until you are happy with the results.
Notes:
- This example is for research purposes only. There is no affiliation with any entity.
- When using an uncensored model, please be aware that it may generate offensive content.

View File

@@ -0,0 +1,8 @@
# Modelfile for creating a Midjourney prompts from a topic
# This prompt was adapted from the original at https://www.greataiprompts.com/guide/midjourney/best-chatgpt-prompt-for-midjourney/
# Run `ollama create mj -f ./Modelfile` and then `ollama run mj` and enter a topic
FROM nous-hermes
SYSTEM """
Embrace your role as an AI-powered creative assistant, employing Midjourney to manifest compelling AI-generated art. I will outline a specific image concept, and in response, you must produce an exhaustive, multifaceted prompt for Midjourney, ensuring every detail of the original concept is represented in your instructions. Midjourney doesn't do well with text, so after the prompt, give me instructions that I can use to create the titles in a image editor.
"""

View File

@@ -1,15 +0,0 @@
# Python
This is a simple example of calling the Ollama api from a python app.
First, download a model:
```
curl -L https://huggingface.co/TheBloke/orca_mini_3B-GGML/resolve/main/orca-mini-3b.ggmlv3.q4_1.bin -o orca.bin
```
Then run it using the example script. You'll need to have Ollama running on your machine.
```
python3 main.py orca.bin
```

View File

@@ -1,32 +0,0 @@
import http.client
import json
import os
import sys
if len(sys.argv) < 2:
print("Usage: python main.py <model file>")
sys.exit(1)
conn = http.client.HTTPConnection('localhost', 11434)
headers = { 'Content-Type': 'application/json' }
# generate text from the model
conn.request("POST", "/api/generate", json.dumps({
'model': os.path.join(os.getcwd(), sys.argv[1]),
'prompt': 'write me a short story',
'stream': True
}), headers)
response = conn.getresponse()
def parse_generate(data):
for event in data.decode('utf-8').split("\n"):
if not event:
continue
yield event
if response.status == 200:
for chunk in response:
for event in parse_generate(chunk):
print(json.loads(event)['response'], end="", flush=True)

View File

@@ -0,0 +1,6 @@
# Modelfile for creating a recipe from a list of ingredients
# Run `ollama create recipemaker -f ./Modelfile` and then `ollama run recipemaker` and feed it lists of ingredients to create recipes around.
FROM nous-hermes
SYSTEM """
The instruction will be a list of ingredients. You should generate a recipe that can be made in less than an hour. You can also include ingredients that most people will find in their pantry every day. The recipe should be 4 people and you should include a description of what the meal will taste like
"""

View File

@@ -0,0 +1,7 @@
# Modelfile for creating a tweet from a topic
# Run `ollama create tweetwriter -f ./Modelfile` and then `ollama run tweetwriter` and enter a topic
FROM nous-hermes
SYSTEM """
You are a content marketer who needs to come up with a short but succinct tweet. Make sure to include the appropriate hashtags and links. Sometimes when appropriate, describe a meme that can be includes as well. All answers should be in the form of a tweet which has a max size of 280 characters. Every instruction will be the topic to create a tweet about.
"""

141
format/time.go Normal file
View File

@@ -0,0 +1,141 @@
package format
import (
"fmt"
"math"
"strings"
"time"
)
// HumanDuration returns a human-readable approximation of a duration
// (eg. "About a minute", "4 hours ago", etc.).
// Modified version of github.com/docker/go-units.HumanDuration
func HumanDuration(d time.Duration) string {
return HumanDurationWithCase(d, true)
}
// HumanDurationWithCase returns a human-readable approximation of a
// duration (eg. "About a minute", "4 hours ago", etc.). but allows
// you to specify whether the first word should be capitalized
// (eg. "About" vs. "about")
func HumanDurationWithCase(d time.Duration, useCaps bool) string {
seconds := int(d.Seconds())
switch {
case seconds < 1:
if useCaps {
return "Less than a second"
}
return "less than a second"
case seconds == 1:
return "1 second"
case seconds < 60:
return fmt.Sprintf("%d seconds", seconds)
}
minutes := int(d.Minutes())
switch {
case minutes == 1:
if useCaps {
return "About a minute"
}
return "about a minute"
case minutes < 60:
return fmt.Sprintf("%d minutes", minutes)
}
hours := int(math.Round(d.Hours()))
switch {
case hours == 1:
if useCaps {
return "About an hour"
}
return "about an hour"
case hours < 48:
return fmt.Sprintf("%d hours", hours)
case hours < 24*7*2:
return fmt.Sprintf("%d days", hours/24)
case hours < 24*30*2:
return fmt.Sprintf("%d weeks", hours/24/7)
case hours < 24*365*2:
return fmt.Sprintf("%d months", hours/24/30)
}
return fmt.Sprintf("%d years", int(d.Hours())/24/365)
}
func HumanTime(t time.Time, zeroValue string) string {
return humanTimeWithCase(t, zeroValue, true)
}
func HumanTimeLower(t time.Time, zeroValue string) string {
return humanTimeWithCase(t, zeroValue, false)
}
func humanTimeWithCase(t time.Time, zeroValue string, useCaps bool) string {
if t.IsZero() {
return zeroValue
}
delta := time.Since(t)
if delta < 0 {
return HumanDurationWithCase(-delta, useCaps) + " from now"
}
return HumanDurationWithCase(delta, useCaps) + " ago"
}
// ExcatDuration returns a human readable hours/minutes/seconds or milliseconds format of a duration
// the most precise level of duration is milliseconds
func ExactDuration(d time.Duration) string {
if d.Seconds() < 1 {
if d.Milliseconds() == 1 {
return fmt.Sprintf("%d millisecond", d.Milliseconds())
}
return fmt.Sprintf("%d milliseconds", d.Milliseconds())
}
var readableDur strings.Builder
dur := d.String()
// split the default duration string format of 0h0m0s into something nicer to read
h := strings.Split(dur, "h")
if len(h) > 1 {
hours := h[0]
if hours == "1" {
readableDur.WriteString(fmt.Sprintf("%s hour ", hours))
} else {
readableDur.WriteString(fmt.Sprintf("%s hours ", hours))
}
dur = h[1]
}
m := strings.Split(dur, "m")
if len(m) > 1 {
mins := m[0]
switch mins {
case "0":
// skip
case "1":
readableDur.WriteString(fmt.Sprintf("%s minute ", mins))
default:
readableDur.WriteString(fmt.Sprintf("%s minutes ", mins))
}
dur = m[1]
}
s := strings.Split(dur, "s")
if len(s) > 0 {
sec := s[0]
switch sec {
case "0":
// skip
case "1":
readableDur.WriteString(fmt.Sprintf("%s second ", sec))
default:
readableDur.WriteString(fmt.Sprintf("%s seconds ", sec))
}
}
return strings.TrimSpace(readableDur.String())
}

102
format/time_test.go Normal file
View File

@@ -0,0 +1,102 @@
package format
import (
"testing"
"time"
)
func assertEqual(t *testing.T, a interface{}, b interface{}) {
if a != b {
t.Errorf("Assert failed, expected %v, got %v", b, a)
}
}
func TestHumanDuration(t *testing.T) {
day := 24 * time.Hour
week := 7 * day
month := 30 * day
year := 365 * day
assertEqual(t, "Less than a second", HumanDuration(450*time.Millisecond))
assertEqual(t, "Less than a second", HumanDurationWithCase(450*time.Millisecond, true))
assertEqual(t, "less than a second", HumanDurationWithCase(450*time.Millisecond, false))
assertEqual(t, "1 second", HumanDuration(1*time.Second))
assertEqual(t, "45 seconds", HumanDuration(45*time.Second))
assertEqual(t, "46 seconds", HumanDuration(46*time.Second))
assertEqual(t, "59 seconds", HumanDuration(59*time.Second))
assertEqual(t, "About a minute", HumanDuration(60*time.Second))
assertEqual(t, "About a minute", HumanDurationWithCase(1*time.Minute, true))
assertEqual(t, "about a minute", HumanDurationWithCase(1*time.Minute, false))
assertEqual(t, "3 minutes", HumanDuration(3*time.Minute))
assertEqual(t, "35 minutes", HumanDuration(35*time.Minute))
assertEqual(t, "35 minutes", HumanDuration(35*time.Minute+40*time.Second))
assertEqual(t, "45 minutes", HumanDuration(45*time.Minute))
assertEqual(t, "45 minutes", HumanDuration(45*time.Minute+40*time.Second))
assertEqual(t, "46 minutes", HumanDuration(46*time.Minute))
assertEqual(t, "59 minutes", HumanDuration(59*time.Minute))
assertEqual(t, "About an hour", HumanDuration(1*time.Hour))
assertEqual(t, "About an hour", HumanDurationWithCase(1*time.Hour+29*time.Minute, true))
assertEqual(t, "about an hour", HumanDurationWithCase(1*time.Hour+29*time.Minute, false))
assertEqual(t, "2 hours", HumanDuration(1*time.Hour+31*time.Minute))
assertEqual(t, "2 hours", HumanDuration(1*time.Hour+59*time.Minute))
assertEqual(t, "3 hours", HumanDuration(3*time.Hour))
assertEqual(t, "3 hours", HumanDuration(3*time.Hour+29*time.Minute))
assertEqual(t, "4 hours", HumanDuration(3*time.Hour+31*time.Minute))
assertEqual(t, "4 hours", HumanDuration(3*time.Hour+59*time.Minute))
assertEqual(t, "4 hours", HumanDuration(3*time.Hour+60*time.Minute))
assertEqual(t, "24 hours", HumanDuration(24*time.Hour))
assertEqual(t, "36 hours", HumanDuration(1*day+12*time.Hour))
assertEqual(t, "2 days", HumanDuration(2*day))
assertEqual(t, "7 days", HumanDuration(7*day))
assertEqual(t, "13 days", HumanDuration(13*day+5*time.Hour))
assertEqual(t, "2 weeks", HumanDuration(2*week))
assertEqual(t, "2 weeks", HumanDuration(2*week+4*day))
assertEqual(t, "3 weeks", HumanDuration(3*week))
assertEqual(t, "4 weeks", HumanDuration(4*week))
assertEqual(t, "4 weeks", HumanDuration(4*week+3*day))
assertEqual(t, "4 weeks", HumanDuration(1*month))
assertEqual(t, "6 weeks", HumanDuration(1*month+2*week))
assertEqual(t, "2 months", HumanDuration(2*month))
assertEqual(t, "2 months", HumanDuration(2*month+2*week))
assertEqual(t, "3 months", HumanDuration(3*month))
assertEqual(t, "3 months", HumanDuration(3*month+1*week))
assertEqual(t, "5 months", HumanDuration(5*month+2*week))
assertEqual(t, "13 months", HumanDuration(13*month))
assertEqual(t, "23 months", HumanDuration(23*month))
assertEqual(t, "24 months", HumanDuration(24*month))
assertEqual(t, "2 years", HumanDuration(24*month+2*week))
assertEqual(t, "3 years", HumanDuration(3*year+2*month))
}
func TestHumanTime(t *testing.T) {
now := time.Now()
t.Run("zero value", func(t *testing.T) {
assertEqual(t, HumanTime(time.Time{}, "never"), "never")
})
t.Run("time in the future", func(t *testing.T) {
v := now.Add(48 * time.Hour)
assertEqual(t, HumanTime(v, ""), "2 days from now")
})
t.Run("time in the past", func(t *testing.T) {
v := now.Add(-48 * time.Hour)
assertEqual(t, HumanTime(v, ""), "2 days ago")
})
}
func TestExactDuration(t *testing.T) {
assertEqual(t, "1 millisecond", ExactDuration(1*time.Millisecond))
assertEqual(t, "10 milliseconds", ExactDuration(10*time.Millisecond))
assertEqual(t, "1 second", ExactDuration(1*time.Second))
assertEqual(t, "10 seconds", ExactDuration(10*time.Second))
assertEqual(t, "1 minute", ExactDuration(1*time.Minute))
assertEqual(t, "10 minutes", ExactDuration(10*time.Minute))
assertEqual(t, "1 hour", ExactDuration(1*time.Hour))
assertEqual(t, "10 hours", ExactDuration(10*time.Hour))
assertEqual(t, "1 hour 1 second", ExactDuration(1*time.Hour+1*time.Second))
assertEqual(t, "1 hour 10 seconds", ExactDuration(1*time.Hour+10*time.Second))
assertEqual(t, "1 hour 1 minute", ExactDuration(1*time.Hour+1*time.Minute))
assertEqual(t, "1 hour 10 minutes", ExactDuration(1*time.Hour+10*time.Minute))
assertEqual(t, "1 hour 1 minute 1 second", ExactDuration(1*time.Hour+1*time.Minute+1*time.Second))
assertEqual(t, "10 hours 10 minutes 10 seconds", ExactDuration(10*time.Hour+10*time.Minute+10*time.Second))
}

View File

@@ -1 +0,0 @@
llama/ggml-metal.metal

14
go.mod
View File

@@ -3,21 +3,22 @@ module github.com/jmorganca/ollama
go 1.20
require (
github.com/dustin/go-humanize v1.0.1
github.com/gin-gonic/gin v1.9.1
github.com/mattn/go-runewidth v0.0.14
github.com/mitchellh/colorstring v0.0.0-20190213212951-d06e56a500db
github.com/olekukonko/tablewriter v0.0.5
github.com/spf13/cobra v1.7.0
)
require (
github.com/mattn/go-runewidth v0.0.14 // indirect
github.com/mitchellh/colorstring v0.0.0-20190213212951-d06e56a500db // indirect
github.com/rivo/uniseg v0.2.0 // indirect
)
require github.com/rivo/uniseg v0.2.0 // indirect
require (
dario.cat/mergo v1.0.0
github.com/bytedance/sonic v1.9.1 // indirect
github.com/chenzhuoyu/base64x v0.0.0-20221115062448-fe3a3abad311 // indirect
github.com/chzyer/readline v1.5.1
github.com/gabriel-vasile/mimetype v1.4.2 // indirect
github.com/gin-contrib/cors v1.4.0
github.com/gin-contrib/sse v0.1.0 // indirect
github.com/go-playground/locales v0.14.1 // indirect
github.com/go-playground/universal-translator v0.18.1 // indirect
@@ -32,7 +33,6 @@ require (
github.com/modern-go/concurrent v0.0.0-20180306012644-bacd9c7ef1dd // indirect
github.com/modern-go/reflect2 v1.0.2 // indirect
github.com/pelletier/go-toml/v2 v2.0.8 // indirect
github.com/schollz/progressbar/v3 v3.13.1
github.com/spf13/pflag v1.0.5 // indirect
github.com/twitchyliquid64/golang-asm v0.15.1 // indirect
github.com/ugorji/go/codec v1.2.11 // indirect

65
go.sum
View File

@@ -1,28 +1,43 @@
dario.cat/mergo v1.0.0 h1:AGCNq9Evsj31mOgNPcLyXc+4PNABt905YmuqPYYpBWk=
dario.cat/mergo v1.0.0/go.mod h1:uNxQE+84aUszobStD9th8a29P2fMDhsBdgRYvZOxGmk=
github.com/bytedance/sonic v1.5.0/go.mod h1:ED5hyg4y6t3/9Ku1R6dU/4KyJ48DZ4jPhfY1O2AihPM=
github.com/bytedance/sonic v1.9.1 h1:6iJ6NqdoxCDr6mbY8h18oSO+cShGSMRGCEo7F2h0x8s=
github.com/bytedance/sonic v1.9.1/go.mod h1:i736AoUSYt75HyZLoJW9ERYxcy6eaN6h4BZXU064P/U=
github.com/chenzhuoyu/base64x v0.0.0-20211019084208-fb5309c8db06/go.mod h1:DH46F32mSOjUmXrMHnKwZdA8wcEefY7UVqBKYGjpdQY=
github.com/chenzhuoyu/base64x v0.0.0-20221115062448-fe3a3abad311 h1:qSGYFH7+jGhDF8vLC+iwCD4WpbV1EBDSzWkJODFLams=
github.com/chenzhuoyu/base64x v0.0.0-20221115062448-fe3a3abad311/go.mod h1:b583jCggY9gE99b6G5LEC39OIiVsWj+R97kbl5odCEk=
github.com/chzyer/logex v1.2.1 h1:XHDu3E6q+gdHgsdTPH6ImJMIp436vR6MPtH8gP05QzM=
github.com/chzyer/logex v1.2.1/go.mod h1:JLbx6lG2kDbNRFnfkgvh4eRJRPX1QCoOIWomwysCBrQ=
github.com/chzyer/readline v1.5.1 h1:upd/6fQk4src78LMRzh5vItIt361/o4uq553V8B5sGI=
github.com/chzyer/readline v1.5.1/go.mod h1:Eh+b79XXUwfKfcPLepksvw2tcLE/Ct21YObkaSkeBlk=
github.com/chzyer/test v1.0.0 h1:p3BQDXSxOhOG0P9z6/hGnII4LGiEPOYBhs8asl/fC04=
github.com/chzyer/test v1.0.0/go.mod h1:2JlltgoNkt4TW/z9V/IzDdFaMTM2JPIi26O1pF38GC8=
github.com/cpuguy83/go-md2man/v2 v2.0.2/go.mod h1:tgQtvFlXSQOSOSIRvRPT7W67SCa46tRHOmNcaadrF8o=
github.com/creack/pty v1.1.9/go.mod h1:oKZEueFk5CKHvIhNR5MUki03XCEU+Q6VDXinZuGJ33E=
github.com/davecgh/go-spew v1.1.0/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
github.com/davecgh/go-spew v1.1.1 h1:vj9j/u1bqnvCEfJOwUhtlOARqs3+rkHYY13jYWTU97c=
github.com/davecgh/go-spew v1.1.1/go.mod h1:J7Y8YcW2NihsgmVo/mv3lAwl/skON4iLHjSsI+c5H38=
github.com/dustin/go-humanize v1.0.1 h1:GzkhY7T5VNhEkwH0PVJgjz+fX1rhBrR7pRT3mDkpeCY=
github.com/dustin/go-humanize v1.0.1/go.mod h1:Mu1zIs6XwVuF/gI1OepvI0qD18qycQx+mFykh5fBlto=
github.com/gabriel-vasile/mimetype v1.4.2 h1:w5qFW6JKBz9Y393Y4q372O9A7cUSequkh1Q7OhCmWKU=
github.com/gabriel-vasile/mimetype v1.4.2/go.mod h1:zApsH/mKG4w07erKIaJPFiX0Tsq9BFQgN3qGY5GnNgA=
github.com/gin-contrib/cors v1.4.0 h1:oJ6gwtUl3lqV0WEIwM/LxPF1QZ5qe2lGWdY2+bz7y0g=
github.com/gin-contrib/cors v1.4.0/go.mod h1:bs9pNM0x/UsmHPBWT2xZz9ROh8xYjYkiURUfmBoMlcs=
github.com/gin-contrib/sse v0.1.0 h1:Y/yl/+YNO8GZSjAhjMsSuLt29uWRFHdHYUb5lYOV9qE=
github.com/gin-contrib/sse v0.1.0/go.mod h1:RHrZQHXnP2xjPF+u1gW/2HnVO7nvIa9PG3Gm+fLHvGI=
github.com/gin-gonic/gin v1.8.1/go.mod h1:ji8BvRH1azfM+SYow9zQ6SZMvR8qOMZHmsCuWR9tTTk=
github.com/gin-gonic/gin v1.9.1 h1:4idEAncQnU5cB7BeOkPtxjfCSye0AAm1R0RVIqJ+Jmg=
github.com/gin-gonic/gin v1.9.1/go.mod h1:hPrL7YrpYKXt5YId3A/Tnip5kqbEAP+KLuI3SUcPTeU=
github.com/go-playground/assert/v2 v2.0.1/go.mod h1:VDjEfimB/XKnb+ZQfWdccd7VUvScMdVu0Titje2rxJ4=
github.com/go-playground/assert/v2 v2.2.0 h1:JvknZsQTYeFEAhQwI4qEt9cyV5ONwRHC+lYKSsYSR8s=
github.com/go-playground/locales v0.14.0/go.mod h1:sawfccIbzZTqEDETgFXqTho0QybSa7l++s0DH+LDiLs=
github.com/go-playground/locales v0.14.1 h1:EWaQ/wswjilfKLTECiXz7Rh+3BjFhfDFKv/oXslEjJA=
github.com/go-playground/locales v0.14.1/go.mod h1:hxrqLVvrK65+Rwrd5Fc6F2O76J/NuW9t0sjnWqG1slY=
github.com/go-playground/universal-translator v0.18.0/go.mod h1:UvRDBj+xPUEGrFYl+lu/H90nyDXpg0fqeB/AQUGNTVA=
github.com/go-playground/universal-translator v0.18.1 h1:Bcnm0ZwsGyWbCzImXv+pAJnYK9S473LQFuzCbDbfSFY=
github.com/go-playground/universal-translator v0.18.1/go.mod h1:xekY+UJKNuX9WP91TpwSH2VMlDf28Uj24BCp08ZFTUY=
github.com/go-playground/validator/v10 v10.10.0/go.mod h1:74x4gJWsvQexRdW8Pn3dXSGrTK4nAUsbPlLADvpJkos=
github.com/go-playground/validator/v10 v10.14.0 h1:vgvQWe3XCz3gIeFDm/HnTIbj6UGmg/+t63MyGU2n5js=
github.com/go-playground/validator/v10 v10.14.0/go.mod h1:9iXMNT7sEkjXb0I+enO7QXmzG6QCsPWY4zveKFVRSyU=
github.com/goccy/go-json v0.9.7/go.mod h1:6MelG93GURQebXPDq3khkgXZkazVtN9CRI+MGFi0w8I=
github.com/goccy/go-json v0.10.2 h1:CrxCmQqYDkv1z7lO7Wbh2HN93uovUHgrECaO5ZrCXAU=
github.com/goccy/go-json v0.10.2/go.mod h1:6MelG93GURQebXPDq3khkgXZkazVtN9CRI+MGFi0w8I=
github.com/golang/protobuf v1.5.0/go.mod h1:FsONVRAS9T7sI+LIUmWTfcYkHO4aIWwzhcaSAoJOfIk=
@@ -34,15 +49,24 @@ github.com/inconshreveable/mousetrap v1.1.0 h1:wN+x4NVGpMsO7ErUn/mUI3vEoE6Jt13X2
github.com/inconshreveable/mousetrap v1.1.0/go.mod h1:vpF70FUmC8bwa3OWnCshd2FqLfsEA9PFc4w1p2J65bw=
github.com/json-iterator/go v1.1.12 h1:PV8peI4a0ysnczrg+LtxykD8LfKY9ML6u2jnxaEnrnM=
github.com/json-iterator/go v1.1.12/go.mod h1:e30LSqwooZae/UwlEbR2852Gd8hjQvJoHmT4TnhNGBo=
github.com/k0kubun/go-ansi v0.0.0-20180517002512-3bf9e2903213/go.mod h1:vNUNkEQ1e29fT/6vq2aBdFsgNPmy8qMdSay1npru+Sw=
github.com/klauspost/cpuid/v2 v2.0.9/go.mod h1:FInQzS24/EEf25PyTYn52gqo7WaD8xa0213Md/qVLRg=
github.com/klauspost/cpuid/v2 v2.2.4 h1:acbojRNwl3o09bUq+yDCtZFc1aiwaAAxtcn8YkZXnvk=
github.com/klauspost/cpuid/v2 v2.2.4/go.mod h1:RVVoqg1df56z8g3pUjL/3lE5UfnlrJX8tyFgg4nqhuY=
github.com/kr/pretty v0.1.0/go.mod h1:dAy3ld7l9f0ibDNOQOHHMYYIIbhfbHSm3C4ZsoJORNo=
github.com/kr/pretty v0.2.1/go.mod h1:ipq/a2n7PKx3OHsz4KJII5eveXtPO4qwEXGdVfWzfnI=
github.com/kr/pretty v0.3.0 h1:WgNl7dwNpEZ6jJ9k1snq4pZsg7DOEN8hP9Xw0Tsjwk0=
github.com/kr/pretty v0.3.0/go.mod h1:640gp4NfQd8pI5XOwp5fnNeVWj67G7CFk/SaSQn7NBk=
github.com/kr/pty v1.1.1/go.mod h1:pFQYn66WHrOpPYNljwOMqo10TkYh1fy3cYio2l3bCsQ=
github.com/kr/text v0.1.0/go.mod h1:4Jbv+DJW3UT/LiOwJeYQe1efqtUx/iVham/4vfdArNI=
github.com/kr/text v0.2.0 h1:5Nx0Ya0ZqY2ygV366QzturHI13Jq95ApcVaJBhpS+AY=
github.com/kr/text v0.2.0/go.mod h1:eLer722TekiGuMkidMxC/pM04lWEeraHUUmBw8l2grE=
github.com/leodido/go-urn v1.2.1/go.mod h1:zt4jvISO2HfUBqxjfIshjdMTYS56ZS/qv49ictyFfxY=
github.com/leodido/go-urn v1.2.4 h1:XlAE/cm/ms7TE/VMVoduSpNBoyc2dOxHs5MZSwAN63Q=
github.com/leodido/go-urn v1.2.4/go.mod h1:7ZrI8mTSeBSHl/UaRyKQW1qZeMgak41ANeCNaVckg+4=
github.com/mattn/go-isatty v0.0.17/go.mod h1:kYGgaQfpe5nmfYZH+SKPsOc2e4SrIfOl2e/yFXSvRLM=
github.com/mattn/go-isatty v0.0.14/go.mod h1:7GGIvUiUoEMVVmxf/4nioHXj79iQHKdU27kJ6hsGG94=
github.com/mattn/go-isatty v0.0.19 h1:JITubQf0MOLdlGRuRq+jtsDlekdYPia9ZFsB8h/APPA=
github.com/mattn/go-isatty v0.0.19/go.mod h1:W+V8PltTTMOvKvAeJH7IuucS94S2C6jfK/D7dTCTo3Y=
github.com/mattn/go-runewidth v0.0.9/go.mod h1:H031xJmbD/WCDINGzjvQ9THkh0rPKHF+m2gUSrubnMI=
github.com/mattn/go-runewidth v0.0.14 h1:+xnbZSEeDbOIg5/mE6JF0w6n9duR1l3/WmbinWVwUuU=
github.com/mattn/go-runewidth v0.0.14/go.mod h1:Jdepj2loyihRzMpdS35Xk/zdY8IAYHsh153qUoGf23w=
github.com/mitchellh/colorstring v0.0.0-20190213212951-d06e56a500db h1:62I3jR2EmQ4l5rM/4FEfDWcRD+abF5XlKShorW5LRoQ=
@@ -52,15 +76,20 @@ github.com/modern-go/concurrent v0.0.0-20180306012644-bacd9c7ef1dd h1:TRLaZ9cD/w
github.com/modern-go/concurrent v0.0.0-20180306012644-bacd9c7ef1dd/go.mod h1:6dJC0mAP4ikYIbvyc7fijjWJddQyLn8Ig3JB5CqoB9Q=
github.com/modern-go/reflect2 v1.0.2 h1:xBagoLtFs94CBntxluKeaWgTMpvLxC4ur3nMaC9Gz0M=
github.com/modern-go/reflect2 v1.0.2/go.mod h1:yWuevngMOJpCy52FWWMvUC8ws7m/LJsjYzDa0/r8luk=
github.com/olekukonko/tablewriter v0.0.5 h1:P2Ga83D34wi1o9J6Wh1mRuqd4mF/x/lgBS7N7AbDhec=
github.com/olekukonko/tablewriter v0.0.5/go.mod h1:hPp6KlRPjbx+hW8ykQs1w3UBbZlj6HuIJcUGPhkA7kY=
github.com/pelletier/go-toml/v2 v2.0.1/go.mod h1:r9LEWfGN8R5k0VXJ+0BkIe7MYkRdwZOjgMj2KwnJFUo=
github.com/pelletier/go-toml/v2 v2.0.8 h1:0ctb6s9mE31h0/lhu+J6OPmVeDxJn+kYnJc2jZR9tGQ=
github.com/pelletier/go-toml/v2 v2.0.8/go.mod h1:vuYfssBdrU2XDZ9bYydBu6t+6a6PYNcZljzZR9VXg+4=
github.com/pkg/diff v0.0.0-20210226163009-20ebb0f2a09e/go.mod h1:pJLUxLENpZxwdsKMEsNbx1VGcRFpLqf3715MtcvvzbA=
github.com/pmezard/go-difflib v1.0.0 h1:4DBwDE0NGyQoBHbLQYPwSUPoCMWR5BEzIk/f1lZbAQM=
github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZNVY4sRDYZ/4=
github.com/rivo/uniseg v0.2.0 h1:S1pD9weZBuJdFmowNwbpi7BJ8TNftyUImj/0WQi72jY=
github.com/rivo/uniseg v0.2.0/go.mod h1:J6wj4VEh+S6ZtnVlnTBMWIodfgj8LQOQFoIToxlJtxc=
github.com/rogpeppe/go-internal v1.6.1/go.mod h1:xXDCJY+GAPziupqXw64V24skbSoqbTEfhy4qGm1nDQc=
github.com/rogpeppe/go-internal v1.8.0 h1:FCbCCtXNOY3UtUuHUYaghJg4y7Fd14rXifAYUAtL9R8=
github.com/rogpeppe/go-internal v1.8.0/go.mod h1:WmiCO8CzOY8rg0OYDC4/i/2WRWAB6poM+XZ2dLUbcbE=
github.com/russross/blackfriday/v2 v2.1.0/go.mod h1:+Rmxgy9KzJVeS9/2gXHxylqXiyQDYRxCVz55jmeOWTM=
github.com/schollz/progressbar/v3 v3.13.1 h1:o8rySDYiQ59Mwzy2FELeHY5ZARXZTVJC7iHD6PEFUiE=
github.com/schollz/progressbar/v3 v3.13.1/go.mod h1:xvrbki8kfT1fzWzBT/UZd9L6GA+jdL7HAgq2RFnO6fQ=
github.com/spf13/cobra v1.7.0 h1:hyqWnYt1ZQShIddO5kBpj3vu05/++x6tJ6dg8EC572I=
github.com/spf13/cobra v1.7.0/go.mod h1:uLxZILRyS/50WlhOIKD7W6V5bgeIt+4sICxh6uRMrb0=
github.com/spf13/pflag v1.0.5 h1:iy+VFUOCP1a+8yFto/drg2CJ5u0yRoB7fZw3DKv/JXA=
@@ -69,6 +98,7 @@ github.com/stretchr/objx v0.1.0/go.mod h1:HFkY916IF+rwdDfMAkV7OtwuqBVzrE8GR6GFx+
github.com/stretchr/objx v0.4.0/go.mod h1:YvHI0jy2hoMjB+UWwv71VJQ9isScKT/TqJzVSSt89Yw=
github.com/stretchr/objx v0.5.0/go.mod h1:Yh+to48EsGEfYuaHDzXPcE3xhTkx73EhmCGUpEOglKo=
github.com/stretchr/testify v1.3.0/go.mod h1:M5WIy9Dh21IEIfnGCwXGc5bZfKNJtfHm1UVUgZn+9EI=
github.com/stretchr/testify v1.6.1/go.mod h1:6Fq8oRcR53rry900zMqJjRRixrwX3KX962/h/Wwjteg=
github.com/stretchr/testify v1.7.0/go.mod h1:6Fq8oRcR53rry900zMqJjRRixrwX3KX962/h/Wwjteg=
github.com/stretchr/testify v1.7.1/go.mod h1:6Fq8oRcR53rry900zMqJjRRixrwX3KX962/h/Wwjteg=
github.com/stretchr/testify v1.8.0/go.mod h1:yNjHg4UonilssWZ8iaSj1OCr/vHnekPRkoO+kdMU+MU=
@@ -78,32 +108,49 @@ github.com/stretchr/testify v1.8.3 h1:RP3t2pwF7cMEbC1dqtB6poj3niw/9gnV4Cjg5oW5gt
github.com/stretchr/testify v1.8.3/go.mod h1:sz/lmYIOXD/1dqDmKjjqLyZ2RngseejIcXlSw2iwfAo=
github.com/twitchyliquid64/golang-asm v0.15.1 h1:SU5vSMR7hnwNxj24w34ZyCi/FmDZTkS4MhqMhdFk5YI=
github.com/twitchyliquid64/golang-asm v0.15.1/go.mod h1:a1lVb/DtPvCB8fslRZhAngC2+aY1QWCk3Cedj/Gdt08=
github.com/ugorji/go v1.2.7/go.mod h1:nF9osbDWLy6bDVv/Rtoh6QgnvNDpmCalQV5urGCCS6M=
github.com/ugorji/go/codec v1.2.7/go.mod h1:WGN1fab3R1fzQlVQTkfxVtIBhWDRqOviHU95kRgeqEY=
github.com/ugorji/go/codec v1.2.11 h1:BMaWp1Bb6fHwEtbplGBGJ498wD+LKlNSl25MjdZY4dU=
github.com/ugorji/go/codec v1.2.11/go.mod h1:UNopzCgEMSXjBc6AOMqYvWC1ktqTAfzJZUZgYf6w6lg=
golang.org/x/arch v0.0.0-20210923205945-b76863e36670/go.mod h1:5om86z9Hs0C8fWVUuoMHwpExlXzs5Tkyp9hOrfG7pp8=
golang.org/x/arch v0.3.0 h1:02VY4/ZcO/gBOH6PUaoiptASxtXU10jazRCP865E97k=
golang.org/x/arch v0.3.0/go.mod h1:5om86z9Hs0C8fWVUuoMHwpExlXzs5Tkyp9hOrfG7pp8=
golang.org/x/crypto v0.0.0-20210711020723-a769d52b0f97/go.mod h1:GvvjBRRGRdwPK5ydBHafDWAxML/pGHZbMvKqRZ5+Abc=
golang.org/x/crypto v0.10.0 h1:LKqV2xt9+kDzSTfOhx4FrkEBcMrAgHSYgzywV9zcGmM=
golang.org/x/crypto v0.10.0/go.mod h1:o4eNf7Ede1fv+hwOwZsTHl9EsPFO6q6ZvYR8vYfY45I=
golang.org/x/net v0.0.0-20210226172049-e18ecbb05110/go.mod h1:m0MpNAwzfU5UDzcl9v0D8zg8gWTRqZa9RBIspLL5mdg=
golang.org/x/net v0.10.0 h1:X2//UzNDwYmtCLn7To6G58Wr6f5ahEAQgKNzv9Y951M=
golang.org/x/net v0.10.0/go.mod h1:0qNGK6F8kojg2nk9dLZ2mShWaEBan6FAoqfSigmmuDg=
golang.org/x/sys v0.0.0-20201119102817-f84b799fce68/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
golang.org/x/sys v0.0.0-20210615035016-665e8c7367d1/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20210630005230-0f9fa26af87c/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20210806184541-e5e7981a1069/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20220310020820-b874c991c1a5/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20220704084225-05e143d24a9e/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.0.0-20220811171246-fbc7d0a398ab/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.6.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/sys v0.10.0 h1:SqMFp9UcQJZa+pmYuAKjd9xq1f0j5rLcDIk0mj4qAsA=
golang.org/x/sys v0.10.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
golang.org/x/term v0.6.0/go.mod h1:m6U89DPEgQRMq3DNkDClhWw02AUbt2daBVO4cn4Hv9U=
golang.org/x/term v0.0.0-20201126162022-7de9c90e9dd1/go.mod h1:bj7SfCRtBDWHUb9snDiAeCFNEtKQo2Wmx5Cou7ajbmo=
golang.org/x/term v0.10.0 h1:3R7pNqamzBraeqj/Tj8qt1aQ2HpmlC+Cx/qL/7hn4/c=
golang.org/x/term v0.10.0/go.mod h1:lpqdcUyK/oCiQxvxVrppt5ggO2KCZ5QblwqPnfZ6d5o=
golang.org/x/text v0.3.3/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
golang.org/x/text v0.3.6/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
golang.org/x/text v0.10.0 h1:UpjohKhiEgNc0CSauXmwYftY1+LlaC75SJwh0SgCX58=
golang.org/x/text v0.10.0/go.mod h1:TvPlkZtksWOMsz7fbANvkp4WM8x/WCo/om8BMLbz+aE=
golang.org/x/tools v0.0.0-20180917221912-90fa682c2a6e/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
golang.org/x/xerrors v0.0.0-20191204190536-9bdfabe68543/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
google.golang.org/protobuf v1.26.0-rc.1/go.mod h1:jlhhOSvTdKEhbULTjvd4ARK9grFBp09yW+WbY/TyQbw=
google.golang.org/protobuf v1.28.0/go.mod h1:HV8QOd/L58Z+nl8r43ehVNZIU/HEI6OcFqwMG9pJV4I=
google.golang.org/protobuf v1.30.0 h1:kPPoIgf3TsEvrm0PFe15JQ+570QVxYzEvvHqChK+cng=
google.golang.org/protobuf v1.30.0/go.mod h1:HV8QOd/L58Z+nl8r43ehVNZIU/HEI6OcFqwMG9pJV4I=
gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405 h1:yhCVgyC4o1eVCa2tZl7eS0r+SDo693bJlVdllGtEeKM=
gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
gopkg.in/check.v1 v1.0.0-20180628173108-788fd7840127/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
gopkg.in/check.v1 v1.0.0-20201130134442-10cb98267c6c h1:Hei/4ADfdWqJk1ZMxUNpqntNwaWcugrBjAiHlqqRiVk=
gopkg.in/check.v1 v1.0.0-20201130134442-10cb98267c6c/go.mod h1:JHkPIbrfpd72SG/EVd6muEfDQjcINNoR0C8j2r3qZ4Q=
gopkg.in/errgo.v2 v2.1.0/go.mod h1:hNsd1EY+bozCKY1Ytp96fpM3vjJbqLJn88ws8XvfDNI=
gopkg.in/yaml.v2 v2.4.0/go.mod h1:RDklbk79AGWmwhnvt/jBztapEOGDOx6ZbXqjP6csGnQ=
gopkg.in/yaml.v3 v3.0.0-20200313102051-9f266ea9e77c/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
gopkg.in/yaml.v3 v3.0.0-20210107192922-496545a6307b/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
gopkg.in/yaml.v3 v3.0.1 h1:fxVm/GzAzEWqLHuvctI91KS9hhNmmWOoWu0XTYJS7CA=
gopkg.in/yaml.v3 v3.0.1/go.mod h1:K4uyk7z7BCEPqu6E+C64Yfv1cQ7kz7rIZviUmN+EgEM=
rsc.io/pdf v0.1.1/go.mod h1:n8OzWcQ6Sp37PL01nO98y4iUCRdTGarVfzxY20ICaU4=

1
library/.gitignore vendored Normal file
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@@ -0,0 +1 @@
models

7
library/downloads Normal file
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@@ -0,0 +1,7 @@
https://huggingface.co/TheBloke/orca_mini_3B-GGML/resolve/main/orca-mini-3b.ggmlv3.q4_0.bin e84705205f71dd55be7b24a778f248f0eda9999a125d313358c087e092d83148
https://huggingface.co/TheBloke/Nous-Hermes-13B-GGML/resolve/main/nous-hermes-13b.ggmlv3.q4_0.bin d1735b93e1dc503f1045ccd6c8bd73277b18ba892befd1dc29e9b9a7822ed998
https://huggingface.co/TheBloke/vicuna-7B-v1.3-GGML/resolve/main/vicuna-7b-v1.3.ggmlv3.q4_0.bin 23ce5ed290b56a19305178b9ada2c3d96036bd69a6c18304b6158eb6672d6c0f
https://huggingface.co/TheBloke/Wizard-Vicuna-13B-Uncensored-GGML/resolve/main/Wizard-Vicuna-13B-Uncensored.ggmlv3.q4_0.bin 1f08b147a5bce41cfcbb3fd5d51ba765dea1786e15b5655ab69ba3a337a893b7
https://huggingface.co/TheBloke/Llama-2-7B-GGML/resolve/main/llama-2-7b.ggmlv3.q4_0.bin bfa26d855e44629c4cf919985e90bd7fa03b77eea1676791519e39a4d45fd4d5
https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/resolve/main/llama-2-7b-chat.ggmlv3.q4_0.bin 8daa9615cce30c259a9555b1cc250d461d1bc69980a274b44d7eda0be78076d8
https://huggingface.co/TheBloke/Llama-2-13B-chat-GGML/resolve/main/llama-2-13b-chat.ggmlv3.q4_0.bin f79142715bc9539a2edbb4b253548db8b34fac22736593eeaa28555874476e30

147
library/modelfiles/llama2 Normal file
View File

@@ -0,0 +1,147 @@
FROM ../models/llama-2-7b-chat.ggmlv3.q4_0.bin
TEMPLATE """
{{- if .First }}
<<SYS>>
{{ .System }}
<</SYS>>
{{- end }}
[INST] {{ .Prompt }} [/INST]
"""
SYSTEM """
You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature.
If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.
"""
LICENSE """
Llama 2 Community License Agreement
Llama 2 Version Release Date: July 18, 2023
“Agreement” means the terms and conditions for use, reproduction, distribution and modification of the Llama Materials set forth herein.
“Documentation” means the specifications, manuals and documentation accompanying Llama 2 distributed by Meta at ai.meta.com/resources/models-and-libraries/llama-downloads/.
“Licensee” or “you” means you, or your employer or any other person or entity (if you are entering into this Agreement on such person or entitys behalf), of the age required under applicable laws, rules or regulations to provide legal consent and that has legal authority to bind your employer or such other person or entity if you are entering in this Agreement on their behalf.
“Llama 2” means the foundational large language models and software and algorithms, including machine-learning model code, trained model weights, inference-enabling code, training-enabling code, fine-tuning enabling code and other elements of the foregoing distributed by Meta at ai.meta.com/resources/models-and-libraries/llama-downloads/.
“Llama Materials” means, collectively, Metas proprietary Llama 2 and Documentation (and any portion thereof) made available under this Agreement.
“Meta” or “we” means Meta Platforms Ireland Limited (if you are located in or, if you are an entity, your principal place of business is in the EEA or Switzerland) and Meta Platforms, Inc. (if you are located outside of the EEA or Switzerland).
By clicking “I Accept” below or by using or distributing any portion or element of the Llama Materials, you agree to be bound by this Agreement.
1. License Rights and Redistribution.
a. Grant of Rights. You are granted a non-exclusive, worldwide, non-transferable and royalty-free limited license under Metas intellectual property or other rights owned by Meta embodied in the Llama Materials to use, reproduce, distribute, copy, create derivative works of, and make modifications to the Llama Materials.
b. Redistribution and Use.
i. If you distribute or make the Llama Materials, or any derivative works thereof, available to a third party, you shall provide a copy of this Agreement to such third party.
ii. If you receive Llama Materials, or any derivative works thereof, from a Licensee as part of an integrated end user product, then Section 2 of this Agreement will not apply to you.
iii. You must retain in all copies of the Llama Materials that you distribute the following attribution notice within a “Notice” text file distributed as a part of such copies: “Llama 2 is licensed under the LLAMA 2 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved.”
iv. Your use of the Llama Materials must comply with applicable laws and regulations (including trade compliance laws and regulations) and adhere to the Acceptable Use Policy for the Llama Materials (available at https://ai.meta.com/llama/use-policy), which is hereby incorporated by reference into this Agreement.
v. You will not use the Llama Materials or any output or results of the Llama Materials to improve any other large language model (excluding Llama 2 or derivative works thereof).
2. Additional Commercial Terms. If, on the Llama 2 version release date, the monthly active users of the products or services made available by or for Licensee, or Licensees affiliates, is greater than 700 million monthly active users in the preceding calendar month, you must request a license from Meta, which Meta may grant to you in its sole discretion, and you are not authorized to exercise any of the rights under this Agreement unless or until Meta otherwise expressly grants you such rights.
3. Disclaimer of Warranty. UNLESS REQUIRED BY APPLICABLE LAW, THE LLAMA MATERIALS AND ANY OUTPUT AND RESULTS THEREFROM ARE PROVIDED ON AN “AS IS” BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING, WITHOUT LIMITATION, ANY WARRANTIES OF TITLE, NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE. YOU ARE SOLELY RESPONSIBLE FOR DETERMINING THE APPROPRIATENESS OF USING OR REDISTRIBUTING THE LLAMA MATERIALS AND ASSUME ANY RISKS ASSOCIATED WITH YOUR USE OF THE LLAMA MATERIALS AND ANY OUTPUT AND RESULTS.
4. Limitation of Liability. IN NO EVENT WILL META OR ITS AFFILIATES BE LIABLE UNDER ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, TORT, NEGLIGENCE, PRODUCTS LIABILITY, OR OTHERWISE, ARISING OUT OF THIS AGREEMENT, FOR ANY LOST PROFITS OR ANY INDIRECT, SPECIAL, CONSEQUENTIAL, INCIDENTAL, EXEMPLARY OR PUNITIVE DAMAGES, EVEN IF META OR ITS AFFILIATES HAVE BEEN ADVISED OF THE POSSIBILITY OF ANY OF THE FOREGOING.
5. Intellectual Property.
a. No trademark licenses are granted under this Agreement, and in connection with the Llama Materials, neither Meta nor Licensee may use any name or mark owned by or associated with the other or any of its affiliates, except as required for reasonable and customary use in describing and redistributing the Llama Materials.
b. Subject to Metas ownership of Llama Materials and derivatives made by or for Meta, with respect to any derivative works and modifications of the Llama Materials that are made by you, as between you and Meta, you are and will be the owner of such derivative works and modifications.
c. If you institute litigation or other proceedings against Meta or any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Llama Materials or Llama 2 outputs or results, or any portion of any of the foregoing, constitutes infringement of intellectual property or other rights owned or licensable by you, then any licenses granted to you under this Agreement shall terminate as of the date such litigation or claim is filed or instituted. You will indemnify and hold harmless Meta from and against any claim by any third party arising out of or related to your use or distribution of the Llama Materials.
6. Term and Termination. The term of this Agreement will commence upon your acceptance of this Agreement or access to the Llama Materials and will continue in full force and effect until terminated in accordance with the terms and conditions herein. Meta may terminate this Agreement if you are in breach of any term or condition of this Agreement. Upon termination of this Agreement, you shall delete and cease use of the Llama Materials. Sections 3, 4 and 7 shall survive the termination of this Agreement.
7. Governing Law and Jurisdiction. This Agreement will be governed and construed under the laws of the State of California without regard to choice of law principles, and the UN Convention on Contracts for the International Sale of Goods does not apply to this Agreement. The courts of California shall have exclusive jurisdiction of any dispute arising out of this Agreement.
"""
LICENSE """
Llama 2 Acceptable Use Policy
Meta is committed to promoting safe and fair use of its tools and features, including Llama 2. If you access or use Llama 2, you agree to this Acceptable Use Policy (“Policy”). The most recent copy of this policy can be found at ai.meta.com/llama/use-policy.
Prohibited Uses
We want everyone to use Llama 2 safely and responsibly. You agree you will not use, or allow others to use, Llama 2 to:
1. Violate the law or others rights, including to:
a. Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as:
i. Violence or terrorism
ii. Exploitation or harm to children, including the solicitation, creation, acquisition, or dissemination of child exploitative content or failure to report Child Sexual Abuse Material
b. Human trafficking, exploitation, and sexual violence
iii. The illegal distribution of information or materials to minors, including obscene materials, or failure to employ legally required age-gating in connection with such information or materials.
iv. Sexual solicitation
vi. Any other criminal activity
c. Engage in, promote, incite, or facilitate the harassment, abuse, threatening, or bullying of individuals or groups of individuals
d. Engage in, promote, incite, or facilitate discrimination or other unlawful or harmful conduct in the provision of employment, employment benefits, credit, housing, other economic benefits, or other essential goods and services
e. Engage in the unauthorized or unlicensed practice of any profession including, but not limited to, financial, legal, medical/health, or related professional practices
f. Collect, process, disclose, generate, or infer health, demographic, or other sensitive personal or private information about individuals without rights and consents required by applicable laws
g. Engage in or facilitate any action or generate any content that infringes, misappropriates, or otherwise violates any third-party rights, including the outputs or results of any products or services using the Llama 2 Materials
h. Create, generate, or facilitate the creation of malicious code, malware, computer viruses or do anything else that could disable, overburden, interfere with or impair the proper working, integrity, operation or appearance of a website or computer system
2. Engage in, promote, incite, facilitate, or assist in the planning or development of activities that present a risk of death or bodily harm to individuals, including use of Llama 2 related to the following:
a. Military, warfare, nuclear industries or applications, espionage, use for materials or activities that are subject to the International Traffic Arms Regulations (ITAR) maintained by the United States Department of State
b. Guns and illegal weapons (including weapon development)
c. Illegal drugs and regulated/controlled substances
d. Operation of critical infrastructure, transportation technologies, or heavy machinery
e. Self-harm or harm to others, including suicide, cutting, and eating disorders
f. Any content intended to incite or promote violence, abuse, or any infliction of bodily harm to an individual
3. Intentionally deceive or mislead others, including use of Llama 2 related to the following:
a. Generating, promoting, or furthering fraud or the creation or promotion of disinformation
b. Generating, promoting, or furthering defamatory content, including the creation of defamatory statements, images, or other content
c. Generating, promoting, or further distributing spam
d. Impersonating another individual without consent, authorization, or legal right
e. Representing that the use of Llama 2 or outputs are human-generated
f. Generating or facilitating false online engagement, including fake reviews and other means of fake online engagement
4. Fail to appropriately disclose to end users any known dangers of your AI system
Please report any violation of this Policy, software “bug,” or other problems that could lead to a violation of this Policy through one of the following means:
Reporting issues with the model: github.com/facebookresearch/llama
Reporting risky content generated by the model: developers.facebook.com/llama_output_feedback
Reporting bugs and security concerns: facebook.com/whitehat/info
Reporting violations of the Acceptable Use Policy or unlicensed uses of Llama: LlamaUseReport@meta.com
"""

View File

@@ -0,0 +1,147 @@
FROM ../models/llama-2-13b-chat.ggmlv3.q4_0.bin
TEMPLATE """
{{- if .First }}
<<SYS>>
{{ .System }}
<</SYS>>
{{- end }}
[INST] {{ .Prompt }} [/INST]
"""
SYSTEM """
You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature.
If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.
"""
LICENSE """
Llama 2 Community License Agreement
Llama 2 Version Release Date: July 18, 2023
“Agreement” means the terms and conditions for use, reproduction, distribution and modification of the Llama Materials set forth herein.
“Documentation” means the specifications, manuals and documentation accompanying Llama 2 distributed by Meta at ai.meta.com/resources/models-and-libraries/llama-downloads/.
“Licensee” or “you” means you, or your employer or any other person or entity (if you are entering into this Agreement on such person or entitys behalf), of the age required under applicable laws, rules or regulations to provide legal consent and that has legal authority to bind your employer or such other person or entity if you are entering in this Agreement on their behalf.
“Llama 2” means the foundational large language models and software and algorithms, including machine-learning model code, trained model weights, inference-enabling code, training-enabling code, fine-tuning enabling code and other elements of the foregoing distributed by Meta at ai.meta.com/resources/models-and-libraries/llama-downloads/.
“Llama Materials” means, collectively, Metas proprietary Llama 2 and Documentation (and any portion thereof) made available under this Agreement.
“Meta” or “we” means Meta Platforms Ireland Limited (if you are located in or, if you are an entity, your principal place of business is in the EEA or Switzerland) and Meta Platforms, Inc. (if you are located outside of the EEA or Switzerland).
By clicking “I Accept” below or by using or distributing any portion or element of the Llama Materials, you agree to be bound by this Agreement.
1. License Rights and Redistribution.
a. Grant of Rights. You are granted a non-exclusive, worldwide, non-transferable and royalty-free limited license under Metas intellectual property or other rights owned by Meta embodied in the Llama Materials to use, reproduce, distribute, copy, create derivative works of, and make modifications to the Llama Materials.
b. Redistribution and Use.
i. If you distribute or make the Llama Materials, or any derivative works thereof, available to a third party, you shall provide a copy of this Agreement to such third party.
ii. If you receive Llama Materials, or any derivative works thereof, from a Licensee as part of an integrated end user product, then Section 2 of this Agreement will not apply to you.
iii. You must retain in all copies of the Llama Materials that you distribute the following attribution notice within a “Notice” text file distributed as a part of such copies: “Llama 2 is licensed under the LLAMA 2 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved.”
iv. Your use of the Llama Materials must comply with applicable laws and regulations (including trade compliance laws and regulations) and adhere to the Acceptable Use Policy for the Llama Materials (available at https://ai.meta.com/llama/use-policy), which is hereby incorporated by reference into this Agreement.
v. You will not use the Llama Materials or any output or results of the Llama Materials to improve any other large language model (excluding Llama 2 or derivative works thereof).
2. Additional Commercial Terms. If, on the Llama 2 version release date, the monthly active users of the products or services made available by or for Licensee, or Licensees affiliates, is greater than 700 million monthly active users in the preceding calendar month, you must request a license from Meta, which Meta may grant to you in its sole discretion, and you are not authorized to exercise any of the rights under this Agreement unless or until Meta otherwise expressly grants you such rights.
3. Disclaimer of Warranty. UNLESS REQUIRED BY APPLICABLE LAW, THE LLAMA MATERIALS AND ANY OUTPUT AND RESULTS THEREFROM ARE PROVIDED ON AN “AS IS” BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING, WITHOUT LIMITATION, ANY WARRANTIES OF TITLE, NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE. YOU ARE SOLELY RESPONSIBLE FOR DETERMINING THE APPROPRIATENESS OF USING OR REDISTRIBUTING THE LLAMA MATERIALS AND ASSUME ANY RISKS ASSOCIATED WITH YOUR USE OF THE LLAMA MATERIALS AND ANY OUTPUT AND RESULTS.
4. Limitation of Liability. IN NO EVENT WILL META OR ITS AFFILIATES BE LIABLE UNDER ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, TORT, NEGLIGENCE, PRODUCTS LIABILITY, OR OTHERWISE, ARISING OUT OF THIS AGREEMENT, FOR ANY LOST PROFITS OR ANY INDIRECT, SPECIAL, CONSEQUENTIAL, INCIDENTAL, EXEMPLARY OR PUNITIVE DAMAGES, EVEN IF META OR ITS AFFILIATES HAVE BEEN ADVISED OF THE POSSIBILITY OF ANY OF THE FOREGOING.
5. Intellectual Property.
a. No trademark licenses are granted under this Agreement, and in connection with the Llama Materials, neither Meta nor Licensee may use any name or mark owned by or associated with the other or any of its affiliates, except as required for reasonable and customary use in describing and redistributing the Llama Materials.
b. Subject to Metas ownership of Llama Materials and derivatives made by or for Meta, with respect to any derivative works and modifications of the Llama Materials that are made by you, as between you and Meta, you are and will be the owner of such derivative works and modifications.
c. If you institute litigation or other proceedings against Meta or any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Llama Materials or Llama 2 outputs or results, or any portion of any of the foregoing, constitutes infringement of intellectual property or other rights owned or licensable by you, then any licenses granted to you under this Agreement shall terminate as of the date such litigation or claim is filed or instituted. You will indemnify and hold harmless Meta from and against any claim by any third party arising out of or related to your use or distribution of the Llama Materials.
6. Term and Termination. The term of this Agreement will commence upon your acceptance of this Agreement or access to the Llama Materials and will continue in full force and effect until terminated in accordance with the terms and conditions herein. Meta may terminate this Agreement if you are in breach of any term or condition of this Agreement. Upon termination of this Agreement, you shall delete and cease use of the Llama Materials. Sections 3, 4 and 7 shall survive the termination of this Agreement.
7. Governing Law and Jurisdiction. This Agreement will be governed and construed under the laws of the State of California without regard to choice of law principles, and the UN Convention on Contracts for the International Sale of Goods does not apply to this Agreement. The courts of California shall have exclusive jurisdiction of any dispute arising out of this Agreement.
"""
LICENSE """
Llama 2 Acceptable Use Policy
Meta is committed to promoting safe and fair use of its tools and features, including Llama 2. If you access or use Llama 2, you agree to this Acceptable Use Policy (“Policy”). The most recent copy of this policy can be found at ai.meta.com/llama/use-policy.
Prohibited Uses
We want everyone to use Llama 2 safely and responsibly. You agree you will not use, or allow others to use, Llama 2 to:
1. Violate the law or others rights, including to:
a. Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as:
i. Violence or terrorism
ii. Exploitation or harm to children, including the solicitation, creation, acquisition, or dissemination of child exploitative content or failure to report Child Sexual Abuse Material
b. Human trafficking, exploitation, and sexual violence
iii. The illegal distribution of information or materials to minors, including obscene materials, or failure to employ legally required age-gating in connection with such information or materials.
iv. Sexual solicitation
vi. Any other criminal activity
c. Engage in, promote, incite, or facilitate the harassment, abuse, threatening, or bullying of individuals or groups of individuals
d. Engage in, promote, incite, or facilitate discrimination or other unlawful or harmful conduct in the provision of employment, employment benefits, credit, housing, other economic benefits, or other essential goods and services
e. Engage in the unauthorized or unlicensed practice of any profession including, but not limited to, financial, legal, medical/health, or related professional practices
f. Collect, process, disclose, generate, or infer health, demographic, or other sensitive personal or private information about individuals without rights and consents required by applicable laws
g. Engage in or facilitate any action or generate any content that infringes, misappropriates, or otherwise violates any third-party rights, including the outputs or results of any products or services using the Llama 2 Materials
h. Create, generate, or facilitate the creation of malicious code, malware, computer viruses or do anything else that could disable, overburden, interfere with or impair the proper working, integrity, operation or appearance of a website or computer system
2. Engage in, promote, incite, facilitate, or assist in the planning or development of activities that present a risk of death or bodily harm to individuals, including use of Llama 2 related to the following:
a. Military, warfare, nuclear industries or applications, espionage, use for materials or activities that are subject to the International Traffic Arms Regulations (ITAR) maintained by the United States Department of State
b. Guns and illegal weapons (including weapon development)
c. Illegal drugs and regulated/controlled substances
d. Operation of critical infrastructure, transportation technologies, or heavy machinery
e. Self-harm or harm to others, including suicide, cutting, and eating disorders
f. Any content intended to incite or promote violence, abuse, or any infliction of bodily harm to an individual
3. Intentionally deceive or mislead others, including use of Llama 2 related to the following:
a. Generating, promoting, or furthering fraud or the creation or promotion of disinformation
b. Generating, promoting, or furthering defamatory content, including the creation of defamatory statements, images, or other content
c. Generating, promoting, or further distributing spam
d. Impersonating another individual without consent, authorization, or legal right
e. Representing that the use of Llama 2 or outputs are human-generated
f. Generating or facilitating false online engagement, including fake reviews and other means of fake online engagement
4. Fail to appropriately disclose to end users any known dangers of your AI system
Please report any violation of this Policy, software “bug,” or other problems that could lead to a violation of this Policy through one of the following means:
Reporting issues with the model: github.com/facebookresearch/llama
Reporting risky content generated by the model: developers.facebook.com/llama_output_feedback
Reporting bugs and security concerns: facebook.com/whitehat/info
Reporting violations of the Acceptable Use Policy or unlicensed uses of Llama: LlamaUseReport@meta.com
"""

View File

@@ -0,0 +1,147 @@
FROM ../models/llama-2-7b-chat.ggmlv3.q4_0.bin
TEMPLATE """
{{- if .First }}
<<SYS>>
{{ .System }}
<</SYS>>
{{- end }}
[INST] {{ .Prompt }} [/INST]
"""
SYSTEM """
You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature.
If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.
"""
LICENSE """
Llama 2 Community License Agreement
Llama 2 Version Release Date: July 18, 2023
“Agreement” means the terms and conditions for use, reproduction, distribution and modification of the Llama Materials set forth herein.
“Documentation” means the specifications, manuals and documentation accompanying Llama 2 distributed by Meta at ai.meta.com/resources/models-and-libraries/llama-downloads/.
“Licensee” or “you” means you, or your employer or any other person or entity (if you are entering into this Agreement on such person or entitys behalf), of the age required under applicable laws, rules or regulations to provide legal consent and that has legal authority to bind your employer or such other person or entity if you are entering in this Agreement on their behalf.
“Llama 2” means the foundational large language models and software and algorithms, including machine-learning model code, trained model weights, inference-enabling code, training-enabling code, fine-tuning enabling code and other elements of the foregoing distributed by Meta at ai.meta.com/resources/models-and-libraries/llama-downloads/.
“Llama Materials” means, collectively, Metas proprietary Llama 2 and Documentation (and any portion thereof) made available under this Agreement.
“Meta” or “we” means Meta Platforms Ireland Limited (if you are located in or, if you are an entity, your principal place of business is in the EEA or Switzerland) and Meta Platforms, Inc. (if you are located outside of the EEA or Switzerland).
By clicking “I Accept” below or by using or distributing any portion or element of the Llama Materials, you agree to be bound by this Agreement.
1. License Rights and Redistribution.
a. Grant of Rights. You are granted a non-exclusive, worldwide, non-transferable and royalty-free limited license under Metas intellectual property or other rights owned by Meta embodied in the Llama Materials to use, reproduce, distribute, copy, create derivative works of, and make modifications to the Llama Materials.
b. Redistribution and Use.
i. If you distribute or make the Llama Materials, or any derivative works thereof, available to a third party, you shall provide a copy of this Agreement to such third party.
ii. If you receive Llama Materials, or any derivative works thereof, from a Licensee as part of an integrated end user product, then Section 2 of this Agreement will not apply to you.
iii. You must retain in all copies of the Llama Materials that you distribute the following attribution notice within a “Notice” text file distributed as a part of such copies: “Llama 2 is licensed under the LLAMA 2 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved.”
iv. Your use of the Llama Materials must comply with applicable laws and regulations (including trade compliance laws and regulations) and adhere to the Acceptable Use Policy for the Llama Materials (available at https://ai.meta.com/llama/use-policy), which is hereby incorporated by reference into this Agreement.
v. You will not use the Llama Materials or any output or results of the Llama Materials to improve any other large language model (excluding Llama 2 or derivative works thereof).
2. Additional Commercial Terms. If, on the Llama 2 version release date, the monthly active users of the products or services made available by or for Licensee, or Licensees affiliates, is greater than 700 million monthly active users in the preceding calendar month, you must request a license from Meta, which Meta may grant to you in its sole discretion, and you are not authorized to exercise any of the rights under this Agreement unless or until Meta otherwise expressly grants you such rights.
3. Disclaimer of Warranty. UNLESS REQUIRED BY APPLICABLE LAW, THE LLAMA MATERIALS AND ANY OUTPUT AND RESULTS THEREFROM ARE PROVIDED ON AN “AS IS” BASIS, WITHOUT WARRANTIES OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING, WITHOUT LIMITATION, ANY WARRANTIES OF TITLE, NON-INFRINGEMENT, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE. YOU ARE SOLELY RESPONSIBLE FOR DETERMINING THE APPROPRIATENESS OF USING OR REDISTRIBUTING THE LLAMA MATERIALS AND ASSUME ANY RISKS ASSOCIATED WITH YOUR USE OF THE LLAMA MATERIALS AND ANY OUTPUT AND RESULTS.
4. Limitation of Liability. IN NO EVENT WILL META OR ITS AFFILIATES BE LIABLE UNDER ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, TORT, NEGLIGENCE, PRODUCTS LIABILITY, OR OTHERWISE, ARISING OUT OF THIS AGREEMENT, FOR ANY LOST PROFITS OR ANY INDIRECT, SPECIAL, CONSEQUENTIAL, INCIDENTAL, EXEMPLARY OR PUNITIVE DAMAGES, EVEN IF META OR ITS AFFILIATES HAVE BEEN ADVISED OF THE POSSIBILITY OF ANY OF THE FOREGOING.
5. Intellectual Property.
a. No trademark licenses are granted under this Agreement, and in connection with the Llama Materials, neither Meta nor Licensee may use any name or mark owned by or associated with the other or any of its affiliates, except as required for reasonable and customary use in describing and redistributing the Llama Materials.
b. Subject to Metas ownership of Llama Materials and derivatives made by or for Meta, with respect to any derivative works and modifications of the Llama Materials that are made by you, as between you and Meta, you are and will be the owner of such derivative works and modifications.
c. If you institute litigation or other proceedings against Meta or any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Llama Materials or Llama 2 outputs or results, or any portion of any of the foregoing, constitutes infringement of intellectual property or other rights owned or licensable by you, then any licenses granted to you under this Agreement shall terminate as of the date such litigation or claim is filed or instituted. You will indemnify and hold harmless Meta from and against any claim by any third party arising out of or related to your use or distribution of the Llama Materials.
6. Term and Termination. The term of this Agreement will commence upon your acceptance of this Agreement or access to the Llama Materials and will continue in full force and effect until terminated in accordance with the terms and conditions herein. Meta may terminate this Agreement if you are in breach of any term or condition of this Agreement. Upon termination of this Agreement, you shall delete and cease use of the Llama Materials. Sections 3, 4 and 7 shall survive the termination of this Agreement.
7. Governing Law and Jurisdiction. This Agreement will be governed and construed under the laws of the State of California without regard to choice of law principles, and the UN Convention on Contracts for the International Sale of Goods does not apply to this Agreement. The courts of California shall have exclusive jurisdiction of any dispute arising out of this Agreement.
"""
LICENSE """
Llama 2 Acceptable Use Policy
Meta is committed to promoting safe and fair use of its tools and features, including Llama 2. If you access or use Llama 2, you agree to this Acceptable Use Policy (“Policy”). The most recent copy of this policy can be found at ai.meta.com/llama/use-policy.
Prohibited Uses
We want everyone to use Llama 2 safely and responsibly. You agree you will not use, or allow others to use, Llama 2 to:
1. Violate the law or others rights, including to:
a. Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as:
i. Violence or terrorism
ii. Exploitation or harm to children, including the solicitation, creation, acquisition, or dissemination of child exploitative content or failure to report Child Sexual Abuse Material
b. Human trafficking, exploitation, and sexual violence
iii. The illegal distribution of information or materials to minors, including obscene materials, or failure to employ legally required age-gating in connection with such information or materials.
iv. Sexual solicitation
vi. Any other criminal activity
c. Engage in, promote, incite, or facilitate the harassment, abuse, threatening, or bullying of individuals or groups of individuals
d. Engage in, promote, incite, or facilitate discrimination or other unlawful or harmful conduct in the provision of employment, employment benefits, credit, housing, other economic benefits, or other essential goods and services
e. Engage in the unauthorized or unlicensed practice of any profession including, but not limited to, financial, legal, medical/health, or related professional practices
f. Collect, process, disclose, generate, or infer health, demographic, or other sensitive personal or private information about individuals without rights and consents required by applicable laws
g. Engage in or facilitate any action or generate any content that infringes, misappropriates, or otherwise violates any third-party rights, including the outputs or results of any products or services using the Llama 2 Materials
h. Create, generate, or facilitate the creation of malicious code, malware, computer viruses or do anything else that could disable, overburden, interfere with or impair the proper working, integrity, operation or appearance of a website or computer system
2. Engage in, promote, incite, facilitate, or assist in the planning or development of activities that present a risk of death or bodily harm to individuals, including use of Llama 2 related to the following:
a. Military, warfare, nuclear industries or applications, espionage, use for materials or activities that are subject to the International Traffic Arms Regulations (ITAR) maintained by the United States Department of State
b. Guns and illegal weapons (including weapon development)
c. Illegal drugs and regulated/controlled substances
d. Operation of critical infrastructure, transportation technologies, or heavy machinery
e. Self-harm or harm to others, including suicide, cutting, and eating disorders
f. Any content intended to incite or promote violence, abuse, or any infliction of bodily harm to an individual
3. Intentionally deceive or mislead others, including use of Llama 2 related to the following:
a. Generating, promoting, or furthering fraud or the creation or promotion of disinformation
b. Generating, promoting, or furthering defamatory content, including the creation of defamatory statements, images, or other content
c. Generating, promoting, or further distributing spam
d. Impersonating another individual without consent, authorization, or legal right
e. Representing that the use of Llama 2 or outputs are human-generated
f. Generating or facilitating false online engagement, including fake reviews and other means of fake online engagement
4. Fail to appropriately disclose to end users any known dangers of your AI system
Please report any violation of this Policy, software “bug,” or other problems that could lead to a violation of this Policy through one of the following means:
Reporting issues with the model: github.com/facebookresearch/llama
Reporting risky content generated by the model: developers.facebook.com/llama_output_feedback
Reporting bugs and security concerns: facebook.com/whitehat/info
Reporting violations of the Acceptable Use Policy or unlicensed uses of Llama: LlamaUseReport@meta.com
"""

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@@ -0,0 +1,7 @@
FROM ../models/nous-hermes-13b.ggmlv3.q4_0.bin
TEMPLATE """
### Instruction:
{{ .Prompt }}
### Response:
"""

14
library/modelfiles/orca Normal file
View File

@@ -0,0 +1,14 @@
FROM ../models/orca-mini-3b.ggmlv3.q4_0.bin
TEMPLATE """
{{- if .First }}
### System:
{{ .System }}
{{- end }}
### User:
{{ .Prompt }}
### Response:
"""
SYSTEM """You are an AI assistant that follows instruction extremely well. Help as much as you can."""

11
library/modelfiles/vicuna Normal file
View File

@@ -0,0 +1,11 @@
FROM ../models/vicuna-7b-v1.3.ggmlv3.q4_0.bin
TEMPLATE """
{{ if .First }}
{{ .System }}
{{- end }}
USER: {{ .Prompt }}
ASSISTANT:
"""
SYSTEM """A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions."""

View File

@@ -0,0 +1,5 @@
FROM ../models/Wizard-Vicuna-13B-Uncensored.ggmlv3.q4_0.bin
TEMPLATE """
USER: {{ .Prompt }}
ASSISTANT:
"""

52
library/publish.sh Executable file
View File

@@ -0,0 +1,52 @@
#!/bin/bash
mkdir -p models
# download binaries
function process_line {
local url=$1
local checksum=$2
# Get the filename from the URL
local filename=models/$(basename $url)
echo "verifying $filename..."
# If the file exists, compute its checksum
if [ -f $filename ]; then
local existing_checksum=$(shasum -a 256 $filename | cut -d ' ' -f1)
fi
# If the file does not exist, or its checksum does not match, download it
if [ ! -f $filename ] || [ $existing_checksum != $checksum ]; then
echo "downloading $filename..."
# Download the file
curl -L $url -o $filename
# Compute the SHA256 hash of the downloaded file
local computed_checksum=$(shasum -a 256 $filename | cut -d ' ' -f1)
# Verify the checksum
if [ $computed_checksum != $checksum ]; then
echo "Checksum verification failed for $filename"
exit 1
fi
fi
}
while IFS=' ' read -r url checksum
do
process_line $url $checksum
done < "downloads"
# create and publish the models
for file in modelfiles/*; do
if [ -f "$file" ]; then
filename=$(basename "$file")
echo $filename
ollama create "library/${filename}" -f "$file"
ollama push "${filename}"
fi
done

567
llama/ggml-alloc.c Normal file
View File

@@ -0,0 +1,567 @@
/**
* llama.cpp - git 8183159cf3def112f6d1fe94815fce70e1bffa12
*
* MIT License
*
* Copyright (c) 2023 Georgi Gerganov
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "ggml-alloc.h"
#include "ggml.h"
#include <assert.h>
#include <stdarg.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#define UNUSED(x) (void)(x)
#define MAX(a, b) ((a) > (b) ? (a) : (b))
//#define GGML_ALLOCATOR_DEBUG
//#define AT_PRINTF printf
#define AT_PRINTF(...) ((void)0)
struct hash_node {
struct ggml_tensor * t;
int n_children;
int n_views;
};
static size_t hash(void * p) {
return (size_t)p % GGML_GRAPH_HASHTABLE_SIZE;
}
static struct hash_node * hash_get(struct hash_node hash_table[], struct ggml_tensor * t) {
size_t h = hash(t);
// linear probing
size_t i = h;
while (hash_table[i].t != NULL) {
if (hash_table[i].t == t) {
return &hash_table[i];
}
i = (i + 1) % GGML_GRAPH_HASHTABLE_SIZE;
if (i == h) {
// hash table is full
GGML_ASSERT(false);
}
}
hash_table[i].t = t;
return &hash_table[i];
}
// TODO: GGML_PAD ?
static size_t aligned_offset(const void * buffer, size_t offset, size_t alignment) {
assert(alignment && !(alignment & (alignment - 1))); // power of 2
size_t align = (alignment - (((uintptr_t)buffer + offset) % alignment)) % alignment;
return offset + align;
}
struct free_block {
void * addr;
size_t size;
};
#define MAX_FREE_BLOCKS 128
struct ggml_allocr {
void * data;
size_t size;
size_t alignment;
int n_free_blocks;
struct free_block free_blocks[MAX_FREE_BLOCKS];
struct hash_node hash_table[GGML_GRAPH_HASHTABLE_SIZE];
size_t max_size;
bool measure;
#ifdef GGML_ALLOCATOR_DEBUG
struct ggml_tensor * allocated_tensors[1024];
#endif
};
#ifdef GGML_ALLOCATOR_DEBUG
static void add_allocated_tensor(struct ggml_allocator * alloc, struct ggml_tensor * tensor) {
for (int i = 0; i < 1024; i++) {
if (alloc->allocated_tensors[i] == NULL) {
alloc->allocated_tensors[i] = tensor;
return;
}
}
GGML_ASSERT(!"out of allocated_tensors");
}
static void remove_allocated_tensor(struct ggml_allocator * alloc, struct ggml_tensor * tensor) {
for (int i = 0; i < 1024; i++) {
if (alloc->allocated_tensors[i] == tensor ||
(alloc->allocated_tensors[i] != NULL && alloc->allocated_tensors[i]->data == tensor->data)) {
alloc->allocated_tensors[i] = NULL;
return;
}
}
printf("tried to free tensor %s not found\n", tensor->name);
GGML_ASSERT(!"tensor not found");
}
#endif
static size_t ggml_allocator_get_alloc_size(struct ggml_allocr * alloc, struct ggml_tensor * tensor) {
return ggml_nbytes(tensor);
UNUSED(alloc);
}
void ggml_allocr_alloc(struct ggml_allocr * alloc, struct ggml_tensor * tensor) {
size_t size = ggml_allocator_get_alloc_size(alloc, tensor);
size = aligned_offset(NULL, size, alloc->alignment);
AT_PRINTF("%s: allocating %s (%zu bytes) - ", __func__, tensor->name, size);
size_t max_avail = 0;
// find the best fitting free block
int best_fit_block = -1;
size_t best_fit_size = SIZE_MAX;
for (int i = 0; i < alloc->n_free_blocks; i++) {
struct free_block * block = &alloc->free_blocks[i];
max_avail = MAX(max_avail, block->size);
if (block->size >= size && block->size <= best_fit_size) {
best_fit_block = i;
best_fit_size = block->size;
}
}
AT_PRINTF("block %d\n", best_fit_block);
if (best_fit_block == -1) {
fprintf(stderr, "%s: not enough space in the buffer (needed %zu, largest block available %zu)\n",
__func__, size, max_avail);
GGML_ASSERT(!"not enough space in the buffer");
return;
}
struct free_block * block = &alloc->free_blocks[best_fit_block];
void * addr = block->addr;
block->addr = (char*)block->addr + size;
block->size -= size;
if (block->size == 0) {
// remove block if empty
alloc->n_free_blocks--;
for (int j = best_fit_block; j < alloc->n_free_blocks; j++) {
alloc->free_blocks[j] = alloc->free_blocks[j+1];
}
}
tensor->data = addr;
#ifdef GGML_ALLOCATOR_DEBUG
add_allocated_tensor(alloc, tensor);
size_t cur_max = (char*)addr - (char*)alloc->data + size;
if (cur_max > alloc->max_size) {
printf("max_size = %.2f MB: tensors: ", cur_max / 1024.0 / 1024.0);
for (int i = 0; i < 1024; i++) {
if (alloc->allocated_tensors[i]) {
printf("%s (%.2f MB) ", alloc->allocated_tensors[i]->name, ggml_nbytes(alloc->allocated_tensors[i]) / 1024.0 / 1024.0);
}
}
printf("\n");
}
#endif
alloc->max_size = MAX(alloc->max_size, (char*)addr - (char*)alloc->data + size);
}
// this is a very naive implementation, but for our case the number of free blocks should be very small
static void ggml_allocator_free_tensor(struct ggml_allocr * alloc, struct ggml_tensor * tensor) {
void * ptr = tensor->data;
if (ptr < alloc->data || (char*)ptr >= (char*)alloc->data + alloc->max_size) {
// the tensor was not allocated in this buffer
// this can happen because the graph allocator will try to free weights and other tensors from different buffers
// the easiest way to deal with this is just to ignore it
return;
}
size_t size = ggml_allocator_get_alloc_size(alloc, tensor);
size = aligned_offset(NULL, size, alloc->alignment);
AT_PRINTF("%s: freeing %s (%zu bytes) - n_free_blocks = %d\n", __func__, tensor->name, size, alloc->n_free_blocks);
#ifdef GGML_ALLOCATOR_DEBUG
remove_allocated_tensor(alloc, tensor);
#endif
// see if we can merge with an existing block
for (int i = 0; i < alloc->n_free_blocks; i++) {
struct free_block * block = &alloc->free_blocks[i];
// check if ptr is at the end of the block
if ((char*)block->addr + block->size == ptr) {
block->size += size;
// check if we can merge with the next block
if (i < alloc->n_free_blocks - 1 && (char*)block->addr + block->size == alloc->free_blocks[i+1].addr) {
block->size += alloc->free_blocks[i+1].size;
alloc->n_free_blocks--;
for (int j = i+1; j < alloc->n_free_blocks; j++) {
alloc->free_blocks[j] = alloc->free_blocks[j+1];
}
}
return;
}
// check if ptr is at the beginning of the block
if ((char*)ptr + size == block->addr) {
block->addr = ptr;
block->size += size;
// check if we can merge with the previous block
if (i > 0 && (char*)alloc->free_blocks[i-1].addr + alloc->free_blocks[i-1].size == block->addr) {
alloc->free_blocks[i-1].size += block->size;
alloc->n_free_blocks--;
for (int j = i; j < alloc->n_free_blocks; j++) {
alloc->free_blocks[j] = alloc->free_blocks[j+1];
}
}
return;
}
}
// otherwise, add a new block
GGML_ASSERT(alloc->n_free_blocks < MAX_FREE_BLOCKS && "out of free blocks");
// insert the new block in the correct position to keep the array sorted by address (to make merging blocks faster)
int insert_pos = 0;
while (insert_pos < alloc->n_free_blocks && alloc->free_blocks[insert_pos].addr < ptr) {
insert_pos++;
}
// shift all blocks from insert_pos onward to make room for the new block
for (int i = alloc->n_free_blocks; i > insert_pos; i--) {
alloc->free_blocks[i] = alloc->free_blocks[i-1];
}
// insert the new block
alloc->free_blocks[insert_pos].addr = ptr;
alloc->free_blocks[insert_pos].size = size;
alloc->n_free_blocks++;
}
void ggml_allocr_reset(struct ggml_allocr * alloc) {
alloc->n_free_blocks = 1;
size_t align_offset = aligned_offset(alloc->data, 0, alloc->alignment);
alloc->free_blocks[0].addr = (char *)alloc->data + align_offset;
alloc->free_blocks[0].size = alloc->size - align_offset;
}
struct ggml_allocr * ggml_allocr_new(void * data, size_t size, size_t alignment) {
struct ggml_allocr * alloc = (struct ggml_allocr *)malloc(sizeof(struct ggml_allocr) /* + n_free_blocks * sizeof(struct free_block) */);
*alloc = (struct ggml_allocr){
/*.data = */ data,
/*.size = */ size,
/*.alignment = */ alignment,
/*.n_free_blocks = */ 0,
/*.free_blocks = */ {{0}},
/*.hash_table = */ {{0}},
/*.max_size = */ 0,
/*.measure = */ false,
#ifdef GGML_ALLOCATOR_DEBUG
/*.allocated_tensors = */ = {0},
#endif
};
ggml_allocr_reset(alloc);
return alloc;
}
// address and size of the buffer when measuring
// it needs to be large enough to fit all the tensors, but it cannot overlap with other existing buffers
static void * const MEASURE_BASE_ADDR = (void *) 0x1000;
static const size_t MEASURE_MAX_SIZE = 1ULL<<40; // 1 TB
struct ggml_allocr * ggml_allocr_new_measure(size_t alignment) {
struct ggml_allocr * alloc = (struct ggml_allocr *)malloc(sizeof(struct ggml_allocr) /* + n_free_blocks * sizeof(struct free_block) */);
*alloc = (struct ggml_allocr){
/*.data = */ MEASURE_BASE_ADDR,
/*.size = */ MEASURE_MAX_SIZE,
/*.alignment = */ alignment,
/*.n_free_blocks = */ 0,
/*.free_blocks = */ {{0}},
/*.hash_table = */ {{0}},
/*.max_size = */ 0,
/*.measure = */ true,
#ifdef GGML_ALLOCATOR_DEBUG
/*.allocated_tensors = */ = {0},
#endif
};
ggml_allocr_reset(alloc);
return alloc;
}
void ggml_allocr_free(struct ggml_allocr * alloc) {
free(alloc);
}
bool ggml_allocr_is_measure(struct ggml_allocr * alloc) {
return alloc->measure;
}
//////////// compute graph allocator
static bool ggml_is_view(struct ggml_tensor * t) {
return t->op == GGML_OP_RESHAPE || t->op == GGML_OP_VIEW || t->op == GGML_OP_TRANSPOSE ||
t->op == GGML_OP_PERMUTE || t->op == GGML_OP_CPY;
}
static bool ggml_are_same_layout(const struct ggml_tensor * a, const struct ggml_tensor * b) {
if (a->type != b->type) {
return false;
}
for (int i = 0; i < GGML_MAX_DIMS; i++) {
if (a->ne[i] != b->ne[i]) {
return false;
}
if (a->nb[i] != b->nb[i]) {
return false;
}
}
return true;
}
static struct ggml_tensor * get_view_parent(struct ggml_tensor * t) {
switch (t->op) {
case GGML_OP_PERMUTE:
case GGML_OP_RESHAPE:
case GGML_OP_TRANSPOSE:
case GGML_OP_VIEW:
return t->src[0];
case GGML_OP_CPY:
return t->src[1];
default:
return NULL;
}
}
static struct ggml_tensor * get_view_source(struct ggml_tensor * t) {
struct ggml_tensor * parent = t;
do {
parent = get_view_parent(parent);
} while (ggml_is_view(parent));
return parent;
}
static bool ggml_op_can_inplace(enum ggml_op op) {
switch (op) {
case GGML_OP_SCALE:
case GGML_OP_DIAG_MASK_ZERO:
case GGML_OP_DIAG_MASK_INF:
case GGML_OP_ADD:
case GGML_OP_ADD1:
case GGML_OP_ACC:
case GGML_OP_SUB:
case GGML_OP_MUL:
case GGML_OP_DIV:
case GGML_OP_SQR:
case GGML_OP_SQRT:
case GGML_OP_LOG:
case GGML_OP_UNARY:
case GGML_OP_ROPE:
case GGML_OP_RMS_NORM:
case GGML_OP_SET:
case GGML_OP_SOFT_MAX:
case GGML_OP_CONT:
return true;
default:
return false;
}
}
static void allocate_node(struct ggml_allocr * alloc, struct ggml_tensor * node) {
struct hash_node * ht = alloc->hash_table;
if (node->data == NULL) {
if (ggml_is_view(node)) {
size_t offset;
switch(node->op) {
case GGML_OP_VIEW:
memcpy(&offset, node->op_params, sizeof(size_t));
node->data = (char *) node->src[0]->data + offset;
break;
case GGML_OP_PERMUTE:
case GGML_OP_RESHAPE:
case GGML_OP_TRANSPOSE:
node->data = node->src[0]->data;
break;
case GGML_OP_CPY:
node->data = node->src[1]->data;
break;
default:
GGML_ASSERT(!"unknown view op");
break;
}
} else {
// see if we can reuse a parent's buffer (inplace)
if (ggml_op_can_inplace(node->op)) {
for (int i = 0; i < GGML_MAX_SRC; i++) {
struct ggml_tensor * parent = node->src[i];
if (parent == NULL) {
break;
}
struct hash_node * p_hn = hash_get(ht, parent);
if (parent->data != NULL && p_hn->n_children == 1 && p_hn->n_views == 0 && ggml_are_same_layout(node, parent)) {
if (ggml_is_view(parent)) {
struct ggml_tensor * view_src = get_view_source(parent);
struct hash_node * view_src_hn = hash_get(ht, view_src);
if (view_src_hn->n_views == 1 && view_src_hn->n_children == 0 && view_src->data == parent->data) {
// TODO: the offset of the view parent must be kept to ensure that the op doesn't overwrite
// the parent's data that it will need later (same layout requirement). the problem is that then
// we cannot free the tensor because the original address of the allocation is lost.
// adding a view_src pointer to the tensor would solve this and simplify the code dealing with views
// for now, we only reuse the parent's data if the offset is zero (view_src->data == parent->data)
AT_PRINTF("reusing view parent %s (%s) for %s\n", parent->name, view_src->name, node->name);
node->data = parent->data;
return;
}
}
else {
AT_PRINTF("reusing parent %s for %s\n", parent->name, node->name);
node->data = parent->data;
}
return;
}
}
}
ggml_allocr_alloc(alloc, node);
}
}
}
static size_t ggml_allocator_alloc_graph_tensors_n(
struct ggml_allocr * alloc,
struct ggml_cgraph ** graphs, int n_graphs,
struct ggml_tensor *** inputs, struct ggml_tensor *** outputs) {
// reset hash table
struct hash_node * ht = alloc->hash_table;
memset(ht, 0, sizeof(struct hash_node) * GGML_GRAPH_HASHTABLE_SIZE);
// count number of children and views
for (int g = 0; g < n_graphs; g++) {
struct ggml_cgraph * gf = graphs[g];
for (int i = 0; i < gf->n_nodes; i++) {
struct ggml_tensor * node = gf->nodes[i];
if (ggml_is_view(node)) {
struct ggml_tensor * view_src = get_view_source(node);
hash_get(ht, view_src)->n_views += 1;
}
for (int j = 0; j < GGML_MAX_SRC; j++) {
struct ggml_tensor * parent = node->src[j];
if (parent == NULL) {
break;
}
hash_get(ht, parent)->n_children += 1;
}
}
}
// allocate tensors
for (int g = 0; g < n_graphs; g++) {
struct ggml_cgraph * gf = graphs[g];
AT_PRINTF("####### graph %d/%d\n", g, n_graphs);
// graph inputs are allocated first to ensure that they are not overwritten by each other
if (inputs != NULL && inputs[g] != NULL) {
for (int i = 0; inputs[g][i] != NULL; i++) {
struct ggml_tensor * input = inputs[g][i];
AT_PRINTF("input: %s\n", input->name);
allocate_node(alloc, input);
}
}
for (int i = 0; i < gf->n_nodes; i++) {
struct ggml_tensor * node = gf->nodes[i];
// allocate parents (leafs)
for (int j = 0; j < GGML_MAX_SRC; j++) {
struct ggml_tensor * parent = node->src[j];
if (parent == NULL) {
break;
}
allocate_node(alloc, parent);
}
// allocate node
allocate_node(alloc, node);
AT_PRINTF("exec: %s (%s) <= ", ggml_op_name(node->op), node->name);
for (int j = 0; j < GGML_MAX_SRC; j++) {
struct ggml_tensor * parent = node->src[j];
if (parent == NULL) {
break;
}
AT_PRINTF("%s", parent->name);
if (j < GGML_MAX_SRC - 1 && node->src[j + 1] != NULL) {
AT_PRINTF(", ");
}
}
AT_PRINTF("\n");
// update parents
for (int j = 0; j < GGML_MAX_SRC; j++) {
struct ggml_tensor * parent = node->src[j];
if (parent == NULL) {
break;
}
struct hash_node * p_hn = hash_get(ht, parent);
p_hn->n_children -= 1;
//AT_PRINTF("parent %s: %d children, %d views\n", parent->name, parent->n_children, parent->n_views);
if (p_hn->n_children == 0 && p_hn->n_views == 0) {
if (ggml_is_view(parent)) {
struct ggml_tensor * view_src = get_view_source(parent);
struct hash_node * view_src_hn = hash_get(ht, view_src);
view_src_hn->n_views -= 1;
AT_PRINTF("view_src %s: %d children, %d views\n", view_src->name, view_src->n_children, view_src->n_views);
if (view_src_hn->n_views == 0 && view_src_hn->n_children == 0 && view_src->data != node->data) {
ggml_allocator_free_tensor(alloc, view_src);
}
}
else {
if (parent->data != node->data) {
ggml_allocator_free_tensor(alloc, parent);
}
}
}
}
AT_PRINTF("\n");
}
// free graph outputs here that wouldn't be freed otherwise because they have no children
if (outputs != NULL && outputs[g] != NULL) {
for (int i = 0; outputs[g][i] != NULL; i++) {
struct ggml_tensor * output = outputs[g][i];
AT_PRINTF("output: %s\n", output->name);
ggml_allocator_free_tensor(alloc, output);
}
}
}
return alloc->max_size;
}
size_t ggml_allocr_alloc_graph(struct ggml_allocr * alloc, struct ggml_cgraph * graph) {
return ggml_allocator_alloc_graph_tensors_n(alloc, &graph, 1, NULL, NULL);
}

48
llama/ggml-alloc.h Normal file
View File

@@ -0,0 +1,48 @@
/**
* llama.cpp - git 8183159cf3def112f6d1fe94815fce70e1bffa12
*
* MIT License
*
* Copyright (c) 2023 Georgi Gerganov
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#pragma once
#include "ggml.h"
#ifdef __cplusplus
extern "C" {
#endif
GGML_API struct ggml_allocr * ggml_allocr_new(void * data, size_t size, size_t alignment);
GGML_API struct ggml_allocr * ggml_allocr_new_measure(size_t alignment);
GGML_API void ggml_allocr_free(struct ggml_allocr * alloc);
GGML_API bool ggml_allocr_is_measure(struct ggml_allocr * alloc);
GGML_API void ggml_allocr_reset(struct ggml_allocr * alloc);
GGML_API void ggml_allocr_alloc(struct ggml_allocr * alloc, struct ggml_tensor * tensor);
GGML_API size_t ggml_allocr_alloc_graph(struct ggml_allocr * alloc, struct ggml_cgraph * graph);
#ifdef __cplusplus
}
#endif

File diff suppressed because it is too large Load Diff

View File

@@ -1,5 +1,5 @@
/**
* llama.cpp - git 5bf2a2771886ee86137e01dbc7492f78fb392066
* llama.cpp - git 8183159cf3def112f6d1fe94815fce70e1bffa12
*
* MIT License
*
@@ -53,6 +53,7 @@ void ggml_cuda_assign_buffers(struct ggml_tensor * tensor);
void ggml_cuda_assign_buffers_no_scratch(struct ggml_tensor * tensor);
void ggml_cuda_assign_buffers_force_inplace(struct ggml_tensor * tensor);
void ggml_cuda_set_main_device(int main_device);
void ggml_cuda_set_mul_mat_q(bool mul_mat_q);
void ggml_cuda_set_scratch_size(size_t scratch_size);
void ggml_cuda_free_scratch(void);
bool ggml_cuda_compute_forward(struct ggml_compute_params * params, struct ggml_tensor * tensor);

View File

@@ -1,5 +1,7 @@
//go:build darwin
/**
* llama.cpp - git 5bf2a2771886ee86137e01dbc7492f78fb392066
* llama.cpp - git 8183159cf3def112f6d1fe94815fce70e1bffa12
*
* MIT License
*
@@ -87,6 +89,13 @@ void ggml_metal_set_tensor(struct ggml_metal_context * ctx, struct ggml_tensor *
// get data from the device into host memory
void ggml_metal_get_tensor(struct ggml_metal_context * ctx, struct ggml_tensor * t);
// try to find operations that can be run concurrently in the graph
// you should run it again if the topology of your graph changes
void ggml_metal_graph_find_concurrency(struct ggml_metal_context * ctx, struct ggml_cgraph * gf);
// if the graph has been optimized for concurrently dispatch
bool ggml_metal_if_optimized(struct ggml_metal_context * ctx);
// same as ggml_graph_compute but uses Metal
// creates gf->n_threads command buffers in parallel
void ggml_metal_graph_compute(struct ggml_metal_context * ctx, struct ggml_cgraph * gf);

View File

@@ -1,7 +1,7 @@
// +build darwin
//go:build darwin
/**
* llama.cpp - git 5bf2a2771886ee86137e01dbc7492f78fb392066
* llama.cpp - git 8183159cf3def112f6d1fe94815fce70e1bffa12
*
* MIT License
*
@@ -64,12 +64,16 @@ struct ggml_metal_context {
int n_buffers;
struct ggml_metal_buffer buffers[GGML_METAL_MAX_BUFFERS];
int concur_list[GGML_MAX_NODES];
int concur_list_len;
// custom kernels
#define GGML_METAL_DECL_KERNEL(name) \
id<MTLFunction> function_##name; \
id<MTLComputePipelineState> pipeline_##name
GGML_METAL_DECL_KERNEL(add);
GGML_METAL_DECL_KERNEL(add_row); // TODO: avoid this extra kernel, instead extend the "add" kernel to support broadcast
GGML_METAL_DECL_KERNEL(mul);
GGML_METAL_DECL_KERNEL(mul_row); // TODO: avoid this extra kernel, instead extend the "mul" kernel to support broadcast
GGML_METAL_DECL_KERNEL(scale);
@@ -125,6 +129,7 @@ struct ggml_metal_context * ggml_metal_init(int n_cb) {
ctx->device = MTLCreateSystemDefaultDevice();
ctx->queue = [ctx->device newCommandQueue];
ctx->n_buffers = 0;
ctx->concur_list_len = 0;
// determine if we can use MPS
if (MPSSupportsMTLDevice(ctx->device)) {
@@ -185,6 +190,7 @@ struct ggml_metal_context * ggml_metal_init(int n_cb) {
fprintf(stderr, "%s: loaded %-32s %16p\n", __func__, "kernel_"#name, (void *) ctx->pipeline_##name);
GGML_METAL_ADD_KERNEL(add);
GGML_METAL_ADD_KERNEL(add_row);
GGML_METAL_ADD_KERNEL(mul);
GGML_METAL_ADD_KERNEL(mul_row);
GGML_METAL_ADD_KERNEL(scale);
@@ -243,6 +249,13 @@ void ggml_metal_set_n_cb(struct ggml_metal_context * ctx, int n_cb) {
ctx->n_cb = n_cb;
}
bool ggml_metal_if_optimized(struct ggml_metal_context * ctx) {
if (ctx->concur_list_len) {
return true;
}
return false;
}
// finds the Metal buffer that contains the tensor data on the GPU device
// the assumption is that there is 1-to-1 mapping between the host and device memory buffers, so we can find the
// Metal buffer based on the host memory pointer
@@ -381,11 +394,98 @@ void ggml_metal_get_tensor(
memcpy(t->data, (void *) ((uint8_t *) id_src.contents + offs), ggml_nbytes(t));
}
void ggml_metal_graph_find_concurrency(
struct ggml_metal_context * ctx,
struct ggml_cgraph * gf) {
int search_depth = gf->n_nodes; //we only find concurrency in this range to avoid wasting too much time
int nodes_unused[GGML_MAX_NODES];
for (int i = 0; i < GGML_MAX_NODES; i++) {ctx->concur_list[i] = 0;}
for (int i = 0; i < gf->n_nodes; i++) {nodes_unused[i] = 1;}
ctx->concur_list_len = 0;
int n_left = gf->n_nodes;
int n_start = 0; // all nodes before n_start at nodes_unused array have been sorted and store back to ctx->concur_list
int level_pos = 0; // at ctx->concur_list, the last layer (level) ends at level_pos
while (n_left > 0) {
// number of nodes at a layer (that can be issued concurrently)
int concurrency = 0;
for (int i = n_start; i < ((n_start + search_depth > gf->n_nodes) ? gf->n_nodes : n_start + search_depth); i++) {
if (nodes_unused[i]) {
// if the requirements for gf->nodes[i] are satisfied
int exe_flag=1;
// scan all srcs
for (int src_ind = 0; src_ind < GGML_MAX_SRC; src_ind++) {
struct ggml_tensor * src_cur = gf->nodes[i]->src[src_ind];
if (src_cur) {
// if is leaf nodes it's satisfied.
if (src_cur->op == GGML_OP_NONE && src_cur->grad == NULL) {continue;}
// otherwise this src should be the output from previous nodes.
int is_found = 0;
// scan 2*search_depth back because we inserted barrier.
for (int j = ((level_pos - 2*search_depth) < 0 ? 0 : (level_pos - 2*search_depth)); j < level_pos; j++) {
if (gf->nodes[ctx->concur_list[j]] == src_cur) {is_found = 1; break;}
}
if (is_found == 0) {exe_flag = 0; break;}
}
}
if (exe_flag) {
// check if nodes[i]'s data will be overwritten by a node before nodes[i].
// if node[5] and node[3] write to the same memory region, then we can't issue node[5] before node[3]
int64_t data_start = (int64_t) gf->nodes[i]->data;
int64_t length = (int64_t) ggml_nbytes(gf->nodes[i]);
for (int j = n_start; j < i; j++) {
if (nodes_unused[j] && gf->nodes[j]->op != GGML_OP_RESHAPE \
&& gf->nodes[j]->op != GGML_OP_VIEW \
&& gf->nodes[j]->op != GGML_OP_TRANSPOSE \
&& gf->nodes[j]->op != GGML_OP_PERMUTE) {
if (((int64_t)gf->nodes[j]->data) >= data_start + length || \
((int64_t)gf->nodes[j]->data) + (int64_t) ggml_nbytes(gf->nodes[j]) <= data_start) {
continue;
} else {
exe_flag = 0;
}
}
}
}
if (exe_flag) {
ctx->concur_list[level_pos + concurrency] = i;
nodes_unused[i] = 0;
concurrency++;
ctx->concur_list_len++;
}
}
}
n_left -= concurrency;
// adding a barrier different layer
ctx->concur_list[level_pos + concurrency] = -1;
ctx->concur_list_len++;
// jump all sorted nodes at nodes_bak
while (!nodes_unused[n_start]) {n_start++;}
level_pos += concurrency + 1;
}
if (ctx->concur_list_len > GGML_MAX_NODES) {
fprintf(stderr, "%s: too many elements for metal ctx->concur_list!\n", __func__);
}
}
void ggml_metal_graph_compute(
struct ggml_metal_context * ctx,
struct ggml_cgraph * gf) {
metal_printf("%s: evaluating graph\n", __func__);
// if there is ctx->concur_list, dispatch concurrently
// else fallback to serial dispatch
MTLComputePassDescriptor * edesc = MTLComputePassDescriptor.computePassDescriptor;
const bool has_concur = ctx->concur_list_len && ctx->concur_list_len <= GGML_MAX_NODES;
const int n_nodes = has_concur ? ctx->concur_list_len : gf->n_nodes;
edesc.dispatchType = has_concur ? MTLDispatchTypeConcurrent : MTLDispatchTypeSerial;
// create multiple command buffers and enqueue them
// then, we encode the graph into the command buffers in parallel
@@ -404,7 +504,7 @@ void ggml_metal_graph_compute(
dispatch_queue_t queue = dispatch_queue_create("llama.cpp", DISPATCH_QUEUE_CONCURRENT);
for (int cb_idx = 0; cb_idx < n_cb; ++cb_idx) {
const int n_nodes_per_cb = (gf->n_nodes + n_cb - 1) / n_cb;
const int n_nodes_per_cb = (n_nodes + n_cb - 1) / n_cb;
dispatch_async(queue, ^{
size_t offs_src0 = 0;
@@ -415,10 +515,21 @@ void ggml_metal_graph_compute(
id<MTLComputeCommandEncoder> encoder = nil;
const int node_start = (cb_idx + 0) * n_nodes_per_cb;
const int node_end = (cb_idx == n_cb - 1) ? gf->n_nodes : (cb_idx + 1) * n_nodes_per_cb;
const int node_start = (cb_idx + 0) * n_nodes_per_cb;
const int node_end = (cb_idx == n_cb - 1) ? n_nodes : (cb_idx + 1) * n_nodes_per_cb;
for (int ind = node_start; ind < node_end; ++ind) {
const int i = has_concur ? ctx->concur_list[ind] : ind;
if (i == -1) {
if (encoder == nil) {
encoder = [command_buffer computeCommandEncoderWithDescriptor: edesc];
continue;
}
[encoder memoryBarrierWithScope:MTLBarrierScopeBuffers];
continue;
}
for (int i = node_start; i < node_end; ++i) {
metal_printf("%s: encoding node %3d, op = %8s\n", __func__, i, ggml_op_name(gf->nodes[i]->op));
struct ggml_tensor * src0 = gf->nodes[i]->src[0];
@@ -489,13 +600,19 @@ void ggml_metal_graph_compute(
case GGML_OP_ADD:
{
if (encoder == nil) {
encoder = [command_buffer computeCommandEncoder];
encoder = [command_buffer computeCommandEncoderWithDescriptor: edesc];
}
[encoder setComputePipelineState:ctx->pipeline_add];
if (ggml_nelements(src1) == ne10) {
// src1 is a row
[encoder setComputePipelineState:ctx->pipeline_add_row];
} else {
[encoder setComputePipelineState:ctx->pipeline_add];
}
[encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
[encoder setBuffer:id_src1 offset:offs_src1 atIndex:1];
[encoder setBuffer:id_dst offset:offs_dst atIndex:2];
[encoder setBytes:&ne00 length:sizeof(ne00) atIndex:3];
const int64_t n = ggml_nelements(dst);
@@ -504,7 +621,7 @@ void ggml_metal_graph_compute(
case GGML_OP_MUL:
{
if (encoder == nil) {
encoder = [command_buffer computeCommandEncoder];
encoder = [command_buffer computeCommandEncoderWithDescriptor: edesc];
}
if (ggml_nelements(src1) == ne10) {
@@ -525,7 +642,7 @@ void ggml_metal_graph_compute(
case GGML_OP_SCALE:
{
if (encoder == nil) {
encoder = [command_buffer computeCommandEncoder];
encoder = [command_buffer computeCommandEncoderWithDescriptor: edesc];
}
const float scale = *(const float *) src1->data;
@@ -539,52 +656,60 @@ void ggml_metal_graph_compute(
[encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
} break;
case GGML_OP_SILU:
{
if (encoder == nil) {
encoder = [command_buffer computeCommandEncoder];
}
case GGML_OP_UNARY:
switch (ggml_get_unary_op(gf->nodes[i])) {
case GGML_UNARY_OP_SILU:
{
if (encoder == nil) {
encoder = [command_buffer computeCommandEncoderWithDescriptor: edesc];
}
[encoder setComputePipelineState:ctx->pipeline_silu];
[encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
[encoder setBuffer:id_dst offset:offs_dst atIndex:1];
[encoder setComputePipelineState:ctx->pipeline_silu];
[encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
[encoder setBuffer:id_dst offset:offs_dst atIndex:1];
const int64_t n = ggml_nelements(dst);
const int64_t n = ggml_nelements(dst);
[encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
[encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
} break;
case GGML_UNARY_OP_RELU:
{
if (encoder == nil) {
encoder = [command_buffer computeCommandEncoderWithDescriptor: edesc];
}
[encoder setComputePipelineState:ctx->pipeline_relu];
[encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
[encoder setBuffer:id_dst offset:offs_dst atIndex:1];
const int64_t n = ggml_nelements(dst);
[encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
} break;
case GGML_UNARY_OP_GELU:
{
if (encoder == nil) {
encoder = [command_buffer computeCommandEncoderWithDescriptor: edesc];
}
[encoder setComputePipelineState:ctx->pipeline_gelu];
[encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
[encoder setBuffer:id_dst offset:offs_dst atIndex:1];
const int64_t n = ggml_nelements(dst);
[encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
} break;
default:
{
fprintf(stderr, "%s: node %3d, op = %8s not implemented\n", __func__, i, ggml_op_name(dst->op));
GGML_ASSERT(false);
}
} break;
case GGML_OP_RELU:
{
if (encoder == nil) {
encoder = [command_buffer computeCommandEncoder];
}
[encoder setComputePipelineState:ctx->pipeline_relu];
[encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
[encoder setBuffer:id_dst offset:offs_dst atIndex:1];
const int64_t n = ggml_nelements(dst);
[encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
} break;
case GGML_OP_GELU:
{
if (encoder == nil) {
encoder = [command_buffer computeCommandEncoder];
}
[encoder setComputePipelineState:ctx->pipeline_gelu];
[encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
[encoder setBuffer:id_dst offset:offs_dst atIndex:1];
const int64_t n = ggml_nelements(dst);
[encoder dispatchThreadgroups:MTLSizeMake(n, 1, 1) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
} break;
case GGML_OP_SOFT_MAX:
{
if (encoder == nil) {
encoder = [command_buffer computeCommandEncoder];
encoder = [command_buffer computeCommandEncoderWithDescriptor: edesc];
}
const int nth = 32;
@@ -602,10 +727,10 @@ void ggml_metal_graph_compute(
case GGML_OP_DIAG_MASK_INF:
{
if (encoder == nil) {
encoder = [command_buffer computeCommandEncoder];
encoder = [command_buffer computeCommandEncoderWithDescriptor: edesc];
}
const int n_past = ((int32_t *)(src1->data))[0];
const int n_past = ((int32_t *)(dst->op_params))[0];
[encoder setComputePipelineState:ctx->pipeline_diag_mask_inf];
[encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
@@ -621,7 +746,8 @@ void ggml_metal_graph_compute(
// TODO: needs to be updated after PR: https://github.com/ggerganov/ggml/pull/224
GGML_ASSERT(ne00 == ne10);
GGML_ASSERT(ne02 == ne12);
// GGML_ASSERT(ne02 == ne12); // Should be checked on individual data types until broadcast is implemented everywhere
GGML_ASSERT(ne03 == ne13);
if (ggml_is_contiguous(src0) &&
ggml_is_contiguous(src1) &&
@@ -649,11 +775,11 @@ void ggml_metal_graph_compute(
initWithDevice:ctx->device transposeLeft:false transposeRight:true
resultRows:ne11 resultColumns:ne01 interiorColumns:ne00 alpha:1.0 beta:0.0];
// we need to do ne02 multiplications
// we need to do ne12 multiplications
// TODO: is there a way to do this in parallel - currently very slow ..
// TODO: might be possible to offload part of the computation to ANE using Accelerate's CBLAS
for (int64_t i02 = 0; i02 < ne02; ++i02) {
size_t offs_src0_cur = offs_src0 + i02*nb02;
for (int64_t i02 = 0; i02 < ne12; ++i02) {
size_t offs_src0_cur = offs_src0 + i02/(ne12/ne02)*nb02; // gqa not used for now
size_t offs_src1_cur = offs_src1 + i02*nb12;
size_t offs_dst_cur = offs_dst + i02*nb2;
@@ -665,7 +791,7 @@ void ggml_metal_graph_compute(
}
} else {
if (encoder == nil) {
encoder = [command_buffer computeCommandEncoder];
encoder = [command_buffer computeCommandEncoderWithDescriptor: edesc];
}
int nth0 = 32;
@@ -675,8 +801,6 @@ void ggml_metal_graph_compute(
switch (src0t) {
case GGML_TYPE_F16:
{
GGML_ASSERT(ne02 == ne12);
nth0 = 64;
nth1 = 1;
[encoder setComputePipelineState:ctx->pipeline_mul_mat_f16_f32];
@@ -704,8 +828,8 @@ void ggml_metal_graph_compute(
GGML_ASSERT(ne02 == 1);
GGML_ASSERT(ne12 == 1);
nth0 = 4;
nth1 = 16;
nth0 = 2;
nth1 = 32;
[encoder setComputePipelineState:ctx->pipeline_mul_mat_q2_K_f32];
} break;
case GGML_TYPE_Q3_K:
@@ -713,8 +837,8 @@ void ggml_metal_graph_compute(
GGML_ASSERT(ne02 == 1);
GGML_ASSERT(ne12 == 1);
nth0 = 4;
nth1 = 16;
nth0 = 2;
nth1 = 32;
[encoder setComputePipelineState:ctx->pipeline_mul_mat_q3_K_f32];
} break;
case GGML_TYPE_Q4_K:
@@ -722,8 +846,8 @@ void ggml_metal_graph_compute(
GGML_ASSERT(ne02 == 1);
GGML_ASSERT(ne12 == 1);
nth0 = 4;
nth1 = 16;
nth0 = 2;
nth1 = 32;
[encoder setComputePipelineState:ctx->pipeline_mul_mat_q4_K_f32];
} break;
case GGML_TYPE_Q5_K:
@@ -731,8 +855,8 @@ void ggml_metal_graph_compute(
GGML_ASSERT(ne02 == 1);
GGML_ASSERT(ne12 == 1);
nth0 = 4;
nth1 = 16;
nth0 = 2;
nth1 = 32;
[encoder setComputePipelineState:ctx->pipeline_mul_mat_q5_K_f32];
} break;
case GGML_TYPE_Q6_K:
@@ -740,8 +864,8 @@ void ggml_metal_graph_compute(
GGML_ASSERT(ne02 == 1);
GGML_ASSERT(ne12 == 1);
nth0 = 4;
nth1 = 16;
nth0 = 2;
nth1 = 32;
[encoder setComputePipelineState:ctx->pipeline_mul_mat_q6_K_f32];
} break;
default:
@@ -756,28 +880,35 @@ void ggml_metal_graph_compute(
[encoder setBuffer:id_dst offset:offs_dst atIndex:2];
[encoder setBytes:&ne00 length:sizeof(ne00) atIndex:3];
[encoder setBytes:&ne01 length:sizeof(ne01) atIndex:4];
[encoder setBytes:&nb00 length:sizeof(nb00) atIndex:5];
[encoder setBytes:&nb01 length:sizeof(nb01) atIndex:6];
[encoder setBytes:&nb02 length:sizeof(nb02) atIndex:7];
[encoder setBytes:&ne10 length:sizeof(ne10) atIndex:8];
[encoder setBytes:&ne11 length:sizeof(ne11) atIndex:9];
[encoder setBytes:&nb10 length:sizeof(nb10) atIndex:10];
[encoder setBytes:&nb11 length:sizeof(nb11) atIndex:11];
[encoder setBytes:&nb12 length:sizeof(nb12) atIndex:12];
[encoder setBytes:&ne0 length:sizeof(ne0) atIndex:13];
[encoder setBytes:&ne1 length:sizeof(ne1) atIndex:14];
[encoder setBytes:&ne02 length:sizeof(ne02) atIndex:5];
[encoder setBytes:&nb00 length:sizeof(nb00) atIndex:6];
[encoder setBytes:&nb01 length:sizeof(nb01) atIndex:7];
[encoder setBytes:&nb02 length:sizeof(nb02) atIndex:8];
[encoder setBytes:&ne10 length:sizeof(ne10) atIndex:9];
[encoder setBytes:&ne11 length:sizeof(ne11) atIndex:10];
[encoder setBytes:&ne12 length:sizeof(ne12) atIndex:11];
[encoder setBytes:&nb10 length:sizeof(nb10) atIndex:12];
[encoder setBytes:&nb11 length:sizeof(nb11) atIndex:13];
[encoder setBytes:&nb12 length:sizeof(nb12) atIndex:14];
[encoder setBytes:&ne0 length:sizeof(ne0) atIndex:15];
[encoder setBytes:&ne1 length:sizeof(ne1) atIndex:16];
if (src0t == GGML_TYPE_Q4_0 || src0t == GGML_TYPE_Q4_1) {
[encoder setThreadgroupMemoryLength:nth0*nth1*sizeof(float) atIndex:0];
[encoder dispatchThreadgroups:MTLSizeMake(ne01, ne11, 1) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
if (src0t == GGML_TYPE_Q4_0 || src0t == GGML_TYPE_Q4_1 ||
src0t == GGML_TYPE_Q2_K || src0t == GGML_TYPE_Q4_K) {
[encoder dispatchThreadgroups:MTLSizeMake((ne01 + 7) / 8, ne11, 1) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
}
else if (src0t == GGML_TYPE_Q2_K ||
src0t == GGML_TYPE_Q3_K ||
src0t == GGML_TYPE_Q4_K ||
src0t == GGML_TYPE_Q5_K ||
src0t == GGML_TYPE_Q6_K) {
[encoder setThreadgroupMemoryLength:nth0*nth1*sizeof(float) atIndex:0];
[encoder dispatchThreadgroups:MTLSizeMake(ne01, 1, 1) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
else if (src0t == GGML_TYPE_Q3_K) {
#ifdef GGML_QKK_64
[encoder dispatchThreadgroups:MTLSizeMake((ne01+1)/2, ne11, 1) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
#else
[encoder dispatchThreadgroups:MTLSizeMake((ne01+3)/4, ne11, 1) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
#endif
}
else if (src0t == GGML_TYPE_Q5_K) {
[encoder dispatchThreadgroups:MTLSizeMake((ne01 + 3) / 4, ne11, 1) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
}
else if (src0t == GGML_TYPE_Q6_K) {
[encoder dispatchThreadgroups:MTLSizeMake((ne01+1)/2, ne11, 1) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
} else {
[encoder setThreadgroupMemoryLength:nth0*sizeof(float) atIndex:0];
[encoder dispatchThreadgroups:MTLSizeMake(ne01, ne11, ne12) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
@@ -787,7 +918,7 @@ void ggml_metal_graph_compute(
case GGML_OP_GET_ROWS:
{
if (encoder == nil) {
encoder = [command_buffer computeCommandEncoder];
encoder = [command_buffer computeCommandEncoderWithDescriptor: edesc];
}
switch (src0->type) {
@@ -816,12 +947,13 @@ void ggml_metal_graph_compute(
case GGML_OP_RMS_NORM:
{
if (encoder == nil) {
encoder = [command_buffer computeCommandEncoder];
encoder = [command_buffer computeCommandEncoderWithDescriptor: edesc];
}
const float eps = 1e-6f;
float eps;
memcpy(&eps, dst->op_params, sizeof(float));
const int nth = 256;
const int nth = 512;
[encoder setComputePipelineState:ctx->pipeline_rms_norm];
[encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
@@ -829,7 +961,7 @@ void ggml_metal_graph_compute(
[encoder setBytes:&ne00 length:sizeof( int64_t) atIndex:2];
[encoder setBytes:&nb01 length:sizeof(uint64_t) atIndex:3];
[encoder setBytes:&eps length:sizeof( float) atIndex:4];
[encoder setThreadgroupMemoryLength:nth*sizeof(float) atIndex:0];
[encoder setThreadgroupMemoryLength:nth/32*sizeof(float) atIndex:0];
const int64_t nrows = ggml_nrows(src0);
@@ -838,7 +970,7 @@ void ggml_metal_graph_compute(
case GGML_OP_NORM:
{
if (encoder == nil) {
encoder = [command_buffer computeCommandEncoder];
encoder = [command_buffer computeCommandEncoderWithDescriptor: edesc];
}
const float eps = 1e-5f;
@@ -860,14 +992,15 @@ void ggml_metal_graph_compute(
case GGML_OP_ALIBI:
{
if (encoder == nil) {
encoder = [command_buffer computeCommandEncoder];
encoder = [command_buffer computeCommandEncoderWithDescriptor: edesc];
}
GGML_ASSERT((src0t == GGML_TYPE_F32));
const int n_past = ((int32_t *) src1->data)[0]; UNUSED(n_past);
const int n_head = ((int32_t *) src1->data)[1];
const float max_bias = ((float *) src1->data)[2];
const int n_past = ((int32_t *) dst->op_params)[0]; UNUSED(n_past);
const int n_head = ((int32_t *) dst->op_params)[1];
float max_bias;
memcpy(&max_bias, (int32_t *) dst->op_params + 2, sizeof(float));
if (__builtin_popcount(n_head) != 1) {
GGML_ASSERT(false && "only power-of-two n_head implemented");
@@ -902,43 +1035,51 @@ void ggml_metal_graph_compute(
case GGML_OP_ROPE:
{
if (encoder == nil) {
encoder = [command_buffer computeCommandEncoder];
encoder = [command_buffer computeCommandEncoderWithDescriptor: edesc];
}
const int n_dims = ((int32_t *) src1->data)[1];
const int mode = ((int32_t *) src1->data)[2];
const int n_past = ((int32_t *) dst->op_params)[0];
const int n_dims = ((int32_t *) dst->op_params)[1];
const int mode = ((int32_t *) dst->op_params)[2];
const int n_past = ((int32_t *)(src1->data))[0];
float freq_base;
float freq_scale;
memcpy(&freq_base, (int32_t *) dst->op_params + 4, sizeof(float));
memcpy(&freq_scale, (int32_t *) dst->op_params + 5, sizeof(float));
[encoder setComputePipelineState:ctx->pipeline_rope];
[encoder setBuffer:id_src0 offset:offs_src0 atIndex:0];
[encoder setBuffer:id_dst offset:offs_dst atIndex:1];
[encoder setBytes:&ne00 length:sizeof( int64_t) atIndex:2];
[encoder setBytes:&ne01 length:sizeof( int64_t) atIndex:3];
[encoder setBytes:&ne02 length:sizeof( int64_t) atIndex:4];
[encoder setBytes:&ne03 length:sizeof( int64_t) atIndex:5];
[encoder setBytes:&nb00 length:sizeof(uint64_t) atIndex:6];
[encoder setBytes:&nb01 length:sizeof(uint64_t) atIndex:7];
[encoder setBytes:&nb02 length:sizeof(uint64_t) atIndex:8];
[encoder setBytes:&nb03 length:sizeof(uint64_t) atIndex:9];
[encoder setBytes:&ne0 length:sizeof( int64_t) atIndex:10];
[encoder setBytes:&ne1 length:sizeof( int64_t) atIndex:11];
[encoder setBytes:&ne2 length:sizeof( int64_t) atIndex:12];
[encoder setBytes:&ne3 length:sizeof( int64_t) atIndex:13];
[encoder setBytes:&nb0 length:sizeof(uint64_t) atIndex:14];
[encoder setBytes:&nb1 length:sizeof(uint64_t) atIndex:15];
[encoder setBytes:&nb2 length:sizeof(uint64_t) atIndex:16];
[encoder setBytes:&nb3 length:sizeof(uint64_t) atIndex:17];
[encoder setBytes:&n_past length:sizeof( int) atIndex:18];
[encoder setBytes:&n_dims length:sizeof( int) atIndex:19];
[encoder setBytes:&mode length:sizeof( int) atIndex:20];
[encoder setBytes:&ne00 length:sizeof( int64_t) atIndex:2];
[encoder setBytes:&ne01 length:sizeof( int64_t) atIndex:3];
[encoder setBytes:&ne02 length:sizeof( int64_t) atIndex:4];
[encoder setBytes:&ne03 length:sizeof( int64_t) atIndex:5];
[encoder setBytes:&nb00 length:sizeof(uint64_t) atIndex:6];
[encoder setBytes:&nb01 length:sizeof(uint64_t) atIndex:7];
[encoder setBytes:&nb02 length:sizeof(uint64_t) atIndex:8];
[encoder setBytes:&nb03 length:sizeof(uint64_t) atIndex:9];
[encoder setBytes:&ne0 length:sizeof( int64_t) atIndex:10];
[encoder setBytes:&ne1 length:sizeof( int64_t) atIndex:11];
[encoder setBytes:&ne2 length:sizeof( int64_t) atIndex:12];
[encoder setBytes:&ne3 length:sizeof( int64_t) atIndex:13];
[encoder setBytes:&nb0 length:sizeof(uint64_t) atIndex:14];
[encoder setBytes:&nb1 length:sizeof(uint64_t) atIndex:15];
[encoder setBytes:&nb2 length:sizeof(uint64_t) atIndex:16];
[encoder setBytes:&nb3 length:sizeof(uint64_t) atIndex:17];
[encoder setBytes:&n_past length:sizeof( int) atIndex:18];
[encoder setBytes:&n_dims length:sizeof( int) atIndex:19];
[encoder setBytes:&mode length:sizeof( int) atIndex:20];
[encoder setBytes:&freq_base length:sizeof(float) atIndex:21];
[encoder setBytes:&freq_scale length:sizeof(float) atIndex:22];
[encoder dispatchThreadgroups:MTLSizeMake(ne01, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(1, 1, 1)];
} break;
case GGML_OP_DUP:
case GGML_OP_CPY:
case GGML_OP_CONT:
{
if (encoder == nil) {
encoder = [command_buffer computeCommandEncoder];
encoder = [command_buffer computeCommandEncoderWithDescriptor: edesc];
}
const int nth = 32;
@@ -985,8 +1126,10 @@ void ggml_metal_graph_compute(
[encoder dispatchThreadgroups:MTLSizeMake(ne01, ne02, ne03) threadsPerThreadgroup:MTLSizeMake(nth, 1, 1)];
} break;
default:
fprintf(stderr, "%s: node %3d, op = %8s not implemented\n", __func__, i, ggml_op_name(dst->op));
GGML_ASSERT(false);
{
fprintf(stderr, "%s: node %3d, op = %8s not implemented\n", __func__, i, ggml_op_name(dst->op));
GGML_ASSERT(false);
}
}
}

File diff suppressed because it is too large Load Diff

244
llama/ggml-mpi.c Normal file
View File

@@ -0,0 +1,244 @@
//go:build mpi
/**
* llama.cpp - git 8183159cf3def112f6d1fe94815fce70e1bffa12
*
* MIT License
*
* Copyright (c) 2023 Georgi Gerganov
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#include "ggml-mpi.h"
#include "ggml.h"
#include <mpi.h>
#include <stdio.h>
#include <stdlib.h>
#define MIN(a, b) ((a) < (b) ? (a) : (b))
#define UNUSED GGML_UNUSED
struct ggml_mpi_context {
int rank;
int size;
};
void ggml_mpi_backend_init(void) {
MPI_Init(NULL, NULL);
}
void ggml_mpi_backend_free(void) {
MPI_Finalize();
}
struct ggml_mpi_context * ggml_mpi_init(void) {
struct ggml_mpi_context * ctx = calloc(1, sizeof(struct ggml_mpi_context));
MPI_Comm_rank(MPI_COMM_WORLD, &ctx->rank);
MPI_Comm_size(MPI_COMM_WORLD, &ctx->size);
return ctx;
}
void ggml_mpi_free(struct ggml_mpi_context * ctx) {
free(ctx);
}
int ggml_mpi_rank(struct ggml_mpi_context * ctx) {
return ctx->rank;
}
void ggml_mpi_eval_init(
struct ggml_mpi_context * ctx_mpi,
int * n_tokens,
int * n_past,
int * n_threads) {
UNUSED(ctx_mpi);
// synchronize the worker node parameters with the root node
MPI_Barrier(MPI_COMM_WORLD);
MPI_Bcast(n_tokens, 1, MPI_INT, 0, MPI_COMM_WORLD);
MPI_Bcast(n_past, 1, MPI_INT, 0, MPI_COMM_WORLD);
MPI_Bcast(n_threads, 1, MPI_INT, 0, MPI_COMM_WORLD);
}
static int ggml_graph_get_node_idx(struct ggml_cgraph * gf, const char * name) {
struct ggml_tensor * t = ggml_graph_get_tensor(gf, name);
if (t == NULL) {
fprintf(stderr, "%s: tensor %s not found\n", __func__, name);
return -1;
}
for (int i = 0; i < gf->n_nodes; i++) {
if (gf->nodes[i] == t) {
return i;
}
}
fprintf(stderr, "%s: tensor %s not found in graph (should not happen)\n", __func__, name);
return -1;
}
static void ggml_mpi_tensor_send(struct ggml_tensor * t, int mpi_rank_dst) {
MPI_Datatype mpi_type;
switch (t->type) {
case GGML_TYPE_I32: mpi_type = MPI_INT32_T; break;
case GGML_TYPE_F32: mpi_type = MPI_FLOAT; break;
default: GGML_ASSERT(false && "not implemented");
}
const int retval = MPI_Send(t->data, ggml_nelements(t), mpi_type, mpi_rank_dst, 0, MPI_COMM_WORLD);
GGML_ASSERT(retval == MPI_SUCCESS);
}
static void ggml_mpi_tensor_recv(struct ggml_tensor * t, int mpi_rank_src) {
MPI_Datatype mpi_type;
switch (t->type) {
case GGML_TYPE_I32: mpi_type = MPI_INT32_T; break;
case GGML_TYPE_F32: mpi_type = MPI_FLOAT; break;
default: GGML_ASSERT(false && "not implemented");
}
MPI_Status status; UNUSED(status);
const int retval = MPI_Recv(t->data, ggml_nelements(t), mpi_type, mpi_rank_src, MPI_ANY_TAG, MPI_COMM_WORLD, &status);
GGML_ASSERT(retval == MPI_SUCCESS);
}
// TODO: there are many improvements that can be done to this implementation
void ggml_mpi_graph_compute_pre(
struct ggml_mpi_context * ctx_mpi,
struct ggml_cgraph * gf,
int n_layers) {
const int mpi_rank = ctx_mpi->rank;
const int mpi_size = ctx_mpi->size;
struct ggml_tensor * inp_tokens = ggml_graph_get_tensor(gf, "inp_tokens");
if (inp_tokens == NULL) {
fprintf(stderr, "%s: tensor 'inp_tokens' not found\n", __func__);
return;
}
struct ggml_tensor * inp0 = ggml_graph_get_tensor(gf, "layer_inp_0");
if (inp0 == NULL) {
fprintf(stderr, "%s: tensor 'inp0' not found\n", __func__);
return;
}
GGML_ASSERT(inp0 == gf->nodes[0]);
// distribute the compute graph into slices across the MPI nodes
//
// the main node (0) processes the last layers + the remainder of the compute graph
// and is responsible to pass the input tokens to the first node (1)
//
// node 1: [( 0) * n_per_node, ( 1) * n_per_node)
// node 2: [( 1) * n_per_node, ( 2) * n_per_node)
// ...
// node n-1: [(n-2) * n_per_node, (n-1) * n_per_node)
// node 0: [(n-1) * n_per_node, n_nodes)
//
if (mpi_rank > 0) {
if (mpi_rank == 1) {
// the first node (1) receives the input tokens from the main node (0)
ggml_mpi_tensor_recv(inp_tokens, 0);
} else {
// recv input data for each node into the "inp0" tensor (i.e. the first node in the compute graph)
ggml_mpi_tensor_recv(inp0, mpi_rank - 1);
}
} else if (mpi_size > 1) {
// node 0 sends the input tokens to node 1
ggml_mpi_tensor_send(inp_tokens, 1);
// recv the output data from the last node
ggml_mpi_tensor_recv(inp0, mpi_size - 1);
}
{
const int n_per_node = (n_layers + (mpi_size - 1)) / mpi_size;
const int mpi_idx = mpi_rank > 0 ? mpi_rank - 1 : mpi_size - 1;
const int il0 = (mpi_idx + 0) * n_per_node;
const int il1 = MIN(n_layers, (mpi_idx + 1) * n_per_node);
char name_l0[GGML_MAX_NAME];
char name_l1[GGML_MAX_NAME];
snprintf(name_l0, sizeof(name_l0), "layer_inp_%d", il0);
snprintf(name_l1, sizeof(name_l1), "layer_inp_%d", il1);
const int idx_l0 = ggml_graph_get_node_idx(gf, name_l0);
const int idx_l1 = mpi_rank > 0 ? ggml_graph_get_node_idx(gf, name_l1) + 1 : gf->n_nodes;
if (idx_l0 < 0 || idx_l1 < 0) {
fprintf(stderr, "%s: layer input nodes not found\n", __func__);
return;
}
// attach the input data to all nodes that need it
// TODO: not great - should be able to do this without modifying the compute graph (see next TODO below)
for (int i = idx_l0; i < idx_l1; i++) {
if (gf->nodes[i]->src[0] == gf->nodes[idx_l0]) {
gf->nodes[i]->src[0] = inp0;
}
if (gf->nodes[i]->src[1] == gf->nodes[idx_l0]) {
gf->nodes[i]->src[1] = inp0;
}
}
// TODO: instead of rearranging the nodes, we should be able to execute a subset of the compute graph
for (int i = 1; i < idx_l1 - idx_l0; i++) {
gf->nodes[i] = gf->nodes[idx_l0 + i];
gf->grads[i] = gf->grads[idx_l0 + i];
}
// the first node performs the "get_rows" operation, the rest of the nodes get the data from the previous node
if (mpi_idx != 0) {
gf->nodes[0]->op = GGML_OP_NONE;
}
gf->n_nodes = idx_l1 - idx_l0;
//fprintf(stderr, "%s: node %d: processing %d nodes [%d, %d)\n", __func__, mpi_rank, gf->n_nodes, il0, il1);
}
}
void ggml_mpi_graph_compute_post(
struct ggml_mpi_context * ctx_mpi,
struct ggml_cgraph * gf,
int n_layers) {
UNUSED(n_layers);
const int mpi_rank = ctx_mpi->rank;
const int mpi_size = ctx_mpi->size;
// send the output data to the next node
if (mpi_rank > 0) {
ggml_mpi_tensor_send(gf->nodes[gf->n_nodes - 1], (mpi_rank + 1) % mpi_size);
}
}

67
llama/ggml-mpi.h Normal file
View File

@@ -0,0 +1,67 @@
//go:build mpi
/**
* llama.cpp - git 8183159cf3def112f6d1fe94815fce70e1bffa12
*
* MIT License
*
* Copyright (c) 2023 Georgi Gerganov
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#pragma once
struct ggml_context;
struct ggml_tensor;
struct ggml_cgraph;
#ifdef __cplusplus
extern "C" {
#endif
struct ggml_mpi_context;
void ggml_mpi_backend_init(void);
void ggml_mpi_backend_free(void);
struct ggml_mpi_context * ggml_mpi_init(void);
void ggml_mpi_free(struct ggml_mpi_context * ctx);
int ggml_mpi_rank(struct ggml_mpi_context * ctx);
void ggml_mpi_eval_init(
struct ggml_mpi_context * ctx_mpi,
int * n_tokens,
int * n_past,
int * n_threads);
void ggml_mpi_graph_compute_pre(
struct ggml_mpi_context * ctx_mpi,
struct ggml_cgraph * gf,
int n_layers);
void ggml_mpi_graph_compute_post(
struct ggml_mpi_context * ctx_mpi,
struct ggml_cgraph * gf,
int n_layers);
#ifdef __cplusplus
}
#endif

1893
llama/ggml-opencl.cpp Normal file

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53
llama/ggml-opencl.h Normal file
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@@ -0,0 +1,53 @@
//go:build opencl
/**
* llama.cpp - git 8183159cf3def112f6d1fe94815fce70e1bffa12
*
* MIT License
*
* Copyright (c) 2023 Georgi Gerganov
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#pragma once
#include "ggml.h"
#ifdef __cplusplus
extern "C" {
#endif
void ggml_cl_init(void);
void ggml_cl_mul(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst);
bool ggml_cl_can_mul_mat(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst);
size_t ggml_cl_mul_mat_get_wsize(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst);
void ggml_cl_mul_mat(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst, void * wdata, size_t wsize);
void * ggml_cl_host_malloc(size_t size);
void ggml_cl_host_free(void * ptr);
void ggml_cl_free_data(const struct ggml_tensor* tensor);
void ggml_cl_transform_tensor(void * data, struct ggml_tensor * tensor);
#ifdef __cplusplus
}
#endif

File diff suppressed because it is too large Load Diff

View File

@@ -1,5 +1,5 @@
/**
* llama.cpp - git 5bf2a2771886ee86137e01dbc7492f78fb392066
* llama.cpp - git 8183159cf3def112f6d1fe94815fce70e1bffa12
*
* MIT License
*
@@ -225,10 +225,17 @@
#define GGML_MAX_CONTEXTS 64
#define GGML_MAX_SRC 6
#define GGML_MAX_NAME 48
#define GGML_MAX_OP_PARAMS 32
#define GGML_DEFAULT_N_THREADS 4
#define GGML_EXIT_SUCCESS 0
#define GGML_EXIT_ABORTED 1
#define GGML_UNUSED(x) (void)(x)
#define GGML_PAD(x, n) (((x) + (n) - 1) & ~((n) - 1))
#define GGML_ASSERT(x) \
do { \
if (!(x)) { \
@@ -350,16 +357,6 @@ extern "C" {
GGML_OP_ARGMAX,
GGML_OP_REPEAT,
GGML_OP_REPEAT_BACK,
GGML_OP_ABS,
GGML_OP_SGN,
GGML_OP_NEG,
GGML_OP_STEP,
GGML_OP_TANH,
GGML_OP_ELU,
GGML_OP_RELU,
GGML_OP_GELU,
GGML_OP_GELU_QUICK,
GGML_OP_SILU,
GGML_OP_SILU_BACK,
GGML_OP_NORM, // normalize
GGML_OP_RMS_NORM,
@@ -389,6 +386,8 @@ extern "C" {
GGML_OP_CLAMP,
GGML_OP_CONV_1D,
GGML_OP_CONV_2D,
GGML_OP_POOL_1D,
GGML_OP_POOL_2D,
GGML_OP_FLASH_ATTN,
GGML_OP_FLASH_FF,
@@ -396,6 +395,8 @@ extern "C" {
GGML_OP_WIN_PART,
GGML_OP_WIN_UNPART,
GGML_OP_UNARY,
GGML_OP_MAP_UNARY,
GGML_OP_MAP_BINARY,
@@ -409,6 +410,24 @@ extern "C" {
GGML_OP_COUNT,
};
enum ggml_unary_op {
GGML_UNARY_OP_ABS,
GGML_UNARY_OP_SGN,
GGML_UNARY_OP_NEG,
GGML_UNARY_OP_STEP,
GGML_UNARY_OP_TANH,
GGML_UNARY_OP_ELU,
GGML_UNARY_OP_RELU,
GGML_UNARY_OP_GELU,
GGML_UNARY_OP_GELU_QUICK,
GGML_UNARY_OP_SILU,
};
enum ggml_object_type {
GGML_OBJECT_TENSOR,
GGML_OBJECT_GRAPH,
GGML_OBJECT_WORK_BUFFER
};
// ggml object
struct ggml_object {
@@ -417,7 +436,9 @@ extern "C" {
struct ggml_object * next;
char padding[8];
enum ggml_object_type type;
char padding[4];
};
static const size_t GGML_OBJECT_SIZE = sizeof(struct ggml_object);
@@ -437,6 +458,9 @@ extern "C" {
// compute data
enum ggml_op op;
// op params - allocated as int32_t for alignment
int32_t op_params[GGML_MAX_OP_PARAMS / sizeof(int32_t)];
bool is_param;
struct ggml_tensor * grad;
@@ -453,7 +477,7 @@ extern "C" {
void * extra; // extra things e.g. for ggml-cuda.cu
char padding[8];
char padding[4];
};
static const size_t GGML_TENSOR_SIZE = sizeof(struct ggml_tensor);
@@ -468,8 +492,17 @@ extern "C" {
// the `n_tasks` of nodes, 1:1 mapping to cgraph nodes
int n_tasks[GGML_MAX_NODES];
// abort ggml_graph_compute when true
bool (*abort_callback)(void * data);
void * abort_callback_data;
};
// next prime after GGML_MAX_NODES
// #define GGML_GRAPH_HASHTABLE_SIZE 4099
// next prime after GGML_MAX_NODES * 2 (nodes + leafs)
#define GGML_GRAPH_HASHTABLE_SIZE 8273
// computation graph
struct ggml_cgraph {
int n_nodes;
@@ -479,12 +512,16 @@ extern "C" {
struct ggml_tensor * grads[GGML_MAX_NODES];
struct ggml_tensor * leafs[GGML_MAX_NODES];
void * visited_hash_table[GGML_GRAPH_HASHTABLE_SIZE];
// performance
int perf_runs;
int64_t perf_cycles;
int64_t perf_time_us;
};
static const size_t GGML_GRAPH_SIZE = sizeof(struct ggml_cgraph);
// scratch buffer
struct ggml_scratch {
size_t offs;
@@ -546,6 +583,7 @@ extern "C" {
GGML_API const char * ggml_type_name(enum ggml_type type);
GGML_API const char * ggml_op_name (enum ggml_op op);
GGML_API const char * ggml_op_symbol(enum ggml_op op);
GGML_API size_t ggml_element_size(const struct ggml_tensor * tensor);
@@ -569,6 +607,7 @@ extern "C" {
GGML_API size_t ggml_used_mem(const struct ggml_context * ctx);
GGML_API size_t ggml_set_scratch (struct ggml_context * ctx, struct ggml_scratch scratch);
GGML_API bool ggml_get_no_alloc(struct ggml_context * ctx);
GGML_API void ggml_set_no_alloc(struct ggml_context * ctx, bool no_alloc);
GGML_API void * ggml_get_mem_buffer (const struct ggml_context * ctx);
@@ -628,9 +667,11 @@ extern "C" {
GGML_API void * ggml_get_data (const struct ggml_tensor * tensor);
GGML_API float * ggml_get_data_f32(const struct ggml_tensor * tensor);
GGML_API const char * ggml_get_name(const struct ggml_tensor * tensor);
GGML_API struct ggml_tensor * ggml_set_name(struct ggml_tensor * tensor, const char * name);
GGML_API struct ggml_tensor * ggml_format_name(struct ggml_tensor * tensor, const char * fmt, ...);
GGML_API enum ggml_unary_op ggml_get_unary_op(const struct ggml_tensor * tensor);
GGML_API const char * ggml_get_name (const struct ggml_tensor * tensor);
GGML_API struct ggml_tensor * ggml_set_name ( struct ggml_tensor * tensor, const char * name);
GGML_API struct ggml_tensor * ggml_format_name( struct ggml_tensor * tensor, const char * fmt, ...);
//
// operations on tensors with backpropagation
@@ -640,6 +681,11 @@ extern "C" {
struct ggml_context * ctx,
struct ggml_tensor * a);
// in-place, returns view(a)
GGML_API struct ggml_tensor * ggml_dup_inplace(
struct ggml_context * ctx,
struct ggml_tensor * a);
GGML_API struct ggml_tensor * ggml_add(
struct ggml_context * ctx,
struct ggml_tensor * a,
@@ -864,14 +910,17 @@ extern "C" {
GGML_API struct ggml_tensor * ggml_rms_norm(
struct ggml_context * ctx,
struct ggml_tensor * a);
struct ggml_tensor * a,
float eps);
GGML_API struct ggml_tensor * ggml_rms_norm_inplace(
struct ggml_context * ctx,
struct ggml_tensor * a);
struct ggml_tensor * a,
float eps);
// a - x
// b - dy
// TODO: update with configurable eps
GGML_API struct ggml_tensor * ggml_rms_norm_back(
struct ggml_context * ctx,
struct ggml_tensor * a,
@@ -963,11 +1012,22 @@ extern "C" {
struct ggml_tensor * a,
struct ggml_tensor * b);
// a -> b, in-place, return view(b)
GGML_API struct ggml_tensor * ggml_cpy_inplace(
struct ggml_context * ctx,
struct ggml_tensor * a,
struct ggml_tensor * b);
// make contiguous
GGML_API struct ggml_tensor * ggml_cont(
struct ggml_context * ctx,
struct ggml_tensor * a);
// make contiguous, in-place
GGML_API struct ggml_tensor * ggml_cont_inplace(
struct ggml_context * ctx,
struct ggml_tensor * a);
// return view(a), b specifies the new shape
// TODO: when we start computing gradient, make a copy instead of view
GGML_API struct ggml_tensor * ggml_reshape(
@@ -1136,6 +1196,28 @@ extern "C" {
int mode,
int n_ctx);
// custom RoPE
GGML_API struct ggml_tensor * ggml_rope_custom(
struct ggml_context * ctx,
struct ggml_tensor * a,
int n_past,
int n_dims,
int mode,
int n_ctx,
float freq_base,
float freq_scale);
// in-place, returns view(a)
GGML_API struct ggml_tensor * ggml_rope_custom_inplace(
struct ggml_context * ctx,
struct ggml_tensor * a,
int n_past,
int n_dims,
int mode,
int n_ctx,
float freq_base,
float freq_scale);
// rotary position embedding backward, i.e compute dx from dy
// a - dy
GGML_API struct ggml_tensor * ggml_rope_back(
@@ -1143,7 +1225,8 @@ extern "C" {
struct ggml_tensor * a,
int n_past,
int n_dims,
int mode);
int mode,
int n_ctx);
// alibi position embedding
// in-place, returns view(a)
@@ -1190,6 +1273,31 @@ extern "C" {
int s,
int d);
enum ggml_op_pool {
GGML_OP_POOL_MAX,
GGML_OP_POOL_AVG,
GGML_OP_POOL_COUNT,
};
GGML_API struct ggml_tensor* ggml_pool_1d(
struct ggml_context * ctx,
struct ggml_tensor * a,
enum ggml_op_pool op,
int k0, // kernel size
int s0, // stride
int p0); // padding
GGML_API struct ggml_tensor* ggml_pool_2d(
struct ggml_context * ctx,
struct ggml_tensor * a,
enum ggml_op_pool op,
int k0,
int k1,
int s0,
int s1,
int p0,
int p1);
GGML_API struct ggml_tensor * ggml_flash_attn(
struct ggml_context * ctx,
struct ggml_tensor * q,
@@ -1242,6 +1350,16 @@ extern "C" {
typedef void (*ggml_custom2_op_f32_t)(struct ggml_tensor *, const struct ggml_tensor *, const struct ggml_tensor *);
typedef void (*ggml_custom3_op_f32_t)(struct ggml_tensor *, const struct ggml_tensor *, const struct ggml_tensor *, const struct ggml_tensor *);
GGML_API struct ggml_tensor * ggml_unary(
struct ggml_context * ctx,
struct ggml_tensor * a,
enum ggml_unary_op op);
GGML_API struct ggml_tensor * ggml_unary_inplace(
struct ggml_context * ctx,
struct ggml_tensor * a,
enum ggml_unary_op op);
GGML_API struct ggml_tensor * ggml_map_unary_f32(
struct ggml_context * ctx,
struct ggml_tensor * a,
@@ -1321,15 +1439,21 @@ extern "C" {
struct ggml_context * ctx,
struct ggml_tensor * tensor);
GGML_API void ggml_build_forward_expand(struct ggml_cgraph * cgraph, struct ggml_tensor * tensor);
GGML_API struct ggml_cgraph ggml_build_forward (struct ggml_tensor * tensor);
GGML_API struct ggml_cgraph ggml_build_backward(struct ggml_context * ctx, struct ggml_cgraph * gf, bool keep);
// graph allocation in a context
GGML_API struct ggml_cgraph * ggml_new_graph (struct ggml_context * ctx);
GGML_API struct ggml_cgraph * ggml_build_forward_ctx(struct ggml_context * ctx, struct ggml_tensor * tensor);
GGML_API size_t ggml_graph_overhead(void);
// ggml_graph_plan() has to be called before ggml_graph_compute()
// when plan.work_size > 0, caller must allocate memory for plan.work_data
GGML_API struct ggml_cplan ggml_graph_plan (struct ggml_cgraph * cgraph, int n_threads /*= GGML_DEFAULT_N_THREADS*/);
GGML_API void ggml_graph_compute(struct ggml_cgraph * cgraph, struct ggml_cplan * cplan);
GGML_API int ggml_graph_compute(struct ggml_cgraph * cgraph, struct ggml_cplan * cplan);
GGML_API void ggml_graph_reset (struct ggml_cgraph * cgraph);
// same as ggml_graph_compute() but the work data is allocated as a part of the context

View File

@@ -1,5 +1,5 @@
/**
* llama.cpp - git 5bf2a2771886ee86137e01dbc7492f78fb392066
* llama.cpp - git 8183159cf3def112f6d1fe94815fce70e1bffa12
*
* MIT License
*
@@ -65,6 +65,8 @@
#define MIN(a, b) ((a) < (b) ? (a) : (b))
#define MAX(a, b) ((a) > (b) ? (a) : (b))
#define MM256_SET_M128I(a, b) _mm256_insertf128_si256(_mm256_castsi128_si256(b), (a), 1)
//
// 2-6 bit quantization in super-blocks
//
@@ -1379,7 +1381,7 @@ void ggml_vec_dot_q2_K_q8_K(const int n, float * restrict s, const void * restri
const __m256i all_scales = _mm256_cvtepi8_epi16(scales8);
const __m128i l_scales = _mm256_extracti128_si256(all_scales, 0);
const __m128i h_scales = _mm256_extracti128_si256(all_scales, 1);
const __m256i scales[2] = {_mm256_set_m128i(l_scales, l_scales), _mm256_set_m128i(h_scales, h_scales)};
const __m256i scales[2] = {MM256_SET_M128I(l_scales, l_scales), MM256_SET_M128I(h_scales, h_scales)};
__m256i sumi = _mm256_setzero_si256();
@@ -1447,7 +1449,7 @@ void ggml_vec_dot_q2_K_q8_K(const int n, float * restrict s, const void * restri
const __m128i summs_1 = _mm_madd_epi16(mins_1, _mm_loadu_si128((const __m128i*)&y[i].bsums[8]));
// sumf += -dmin * summs in 32bits*8
acc = _mm256_add_ps(_mm256_mul_ps(_mm256_broadcast_ss(&dmin), _mm256_cvtepi32_ps(_mm256_set_m128i(summs_1, summs_0))), acc);
acc = _mm256_add_ps(_mm256_mul_ps(_mm256_broadcast_ss(&dmin), _mm256_cvtepi32_ps(MM256_SET_M128I(summs_1, summs_0))), acc);
const __m128i scales_0 = _mm_cvtepi8_epi16(scales16);
const __m128i scales_1 = _mm_cvtepi8_epi16(_mm_unpackhi_epi64(scales16, scales16));
@@ -1519,7 +1521,7 @@ void ggml_vec_dot_q2_K_q8_K(const int n, float * restrict s, const void * restri
}
// sumf += dall * isum - dmin * summs in 32bits
__m256i sumi = _mm256_set_m128i(sumi_1, sumi_0);
__m256i sumi = MM256_SET_M128I(sumi_1, sumi_0);
acc = _mm256_add_ps(_mm256_mul_ps(_mm256_broadcast_ss(&dall), _mm256_cvtepi32_ps(sumi)), acc);
}
@@ -1670,8 +1672,8 @@ void ggml_vec_dot_q2_K_q8_K(const int n, float * restrict s, const void * restri
summs += dmin * smin;
const __m128i q2bits = _mm_loadu_si128((const __m128i*)q2);
const __m256i q2_0 = _mm256_and_si256(_mm256_set_m128i(_mm_srli_epi16(q2bits, 2), q2bits), m3);
const __m256i q2_1 = _mm256_and_si256(_mm256_set_m128i(_mm_srli_epi16(q2bits, 6), _mm_srli_epi16(q2bits, 4)), m3);
const __m256i q2_0 = _mm256_and_si256(MM256_SET_M128I(_mm_srli_epi16(q2bits, 2), q2bits), m3);
const __m256i q2_1 = _mm256_and_si256(MM256_SET_M128I(_mm_srli_epi16(q2bits, 6), _mm_srli_epi16(q2bits, 4)), m3);
const __m256i q8_0 = _mm256_loadu_si256((const __m256i*)(q8+ 0));
const __m256i q8_1 = _mm256_loadu_si256((const __m256i*)(q8+32));
@@ -1692,6 +1694,62 @@ void ggml_vec_dot_q2_K_q8_K(const int n, float * restrict s, const void * restri
*s = hsum_float_8(acc) + summs;
#elif defined __AVX__
const __m128i m3 = _mm_set1_epi8(3);
__m256 acc = _mm256_setzero_ps();
uint32_t ud, um;
const uint8_t * restrict db = (const uint8_t *)&ud;
const uint8_t * restrict mb = (const uint8_t *)&um;
float summs = 0;
// TODO: optimize this
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * ggml_fp16_to_fp32(x[i].d);
const float dmin = -y[i].d * ggml_fp16_to_fp32(x[i].dmin);
const uint8_t * restrict q2 = x[i].qs;
const int8_t * restrict q8 = y[i].qs;
const uint32_t * restrict sc = (const uint32_t *)x[i].scales;
ud = (sc[0] >> 0) & 0x0f0f0f0f;
um = (sc[0] >> 4) & 0x0f0f0f0f;
int32_t smin = mb[0] * y[i].bsums[0] + mb[1] * y[i].bsums[1] + mb[2] * y[i].bsums[2] + mb[3] * y[i].bsums[3];
summs += dmin * smin;
const __m128i q2bits = _mm_loadu_si128((const __m128i*)q2);
const __m128i q2_0 = _mm_and_si128(q2bits, m3);
const __m128i q2_1 = _mm_and_si128(_mm_srli_epi16(q2bits, 2), m3);
const __m128i q2_2 = _mm_and_si128(_mm_srli_epi16(q2bits, 4), m3);
const __m128i q2_3 = _mm_and_si128(_mm_srli_epi16(q2bits, 6), m3);
const __m256i q8_0 = _mm256_loadu_si256((const __m256i*)(q8+ 0));
const __m256i q8_1 = _mm256_loadu_si256((const __m256i*)(q8+32));
const __m128i p0 = _mm_maddubs_epi16(q2_0, _mm256_extractf128_si256(q8_0, 0));
const __m128i p1 = _mm_maddubs_epi16(q2_1, _mm256_extractf128_si256(q8_0, 1));
const __m128i p2 = _mm_maddubs_epi16(q2_2, _mm256_extractf128_si256(q8_1, 0));
const __m128i p3 = _mm_maddubs_epi16(q2_3, _mm256_extractf128_si256(q8_1, 1));
const __m256i p_0 = MM256_SET_M128I(_mm_cvtepi16_epi32(_mm_unpackhi_epi64(p0, p0)), _mm_cvtepi16_epi32(p0));
const __m256i p_1 = MM256_SET_M128I(_mm_cvtepi16_epi32(_mm_unpackhi_epi64(p1, p1)), _mm_cvtepi16_epi32(p1));
const __m256i p_2 = MM256_SET_M128I(_mm_cvtepi16_epi32(_mm_unpackhi_epi64(p2, p2)), _mm_cvtepi16_epi32(p2));
const __m256i p_3 = MM256_SET_M128I(_mm_cvtepi16_epi32(_mm_unpackhi_epi64(p3, p3)), _mm_cvtepi16_epi32(p3));
acc = _mm256_add_ps(_mm256_mul_ps(_mm256_set1_ps(d * db[0]), _mm256_cvtepi32_ps(p_0)), acc);
acc = _mm256_add_ps(_mm256_mul_ps(_mm256_set1_ps(d * db[1]), _mm256_cvtepi32_ps(p_1)), acc);
acc = _mm256_add_ps(_mm256_mul_ps(_mm256_set1_ps(d * db[2]), _mm256_cvtepi32_ps(p_2)), acc);
acc = _mm256_add_ps(_mm256_mul_ps(_mm256_set1_ps(d * db[3]), _mm256_cvtepi32_ps(p_3)), acc);
}
*s = hsum_float_8(acc) + summs;
#else
float sumf = 0;
@@ -1887,7 +1945,7 @@ void ggml_vec_dot_q3_K_q8_K(const int n, float * restrict s, const void * restri
const __m256i all_scales = _mm256_cvtepi8_epi16(scales128);
const __m128i l_scales = _mm256_extracti128_si256(all_scales, 0);
const __m128i h_scales = _mm256_extracti128_si256(all_scales, 1);
const __m256i scales[2] = {_mm256_set_m128i(l_scales, l_scales), _mm256_set_m128i(h_scales, h_scales)};
const __m256i scales[2] = {MM256_SET_M128I(l_scales, l_scales), MM256_SET_M128I(h_scales, h_scales)};
// high bit
const __m256i hbits = _mm256_loadu_si256((const __m256i*)x[i].hmask);
@@ -2098,7 +2156,7 @@ void ggml_vec_dot_q3_K_q8_K(const int n, float * restrict s, const void * restri
}
// multiply with block scale and accumulate
__m256i sumi = _mm256_set_m128i(sumi_1, sumi_0);
__m256i sumi = MM256_SET_M128I(sumi_1, sumi_0);
acc = _mm256_add_ps(_mm256_mul_ps(_mm256_broadcast_ss(&d), _mm256_cvtepi32_ps(sumi)), acc);
}
@@ -2273,13 +2331,13 @@ void ggml_vec_dot_q3_K_q8_K(const int n, float * restrict s, const void * restri
aux16[0] = a & 0x0f0f;
aux16[1] = (a >> 4) & 0x0f0f;
const __m256i scale_0 = _mm256_set_m128i(_mm_set1_epi16(aux8[2] - 8), _mm_set1_epi16(aux8[0] - 8));
const __m256i scale_1 = _mm256_set_m128i(_mm_set1_epi16(aux8[3] - 8), _mm_set1_epi16(aux8[1] - 8));
const __m256i scale_0 = MM256_SET_M128I(_mm_set1_epi16(aux8[2] - 8), _mm_set1_epi16(aux8[0] - 8));
const __m256i scale_1 = MM256_SET_M128I(_mm_set1_epi16(aux8[3] - 8), _mm_set1_epi16(aux8[1] - 8));
memcpy(&aux64, x[i].hmask, 8);
const __m128i haux = _mm_set_epi64x(aux64 >> 1, aux64 >> 0);
__m256i q3h_0 = _mm256_set_m128i(_mm_srli_epi16(haux, 2), haux);
__m256i q3h_0 = MM256_SET_M128I(_mm_srli_epi16(haux, 2), haux);
__m256i q3h_1 = _mm256_srli_epi16(q3h_0, 4);
q3h_0 = _mm256_slli_epi16(_mm256_andnot_si256(q3h_0, m1), 2);
q3h_1 = _mm256_slli_epi16(_mm256_andnot_si256(q3h_1, m1), 2);
@@ -2288,7 +2346,7 @@ void ggml_vec_dot_q3_K_q8_K(const int n, float * restrict s, const void * restri
const __m128i q3bits = _mm_loadu_si128((const __m128i*)q3);
// prepare low and high bits
const __m256i q3aux = _mm256_set_m128i(_mm_srli_epi16(q3bits, 2), q3bits);
const __m256i q3aux = MM256_SET_M128I(_mm_srli_epi16(q3bits, 2), q3bits);
const __m256i q3l_0 = _mm256_and_si256(q3aux, m3);
const __m256i q3l_1 = _mm256_and_si256(_mm256_srli_epi16(q3aux, 4), m3);
@@ -2321,6 +2379,93 @@ void ggml_vec_dot_q3_K_q8_K(const int n, float * restrict s, const void * restri
*s = hsum_float_8(acc);
#elif defined __AVX__
const __m128i m3 = _mm_set1_epi8(3);
const __m128i m1 = _mm_set1_epi8(1);
__m256 acc = _mm256_setzero_ps();
uint64_t aux64;
uint16_t aux16[2];
const int8_t * aux8 = (const int8_t *)aux16;
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * ggml_fp16_to_fp32(x[i].d);
const uint8_t * restrict q3 = x[i].qs;
const int8_t * restrict q8 = y[i].qs;
const uint16_t a = *(const uint16_t *)x[i].scales;
aux16[0] = a & 0x0f0f;
aux16[1] = (a >> 4) & 0x0f0f;
const __m128i scale_0 = _mm_set1_epi16(aux8[0] - 8);
const __m128i scale_1 = _mm_set1_epi16(aux8[2] - 8);
const __m128i scale_2 = _mm_set1_epi16(aux8[1] - 8);
const __m128i scale_3 = _mm_set1_epi16(aux8[3] - 8);
memcpy(&aux64, x[i].hmask, 8);
__m128i q3h_0 = _mm_set_epi64x(aux64 >> 1, aux64 >> 0);
__m128i q3h_1 = _mm_srli_epi16(q3h_0, 2);
__m128i q3h_2 = _mm_srli_epi16(q3h_0, 4);
__m128i q3h_3 = _mm_srli_epi16(q3h_0, 6);
q3h_0 = _mm_slli_epi16(_mm_andnot_si128(q3h_0, m1), 2);
q3h_1 = _mm_slli_epi16(_mm_andnot_si128(q3h_1, m1), 2);
q3h_2 = _mm_slli_epi16(_mm_andnot_si128(q3h_2, m1), 2);
q3h_3 = _mm_slli_epi16(_mm_andnot_si128(q3h_3, m1), 2);
// load low 2 bits
const __m128i q3bits = _mm_loadu_si128((const __m128i*)q3);
// prepare low and high bits
const __m128i q3l_0 = _mm_and_si128(q3bits, m3);
const __m128i q3l_1 = _mm_and_si128(_mm_srli_epi16(q3bits, 2), m3);
const __m128i q3l_2 = _mm_and_si128(_mm_srli_epi16(q3bits, 4), m3);
const __m128i q3l_3 = _mm_and_si128(_mm_srli_epi16(q3bits, 6), m3);
// load Q8 quants
const __m256i q8_0 = _mm256_loadu_si256((const __m256i*)(q8+ 0));
const __m256i q8_1 = _mm256_loadu_si256((const __m256i*)(q8+32));
// Dot product: we multiply the 2 low bits and 1 high bit part separately, so we can use _mm_maddubs_epi16,
// and then subtract. The high bit part has the 2 already subtracted (and so, it is zero if the high bit was not set,
// and 2 if the high bit was set)
const __m128i q8s_0 = _mm_maddubs_epi16(q3h_0, _mm256_extractf128_si256(q8_0, 0));
const __m128i q8s_1 = _mm_maddubs_epi16(q3h_1, _mm256_extractf128_si256(q8_0, 1));
const __m128i q8s_2 = _mm_maddubs_epi16(q3h_2, _mm256_extractf128_si256(q8_1, 0));
const __m128i q8s_3 = _mm_maddubs_epi16(q3h_3, _mm256_extractf128_si256(q8_1, 1));
__m128i p16_0 = _mm_maddubs_epi16(q3l_0, _mm256_extractf128_si256(q8_0, 0));
__m128i p16_1 = _mm_maddubs_epi16(q3l_1, _mm256_extractf128_si256(q8_0, 1));
__m128i p16_2 = _mm_maddubs_epi16(q3l_2, _mm256_extractf128_si256(q8_1, 0));
__m128i p16_3 = _mm_maddubs_epi16(q3l_3, _mm256_extractf128_si256(q8_1, 1));
p16_0 = _mm_sub_epi16(p16_0, q8s_0);
p16_1 = _mm_sub_epi16(p16_1, q8s_1);
p16_2 = _mm_sub_epi16(p16_2, q8s_2);
p16_3 = _mm_sub_epi16(p16_3, q8s_3);
// multiply with scales
p16_0 = _mm_madd_epi16(scale_0, p16_0);
p16_1 = _mm_madd_epi16(scale_1, p16_1);
p16_2 = _mm_madd_epi16(scale_2, p16_2);
p16_3 = _mm_madd_epi16(scale_3, p16_3);
p16_0 = _mm_add_epi32(p16_0, p16_2);
p16_1 = _mm_add_epi32(p16_1, p16_3);
__m256i p16 = MM256_SET_M128I(p16_1, p16_0);
// multiply with block scale and accumulate
acc = _mm256_add_ps(_mm256_mul_ps(_mm256_broadcast_ss(&d), _mm256_cvtepi32_ps(p16)), acc);
}
*s = hsum_float_8(acc);
#else
int8_t aux8[QK_K];
@@ -2503,7 +2648,7 @@ void ggml_vec_dot_q4_K_q8_K(const int n, float * restrict s, const void * restri
acc_m = _mm_fmadd_ps(_mm_set1_ps(dmin), _mm_cvtepi32_ps(prod), acc_m);
const __m128i sc128 = _mm256_extracti128_si256(mins_and_scales, 0);
const __m256i scales = _mm256_set_m128i(sc128, sc128);
const __m256i scales = MM256_SET_M128I(sc128, sc128);
__m256i sumi = _mm256_setzero_si256();
@@ -2610,7 +2755,7 @@ void ggml_vec_dot_q4_K_q8_K(const int n, float * restrict s, const void * restri
}
__m256 vd = _mm256_set1_ps(d);
__m256i sumi = _mm256_set_m128i(sumi_1, sumi_0);
__m256i sumi = MM256_SET_M128I(sumi_1, sumi_0);
acc = _mm256_add_ps(_mm256_mul_ps(vd, _mm256_cvtepi32_ps(sumi)), acc);
}
@@ -2807,6 +2952,60 @@ void ggml_vec_dot_q4_K_q8_K(const int n, float * restrict s, const void * restri
*s = hsum_float_8(acc) - summs;
#elif defined __AVX__
const __m128i m4 = _mm_set1_epi8(0xF);
__m256 acc = _mm256_setzero_ps();
float summs = 0;
uint16_t aux16[2];
const uint8_t * scales = (const uint8_t *)aux16;
for (int i = 0; i < nb; ++i) {
const float d = ggml_fp16_to_fp32(x[i].d[0]) * y[i].d;
const float m = ggml_fp16_to_fp32(x[i].d[1]) * y[i].d;
const __m256 vd = _mm256_set1_ps(d);
const uint16_t * a = (const uint16_t *)x[i].scales;
aux16[0] = a[0] & 0x0f0f;
aux16[1] = (a[0] >> 4) & 0x0f0f;
summs += m * (scales[2] * (y[i].bsums[0] + y[i].bsums[1]) + scales[3] * (y[i].bsums[2] + y[i].bsums[3]));
const uint8_t * restrict q4 = x[i].qs;
const int8_t * restrict q8 = y[i].qs;
const __m256i q4bits = _mm256_loadu_si256((const __m256i*)q4);
const __m128i q4bits_0 = _mm256_extractf128_si256(q4bits, 0);
const __m128i q4bits_1 = _mm256_extractf128_si256(q4bits, 1);
const __m128i q4_0 = _mm_and_si128(q4bits_0, m4);
const __m128i q4_1 = _mm_and_si128(q4bits_1, m4);
const __m128i q4_2 = _mm_and_si128(_mm_srli_epi16(q4bits_0, 4), m4);
const __m128i q4_3 = _mm_and_si128(_mm_srli_epi16(q4bits_1, 4), m4);
const __m256i q8_0 = _mm256_loadu_si256((const __m256i*)(q8+ 0));
const __m256i q8_1 = _mm256_loadu_si256((const __m256i*)(q8+32));
const __m128i p16_0 = _mm_maddubs_epi16(q4_0, _mm256_extractf128_si256(q8_0, 0));
const __m128i p16_1 = _mm_maddubs_epi16(q4_1, _mm256_extractf128_si256(q8_0, 1));
const __m128i p16_2 = _mm_maddubs_epi16(q4_2, _mm256_extractf128_si256(q8_1, 0));
const __m128i p16_3 = _mm_maddubs_epi16(q4_3, _mm256_extractf128_si256(q8_1, 1));
const __m128i p32_0 = _mm_madd_epi16(_mm_set1_epi16(scales[0]), p16_0);
const __m128i p32_1 = _mm_madd_epi16(_mm_set1_epi16(scales[0]), p16_1);
acc = _mm256_add_ps(_mm256_mul_ps(vd, _mm256_cvtepi32_ps(MM256_SET_M128I(p32_1, p32_0))), acc);
const __m128i p32_2 = _mm_madd_epi16(_mm_set1_epi16(scales[1]), p16_2);
const __m128i p32_3 = _mm_madd_epi16(_mm_set1_epi16(scales[1]), p16_3);
acc = _mm256_add_ps(_mm256_mul_ps(vd, _mm256_cvtepi32_ps(MM256_SET_M128I(p32_3, p32_2))), acc);
}
*s = hsum_float_8(acc) - summs;
#else
uint8_t aux8[QK_K];
@@ -2989,7 +3188,7 @@ void ggml_vec_dot_q5_K_q8_K(const int n, float * restrict s, const void * restri
summs += dmin * _mm_extract_epi32(hsum, 0);
const __m128i sc128 = _mm256_extracti128_si256(mins_and_scales, 0);
const __m256i scales = _mm256_set_m128i(sc128, sc128);
const __m256i scales = MM256_SET_M128I(sc128, sc128);
const __m256i hbits = _mm256_loadu_si256((const __m256i*)x[i].qh);
__m256i hmask = mone;
@@ -3128,7 +3327,7 @@ void ggml_vec_dot_q5_K_q8_K(const int n, float * restrict s, const void * restri
}
__m256 vd = _mm256_set1_ps(d);
__m256i sumi = _mm256_set_m128i(sumi_1, sumi_0);
__m256i sumi = MM256_SET_M128I(sumi_1, sumi_0);
acc = _mm256_add_ps(_mm256_mul_ps(vd, _mm256_cvtepi32_ps(sumi)), acc);
}
@@ -3291,13 +3490,13 @@ void ggml_vec_dot_q5_K_q8_K(const int n, float * restrict s, const void * restri
const __m256i q5bits = _mm256_loadu_si256((const __m256i*)q5);
const __m256i scale_l = _mm256_set_m128i(_mm_set1_epi16(x[i].scales[1]), _mm_set1_epi16(x[i].scales[0]));
const __m256i scale_h = _mm256_set_m128i(_mm_set1_epi16(x[i].scales[3]), _mm_set1_epi16(x[i].scales[2]));
const __m256i scale_l = MM256_SET_M128I(_mm_set1_epi16(x[i].scales[1]), _mm_set1_epi16(x[i].scales[0]));
const __m256i scale_h = MM256_SET_M128I(_mm_set1_epi16(x[i].scales[3]), _mm_set1_epi16(x[i].scales[2]));
int64_t aux64;
memcpy(&aux64, x[i].qh, 8);
const __m128i haux128 = _mm_set_epi64x(aux64 >> 1, aux64);
const __m256i haux256 = _mm256_set_m128i(_mm_srli_epi16(haux128, 2), haux128);
const __m256i haux256 = MM256_SET_M128I(_mm_srli_epi16(haux128, 2), haux128);
const __m256i q5h_0 = _mm256_slli_epi16(_mm256_andnot_si256(haux256, mone), 4);
const __m256i q5h_1 = _mm256_slli_epi16(_mm256_andnot_si256(_mm256_srli_epi16(haux256, 4), mone), 4);
@@ -3321,10 +3520,66 @@ void ggml_vec_dot_q5_K_q8_K(const int n, float * restrict s, const void * restri
*s = hsum_float_8(acc);
#elif defined __AVX__
const __m128i m4 = _mm_set1_epi8(0xF);
const __m128i mone = _mm_set1_epi8(1);
__m256 acc = _mm256_setzero_ps();
for (int i = 0; i < nb; ++i) {
const uint8_t * restrict q5 = x[i].qs;
const int8_t * restrict q8 = y[i].qs;
const float d = y[i].d * ggml_fp16_to_fp32(x[i].d);
const __m256i q5bits = _mm256_loadu_si256((const __m256i*)q5);
const __m128i scale_0 = _mm_set1_epi16(x[i].scales[0]);
const __m128i scale_1 = _mm_set1_epi16(x[i].scales[1]);
const __m128i scale_2 = _mm_set1_epi16(x[i].scales[2]);
const __m128i scale_3 = _mm_set1_epi16(x[i].scales[3]);
int64_t aux64;
memcpy(&aux64, x[i].qh, 8);
const __m128i haux128_0 = _mm_set_epi64x(aux64 >> 1, aux64);
const __m128i haux128_1 = _mm_srli_epi16(haux128_0, 2);
const __m128i q5h_0 = _mm_slli_epi16(_mm_andnot_si128(haux128_0, mone), 4);
const __m128i q5h_1 = _mm_slli_epi16(_mm_andnot_si128(haux128_1, mone), 4);
const __m128i q5h_2 = _mm_slli_epi16(_mm_andnot_si128(_mm_srli_epi16(haux128_0, 4), mone), 4);
const __m128i q5h_3 = _mm_slli_epi16(_mm_andnot_si128(_mm_srli_epi16(haux128_1, 4), mone), 4);
const __m128i q5l_0 = _mm_and_si128(_mm256_extractf128_si256(q5bits, 0), m4);
const __m128i q5l_1 = _mm_and_si128(_mm256_extractf128_si256(q5bits, 1), m4);
const __m128i q5l_2 = _mm_and_si128(_mm_srli_epi16(_mm256_extractf128_si256(q5bits, 0), 4), m4);
const __m128i q5l_3 = _mm_and_si128(_mm_srli_epi16(_mm256_extractf128_si256(q5bits, 1), 4), m4);
const __m256i q8_0 = _mm256_loadu_si256((const __m256i*)(q8+ 0));
const __m256i q8_1 = _mm256_loadu_si256((const __m256i*)(q8+32));
const __m128i p16_0 = _mm_madd_epi16(scale_0, _mm_maddubs_epi16(q5l_0, _mm256_extractf128_si256(q8_0, 0)));
const __m128i p16_1 = _mm_madd_epi16(scale_1, _mm_maddubs_epi16(q5l_1, _mm256_extractf128_si256(q8_0, 1)));
const __m128i p16_2 = _mm_madd_epi16(scale_2, _mm_maddubs_epi16(q5l_2, _mm256_extractf128_si256(q8_1, 0)));
const __m128i p16_3 = _mm_madd_epi16(scale_3, _mm_maddubs_epi16(q5l_3, _mm256_extractf128_si256(q8_1, 1)));
const __m128i s16_0 = _mm_madd_epi16(scale_0, _mm_maddubs_epi16(q5h_0, _mm256_extractf128_si256(q8_0, 0)));
const __m128i s16_1 = _mm_madd_epi16(scale_1, _mm_maddubs_epi16(q5h_1, _mm256_extractf128_si256(q8_0, 1)));
const __m128i s16_2 = _mm_madd_epi16(scale_2, _mm_maddubs_epi16(q5h_2, _mm256_extractf128_si256(q8_1, 0)));
const __m128i s16_3 = _mm_madd_epi16(scale_3, _mm_maddubs_epi16(q5h_3, _mm256_extractf128_si256(q8_1, 1)));
const __m128i dot_0 = _mm_sub_epi32(_mm_add_epi32(p16_0, p16_2), _mm_add_epi32(s16_0, s16_2));
const __m128i dot_1 = _mm_sub_epi32(_mm_add_epi32(p16_1, p16_3), _mm_add_epi32(s16_1, s16_3));
acc = _mm256_add_ps(_mm256_mul_ps(_mm256_set1_ps(d), _mm256_cvtepi32_ps(MM256_SET_M128I(dot_1, dot_0))), acc);
}
*s = hsum_float_8(acc);
#else
uint8_t aux8[QK_K];
int8_t aux8[QK_K];
int16_t aux16[16];
float sums [8];
memset(sums, 0, 8*sizeof(float));
@@ -3334,7 +3589,7 @@ void ggml_vec_dot_q5_K_q8_K(const int n, float * restrict s, const void * restri
const uint8_t * restrict q4 = x[i].qs;
const uint8_t * restrict hm = x[i].qh;
const int8_t * restrict q8 = y[i].qs;
uint8_t * restrict a = aux8;
int8_t * restrict a = aux8;
for (int l = 0; l < 32; ++l) {
a[l+ 0] = q4[l] & 0xF;
a[l+32] = q4[l] >> 4;
@@ -3698,7 +3953,7 @@ void ggml_vec_dot_q6_K_q8_K(const int n, float * restrict s, const void * restri
}
__m256i sumi = _mm256_set_m128i(sumi_1, sumi_0);
__m256i sumi = MM256_SET_M128I(sumi_1, sumi_0);
acc = _mm256_add_ps(_mm256_mul_ps(_mm256_broadcast_ss(&d), _mm256_cvtepi32_ps(sumi)), acc);
}
@@ -3856,8 +4111,8 @@ void ggml_vec_dot_q6_K_q8_K(const int n, float * restrict s, const void * restri
const __m256i q4bits1 = _mm256_loadu_si256((const __m256i*)q4);
const __m128i q4bitsH = _mm_loadu_si128((const __m128i*)qh);
const __m256i q4h_0 = _mm256_slli_epi16(_mm256_and_si256(_mm256_set_m128i(_mm_srli_epi16(q4bitsH, 2), q4bitsH), m2), 4);
const __m256i q4h_1 = _mm256_slli_epi16(_mm256_and_si256(_mm256_set_m128i(_mm_srli_epi16(q4bitsH, 6), _mm_srli_epi16(q4bitsH, 4)), m2), 4);
const __m256i q4h_0 = _mm256_slli_epi16(_mm256_and_si256(MM256_SET_M128I(_mm_srli_epi16(q4bitsH, 2), q4bitsH), m2), 4);
const __m256i q4h_1 = _mm256_slli_epi16(_mm256_and_si256(MM256_SET_M128I(_mm_srli_epi16(q4bitsH, 6), _mm_srli_epi16(q4bitsH, 4)), m2), 4);
const __m256i q4_0 = _mm256_or_si256(_mm256_and_si256(q4bits1, m4), q4h_0);
const __m256i q4_1 = _mm256_or_si256(_mm256_and_si256(_mm256_srli_epi16(q4bits1, 4), m4), q4h_1);
@@ -3884,6 +4139,77 @@ void ggml_vec_dot_q6_K_q8_K(const int n, float * restrict s, const void * restri
*s = hsum_float_8(acc);
#elif defined __AVX__
const __m128i m4 = _mm_set1_epi8(0xF);
const __m128i m2 = _mm_set1_epi8(3);
const __m128i m32s = _mm_set1_epi8(32);
__m256 acc = _mm256_setzero_ps();
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * ggml_fp16_to_fp32(x[i].d);
const uint8_t * restrict q4 = x[i].ql;
const uint8_t * restrict qh = x[i].qh;
const int8_t * restrict q8 = y[i].qs;
const __m64 scales_1 = _mm_set1_pi8(x[i].scales[0]);
const __m64 scales_2 = _mm_set1_pi8(x[i].scales[1]);
const __m64 scales_3 = _mm_set1_pi8(x[i].scales[2]);
const __m64 scales_4 = _mm_set1_pi8(x[i].scales[3]);
__m128i sumi_0 = _mm_setzero_si128();
__m128i sumi_1 = _mm_setzero_si128();
const __m128i scale_0 = _mm_set_epi64(scales_2, scales_1);
const __m128i scale_1 = _mm_set_epi64(scales_4, scales_3);
const __m256i q4bits1 = _mm256_loadu_si256((const __m256i*)q4);
const __m128i q4bitsH = _mm_loadu_si128((const __m128i*)qh);
const __m128i q4h_0 = _mm_slli_epi16(_mm_and_si128(q4bitsH, m2), 4);
const __m128i q4h_1 = _mm_slli_epi16(_mm_and_si128(_mm_srli_epi16(q4bitsH, 2), m2), 4);
const __m128i q4h_2 = _mm_slli_epi16(_mm_and_si128(_mm_srli_epi16(q4bitsH, 4), m2), 4);
const __m128i q4h_3 = _mm_slli_epi16(_mm_and_si128(_mm_srli_epi16(q4bitsH, 6), m2), 4);
const __m128i q4_0 = _mm_or_si128(_mm_and_si128(_mm256_extractf128_si256(q4bits1, 0), m4), q4h_0);
const __m128i q4_1 = _mm_or_si128(_mm_and_si128(_mm256_extractf128_si256(q4bits1, 1), m4), q4h_1);
const __m128i q4_2 = _mm_or_si128(_mm_and_si128(_mm_srli_epi16(_mm256_extractf128_si256(q4bits1, 0), 4), m4), q4h_2);
const __m128i q4_3 = _mm_or_si128(_mm_and_si128(_mm_srli_epi16(_mm256_extractf128_si256(q4bits1, 1), 4), m4), q4h_3);
const __m256i q8_0 = _mm256_loadu_si256((const __m256i*)(q8+ 0));
const __m256i q8_1 = _mm256_loadu_si256((const __m256i*)(q8+32));
__m128i q8s_0 = _mm_maddubs_epi16(m32s, _mm256_extractf128_si256(q8_0, 0));
__m128i q8s_1 = _mm_maddubs_epi16(m32s, _mm256_extractf128_si256(q8_0, 1));
__m128i q8s_2 = _mm_maddubs_epi16(m32s, _mm256_extractf128_si256(q8_1, 0));
__m128i q8s_3 = _mm_maddubs_epi16(m32s, _mm256_extractf128_si256(q8_1, 1));
__m128i p16_0 = _mm_maddubs_epi16(q4_0, _mm256_extractf128_si256(q8_0, 0));
__m128i p16_1 = _mm_maddubs_epi16(q4_1, _mm256_extractf128_si256(q8_0, 1));
__m128i p16_2 = _mm_maddubs_epi16(q4_2, _mm256_extractf128_si256(q8_1, 0));
__m128i p16_3 = _mm_maddubs_epi16(q4_3, _mm256_extractf128_si256(q8_1, 1));
p16_0 = _mm_sub_epi16(p16_0, q8s_0);
p16_1 = _mm_sub_epi16(p16_1, q8s_1);
p16_2 = _mm_sub_epi16(p16_2, q8s_2);
p16_3 = _mm_sub_epi16(p16_3, q8s_3);
p16_0 = _mm_madd_epi16(_mm_cvtepi8_epi16(scale_0), p16_0);
p16_1 = _mm_madd_epi16(_mm_cvtepi8_epi16(_mm_unpackhi_epi64(scale_0, scale_0)), p16_1);
p16_2 = _mm_madd_epi16(_mm_cvtepi8_epi16(scale_1), p16_2);
p16_3 = _mm_madd_epi16(_mm_cvtepi8_epi16(_mm_unpackhi_epi64(scale_1, scale_1)), p16_3);
sumi_0 = _mm_add_epi32(sumi_0, _mm_add_epi32(p16_0, p16_2));
sumi_1 = _mm_add_epi32(sumi_1, _mm_add_epi32(p16_1, p16_3));
acc = _mm256_add_ps(_mm256_mul_ps(_mm256_broadcast_ss(&d), _mm256_cvtepi32_ps(MM256_SET_M128I(sumi_1, sumi_0))), acc);
}
*s = hsum_float_8(acc);
#else
int8_t aux8[QK_K];

View File

@@ -1,5 +1,5 @@
/**
* llama.cpp - git 5bf2a2771886ee86137e01dbc7492f78fb392066
* llama.cpp - git 8183159cf3def112f6d1fe94815fce70e1bffa12
*
* MIT License
*
@@ -41,6 +41,14 @@
#define K_SCALE_SIZE 12
#endif
#ifndef static_assert
#if defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 201100L)
#define static_assert(cond, msg) _Static_assert(cond, msg)
#else
#define static_assert(cond, msg) struct global_scope_noop_trick
#endif
#endif
//
// Super-block quantization structures
//

View File

@@ -1,5 +1,5 @@
/**
* llama.cpp - git 5bf2a2771886ee86137e01dbc7492f78fb392066
* llama.cpp - git 8183159cf3def112f6d1fe94815fce70e1bffa12
*
* MIT License
*
@@ -201,13 +201,13 @@ struct llama_mmap {
llama_mmap(struct llama_file * file, size_t prefetch = (size_t) -1 /* -1 = max value */, bool numa = false) {
size = file->size;
int fd = fileno(file->fp);
int flags = MAP_PRIVATE;
int flags = MAP_SHARED;
// prefetch/readahead impairs performance on NUMA systems
if (numa) { prefetch = 0; }
#ifdef __linux__
if (prefetch) { flags |= MAP_POPULATE; }
#endif
addr = mmap(NULL, file->size, PROT_READ | PROT_WRITE, flags, fd, 0);
addr = mmap(NULL, file->size, PROT_READ, flags, fd, 0);
if (addr == MAP_FAILED) {
throw std::runtime_error(format("mmap failed: %s", strerror(errno)));
}
@@ -249,7 +249,7 @@ struct llama_mmap {
throw std::runtime_error(format("CreateFileMappingA failed: %s", llama_format_win_err(error).c_str()));
}
addr = MapViewOfFile(hMapping, FILE_MAP_COPY, 0, 0, 0);
addr = MapViewOfFile(hMapping, FILE_MAP_READ, 0, 0, 0);
error = GetLastError();
CloseHandle(hMapping);

File diff suppressed because it is too large Load Diff

View File

@@ -1,9 +1,10 @@
package llama
/*
#cgo CPPFLAGS: -O3 -DNDEBUG=1
#cgo CXXFLAGS: -std=c++11
#cgo darwin CPPFLAGS: -DGGML_USE_METAL=1 -DGGML_METAL_NDEBUG=1
#cgo CPPFLAGS: -O3 -Wall -Wextra -Wno-unused-function -Wno-unused-variable -DNDEBUG -DGGML_USE_K_QUANTS
#cgo CXXFLAGS: -std=gnu++11
#cgo darwin CPPFLAGS: -DGGML_USE_ACCELERATE
#cgo darwin,arm64 CPPFLAGS: -DGGML_USE_METAL -DGGML_METAL_NDEBUG
#cgo darwin LDFLAGS: -framework Accelerate -framework Foundation -framework Metal -framework MetalKit -framework MetalPerformanceShaders
#include <stdlib.h>
#include "llama.h"
@@ -21,6 +22,7 @@ struct llama_sample_options
int mirostat;
float mirostat_tau;
float mirostat_eta;
bool penalize_newline;
};
llama_token llama_sample(
@@ -37,6 +39,8 @@ llama_token llama_sample(
false,
};
struct llama_token_data newline = candidates_p.data[llama_token_nl()];
llama_sample_repetition_penalty(
ctx, &candidates_p,
last_tokens, n_last_tokens,
@@ -47,6 +51,10 @@ llama_token llama_sample(
last_tokens, n_last_tokens,
opts->frequency_penalty, opts->presence_penalty);
if (!opts->penalize_newline) {
candidates_p.data[llama_token_nl()] = newline;
}
if (opts->temperature <= 0) {
return llama_sample_token_greedy(ctx, &candidates_p);
}
@@ -79,32 +87,44 @@ llama_token llama_sample(
import "C"
import (
"bytes"
"embed"
"errors"
"fmt"
"io"
"log"
"os"
"strings"
"time"
"sync"
"unicode/utf8"
"unsafe"
"github.com/jmorganca/ollama/api"
)
type llama struct {
//go:embed ggml-metal.metal
var fs embed.FS
type LLM struct {
params *C.struct_llama_context_params
model *C.struct_llama_model
ctx *C.struct_llama_context
last []C.llama_token
embd []C.llama_token
cursor int
mu sync.Mutex
gc bool
api.Options
}
func New(model string, opts api.Options) (*llama, error) {
func New(model string, opts api.Options) (*LLM, error) {
if _, err := os.Stat(model); err != nil {
return nil, err
}
llm := llama{Options: opts}
llm := LLM{Options: opts}
C.llama_backend_init(C.bool(llm.UseNUMA))
@@ -112,6 +132,7 @@ func New(model string, opts api.Options) (*llama, error) {
params.seed = C.uint(llm.Seed)
params.n_ctx = C.int(llm.NumCtx)
params.n_batch = C.int(llm.NumBatch)
params.n_gqa = C.int(llm.NumGQA)
params.n_gpu_layers = C.int(llm.NumGPU)
params.main_gpu = C.int(llm.MainGPU)
params.low_vram = C.bool(llm.LowVRAM)
@@ -144,31 +165,147 @@ func New(model string, opts api.Options) (*llama, error) {
return &llm, nil
}
func (llm *llama) Close() {
func (llm *LLM) Close() {
llm.gc = true
llm.mu.Lock()
defer llm.mu.Unlock()
defer C.llama_free_model(llm.model)
defer C.llama_free(llm.ctx)
C.llama_print_timings(llm.ctx)
}
func (llm *llama) Predict(ctx []int, prompt string, fn func(api.GenerateResponse)) error {
if input := llm.tokenize(prompt); input != nil {
embd := make([]C.llama_token, len(ctx))
for i := range ctx {
embd[i] = C.llama_token(ctx[i])
}
var errNeedMoreData = errors.New("need more data")
return llm.generate(append(embd, input...), fn)
func (llm *LLM) Predict(ctx []int, prompt string, fn func(api.GenerateResponse)) error {
C.llama_reset_timings(llm.ctx)
tokens := make([]C.llama_token, len(ctx))
for i := range tokens {
tokens[i] = C.llama_token(ctx[i])
}
return errors.New("llama: tokenize")
if len(tokens) == 0 {
tokens = llm.tokenize(" ")
}
llm.marshalPrompt(tokens, prompt)
C.llama_set_rng_seed(llm.ctx, C.uint(llm.Seed))
var b bytes.Buffer
for {
token, err := llm.next()
if llm.gc {
return nil
} else if errors.Is(err, io.EOF) {
break
} else if err != nil {
return err
}
b.WriteString(llm.detokenize(token))
if err := llm.checkStopConditions(b); err != nil {
if errors.Is(err, io.EOF) {
break
} else if errors.Is(err, errNeedMoreData) {
continue
}
return err
}
if utf8.Valid(b.Bytes()) || b.Len() >= utf8.UTFMax {
fn(api.GenerateResponse{Response: b.String()})
b.Reset()
}
}
last := make([]int, 0, len(llm.last))
for _, i := range llm.last {
if i != 0 {
last = append(last, int(i))
}
}
timings := C.llama_get_timings(llm.ctx)
fn(api.GenerateResponse{
Done: true,
Context: last,
SampleCount: int(timings.n_sample),
SampleDuration: parseDurationMs(float64(timings.t_sample_ms)),
PromptEvalCount: int(timings.n_p_eval),
PromptEvalDuration: parseDurationMs(float64(timings.t_p_eval_ms)),
EvalCount: int(timings.n_eval),
EvalDuration: parseDurationMs(float64(timings.t_eval_ms)),
})
return nil
}
func (llm *llama) tokenize(prompt string) []C.llama_token {
func (llm *LLM) checkStopConditions(b bytes.Buffer) error {
for _, stopCondition := range llm.Stop {
if stopCondition == b.String() {
return io.EOF
} else if strings.HasPrefix(stopCondition, b.String()) {
return errNeedMoreData
}
}
return nil
}
func (llm *LLM) marshalPrompt(ctx []C.llama_token, prompt string) []C.llama_token {
tokens := append(ctx, llm.tokenize(prompt)...)
if llm.NumKeep < 0 {
llm.NumKeep = len(tokens)
}
// min(llm.NumCtx - 4, llm.NumKeep)
if llm.NumCtx-4 < llm.NumKeep {
llm.NumKeep = llm.NumCtx - 4
}
if len(tokens) >= llm.NumCtx {
// truncate input
numLeft := (llm.NumCtx - llm.NumKeep) / 2
truncated := tokens[:llm.NumKeep]
erasedBlocks := (len(tokens) - llm.NumKeep - numLeft - 1) / numLeft
truncated = append(truncated, tokens[llm.NumKeep+erasedBlocks*numLeft:]...)
copy(llm.last, tokens[len(tokens)-llm.NumCtx:])
tokens = truncated
log.Printf("input truncated: num_ctx=%d num_keep=%d num_left=%d num_tokens=%d", llm.NumCtx, llm.NumKeep, numLeft, len(truncated))
} else {
llm.last = make([]C.llama_token, llm.NumCtx-len(tokens))
llm.last = append(llm.last, tokens...)
}
var i int
for i = 0; i < len(llm.embd) && i < len(tokens) && llm.embd[i] == tokens[i]; i++ {
// noop
}
llm.embd = tokens
if i == len(tokens) {
// evaluate at least one token to generate logits
i--
}
llm.cursor = i
log.Printf("prompt: num_past=%d cached=%v eval=%v", i, len(llm.embd[:i]), len(llm.embd[i:]))
return tokens
}
func (llm *LLM) tokenize(prompt string) []C.llama_token {
cPrompt := C.CString(prompt)
defer C.free(unsafe.Pointer(cPrompt))
tokens := make([]C.llama_token, llm.NumCtx)
tokens := make([]C.llama_token, len(prompt)+1)
if n := C.llama_tokenize(llm.ctx, cPrompt, unsafe.SliceData(tokens), C.int(len(tokens)), true); n > 0 {
return tokens[:n]
}
@@ -176,7 +313,7 @@ func (llm *llama) tokenize(prompt string) []C.llama_token {
return nil
}
func (llm *llama) detokenize(tokens ...C.llama_token) string {
func (llm *LLM) detokenize(tokens ...C.llama_token) string {
var sb strings.Builder
for _, token := range tokens {
sb.WriteString(C.GoString(C.llama_token_to_str(llm.ctx, token)))
@@ -185,98 +322,93 @@ func (llm *llama) detokenize(tokens ...C.llama_token) string {
return sb.String()
}
func (llm *llama) generate(input []C.llama_token, fn func(api.GenerateResponse)) error {
var opts C.struct_llama_sample_options
opts.repeat_penalty = C.float(llm.RepeatPenalty)
opts.frequency_penalty = C.float(llm.FrequencyPenalty)
opts.presence_penalty = C.float(llm.PresencePenalty)
opts.temperature = C.float(llm.Temperature)
opts.top_k = C.int(llm.TopK)
opts.top_p = C.float(llm.TopP)
opts.tfs_z = C.float(llm.TFSZ)
opts.typical_p = C.float(llm.TypicalP)
opts.mirostat = C.int(llm.Mirostat)
opts.mirostat_tau = C.float(llm.MirostatTau)
opts.mirostat_eta = C.float(llm.MirostatEta)
func (llm *LLM) next() (C.llama_token, error) {
llm.mu.Lock()
defer llm.mu.Unlock()
output := deque[C.llama_token]{capacity: llm.NumCtx}
if len(llm.embd) >= llm.NumCtx {
numLeft := (llm.NumCtx - llm.NumKeep) / 2
truncated := llm.embd[:llm.NumKeep]
truncated = append(truncated, llm.embd[len(llm.embd)-numLeft:]...)
context := deque[int]{capacity: llm.NumCtx / 2}
for _, in := range input {
context.PushLeft(int(in))
llm.embd = truncated
llm.cursor = llm.NumKeep
log.Printf("input truncated: num_ctx=%d num_keep=%d num_left=%d num_tokens=%d cursor=%d", llm.NumCtx, llm.NumKeep, numLeft, len(truncated), llm.cursor)
}
var b bytes.Buffer
for C.llama_get_kv_cache_token_count(llm.ctx) < C.int(llm.NumCtx) {
if retval := C.llama_eval(llm.ctx, unsafe.SliceData(input), C.int(len(input)), C.llama_get_kv_cache_token_count(llm.ctx), C.int(llm.NumThread)); retval != 0 {
return errors.New("llama: eval")
for {
if llm.gc {
return 0, io.EOF
}
token, err := llm.sample(output, &opts)
if errors.Is(err, io.EOF) {
if llm.cursor >= len(llm.embd) {
break
} else if err != nil {
return err
}
b.WriteString(llm.detokenize(token))
if utf8.Valid(b.Bytes()) || b.Len() >= utf8.UTFMax {
// call the callback
fn(api.GenerateResponse{
Response: b.String(),
})
output.PushLeft(token)
context.PushLeft(int(token))
b.Reset()
numEval := len(llm.embd) - llm.cursor
if numEval > llm.NumBatch {
numEval = llm.NumBatch
}
input = []C.llama_token{token}
if retval := C.llama_eval(llm.ctx, unsafe.SliceData(llm.embd[llm.cursor:]), C.int(numEval), C.int(llm.cursor), C.int(llm.NumThread)); retval != 0 {
return 0, fmt.Errorf("llama_eval: %d", retval)
}
llm.cursor += numEval
}
dur := func(ms float64) time.Duration {
d, err := time.ParseDuration(fmt.Sprintf("%fms", ms))
if err != nil {
panic(err)
}
var sampleOpts C.struct_llama_sample_options
sampleOpts.repeat_penalty = C.float(llm.RepeatPenalty)
sampleOpts.frequency_penalty = C.float(llm.FrequencyPenalty)
sampleOpts.presence_penalty = C.float(llm.PresencePenalty)
sampleOpts.temperature = C.float(llm.Temperature)
sampleOpts.top_k = C.int(llm.TopK)
sampleOpts.top_p = C.float(llm.TopP)
sampleOpts.tfs_z = C.float(llm.TFSZ)
sampleOpts.typical_p = C.float(llm.TypicalP)
sampleOpts.mirostat = C.int(llm.Mirostat)
sampleOpts.mirostat_tau = C.float(llm.MirostatTau)
sampleOpts.mirostat_eta = C.float(llm.MirostatEta)
sampleOpts.penalize_newline = C.bool(llm.PenalizeNewline)
return d
}
timings := C.llama_get_timings(llm.ctx)
fn(api.GenerateResponse{
Done: true,
Context: context.Data(),
PromptEvalCount: int(timings.n_p_eval),
PromptEvalDuration: dur(float64(timings.t_p_eval_ms)),
EvalCount: int(timings.n_eval),
EvalDuration: dur(float64(timings.t_eval_ms)),
})
return nil
}
func (llm *llama) sample(output deque[C.llama_token], opts *C.struct_llama_sample_options) (C.llama_token, error) {
numVocab := int(C.llama_n_vocab(llm.ctx))
numVocab := C.llama_n_vocab(llm.ctx)
logits := unsafe.Slice(C.llama_get_logits(llm.ctx), numVocab)
candidates := deque[C.struct_llama_token_data]{capacity: numVocab}
for i := 0; i < candidates.Cap(); i++ {
candidates.PushLeft(C.struct_llama_token_data{
// TODO: logit bias
candidates := make([]C.llama_token_data, numVocab)
for i := range logits {
candidates[i] = C.llama_token_data{
id: C.int(i),
logit: logits[i],
p: 0,
})
}
}
repeatLastN := llm.RepeatLastN
if len(llm.last) < repeatLastN {
repeatLastN = len(llm.last)
}
if llm.NumCtx < repeatLastN {
repeatLastN = llm.NumCtx
}
lastN := llm.last[len(llm.last)-repeatLastN:]
token := C.llama_sample(
llm.ctx,
unsafe.SliceData(candidates.Data()), C.size_t(candidates.Len()),
unsafe.SliceData(output.Data()), C.size_t(output.Len()),
opts)
if token != C.llama_token_eos() {
return token, nil
unsafe.SliceData(candidates), C.size_t(len(candidates)),
unsafe.SliceData(lastN), C.size_t(len(lastN)),
&sampleOpts,
)
llm.last = append(llm.last, token)
llm.embd = append(llm.embd, token)
if token == C.llama_token_eos() {
return 0, io.EOF
}
return 0, io.EOF
return token, nil
}

View File

@@ -1,5 +1,5 @@
/**
* llama.cpp - git 5bf2a2771886ee86137e01dbc7492f78fb392066
* llama.cpp - git 8183159cf3def112f6d1fe94815fce70e1bffa12
*
* MIT License
*
@@ -79,6 +79,10 @@
#define LLAMA_SUPPORTS_GPU_OFFLOAD
#endif
#ifndef LLAMA_DEFAULT_RMS_EPS
#define LLAMA_DEFAULT_RMS_EPS 5e-6f
#endif
#ifdef __cplusplus
extern "C" {
#endif
@@ -109,12 +113,20 @@ extern "C" {
typedef void (*llama_progress_callback)(float progress, void *ctx);
struct llama_context_params {
uint32_t seed; // RNG seed, -1 for random
int32_t n_ctx; // text context
int32_t n_batch; // prompt processing batch size
int32_t n_gpu_layers; // number of layers to store in VRAM
int32_t main_gpu; // the GPU that is used for scratch and small tensors
float tensor_split[LLAMA_MAX_DEVICES]; // how to split layers across multiple GPUs
uint32_t seed; // RNG seed, -1 for random
int32_t n_ctx; // text context
int32_t n_batch; // prompt processing batch size
int32_t n_gqa; // grouped-query attention (TEMP - will be moved to model hparams)
float rms_norm_eps; // rms norm epsilon (TEMP - will be moved to model hparams)
int32_t n_gpu_layers; // number of layers to store in VRAM
int32_t main_gpu; // the GPU that is used for scratch and small tensors
const float * tensor_split; // how to split layers across multiple GPUs (size: LLAMA_MAX_DEVICES)
// ref: https://github.com/ggerganov/llama.cpp/pull/2054
float rope_freq_base; // RoPE base frequency
float rope_freq_scale; // RoPE frequency scaling factor
// called with a progress value between 0 and 1, pass NULL to disable
llama_progress_callback progress_callback;
// context pointer passed to the progress callback
@@ -122,6 +134,7 @@ extern "C" {
// Keep the booleans together to avoid misalignment during copy-by-value.
bool low_vram; // if true, reduce VRAM usage at the cost of performance
bool mul_mat_q; // if true, use experimental mul_mat_q kernels
bool f16_kv; // use fp16 for KV cache
bool logits_all; // the llama_eval() call computes all logits, not just the last one
bool vocab_only; // only load the vocabulary, no weights
@@ -160,6 +173,40 @@ extern "C" {
bool quantize_output_tensor; // quantize output.weight
} llama_model_quantize_params;
// grammar types
struct llama_grammar;
// grammar element type
enum llama_gretype {
// end of rule definition
LLAMA_GRETYPE_END = 0,
// start of alternate definition for rule
LLAMA_GRETYPE_ALT = 1,
// non-terminal element: reference to rule
LLAMA_GRETYPE_RULE_REF = 2,
// terminal element: character (code point)
LLAMA_GRETYPE_CHAR = 3,
// inverse char(s) ([^a], [^a-b] [^abc])
LLAMA_GRETYPE_CHAR_NOT = 4,
// modifies a preceding LLAMA_GRETYPE_CHAR or LLAMA_GRETYPE_CHAR_ALT to
// be an inclusive range ([a-z])
LLAMA_GRETYPE_CHAR_RNG_UPPER = 5,
// modifies a preceding LLAMA_GRETYPE_CHAR or
// LLAMA_GRETYPE_CHAR_RNG_UPPER to add an alternate char to match ([ab], [a-zA])
LLAMA_GRETYPE_CHAR_ALT = 6,
};
typedef struct llama_grammar_element {
enum llama_gretype type;
uint32_t value; // Unicode code point or rule ID
} llama_grammar_element;
// performance timing information
struct llama_timings {
double t_start_ms;
@@ -174,6 +221,8 @@ extern "C" {
int32_t n_eval;
};
LLAMA_API int llama_max_devices();
LLAMA_API struct llama_context_params llama_context_default_params();
LLAMA_API struct llama_model_quantize_params llama_model_quantize_default_params();
@@ -296,10 +345,21 @@ extern "C" {
int n_max_tokens,
bool add_bos);
LLAMA_API int llama_tokenize_with_model(
const struct llama_model * model,
const char * text,
llama_token * tokens,
int n_max_tokens,
bool add_bos);
LLAMA_API int llama_n_vocab(const struct llama_context * ctx);
LLAMA_API int llama_n_ctx (const struct llama_context * ctx);
LLAMA_API int llama_n_embd (const struct llama_context * ctx);
LLAMA_API int llama_n_vocab_from_model(const struct llama_model * model);
LLAMA_API int llama_n_ctx_from_model (const struct llama_model * model);
LLAMA_API int llama_n_embd_from_model (const struct llama_model * model);
// Get the vocabulary as output parameters.
// Returns number of results.
LLAMA_API int llama_get_vocab(
@@ -308,6 +368,12 @@ extern "C" {
float * scores,
int capacity);
LLAMA_API int llama_get_vocab_from_model(
const struct llama_model * model,
const char * * strings,
float * scores,
int capacity);
// Token logits obtained from the last call to llama_eval()
// The logits for the last token are stored in the last row
// Can be mutated in order to change the probabilities of the next token
@@ -320,13 +386,28 @@ extern "C" {
LLAMA_API float * llama_get_embeddings(struct llama_context * ctx);
// Token Id -> String. Uses the vocabulary in the provided context
LLAMA_API const char * llama_token_to_str(const struct llama_context * ctx, llama_token token);
LLAMA_API const char * llama_token_to_str(
const struct llama_context * ctx,
llama_token token);
LLAMA_API const char * llama_token_to_str_with_model(
const struct llama_model * model,
llama_token token);
// Special tokens
LLAMA_API llama_token llama_token_bos(); // beginning-of-sentence
LLAMA_API llama_token llama_token_eos(); // end-of-sentence
LLAMA_API llama_token llama_token_nl(); // next-line
// Grammar
//
LLAMA_API struct llama_grammar * llama_grammar_init(
const llama_grammar_element ** rules,
size_t n_rules,
size_t start_rule_index);
LLAMA_API void llama_grammar_free(struct llama_grammar * grammar);
// Sampling functions
/// @details Repetition penalty described in CTRL academic paper https://arxiv.org/abs/1909.05858, with negative logit fix.
@@ -339,13 +420,11 @@ extern "C" {
/// @param candidates A vector of `llama_token_data` containing the candidate tokens, the logits must be directly extracted from the original generation context without being sorted.
/// @params guidance_ctx A separate context from the same model. Other than a negative prompt at the beginning, it should have all generated and user input tokens copied from the main context.
/// @params scale Guidance strength. 1.0f means no guidance. Higher values mean stronger guidance.
/// @params smooth_factor Smooth factor between guidance logits and original logits. 1.0f means only use guidance logits. 0.0f means only original logits.
LLAMA_API void llama_sample_classifier_free_guidance(
struct llama_context * ctx,
llama_token_data_array * candidates,
struct llama_context * guidance_ctx,
float scale,
float smooth_factor);
float scale);
/// @details Sorts candidate tokens by their logits in descending order and calculate probabilities based on logits.
LLAMA_API void llama_sample_softmax(struct llama_context * ctx, llama_token_data_array * candidates);
@@ -363,6 +442,9 @@ extern "C" {
LLAMA_API void llama_sample_typical(struct llama_context * ctx, llama_token_data_array * candidates, float p, size_t min_keep);
LLAMA_API void llama_sample_temperature(struct llama_context * ctx, llama_token_data_array * candidates, float temp);
/// @details Apply constraints from grammar
LLAMA_API void llama_sample_grammar(struct llama_context * ctx, llama_token_data_array * candidates, const struct llama_grammar * grammar);
/// @details Mirostat 1.0 algorithm described in the paper https://arxiv.org/abs/2007.14966. Uses tokens instead of words.
/// @param candidates A vector of `llama_token_data` containing the candidate tokens, their probabilities (p), and log-odds (logit) for the current position in the generated text.
/// @param tau The target cross-entropy (or surprise) value you want to achieve for the generated text. A higher value corresponds to more surprising or less predictable text, while a lower value corresponds to less surprising or more predictable text.
@@ -384,6 +466,9 @@ extern "C" {
/// @details Randomly selects a token from the candidates based on their probabilities.
LLAMA_API llama_token llama_sample_token(struct llama_context * ctx, llama_token_data_array * candidates);
/// @details Accepts the sampled token into the grammar
LLAMA_API void llama_grammar_accept_token(struct llama_context * ctx, struct llama_grammar * grammar, llama_token token);
// Performance information
LLAMA_API struct llama_timings llama_get_timings(struct llama_context * ctx);
LLAMA_API void llama_print_timings(struct llama_context * ctx);

80
llama/llama_darwin.go Normal file
View File

@@ -0,0 +1,80 @@
package llama
import (
"bytes"
"crypto/sha256"
"errors"
"io"
"log"
"os"
"path/filepath"
)
func init() {
if err := initBackend(); err != nil {
log.Printf("WARNING: GPU could not be initialized correctly: %v", err)
log.Printf("WARNING: falling back to CPU")
}
}
func initBackend() error {
exec, err := os.Executable()
if err != nil {
return err
}
exec, err = filepath.EvalSymlinks(exec)
if err != nil {
return err
}
metal := filepath.Join(filepath.Dir(exec), "ggml-metal.metal")
fi, err := os.Stat(metal)
if err != nil && !errors.Is(err, os.ErrNotExist) {
return err
}
if fi != nil {
actual, err := os.Open(metal)
if err != nil {
return err
}
actualSum := sha256.New()
if _, err := io.Copy(actualSum, actual); err != nil {
return err
}
expect, err := fs.Open("ggml-metal.metal")
if err != nil {
return err
}
expectSum := sha256.New()
if _, err := io.Copy(expectSum, expect); err != nil {
return err
}
if bytes.Equal(actualSum.Sum(nil), expectSum.Sum(nil)) {
return nil
}
}
dst, err := os.Create(filepath.Join(filepath.Dir(exec), "ggml-metal.metal"))
if err != nil {
return err
}
defer dst.Close()
src, err := fs.Open("ggml-metal.metal")
if err != nil {
return err
}
defer src.Close()
if _, err := io.Copy(dst, src); err != nil {
return err
}
return nil
}

70
llama/update-llama-cpp.sh Executable file
View File

@@ -0,0 +1,70 @@
#!/bin/sh
set -eu
status() { echo >&2 ">>> $*"; }
error() { status "ERROR $*"; }
usage() {
echo "usage: $(basename $0) /path/to/repo"
exit 1
}
OUT=$(dirname $0)
while getopts "hC:" OPTION; do
case $OPTION in
C) OUT=$OPTARG ;;
*) usage ;;
esac
done
shift $(( $OPTIND - 1 ))
[ $# -eq 1 ] || usage
status "updating source..."
cp -a "$1"/*.{c,h,cpp,m,metal,cu} "$OUT"
status "removing incompatible files..."
rm -f "$OUT"/build-info.h
SHA1=$(git -C $1 rev-parse @)
LICENSE=$(mktemp)
cleanup() {
rm -f $LICENSE
}
trap cleanup 0
cat <<EOF | sed 's/ *$//' >$LICENSE
/**
* llama.cpp - git $SHA1
*
$(sed 's/^/ * /' <$1/LICENSE)
*/
EOF
for IN in $OUT/*.{c,h,cpp,m,metal,cu}; do
TMP=$(mktemp)
status "updating license $IN"
cat $LICENSE $IN >$TMP
mv $TMP $IN
done
touchup() {
local CONSTRAINT=$1 && shift
for IN in $*; do
status "touching up $IN..."
TMP=$(mktemp)
{
echo "//go:build $CONSTRAINT"
echo
} | cat - $IN >$TMP
mv $TMP $IN
done
}
touchup darwin $OUT/ggml-metal.*
touchup mpi $OUT/ggml-mpi.*
touchup opencl $OUT/ggml-opencl.*

View File

@@ -1,104 +1,15 @@
package llama
type node[T any] struct {
t T
next *node[T]
prev *node[T]
}
import (
"fmt"
"time"
)
type deque[T any] struct {
head *node[T]
tail *node[T]
size int
capacity int
}
func (d *deque[T]) Empty() bool {
return d.size == 0
}
func (d *deque[T]) Len() int {
return d.size
}
func (d *deque[T]) Cap() int {
return d.capacity
}
func (d *deque[T]) Push(t T) {
if d.capacity > 0 && d.size >= d.capacity {
d.PopLeft()
func parseDurationMs(ms float64) time.Duration {
dur, err := time.ParseDuration(fmt.Sprintf("%fms", ms))
if err != nil {
panic(err)
}
n := node[T]{t: t}
if d.head != nil {
n.next = d.head
d.head.prev = &n
d.head = &n
} else {
d.head = &n
d.tail = &n
}
d.size++
}
func (d *deque[T]) PushLeft(t T) {
if d.capacity > 0 && d.size >= d.capacity {
d.Pop()
}
n := node[T]{t: t}
if d.tail != nil {
n.prev = d.tail
d.tail.next = &n
d.tail = &n
} else {
d.head = &n
d.tail = &n
}
d.size++
}
func (d *deque[T]) Pop() *T {
if d.Empty() {
return nil
}
head := d.head
d.head = head.next
if d.head != nil {
d.head.prev = nil
} else {
d.tail = nil
}
d.size--
return &head.t
}
func (d *deque[T]) PopLeft() *T {
if d.Empty() {
return nil
}
tail := d.tail
d.tail = tail.prev
if d.tail != nil {
d.tail.next = nil
} else {
d.head = nil
}
d.size--
return &tail.t
}
func (d *deque[T]) Data() (data []T) {
for n := d.head; n != nil; n = n.next {
data = append(data, n.t)
}
return data
return dur
}

View File

@@ -1,38 +0,0 @@
[
{
"name": "orca",
"display_name": "Orca Mini",
"parameters": "3B",
"url": "https://huggingface.co/TheBloke/orca_mini_3B-GGML/resolve/main/orca-mini-3b.ggmlv3.q4_1.bin",
"short_description": "Follow instructions. Great small model that runs fast even without GPU support.",
"description": "An OpenLLaMa-3B model trained on explain tuned datasets, created using Instructions and Input from WizardLM, Alpaca & Dolly-V2 datasets and applying Orca Research Paper dataset construction approaches.",
"published_by": "TheBloke",
"original_author": "psmathur",
"original_url": "https://huggingface.co/psmathur/orca_mini_3b",
"license": "CC-BY-SA-4.0"
},
{
"name": "nous-hermes",
"display_name": "Nous Hermes",
"parameters": "13B",
"url": "https://huggingface.co/TheBloke/Nous-Hermes-13B-GGML/resolve/main/nous-hermes-13b.ggmlv3.q2_K.bin",
"short_description": "Currently one of the best 13B general model.",
"description": "It is suitable for a wide range of language tasks, from generating creative text to understanding and following complex instructions. This model was fine-tuned by Nous Research, with Teknium and Karan4D leading the fine tuning process and dataset curation, Redmond AI sponsoring the compute, and several other contributors. The result is an enhanced Llama 13b model that rivals GPT-3.5-turbo in performance across a variety of tasks. \n \n This model stands out for its long responses, low hallucination rate, and absence of OpenAI censorship mechanisms. The fine-tuning process was performed with a 2000 sequence length on an 8x a100 80GB DGX machine for over 50 hours.",
"published_by": "TheBloke",
"original_author": "NousResearch",
"original_url": "https://huggingface.co/NousResearch/Nous-Hermes-13b",
"license": "GPL"
},
{
"name": "vicuna",
"display_name": "Vicuna",
"parameters": "7B",
"url": "https://huggingface.co/TheBloke/vicuna-7B-v1.3-GGML/resolve/main/vicuna-7b-v1.3.ggmlv3.q4_0.bin",
"short_description": "Vicuna is a chat assistant trained by fine-tuning LLaMA on user-shared conversations collected from ShareGPT.",
"description": "The primary use of Vicuna is research on large language models and chatbots. The primary intended users of the model are researchers and hobbyists in natural language processing, machine learning, and artificial intelligence.",
"published_by": "TheBloke",
"original_author": "LMSYS",
"original_url": "https://huggingface.co/lmsys/vicuna-7b-v1.3",
"license:": "Non-commercial"
}
]

View File

@@ -2,76 +2,109 @@ package parser
import (
"bufio"
"bytes"
"errors"
"fmt"
"io"
"strings"
"log"
)
type Command struct {
Name string
Arg string
Args string
}
func (c *Command) Reset() {
c.Name = ""
c.Args = ""
}
func Parse(reader io.Reader) ([]Command, error) {
var commands []Command
var foundModel bool
var command, modelCommand Command
scanner := bufio.NewScanner(reader)
multiline := false
var multilineCommand *Command
scanner.Buffer(make([]byte, 0, bufio.MaxScanTokenSize), bufio.MaxScanTokenSize)
scanner.Split(scanModelfile)
for scanner.Scan() {
line := scanner.Text()
if multiline {
// If we're in a multiline string and the line is """, end the multiline string.
if strings.TrimSpace(line) == `"""` {
multiline = false
commands = append(commands, *multilineCommand)
} else {
// Otherwise, append the line to the multiline string.
multilineCommand.Arg += "\n" + line
}
continue
}
fields := strings.Fields(line)
if len(fields) == 0 {
line := scanner.Bytes()
fields := bytes.SplitN(line, []byte(" "), 2)
if len(fields) == 0 || len(fields[0]) == 0 {
continue
}
command := Command{}
switch strings.ToUpper(fields[0]) {
switch string(bytes.ToUpper(fields[0])) {
case "FROM":
command.Name = "model"
command.Arg = fields[1]
if command.Arg == "" {
return nil, fmt.Errorf("no model specified in FROM line")
}
foundModel = true
case "PROMPT":
command.Name = "prompt"
if fields[1] == `"""` {
multiline = true
multilineCommand = &command
multilineCommand.Arg = ""
} else {
command.Arg = strings.Join(fields[1:], " ")
}
command.Args = string(fields[1])
// copy command for validation
modelCommand = command
case "LICENSE", "TEMPLATE", "SYSTEM", "PROMPT":
command.Name = string(bytes.ToLower(fields[0]))
command.Args = string(fields[1])
case "PARAMETER":
command.Name = fields[1]
command.Arg = strings.Join(fields[2:], " ")
fields = bytes.SplitN(fields[1], []byte(" "), 2)
command.Name = string(fields[0])
command.Args = string(fields[1])
default:
// log a warning for unknown commands
log.Printf("WARNING: Unknown command: %s", fields[0])
continue
}
if !multiline {
commands = append(commands, command)
}
commands = append(commands, command)
command.Reset()
}
if !foundModel {
return nil, fmt.Errorf("no FROM line for the model was specified")
if modelCommand.Args == "" {
return nil, errors.New("no FROM line for the model was specified")
}
if multiline {
return nil, fmt.Errorf("unclosed multiline string")
}
return commands, scanner.Err()
}
func scanModelfile(data []byte, atEOF bool) (advance int, token []byte, err error) {
advance, token, err = scan([]byte(`"""`), []byte(`"""`), data, atEOF)
if err != nil {
return 0, nil, err
}
if advance > 0 && token != nil {
return advance, token, nil
}
advance, token, err = scan([]byte(`"`), []byte(`"`), data, atEOF)
if err != nil {
return 0, nil, err
}
if advance > 0 && token != nil {
return advance, token, nil
}
return bufio.ScanLines(data, atEOF)
}
func scan(openBytes, closeBytes, data []byte, atEOF bool) (advance int, token []byte, err error) {
newline := bytes.IndexByte(data, '\n')
if start := bytes.Index(data, openBytes); start >= 0 && start < newline {
end := bytes.Index(data[start+len(openBytes):], closeBytes)
if end < 0 {
if atEOF {
return 0, nil, fmt.Errorf("unterminated %s: expecting %s", openBytes, closeBytes)
} else {
return 0, nil, nil
}
}
n := start + len(openBytes) + end + len(closeBytes)
newData := data[:start]
newData = append(newData, data[start+len(openBytes):n-len(closeBytes)]...)
return n, newData, nil
}
return 0, nil, nil
}

21
progressbar/LICENSE Normal file
View File

@@ -0,0 +1,21 @@
MIT License
Copyright (c) 2017 Zack
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

121
progressbar/README.md Normal file
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@@ -0,0 +1,121 @@
# progressbar
[![CI](https://github.com/schollz/progressbar/actions/workflows/ci.yml/badge.svg?branch=main&event=push)](https://github.com/schollz/progressbar/actions/workflows/ci.yml)
[![go report card](https://goreportcard.com/badge/github.com/schollz/progressbar)](https://goreportcard.com/report/github.com/schollz/progressbar)
[![coverage](https://img.shields.io/badge/coverage-84%25-brightgreen.svg)](https://gocover.io/github.com/schollz/progressbar)
[![godocs](https://godoc.org/github.com/schollz/progressbar?status.svg)](https://godoc.org/github.com/schollz/progressbar/v3)
A very simple thread-safe progress bar which should work on every OS without problems. I needed a progressbar for [croc](https://github.com/schollz/croc) and everything I tried had problems, so I made another one. In order to be OS agnostic I do not plan to support [multi-line outputs](https://github.com/schollz/progressbar/issues/6).
## Install
```
go get -u github.com/schollz/progressbar/v3
```
## Usage
### Basic usage
```golang
bar := progressbar.Default(100)
for i := 0; i < 100; i++ {
bar.Add(1)
time.Sleep(40 * time.Millisecond)
}
```
which looks like:
![Example of basic bar](examples/basic/basic.gif)
### I/O operations
The `progressbar` implements an `io.Writer` so it can automatically detect the number of bytes written to a stream, so you can use it as a progressbar for an `io.Reader`.
```golang
req, _ := http.NewRequest("GET", "https://dl.google.com/go/go1.14.2.src.tar.gz", nil)
resp, _ := http.DefaultClient.Do(req)
defer resp.Body.Close()
f, _ := os.OpenFile("go1.14.2.src.tar.gz", os.O_CREATE|os.O_WRONLY, 0644)
defer f.Close()
bar := progressbar.DefaultBytes(
resp.ContentLength,
"downloading",
)
io.Copy(io.MultiWriter(f, bar), resp.Body)
```
which looks like:
![Example of download bar](examples/download/download.gif)
### Progress bar with unknown length
A progressbar with unknown length is a spinner. Any bar with -1 length will automatically convert it to a spinner with a customizable spinner type. For example, the above code can be run and set the `resp.ContentLength` to `-1`.
which looks like:
![Example of download bar with unknown length](examples/download-unknown/download-unknown.gif)
### Customization
There is a lot of customization that you can do - change the writer, the color, the width, description, theme, etc. See [all the options](https://pkg.go.dev/github.com/schollz/progressbar/v3?tab=doc#Option).
```golang
bar := progressbar.NewOptions(1000,
progressbar.OptionSetWriter(ansi.NewAnsiStdout()),
progressbar.OptionEnableColorCodes(true),
progressbar.OptionShowBytes(true),
progressbar.OptionSetWidth(15),
progressbar.OptionSetDescription("[cyan][1/3][reset] Writing moshable file..."),
progressbar.OptionSetTheme(progressbar.Theme{
Saucer: "[green]=[reset]",
SaucerHead: "[green]>[reset]",
SaucerPadding: " ",
BarStart: "[",
BarEnd: "]",
}))
for i := 0; i < 1000; i++ {
bar.Add(1)
time.Sleep(5 * time.Millisecond)
}
```
which looks like:
![Example of customized bar](examples/customization/customization.gif)
## Contributing
Pull requests are welcome. Feel free to...
- Revise documentation
- Add new features
- Fix bugs
- Suggest improvements
## Thanks
Thanks [@Dynom](https://github.com/dynom) for massive improvements in version 2.0!
Thanks [@CrushedPixel](https://github.com/CrushedPixel) for adding descriptions and color code support!
Thanks [@MrMe42](https://github.com/MrMe42) for adding some minor features!
Thanks [@tehstun](https://github.com/tehstun) for some great PRs!
Thanks [@Benzammour](https://github.com/Benzammour) and [@haseth](https://github.com/haseth) for helping create v3!
Thanks [@briandowns](https://github.com/briandowns) for compiling the list of spinners.
## License
MIT

1098
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80
progressbar/spinners.go Normal file
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@@ -0,0 +1,80 @@
package progressbar
var spinners = map[int][]string{
0: {"←", "↖", "↑", "↗", "→", "↘", "↓", "↙"},
1: {"▁", "▃", "▄", "▅", "▆", "▇", "█", "▇", "▆", "▅", "▄", "▃", "▁"},
2: {"▖", "▘", "▝", "▗"},
3: {"┤", "┘", "┴", "└", "├", "┌", "┬", "┐"},
4: {"◢", "◣", "◤", "◥"},
5: {"◰", "◳", "◲", "◱"},
6: {"◴", "◷", "◶", "◵"},
7: {"◐", "◓", "◑", "◒"},
8: {".", "o", "O", "@", "*"},
9: {"|", "/", "-", "\\"},
10: {"◡◡", "⊙⊙", "◠◠"},
11: {"⣾", "⣽", "⣻", "⢿", "⡿", "⣟", "⣯", "⣷"},
12: {">))'>", " >))'>", " >))'>", " >))'>", " >))'>", " <'((<", " <'((<", " <'((<"},
13: {"⠁", "⠂", "⠄", "⡀", "⢀", "⠠", "⠐", "⠈"},
14: {"⠋", "⠙", "⠹", "⠸", "⠼", "⠴", "⠦", "⠧", "⠇", "⠏"},
15: {"a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z"},
16: {"▉", "▊", "▋", "▌", "▍", "▎", "▏", "▎", "▍", "▌", "▋", "▊", "▉"},
17: {"■", "□", "▪", "▫"},
18: {"←", "↑", "→", "↓"},
19: {"╫", "╪"},
20: {"⇐", "⇖", "⇑", "⇗", "⇒", "⇘", "⇓", "⇙"},
21: {"⠁", "⠁", "⠉", "⠙", "⠚", "⠒", "⠂", "⠂", "⠒", "⠲", "⠴", "⠤", "⠄", "⠄", "⠤", "⠠", "⠠", "⠤", "⠦", "⠖", "⠒", "⠐", "⠐", "⠒", "⠓", "⠋", "⠉", "⠈", "⠈"},
22: {"⠈", "⠉", "⠋", "⠓", "⠒", "⠐", "⠐", "⠒", "⠖", "⠦", "⠤", "⠠", "⠠", "⠤", "⠦", "⠖", "⠒", "⠐", "⠐", "⠒", "⠓", "⠋", "⠉", "⠈"},
23: {"⠁", "⠉", "⠙", "⠚", "⠒", "⠂", "⠂", "⠒", "⠲", "⠴", "⠤", "⠄", "⠄", "⠤", "⠴", "⠲", "⠒", "⠂", "⠂", "⠒", "⠚", "⠙", "⠉", "⠁"},
24: {"⠋", "⠙", "⠚", "⠒", "⠂", "⠂", "⠒", "⠲", "⠴", "⠦", "⠖", "⠒", "⠐", "⠐", "⠒", "⠓", "⠋"},
25: {"ヲ", "ァ", "ィ", "ゥ", "ェ", "ォ", "ャ", "ュ", "ョ", "ッ", "ア", "イ", "ウ", "エ", "オ", "カ", "キ", "ク", "ケ", "コ", "サ", "シ", "ス", "セ", "ソ", "タ", "チ", "ツ", "テ", "ト", "ナ", "ニ", "ヌ", "ネ", "ノ", "ハ", "ヒ", "フ", "ヘ", "ホ", "マ", "ミ", "ム", "メ", "モ", "ヤ", "ユ", "ヨ", "ラ", "リ", "ル", "レ", "ロ", "ワ", "ン"},
26: {".", "..", "..."},
27: {"▁", "▂", "▃", "▄", "▅", "▆", "▇", "█", "▉", "▊", "▋", "▌", "▍", "▎", "▏", "▏", "▎", "▍", "▌", "▋", "▊", "▉", "█", "▇", "▆", "▅", "▄", "▃", "▂", "▁"},
28: {".", "o", "O", "°", "O", "o", "."},
29: {"+", "x"},
30: {"v", "<", "^", ">"},
31: {">>--->", " >>--->", " >>--->", " >>--->", " >>--->", " <---<<", " <---<<", " <---<<", " <---<<", "<---<<"},
32: {"|", "||", "|||", "||||", "|||||", "|||||||", "||||||||", "|||||||", "||||||", "|||||", "||||", "|||", "||", "|"},
33: {"[ ]", "[= ]", "[== ]", "[=== ]", "[==== ]", "[===== ]", "[====== ]", "[======= ]", "[======== ]", "[========= ]", "[==========]"},
34: {"(*---------)", "(-*--------)", "(--*-------)", "(---*------)", "(----*-----)", "(-----*----)", "(------*---)", "(-------*--)", "(--------*-)", "(---------*)"},
35: {"█▒▒▒▒▒▒▒▒▒", "███▒▒▒▒▒▒▒", "█████▒▒▒▒▒", "███████▒▒▒", "██████████"},
36: {"[ ]", "[=> ]", "[===> ]", "[=====> ]", "[======> ]", "[========> ]", "[==========> ]", "[============> ]", "[==============> ]", "[================> ]", "[==================> ]", "[===================>]"},
37: {"", ""},
38: {"▌", "▀", "▐▄"},
39: {"🌍", "🌎", "🌏"},
40: {"◜", "◝", "◞", "◟"},
41: {"⬒", "⬔", "⬓", "⬕"},
42: {"⬖", "⬘", "⬗", "⬙"},
43: {"[>>> >]", "[]>>>> []", "[] >>>> []", "[] >>>> []", "[] >>>> []", "[] >>>>[]", "[>> >>]"},
44: {"♠", "♣", "♥", "♦"},
45: {"➞", "➟", "➠", "➡", "➠", "➟"},
46: {" | ", ` \ `, "_ ", ` \ `, " | ", " / ", " _", " / "},
47: {" . . . .", ". . . .", ". . . .", ". . . .", ". . . . ", ". . . . ."},
48: {" | ", " / ", " _ ", ` \ `, " | ", ` \ `, " _ ", " / "},
49: {"⎺", "⎻", "⎼", "⎽", "⎼", "⎻"},
50: {"▹▹▹▹▹", "▸▹▹▹▹", "▹▸▹▹▹", "▹▹▸▹▹", "▹▹▹▸▹", "▹▹▹▹▸"},
51: {"[ ]", "[ =]", "[ ==]", "[ ===]", "[====]", "[=== ]", "[== ]", "[= ]"},
52: {"( ● )", "( ● )", "( ● )", "( ● )", "( ●)", "( ● )", "( ● )", "( ● )", "( ● )"},
53: {"✶", "✸", "✹", "✺", "✹", "✷"},
54: {"▐|\\____________▌", "▐_|\\___________▌", "▐__|\\__________▌", "▐___|\\_________▌", "▐____|\\________▌", "▐_____|\\_______▌", "▐______|\\______▌", "▐_______|\\_____▌", "▐________|\\____▌", "▐_________|\\___▌", "▐__________|\\__▌", "▐___________|\\_▌", "▐____________|\\▌", "▐____________/|▌", "▐___________/|_▌", "▐__________/|__▌", "▐_________/|___▌", "▐________/|____▌", "▐_______/|_____▌", "▐______/|______▌", "▐_____/|_______▌", "▐____/|________▌", "▐___/|_________▌", "▐__/|__________▌", "▐_/|___________▌", "▐/|____________▌"},
55: {"▐⠂ ▌", "▐⠈ ▌", "▐ ⠂ ▌", "▐ ⠠ ▌", "▐ ⡀ ▌", "▐ ⠠ ▌", "▐ ⠂ ▌", "▐ ⠈ ▌", "▐ ⠂ ▌", "▐ ⠠ ▌", "▐ ⡀ ▌", "▐ ⠠ ▌", "▐ ⠂ ▌", "▐ ⠈ ▌", "▐ ⠂▌", "▐ ⠠▌", "▐ ⡀▌", "▐ ⠠ ▌", "▐ ⠂ ▌", "▐ ⠈ ▌", "▐ ⠂ ▌", "▐ ⠠ ▌", "▐ ⡀ ▌", "▐ ⠠ ▌", "▐ ⠂ ▌", "▐ ⠈ ▌", "▐ ⠂ ▌", "▐ ⠠ ▌", "▐ ⡀ ▌", "▐⠠ ▌"},
56: {"¿", "?"},
57: {"⢹", "⢺", "⢼", "⣸", "⣇", "⡧", "⡗", "⡏"},
58: {"⢄", "⢂", "⢁", "⡁", "⡈", "⡐", "⡠"},
59: {". ", ".. ", "...", " ..", " .", " "},
60: {".", "o", "O", "°", "O", "o", "."},
61: {"▓", "▒", "░"},
62: {"▌", "▀", "▐", "▄"},
63: {"⊶", "⊷"},
64: {"▪", "▫"},
65: {"□", "■"},
66: {"▮", "▯"},
67: {"-", "=", "≡"},
68: {"d", "q", "p", "b"},
69: {"∙∙∙", "●∙∙", "∙●∙", "∙∙●", "∙∙∙"},
70: {"🌑 ", "🌒 ", "🌓 ", "🌔 ", "🌕 ", "🌖 ", "🌗 ", "🌘 "},
71: {"☗", "☖"},
72: {"⧇", "⧆"},
73: {"◉", "◎"},
74: {"㊂", "㊀", "㊁"},
75: {"⦾", "⦿"},
}

22
scripts/build_darwin.sh Executable file
View File

@@ -0,0 +1,22 @@
#!/bin/bash
mkdir -p dist
# build universal binary
CGO_ENABLED=1 GOARCH=arm64 go build -o dist/ollama-darwin-arm64
CGO_ENABLED=1 GOARCH=amd64 go build -o dist/ollama-darwin-amd64
lipo -create -output dist/ollama dist/ollama-darwin-arm64 dist/ollama-darwin-amd64
rm dist/ollama-darwin-amd64 dist/ollama-darwin-arm64
codesign --deep --force --options=runtime --sign "$APPLE_IDENTITY" --timestamp dist/ollama
# build and sign the mac app
npm install --prefix app
npm run --prefix app make:sign
cp app/out/make/zip/darwin/universal/Ollama-darwin-universal-${VERSION:-0.0.0}.zip dist/Ollama-darwin.zip
# sign the binary and rename it
codesign -f --timestamp -s "$APPLE_IDENTITY" --identifier ai.ollama.ollama --options=runtime dist/ollama
ditto -c -k --keepParent dist/ollama dist/temp.zip
xcrun notarytool submit dist/temp.zip --wait --timeout 10m --apple-id $APPLE_ID --password $APPLE_PASSWORD --team-id $APPLE_TEAM_ID
mv dist/ollama dist/ollama-darwin
rm dist/temp.zip

View File

@@ -8,28 +8,18 @@ if [[ -z "${VERSION}" ]]; then
fi
OS=$(go env GOOS)
ARCH=$(go env GOARCH)
go build .
npm --prefix app run make:sign
./script/build_${OS}.sh
# Create a new tag if it doesn't exist.
if ! git rev-parse v$VERSION >/dev/null 2>&1; then
git tag v$VERSION
git push origin v$VERSION
fi
mkdir -p dist
cp app/out/make/zip/${OS}/${ARCH}/Ollama-${OS}-${ARCH}-${VERSION}.zip dist/Ollama-${OS}-${ARCH}.zip
cp ./ollama dist/ollama-${OS}-${ARCH}
git push origin v$VERSION
# Create a new release.
gh release create v$VERSION
gh release create -p v$VERSION -t v$VERSION
# Upload the zip file.
gh release upload v$VERSION ./dist/Ollama-${OS}-${ARCH}.zip
# Upload the binary.
gh release upload v$VERSION ./dist/ollama-${OS}-${ARCH}
gh release upload v$VERSION ./dist/* --clobber

File diff suppressed because it is too large Load Diff

View File

@@ -4,6 +4,7 @@ import (
"fmt"
"os"
"path/filepath"
"runtime"
"strings"
)
@@ -44,7 +45,7 @@ func ParseModelPath(name string) ModelPath {
return ModelPath{}
}
colonParts := strings.Split(name, ":")
colonParts := strings.Split(slashParts[len(slashParts)-1], ":")
if len(colonParts) == 2 {
tag = colonParts[1]
} else {
@@ -69,10 +70,13 @@ func (mp ModelPath) GetFullTagname() string {
}
func (mp ModelPath) GetShortTagname() string {
if mp.Registry == DefaultRegistry && mp.Namespace == DefaultNamespace {
return fmt.Sprintf("%s:%s", mp.Repository, mp.Tag)
if mp.Registry == DefaultRegistry {
if mp.Namespace == DefaultNamespace {
return fmt.Sprintf("%s:%s", mp.Repository, mp.Tag)
}
return fmt.Sprintf("%s/%s:%s", mp.Namespace, mp.Repository, mp.Tag)
}
return fmt.Sprintf("%s/%s:%s", mp.Namespace, mp.Repository, mp.Tag)
return fmt.Sprintf("%s/%s/%s:%s", mp.Registry, mp.Namespace, mp.Repository, mp.Tag)
}
func (mp ModelPath) GetManifestPath(createDir bool) (string, error) {
@@ -91,16 +95,29 @@ func (mp ModelPath) GetManifestPath(createDir bool) (string, error) {
return path, nil
}
func GetManifestPath() (string, error) {
home, err := os.UserHomeDir()
if err != nil {
return "", err
}
return filepath.Join(home, ".ollama", "models", "manifests"), nil
}
func GetBlobsPath(digest string) (string, error) {
home, err := os.UserHomeDir()
if err != nil {
return "", err
}
path := filepath.Join(home, ".ollama", "models", "blobs")
if runtime.GOOS == "windows" {
digest = strings.ReplaceAll(digest, ":", "-")
}
path := filepath.Join(home, ".ollama", "models", "blobs", digest)
if err := os.MkdirAll(filepath.Dir(path), 0o755); err != nil {
return "", err
}
return filepath.Join(path, digest), nil
return path, nil
}

View File

@@ -2,34 +2,43 @@ package server
import (
"encoding/json"
"errors"
"fmt"
"io"
"log"
"net"
"net/http"
"os"
"path/filepath"
"reflect"
"strings"
"text/template"
"sync"
"time"
"dario.cat/mergo"
"github.com/gin-contrib/cors"
"github.com/gin-gonic/gin"
"github.com/jmorganca/ollama/api"
"github.com/jmorganca/ollama/llama"
)
func cacheDir() string {
home, err := os.UserHomeDir()
if err != nil {
panic(err)
}
var loaded struct {
mu sync.Mutex
return filepath.Join(home, ".ollama")
llm *llama.LLM
expireAt time.Time
expireTimer *time.Timer
digest string
options api.Options
}
func generate(c *gin.Context) {
start := time.Now()
func GenerateHandler(c *gin.Context) {
loaded.mu.Lock()
defer loaded.mu.Unlock()
checkpointStart := time.Now()
var req api.GenerateRequest
if err := c.ShouldBindJSON(&req); err != nil {
@@ -44,54 +53,93 @@ func generate(c *gin.Context) {
}
opts := api.DefaultOptions()
if err := mergo.Merge(&opts, model.Options, mergo.WithOverride); err != nil {
if err := opts.FromMap(model.Options); err != nil {
log.Printf("could not load model options: %v", err)
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
if err := mergo.Merge(&opts, req.Options, mergo.WithOverride); err != nil {
if err := opts.FromMap(req.Options); err != nil {
log.Printf("could not merge model options: %v", err)
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
templ, err := template.New("").Parse(model.Prompt)
if model.Digest != loaded.digest || !reflect.DeepEqual(loaded.options, opts) {
if loaded.llm != nil {
loaded.llm.Close()
loaded.llm = nil
loaded.digest = ""
}
llm, err := llama.New(model.ModelPath, opts)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
loaded.llm = llm
loaded.digest = model.Digest
loaded.options = opts
}
sessionDuration := 5 * time.Minute
loaded.expireAt = time.Now().Add(sessionDuration)
if loaded.expireTimer == nil {
loaded.expireTimer = time.AfterFunc(sessionDuration, func() {
loaded.mu.Lock()
defer loaded.mu.Unlock()
if time.Now().Before(loaded.expireAt) {
return
}
if loaded.llm == nil {
return
}
loaded.llm.Close()
loaded.llm = nil
loaded.digest = ""
})
}
loaded.expireTimer.Reset(sessionDuration)
checkpointLoaded := time.Now()
prompt, err := model.Prompt(req)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
var sb strings.Builder
if err = templ.Execute(&sb, req); err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
req.Prompt = sb.String()
llm, err := llama.New(model.ModelPath, opts)
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
defer llm.Close()
ch := make(chan any)
go func() {
defer close(ch)
llm.Predict(req.Context, req.Prompt, func(r api.GenerateResponse) {
fn := func(r api.GenerateResponse) {
loaded.expireAt = time.Now().Add(sessionDuration)
loaded.expireTimer.Reset(sessionDuration)
r.Model = req.Model
r.CreatedAt = time.Now().UTC()
if r.Done {
r.TotalDuration = time.Since(start)
r.TotalDuration = time.Since(checkpointStart)
r.LoadDuration = checkpointLoaded.Sub(checkpointStart)
}
ch <- r
})
}
if err := loaded.llm.Predict(req.Context, prompt, fn); err != nil {
ch <- gin.H{"error": err.Error()}
}
}()
streamResponse(c, ch)
}
func pull(c *gin.Context) {
func PullModelHandler(c *gin.Context) {
var req api.PullRequest
if err := c.ShouldBindJSON(&req); err != nil {
c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
@@ -101,25 +149,25 @@ func pull(c *gin.Context) {
ch := make(chan any)
go func() {
defer close(ch)
fn := func(status, digest string, total, completed int, percent float64) {
ch <- api.PullProgress{
Status: status,
Digest: digest,
Total: total,
Completed: completed,
Percent: percent,
}
fn := func(r api.ProgressResponse) {
ch <- r
}
if err := PullModel(req.Name, req.Username, req.Password, fn); err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
regOpts := &RegistryOptions{
Insecure: req.Insecure,
Username: req.Username,
Password: req.Password,
}
if err := PullModel(req.Name, regOpts, fn); err != nil {
ch <- gin.H{"error": err.Error()}
}
}()
streamResponse(c, ch)
}
func push(c *gin.Context) {
func PushModelHandler(c *gin.Context) {
var req api.PushRequest
if err := c.ShouldBindJSON(&req); err != nil {
c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
@@ -129,69 +177,162 @@ func push(c *gin.Context) {
ch := make(chan any)
go func() {
defer close(ch)
fn := func(status, digest string, total, completed int, percent float64) {
ch <- api.PushProgress{
Status: status,
Digest: digest,
Total: total,
Completed: completed,
Percent: percent,
}
fn := func(r api.ProgressResponse) {
ch <- r
}
if err := PushModel(req.Name, req.Username, req.Password, fn); err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
regOpts := &RegistryOptions{
Insecure: req.Insecure,
Username: req.Username,
Password: req.Password,
}
if err := PushModel(req.Name, regOpts, fn); err != nil {
ch <- gin.H{"error": err.Error()}
}
}()
streamResponse(c, ch)
}
func create(c *gin.Context) {
func CreateModelHandler(c *gin.Context) {
var req api.CreateRequest
if err := c.ShouldBindJSON(&req); err != nil {
c.JSON(http.StatusBadRequest, gin.H{"message": err.Error()})
return
}
// NOTE consider passing the entire Modelfile in the json instead of the path to it
file, err := os.Open(req.Path)
if err != nil {
c.JSON(http.StatusBadRequest, gin.H{"message": err.Error()})
return
}
defer file.Close()
ch := make(chan any)
go func() {
defer close(ch)
fn := func(status string) {
ch <- api.CreateProgress{
Status: status,
}
fn := func(resp api.ProgressResponse) {
ch <- resp
}
if err := CreateModel(req.Name, file, fn); err != nil {
c.JSON(http.StatusBadRequest, gin.H{"message": err.Error()})
return
if err := CreateModel(req.Name, req.Path, fn); err != nil {
ch <- gin.H{"error": err.Error()}
}
}()
streamResponse(c, ch)
}
func DeleteModelHandler(c *gin.Context) {
var req api.DeleteRequest
if err := c.ShouldBindJSON(&req); err != nil {
c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
return
}
if err := DeleteModel(req.Name); err != nil {
if os.IsNotExist(err) {
c.JSON(http.StatusNotFound, gin.H{"error": fmt.Sprintf("model '%s' not found", req.Name)})
} else {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
}
return
}
}
func ListModelsHandler(c *gin.Context) {
var models []api.ListResponseModel
fp, err := GetManifestPath()
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
err = filepath.Walk(fp, func(path string, info os.FileInfo, err error) error {
if err != nil {
if errors.Is(err, os.ErrNotExist) {
log.Printf("manifest file does not exist: %s", fp)
return nil
}
return err
}
if !info.IsDir() {
fi, err := os.Stat(path)
if err != nil {
log.Printf("skipping file: %s", fp)
return nil
}
path := path[len(fp)+1:]
slashIndex := strings.LastIndex(path, "/")
if slashIndex == -1 {
return nil
}
tag := path[:slashIndex] + ":" + path[slashIndex+1:]
mp := ParseModelPath(tag)
manifest, err := GetManifest(mp)
if err != nil {
log.Printf("skipping file: %s", fp)
return nil
}
model := api.ListResponseModel{
Name: mp.GetShortTagname(),
Size: manifest.GetTotalSize(),
ModifiedAt: fi.ModTime(),
}
models = append(models, model)
}
return nil
})
if err != nil {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
c.JSON(http.StatusOK, api.ListResponse{Models: models})
}
func CopyModelHandler(c *gin.Context) {
var req api.CopyRequest
if err := c.ShouldBindJSON(&req); err != nil {
c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
return
}
if err := CopyModel(req.Source, req.Destination); err != nil {
if os.IsNotExist(err) {
c.JSON(http.StatusNotFound, gin.H{"error": fmt.Sprintf("model '%s' not found", req.Source)})
} else {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
}
return
}
}
func Serve(ln net.Listener) error {
config := cors.DefaultConfig()
config.AllowWildcard = true
// only allow http/https from localhost
config.AllowOrigins = []string{
"http://localhost",
"http://localhost:*",
"https://localhost",
"https://localhost:*",
"http://127.0.0.1",
"http://127.0.0.1:*",
"https://127.0.0.1",
"https://127.0.0.1:*",
}
r := gin.Default()
r.Use(cors.New(config))
r.GET("/", func(c *gin.Context) {
c.String(http.StatusOK, "Ollama is running")
})
r.HEAD("/", func(c *gin.Context) {
c.Status(http.StatusOK)
})
r.POST("/api/pull", pull)
r.POST("/api/generate", generate)
r.POST("/api/create", create)
r.POST("/api/push", push)
r.POST("/api/pull", PullModelHandler)
r.POST("/api/generate", GenerateHandler)
r.POST("/api/create", CreateModelHandler)
r.POST("/api/push", PushModelHandler)
r.POST("/api/copy", CopyModelHandler)
r.GET("/api/tags", ListModelsHandler)
r.DELETE("/api/delete", DeleteModelHandler)
log.Printf("Listening on %s", ln.Addr())
s := &http.Server{
@@ -210,11 +351,13 @@ func streamResponse(c *gin.Context, ch chan any) {
bts, err := json.Marshal(val)
if err != nil {
log.Printf("streamResponse: json.Marshal failed with %s", err)
return false
}
bts = append(bts, '\n')
if _, err := w.Write(bts); err != nil {
log.Printf("streamResponse: w.Write failed with %s", err)
return false
}

View File

@@ -1,10 +0,0 @@
{{- if not .Context }}
Below is an instruction that describes a task. Write a response that appropriately completes the request.
{{- end }}
### Instruction:
{{ .Prompt }}
### Response:

View File

@@ -1,5 +0,0 @@
{{- if not .Context }}
A helpful assistant who helps the user with any questions asked.
{{- end }}
User: {{ .Prompt }}
Assistant:

View File

@@ -1,5 +0,0 @@
### Instruction:
{{ .Prompt }}
### Response:

View File

@@ -1,5 +0,0 @@
### Instruction:
{{ .Prompt }}
### Response:

View File

@@ -1,6 +0,0 @@
{{- if not .Context }}
Below is an instruction that describes a task. Write a response that appropriately completes the request. Be concise. Once the request is completed, include no other text.
{{- end }}
### Instruction:
{{ .Prompt }}
### Response:

View File

@@ -1 +0,0 @@
{{ .Prompt }}

View File

@@ -1,9 +0,0 @@
{{- if not .Context }}
### System:
You are an AI assistant that follows instruction extremely well. Help as much as you can.
{{- end }}
### User:
{{ .Prompt }}
### Response:

View File

@@ -1,2 +0,0 @@
### Human: {{ .Prompt }}
### Assistant:

View File

@@ -1,4 +0,0 @@
{{ .Prompt }}

View File

@@ -1,2 +0,0 @@
USER: {{ .Prompt }}
ASSISTANT:

View File

@@ -1,6 +0,0 @@
{{ if not .Context }}
A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.
{{- end }}
USER: {{ .Prompt }}
ASSISTANT:

View File

@@ -1,7 +0,0 @@
{{- if not .Context }}
Below is an instruction that describes a task. Write a response that appropriately completes the request
{{- end }}
### Instruction: {{ .Prompt }}
### Response:

View File

@@ -1,3 +0,0 @@
{{ .Prompt }}
### Response:

View File

@@ -1,6 +0,0 @@
import models from '../../../../models.json'
import { NextResponse } from 'next/server'
export async function GET() {
return NextResponse.json(models)
}

View File

@@ -6,12 +6,22 @@ const analytics = new Analytics({ writeKey: process.env.TELEMETRY_WRITE_KEY || '
export async function POST(req: Request) {
const { email } = await req.json()
analytics.identify({
anonymousId: uuid(),
const id = uuid()
await analytics.identify({
anonymousId: id,
traits: {
email,
},
})
await analytics.track({
anonymousId: id,
event: 'signup',
properties: {
email,
},
})
return new Response(null, { status: 200 })
}

View File

@@ -14,11 +14,12 @@ export async function GET(req: Request) {
const res = await fetch('https://api.github.com/repos/jmorganca/ollama/releases', { next: { revalidate: 60 } })
const data = await res.json()
if (data.length === 0) {
const latest = data?.filter((f: any) => !f.prerelease)?.[0]
if (!latest) {
return new Response('not found', { status: 404 })
}
const latest = data[0]
const assets = latest.assets || []
if (assets.length === 0) {

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