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...

66 Commits

Author SHA1 Message Date
Matt Williams
4522109b11 addressing new comments after merge
Signed-off-by: Matt Williams <m@technovangelist.com>
2023-10-15 14:17:23 -07:00
Matt Williams
b2974a7095 applied mikes comments
Signed-off-by: Matt Williams <m@technovangelist.com>
2023-10-14 08:29:24 -07:00
Matt Williams
3c975f898f update doc to refer to docker image
Signed-off-by: Matt Williams <m@technovangelist.com>
2023-10-12 15:57:50 -07:00
Matt Williams
9245c8a1df add how to quantize doc
Signed-off-by: Matt Williams <m@technovangelist.com>
2023-10-12 15:34:57 -07:00
Michael Yang
7a537cdca9 Merge pull request #770 from jmorganca/mxyng/fix-download
fix download
2023-10-12 12:56:43 -07:00
Michael Yang
257ffeb997 fix download 2023-10-12 12:52:43 -07:00
Matt Williams
9b513bb6b1 Merge pull request #753 from jmorganca/mattw/examplereorg
rename the examples to be more descriptive
2023-10-12 11:24:12 -07:00
Matt Williams
042100f797 final rename
Signed-off-by: Matt Williams <m@technovangelist.com>
2023-10-12 11:23:41 -07:00
Bruce MacDonald
7804b8fab9 validate api options fields from map (#711) 2023-10-12 11:18:11 -04:00
Bruce MacDonald
56497663c8 relay model runner error message to client (#720)
* give direction to user when runner fails
* also relay errors from timeout
* increase timeout to 3 minutes
2023-10-12 11:16:37 -04:00
Matt Williams
e1afcb8af2 simple gen to simple
Signed-off-by: Matt Williams <m@technovangelist.com>
2023-10-11 21:29:07 -07:00
Matt Williams
385eeea357 remove with
Signed-off-by: Matt Williams <m@technovangelist.com>
2023-10-11 21:26:11 -07:00
Matt Williams
8a41b244e8 add golang gen
Signed-off-by: Matt Williams <m@technovangelist.com>
2023-10-11 21:20:50 -07:00
Jeffrey Morgan
92578798bb fix relative links in README.md 2023-10-11 19:24:06 -04:00
Michael Yang
788637918a Merge pull request #760 from jmorganca/mxyng/more-downloads
Mxyng/more downloads
2023-10-11 14:33:10 -07:00
Michael Yang
c413a55093 download: handle inner errors 2023-10-11 14:15:30 -07:00
Michael Yang
630bb75d2a dynamically size download parts based on file size 2023-10-11 14:10:25 -07:00
Michael Yang
a2055a1e93 update download 2023-10-11 14:10:25 -07:00
Michael Yang
b599946b74 add format bytes 2023-10-11 14:08:23 -07:00
Michael Yang
aca2d65b82 Merge pull request #757 from jmorganca/mxyng/format-time
cleanup format time
2023-10-11 11:12:29 -07:00
Michael Yang
b5e08e3373 cleanup format time 2023-10-11 11:09:27 -07:00
Bruce MacDonald
274d5a5fdf optional parameter to not stream response (#639)
* update streaming request accept header
* add optional stream param to request bodies
2023-10-11 12:54:27 -04:00
Matt Williams
fc6b49be32 add ts alternate to python langchain simplegen
Signed-off-by: Matt Williams <m@technovangelist.com>
2023-10-11 09:50:15 -07:00
Bruce MacDonald
77295f716e prevent waiting on exited command (#752)
* prevent waiting on exited command
* close llama runner once
2023-10-11 12:32:13 -04:00
Matt Williams
615f7d1dea cleanup readme.
Signed-off-by: Matt Williams <m@technovangelist.com>
2023-10-11 06:13:29 -07:00
Matt Williams
cdf5e106ae rename dirs
Signed-off-by: Matt Williams <m@technovangelist.com>
2023-10-11 06:10:24 -07:00
Matt Williams
a85329f59a rename the models to be more descriptive
Signed-off-by: Matt Williams <m@technovangelist.com>
2023-10-10 17:40:02 -07:00
Bruce MacDonald
f2ba1311aa improve vram safety with 5% vram memory buffer (#724)
* check free memory not total
* wait for subprocess to exit
2023-10-10 16:16:09 -04:00
Jeffrey Morgan
65dcd0ce35 always cleanup blob download (#747) 2023-10-10 13:12:29 -04:00
Michael Yang
0040f543a2 Merge pull request #743 from jmorganca/mxyng/http-proxy
handle upstream proxies
2023-10-10 09:59:06 -07:00
Matt Williams
767f9bdbbb Merge pull request #585 from jmorganca/matt/examplementors
add the example for ask the mentors
2023-10-09 13:58:14 -07:00
Costa Alexoglou
f7f5169c94 Update api.md (#741)
Avoid triple ticks in visual editor and also copied in clipboard.
2023-10-09 16:01:46 -04:00
Michael Yang
2cfffea02e handle client proxy 2023-10-09 12:33:47 -07:00
Michael Yang
f6e98334e4 handle upstream proxies 2023-10-09 11:42:36 -07:00
Jeffrey Morgan
ab0668293c llm: fix build on amd64 2023-10-06 14:39:54 -07:00
Bruce MacDonald
af4cf55884 not found error before pulling model (#718) 2023-10-06 16:06:20 -04:00
Bruce MacDonald
d6786f2945 add feedback for reading model metadata (#722) 2023-10-06 16:05:32 -04:00
Michael Yang
38dc2f79bc Merge pull request #626 from jmorganca/mxyng/concurrent-downloads
parallel chunked downloads
2023-10-06 13:01:29 -07:00
Michael Yang
cb961c87ca Merge pull request #679 from jamesbraza/modelfile-docs
`Modelfile` syntax highlighting
2023-10-06 12:59:45 -07:00
Michael Yang
0560b28a8d names 2023-10-06 12:56:56 -07:00
Michael Yang
10199c5987 replace done channel with file check 2023-10-06 12:56:56 -07:00
Michael Yang
288814d3e4 fix ref counts 2023-10-06 12:56:43 -07:00
Michael Yang
04733438da check head request response 2023-10-06 12:56:43 -07:00
Michael Yang
711e891f0f fix resumable downloads
glob returns files in lexical order which is not appropriate when
rebuilding the parts list
2023-10-06 12:56:43 -07:00
Michael Yang
090d08422b handle unexpected eofs 2023-10-06 12:56:43 -07:00
Michael Yang
5b84404c64 handle concurrent requests for the same blobs 2023-10-06 12:56:43 -07:00
Michael Yang
8544edca21 parallel chunked downloads 2023-10-06 12:56:43 -07:00
Bruce MacDonald
5d22319a2c rename server subprocess (#700)
- this makes it easier to see that the subprocess is associated with ollama
2023-10-06 10:15:42 -04:00
Bruce MacDonald
2130c0708b output type parsed from modelfile (#678) 2023-10-05 14:58:04 -04:00
Patrick Devine
61ff1946e6 revise help text (#706) 2023-10-05 11:36:07 -07:00
Bruce MacDonald
d06bc0cb6e enable q8, q5, 5_1, and f32 for linux gpu (#699) 2023-10-05 12:53:47 -04:00
Alexander F. Rødseth
d104b7e997 Fix go test./... issue: fmt.Println arg list ends with redundant newline (#705) 2023-10-05 11:11:04 -04:00
Bruce MacDonald
9e2de1bd2c increase streaming buffer size (#692) 2023-10-04 14:09:00 -04:00
Jeffrey Morgan
dc87e9c9ae update Dockerfile to pass GOFLAGS 2023-10-03 07:05:15 -07:00
Michael Yang
367cb68dc1 Merge pull request #686 from jmorganca/mxyng/starcoder
decode starcoder
2023-10-02 22:47:19 -07:00
Michael Yang
c02c0cd483 starcoder 2023-10-02 19:56:51 -07:00
Patrick Devine
1852755154 show a default message when license/parameters/system prompt/template aren't specified (#681) 2023-10-02 14:34:52 -07:00
James Braza
6f2ce74231 Got rif of all caps to show it can be lower case 2023-10-02 13:54:27 -07:00
James Braza
6edcc5c79f Using code highlighting syntax around Modelfile 2023-10-02 13:46:05 -07:00
Bruce MacDonald
b1f7123301 clean up num_gpu calculation code (#673) 2023-10-02 14:53:42 -04:00
Bruce MacDonald
1fbf3585d6 Relay default values to llama runner (#672)
* include seed in params for llama.cpp server and remove empty filter for temp

* relay default predict options to llama.cpp

- reorganize options to match predict request for readability

* omit empty stop

---------

Co-authored-by: hallh <hallh@users.noreply.github.com>
2023-10-02 14:53:16 -04:00
Patrick Devine
99d5161e8a don't wordwrap when stdout is redirected or piped (#662) 2023-10-02 11:50:55 -07:00
Michael
ea8380be45 add community project: Chatbot Ollama
add community project: Chatbot Ollama by @ivanfioravanti
2023-10-02 09:04:31 -07:00
Jeffrey Morgan
4f25092dc1 fix build_docker.sh permissions 2023-10-01 16:42:32 -07:00
Jiayu Liu
4fc10acce9 add some missing code directives in docs (#664) 2023-10-01 11:51:01 -07:00
Matt Williams
a92fdff620 add the example for ask the mentors
Signed-off-by: Matt Williams <m@technovangelist.com>
2023-09-24 15:58:32 -07:00
83 changed files with 2465 additions and 669 deletions

View File

@@ -1,7 +1,6 @@
FROM nvidia/cuda:11.8.0-devel-ubuntu22.04
ARG TARGETARCH
ARG VERSION=0.0.0
ARG GOFLAGS="'-ldflags=-w -s'"
WORKDIR /go/src/github.com/jmorganca/ollama
@@ -11,6 +10,7 @@ RUN mkdir -p /usr/local && tar xz -C /usr/local </tmp/go1.21.1.tar.gz
COPY . .
ENV GOARCH=$TARGETARCH
ENV GOFLAGS=$GOFLAGS
RUN /usr/local/go/bin/go generate ./... \
&& /usr/local/go/bin/go build .

View File

@@ -14,6 +14,7 @@ RUN yum install -y git cmake
FROM base-${TARGETARCH}
ARG TARGETARCH
ARG GOFLAGS="'-ldflags -w -s'"
# install go
ADD https://dl.google.com/go/go1.21.1.linux-$TARGETARCH.tar.gz /tmp/go1.21.1.tar.gz
@@ -22,11 +23,10 @@ RUN mkdir -p /usr/local && tar xz -C /usr/local </tmp/go1.21.1.tar.gz
# build the final binary
WORKDIR /go/src/github.com/jmorganca/ollama
COPY . .
ENV GOOS=linux
ENV GOARCH=$TARGETARCH
ARG VERSION=0.0.0
ARG GOFLAGS="'-ldflags -w -s'"
ENV GOFLAGS=$GOFLAGS
RUN /usr/local/go/bin/go generate ./... && \
/usr/local/go/bin/go build .

View File

@@ -13,7 +13,7 @@ Get up and running with large language models locally.
### macOS
[Download](https://ollama.ai/download/Ollama-darwin.zip)
[Download](https://ollama.ai/download/Ollama-darwin.zip)
### Linux & WSL2
@@ -23,7 +23,7 @@ curl https://ollama.ai/install.sh | sh
[Manual install instructions](https://github.com/jmorganca/ollama/blob/main/docs/linux.md)
### Windows
### Windows
coming soon
@@ -37,7 +37,7 @@ ollama run llama2
## Model library
Ollama supports a list of open-source models available on [ollama.ai/library](https://ollama.ai/library "ollama model library")
Ollama supports a list of open-source models available on [ollama.ai/library](https://ollama.ai/library 'ollama model library')
Here are some example open-source models that can be downloaded:
@@ -66,13 +66,13 @@ Ollama supports importing GGUF and GGML file formats in the Modelfile. This mean
FROM ./vicuna-33b.Q4_0.gguf
```
3. Create the model in Ollama
2. Create the model in Ollama
```
ollama create name -f path_to_modelfile
```
5. Run the model
3. Run the model
```
ollama run name
@@ -109,7 +109,7 @@ ollama run mario
Hello! It's your friend Mario.
```
For more examples, see the [examples](./examples) directory. For more information on working with a Modelfile, see the [Modelfile](./docs/modelfile.md) documentation.
For more examples, see the [examples](examples) directory. For more information on working with a Modelfile, see the [Modelfile](docs/modelfile.md) documentation.
## CLI Reference
@@ -195,7 +195,7 @@ Finally, in a separate shell, run a model:
## REST API
> See the [API documentation](./docs/api.md) for all endpoints.
> See the [API documentation](docs/api.md) for all endpoints.
Ollama has an API for running and managing models. For example to generate text from a model:
@@ -217,6 +217,7 @@ curl -X POST http://localhost:11434/api/generate -d '{
- [Dagger Chatbot](https://github.com/samalba/dagger-chatbot)
- [LiteLLM](https://github.com/BerriAI/litellm)
- [Discord AI Bot](https://github.com/mekb-turtle/discord-ai-bot)
- [Chatbot UI](https://github.com/ivanfioravanti/chatbot-ollama)
- [HTML UI](https://github.com/rtcfirefly/ollama-ui)
- [Typescript UI](https://github.com/ollama-interface/Ollama-Gui?tab=readme-ov-file)
- [Dumbar](https://github.com/JerrySievert/Dumbar)

View File

@@ -7,6 +7,7 @@ import (
"encoding/json"
"fmt"
"io"
"net"
"net/http"
"net/url"
"os"
@@ -18,14 +19,11 @@ import (
const DefaultHost = "127.0.0.1:11434"
var (
envHost = os.Getenv("OLLAMA_HOST")
)
var envHost = os.Getenv("OLLAMA_HOST")
type Client struct {
Base url.URL
HTTP http.Client
Headers http.Header
base *url.URL
http http.Client
}
func checkError(resp *http.Response, body []byte) error {
@@ -44,34 +42,44 @@ func checkError(resp *http.Response, body []byte) error {
return apiError
}
// Host returns the default host to use for the client. It is determined in the following order:
// 1. The OLLAMA_HOST environment variable
// 2. The default host (localhost:11434)
func Host() string {
if envHost != "" {
return envHost
}
return DefaultHost
}
// FromEnv creates a new client using Host() as the host. An error is returns
// if the host is invalid.
func FromEnv() (*Client, error) {
h := Host()
if !strings.HasPrefix(h, "http://") && !strings.HasPrefix(h, "https://") {
h = "http://" + h
func ClientFromEnvironment() (*Client, error) {
scheme, hostport, ok := strings.Cut(os.Getenv("OLLAMA_HOST"), "://")
if !ok {
scheme, hostport = "http", os.Getenv("OLLAMA_HOST")
}
u, err := url.Parse(h)
host, port, err := net.SplitHostPort(hostport)
if err != nil {
return nil, fmt.Errorf("could not parse host: %w", err)
host, port = "127.0.0.1", "11434"
if ip := net.ParseIP(strings.Trim(os.Getenv("OLLAMA_HOST"), "[]")); ip != nil {
host = ip.String()
}
}
if u.Port() == "" {
u.Host += ":11434"
client := Client{
base: &url.URL{
Scheme: scheme,
Host: net.JoinHostPort(host, port),
},
}
return &Client{Base: *u, HTTP: http.Client{}}, nil
mockRequest, err := http.NewRequest("HEAD", client.base.String(), nil)
if err != nil {
return nil, err
}
proxyURL, err := http.ProxyFromEnvironment(mockRequest)
if err != nil {
return nil, err
}
client.http = http.Client{
Transport: &http.Transport{
Proxy: http.ProxyURL(proxyURL),
},
}
return &client, nil
}
func (c *Client) do(ctx context.Context, method, path string, reqData, respData any) error {
@@ -86,7 +94,7 @@ func (c *Client) do(ctx context.Context, method, path string, reqData, respData
reqBody = bytes.NewReader(data)
}
requestURL := c.Base.JoinPath(path)
requestURL := c.base.JoinPath(path)
request, err := http.NewRequestWithContext(ctx, method, requestURL.String(), reqBody)
if err != nil {
return err
@@ -96,11 +104,7 @@ func (c *Client) do(ctx context.Context, method, path string, reqData, respData
request.Header.Set("Accept", "application/json")
request.Header.Set("User-Agent", fmt.Sprintf("ollama/%s (%s %s) Go/%s", version.Version, runtime.GOARCH, runtime.GOOS, runtime.Version()))
for k, v := range c.Headers {
request.Header[k] = v
}
respObj, err := c.HTTP.Do(request)
respObj, err := c.http.Do(request)
if err != nil {
return err
}
@@ -123,6 +127,8 @@ func (c *Client) do(ctx context.Context, method, path string, reqData, respData
return nil
}
const maxBufferSize = 512 * 1000 // 512KB
func (c *Client) stream(ctx context.Context, method, path string, data any, fn func([]byte) error) error {
var buf *bytes.Buffer
if data != nil {
@@ -134,23 +140,26 @@ func (c *Client) stream(ctx context.Context, method, path string, data any, fn f
buf = bytes.NewBuffer(bts)
}
requestURL := c.Base.JoinPath(path)
requestURL := c.base.JoinPath(path)
request, err := http.NewRequestWithContext(ctx, method, requestURL.String(), buf)
if err != nil {
return err
}
request.Header.Set("Content-Type", "application/json")
request.Header.Set("Accept", "application/json")
request.Header.Set("Accept", "application/x-ndjson")
request.Header.Set("User-Agent", fmt.Sprintf("ollama/%s (%s %s) Go/%s", version.Version, runtime.GOARCH, runtime.GOOS, runtime.Version()))
response, err := http.DefaultClient.Do(request)
response, err := c.http.Do(request)
if err != nil {
return err
}
defer response.Body.Close()
scanner := bufio.NewScanner(response.Body)
// increase the buffer size to avoid running out of space
scanBuf := make([]byte, 0, maxBufferSize)
scanner.Buffer(scanBuf, maxBufferSize)
for scanner.Scan() {
var errorResponse struct {
Error string `json:"error,omitempty"`

View File

@@ -37,6 +37,7 @@ type GenerateRequest struct {
System string `json:"system"`
Template string `json:"template"`
Context []int `json:"context,omitempty"`
Stream *bool `json:"stream,omitempty"`
Options map[string]interface{} `json:"options"`
}
@@ -53,8 +54,9 @@ type EmbeddingResponse struct {
}
type CreateRequest struct {
Name string `json:"name"`
Path string `json:"path"`
Name string `json:"name"`
Path string `json:"path"`
Stream *bool `json:"stream,omitempty"`
}
type DeleteRequest struct {
@@ -81,6 +83,9 @@ type CopyRequest struct {
type PullRequest struct {
Name string `json:"name"`
Insecure bool `json:"insecure,omitempty"`
Username string `json:"username"`
Password string `json:"password"`
Stream *bool `json:"stream,omitempty"`
}
type ProgressResponse struct {
@@ -93,6 +98,9 @@ type ProgressResponse struct {
type PushRequest struct {
Name string `json:"name"`
Insecure bool `json:"insecure,omitempty"`
Username string `json:"username"`
Password string `json:"password"`
Stream *bool `json:"stream,omitempty"`
}
type ListResponse struct {
@@ -113,7 +121,7 @@ type TokenResponse struct {
type GenerateResponse struct {
Model string `json:"model"`
CreatedAt time.Time `json:"created_at"`
Response string `json:"response,omitempty"`
Response string `json:"response"`
Done bool `json:"done"`
Context []int `json:"context,omitempty"`
@@ -197,6 +205,8 @@ type Options struct {
NumThread int `json:"num_thread,omitempty"`
}
var ErrInvalidOpts = fmt.Errorf("invalid options")
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
@@ -210,6 +220,7 @@ func (opts *Options) FromMap(m map[string]interface{}) error {
}
}
invalidOpts := []string{}
for key, val := range m {
if opt, ok := jsonOpts[key]; ok {
field := valueOpts.FieldByName(opt.Name)
@@ -227,12 +238,12 @@ func (opts *Options) FromMap(m map[string]interface{}) error {
// when JSON unmarshals numbers, it uses float64, not int
field.SetInt(int64(t))
default:
log.Printf("could not convert model parameter %v to int, skipped", key)
log.Printf("could not convert model parameter %v of type %T to int, skipped", key, val)
}
case reflect.Bool:
val, ok := val.(bool)
if !ok {
log.Printf("could not convert model parameter %v to bool, skipped", key)
log.Printf("could not convert model parameter %v of type %T to bool, skipped", key, val)
continue
}
field.SetBool(val)
@@ -240,14 +251,14 @@ func (opts *Options) FromMap(m map[string]interface{}) error {
// JSON unmarshals to float64
val, ok := val.(float64)
if !ok {
log.Printf("could not convert model parameter %v to float32, skipped", key)
log.Printf("could not convert model parameter %v of type %T to float32, skipped", key, val)
continue
}
field.SetFloat(val)
case reflect.String:
val, ok := val.(string)
if !ok {
log.Printf("could not convert model parameter %v to string, skipped", key)
log.Printf("could not convert model parameter %v of type %T to string, skipped", key, val)
continue
}
field.SetString(val)
@@ -255,7 +266,7 @@ func (opts *Options) FromMap(m map[string]interface{}) error {
// JSON unmarshals to []interface{}, not []string
val, ok := val.([]interface{})
if !ok {
log.Printf("could not convert model parameter %v to slice, skipped", key)
log.Printf("could not convert model parameter %v of type %T to slice, skipped", key, val)
continue
}
// convert []interface{} to []string
@@ -263,7 +274,7 @@ func (opts *Options) FromMap(m map[string]interface{}) error {
for i, item := range val {
str, ok := item.(string)
if !ok {
log.Printf("could not convert model parameter %v to slice of strings, skipped", key)
log.Printf("could not convert model parameter %v of type %T to slice of strings, skipped", key, item)
continue
}
slice[i] = str
@@ -273,45 +284,51 @@ func (opts *Options) FromMap(m map[string]interface{}) error {
return fmt.Errorf("unknown type loading config params: %v", field.Kind())
}
}
} else {
invalidOpts = append(invalidOpts, key)
}
}
if len(invalidOpts) > 0 {
return fmt.Errorf("%w: %v", ErrInvalidOpts, strings.Join(invalidOpts, ", "))
}
return nil
}
func DefaultOptions() Options {
return Options{
Seed: -1,
UseNUMA: false,
NumCtx: 2048,
NumKeep: -1,
NumBatch: 512,
NumGPU: -1, // -1 here indicates that NumGPU should be set dynamically
NumGQA: 1,
LowVRAM: false,
F16KV: true,
UseMMap: true,
UseMLock: false,
RopeFrequencyBase: 10000.0,
RopeFrequencyScale: 1.0,
EmbeddingOnly: true,
RepeatLastN: 64,
RepeatPenalty: 1.1,
FrequencyPenalty: 0.0,
PresencePenalty: 0.0,
// options set on request to runner
NumPredict: -1,
NumKeep: -1,
Temperature: 0.8,
TopK: 40,
TopP: 0.9,
TFSZ: 1.0,
TypicalP: 1.0,
RepeatLastN: 64,
RepeatPenalty: 1.1,
PresencePenalty: 0.0,
FrequencyPenalty: 0.0,
Mirostat: 0,
MirostatTau: 5.0,
MirostatEta: 0.1,
PenalizeNewline: true,
Seed: -1,
NumThread: 0, // let the runtime decide
// options set when the model is loaded
NumCtx: 2048,
RopeFrequencyBase: 10000.0,
RopeFrequencyScale: 1.0,
NumBatch: 512,
NumGPU: -1, // -1 here indicates that NumGPU should be set dynamically
NumGQA: 1,
NumThread: 0, // let the runtime decide
LowVRAM: false,
F16KV: true,
UseMLock: false,
UseMMap: true,
UseNUMA: false,
EmbeddingOnly: true,
}
}

View File

@@ -61,7 +61,7 @@ func CreateHandler(cmd *cobra.Command, args []string) error {
return err
}
client, err := api.FromEnv()
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
@@ -119,7 +119,7 @@ func CreateHandler(cmd *cobra.Command, args []string) error {
}
func RunHandler(cmd *cobra.Command, args []string) error {
client, err := api.FromEnv()
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
@@ -144,7 +144,7 @@ func RunHandler(cmd *cobra.Command, args []string) error {
}
func PushHandler(cmd *cobra.Command, args []string) error {
client, err := api.FromEnv()
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
@@ -188,7 +188,7 @@ func PushHandler(cmd *cobra.Command, args []string) error {
}
func ListHandler(cmd *cobra.Command, args []string) error {
client, err := api.FromEnv()
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
@@ -221,7 +221,7 @@ func ListHandler(cmd *cobra.Command, args []string) error {
}
func DeleteHandler(cmd *cobra.Command, args []string) error {
client, err := api.FromEnv()
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
@@ -237,7 +237,7 @@ func DeleteHandler(cmd *cobra.Command, args []string) error {
}
func ShowHandler(cmd *cobra.Command, args []string) error {
client, err := api.FromEnv()
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
@@ -315,7 +315,7 @@ func ShowHandler(cmd *cobra.Command, args []string) error {
}
func CopyHandler(cmd *cobra.Command, args []string) error {
client, err := api.FromEnv()
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
@@ -338,7 +338,7 @@ func PullHandler(cmd *cobra.Command, args []string) error {
}
func pull(model string, insecure bool) error {
client, err := api.FromEnv()
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
@@ -380,7 +380,20 @@ func pull(model string, insecure bool) error {
func RunGenerate(cmd *cobra.Command, args []string) error {
if len(args) > 1 {
// join all args into a single prompt
return generate(cmd, args[0], strings.Join(args[1:], " "))
wordWrap := false
if term.IsTerminal(int(os.Stdout.Fd())) {
wordWrap = true
}
nowrap, err := cmd.Flags().GetBool("nowordwrap")
if err != nil {
return err
}
if nowrap {
wordWrap = false
}
return generate(cmd, args[0], strings.Join(args[1:], " "), wordWrap)
}
if readline.IsTerminal(int(os.Stdin.Fd())) {
@@ -392,8 +405,8 @@ func RunGenerate(cmd *cobra.Command, args []string) error {
type generateContextKey string
func generate(cmd *cobra.Command, model, prompt string) error {
client, err := api.FromEnv()
func generate(cmd *cobra.Command, model, prompt string, wordWrap bool) error {
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}
@@ -408,24 +421,9 @@ func generate(cmd *cobra.Command, model, prompt string) error {
generateContext = []int{}
}
var wrapTerm bool
termType := os.Getenv("TERM")
if termType == "xterm-256color" {
wrapTerm = true
}
termWidth, _, err := term.GetSize(int(0))
if err != nil {
wrapTerm = false
}
// override wrapping if the user turned it off
nowrap, err := cmd.Flags().GetBool("nowordwrap")
if err != nil {
return err
}
if nowrap {
wrapTerm = false
wordWrap = false
}
cancelCtx, cancel := context.WithCancel(context.Background())
@@ -452,7 +450,7 @@ func generate(cmd *cobra.Command, model, prompt string) error {
latest = response
if wrapTerm {
if wordWrap {
for _, ch := range response.Response {
if currentLineLength+1 > termWidth-5 {
// backtrack the length of the last word and clear to the end of the line
@@ -481,18 +479,7 @@ func generate(cmd *cobra.Command, model, prompt string) error {
}
if err := client.Generate(cancelCtx, &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)
}
} else if strings.Contains(err.Error(), "context canceled") && abort {
if strings.Contains(err.Error(), "context canceled") && abort {
spinner.Finish()
return nil
}
@@ -533,7 +520,7 @@ func generateInteractive(cmd *cobra.Command, model string) error {
}
// load the model
if err := generate(cmd, model, ""); err != nil {
if err := generate(cmd, model, "", false); err != nil {
return err
}
@@ -560,8 +547,35 @@ func generateInteractive(cmd *cobra.Command, model string) error {
)
usage := func() {
fmt.Fprintln(os.Stderr, "commands:")
fmt.Fprintln(os.Stderr, completer.Tree(" "))
fmt.Fprintln(os.Stderr, "Available Commands:")
fmt.Fprintln(os.Stderr, " /set Set session variables")
fmt.Fprintln(os.Stderr, " /show Show model information")
fmt.Fprintln(os.Stderr, " /bye Exit")
fmt.Fprintln(os.Stderr, " /?, /help Help for a command")
fmt.Fprintln(os.Stderr, "")
fmt.Fprintln(os.Stderr, "Use \"\"\" to begin a multi-line message.")
fmt.Fprintln(os.Stderr, "")
}
usageSet := func() {
fmt.Fprintln(os.Stderr, "Available Commands:")
fmt.Fprintln(os.Stderr, " /set history Enable history")
fmt.Fprintln(os.Stderr, " /set nohistory Disable history")
fmt.Fprintln(os.Stderr, " /set wordwrap Enable wordwrap")
fmt.Fprintln(os.Stderr, " /set nowordwrap Disable wordwrap")
fmt.Fprintln(os.Stderr, " /set verbose Show LLM stats")
fmt.Fprintln(os.Stderr, " /set quiet Disable LLM stats")
fmt.Fprintln(os.Stderr, "")
}
usageShow := func() {
fmt.Fprintln(os.Stderr, "Available Commands:")
fmt.Fprintln(os.Stderr, " /show license Show model license")
fmt.Fprintln(os.Stderr, " /show modelfile Show Modelfile for this model")
fmt.Fprintln(os.Stderr, " /show parameters Show parameters for this model")
fmt.Fprintln(os.Stderr, " /show system Show system prompt")
fmt.Fprintln(os.Stderr, " /show template Show prompt template")
fmt.Fprintln(os.Stderr, "")
}
var painter Painter
@@ -579,6 +593,21 @@ func generateInteractive(cmd *cobra.Command, model string) error {
}
defer scanner.Close()
var wordWrap bool
termType := os.Getenv("TERM")
if termType == "xterm-256color" {
wordWrap = true
}
// override wrapping if the user turned it off
nowrap, err := cmd.Flags().GetBool("nowordwrap")
if err != nil {
return err
}
if nowrap {
wordWrap = false
}
var multiLineBuffer string
var isMultiLine bool
@@ -632,10 +661,10 @@ func generateInteractive(cmd *cobra.Command, model string) error {
case "nohistory":
scanner.HistoryDisable()
case "wordwrap":
cmd.Flags().Set("nowordwrap", "false")
wordWrap = true
fmt.Println("Set 'wordwrap' mode.")
case "nowordwrap":
cmd.Flags().Set("nowordwrap", "true")
wordWrap = false
fmt.Println("Set 'nowordwrap' mode.")
case "verbose":
cmd.Flags().Set("verbose", "true")
@@ -660,7 +689,7 @@ func generateInteractive(cmd *cobra.Command, model string) error {
fmt.Printf("Unknown command '/set %s'. Type /? for help\n", args[1])
}
} else {
usage()
usageSet()
}
case strings.HasPrefix(line, "/show"):
args := strings.Fields(line)
@@ -673,23 +702,49 @@ func generateInteractive(cmd *cobra.Command, model string) error {
switch args[1] {
case "license":
fmt.Println(resp.License)
if resp.License == "" {
fmt.Print("No license was specified for this model.\n\n")
} else {
fmt.Println(resp.License)
}
case "modelfile":
fmt.Println(resp.Modelfile)
case "parameters":
fmt.Println(resp.Parameters)
if resp.Parameters == "" {
fmt.Print("No parameters were specified for this model.\n\n")
} else {
fmt.Println(resp.Parameters)
}
case "system":
fmt.Println(resp.System)
if resp.System == "" {
fmt.Print("No system prompt was specified for this model.\n\n")
} else {
fmt.Println(resp.System)
}
case "template":
fmt.Println(resp.Template)
if resp.Template == "" {
fmt.Print("No prompt template was specified for this model.\n\n")
} else {
fmt.Println(resp.Template)
}
default:
fmt.Printf("Unknown command '/show %s'. Type /? for help\n", args[1])
}
} else {
usageShow()
}
case strings.HasPrefix(line, "/help"), strings.HasPrefix(line, "/?"):
args := strings.Fields(line)
if len(args) > 1 {
switch args[1] {
case "set", "/set":
usageSet()
case "show", "/show":
usageShow()
}
} else {
usage()
}
case line == "/help", line == "/?":
usage()
case line == "/exit", line == "/bye":
return nil
case strings.HasPrefix(line, "/"):
@@ -698,7 +753,7 @@ func generateInteractive(cmd *cobra.Command, model string) error {
}
if len(line) > 0 && line[0] != '/' {
if err := generate(cmd, model, line); err != nil {
if err := generate(cmd, model, line, wordWrap); err != nil {
return err
}
}
@@ -710,7 +765,7 @@ func generateBatch(cmd *cobra.Command, model string) error {
for scanner.Scan() {
prompt := scanner.Text()
fmt.Printf(">>> %s\n", prompt)
if err := generate(cmd, model, prompt); err != nil {
if err := generate(cmd, model, prompt, false); err != nil {
return err
}
}
@@ -840,7 +895,7 @@ func startMacApp(client *api.Client) error {
}
func checkServerHeartbeat(_ *cobra.Command, _ []string) error {
client, err := api.FromEnv()
client, err := api.ClientFromEnvironment()
if err != nil {
return err
}

View File

@@ -12,7 +12,6 @@
- [Push a Model](#push-a-model)
- [Generate Embeddings](#generate-embeddings)
## Conventions
### Model names
@@ -40,12 +39,13 @@ Generate a response for a given prompt with a provided model. This is a streamin
- `model`: (required) the [model name](#model-names)
- `prompt`: the prompt to generate a response for
Advanced parameters:
Advanced parameters (optional):
- `options`: additional model parameters listed in the documentation for the [Modelfile](./modelfile.md#valid-parameters-and-values) such as `temperature`
- `system`: system prompt to (overrides what is defined in the `Modelfile`)
- `template`: the full prompt or prompt template (overrides what is defined in the `Modelfile`)
- `context`: the context parameter returned from a previous request to `/generate`, this can be used to keep a short conversational memory
- `stream`: if `false` the response will be be returned as a single response object, rather than a stream of objects
### Request
@@ -80,6 +80,7 @@ The final response in the stream also includes additional data about the generat
- `eval_count`: number of tokens the response
- `eval_duration`: time in nanoseconds spent generating the response
- `context`: an encoding of the conversation used in this response, this can be sent in the next request to keep a conversational memory
- `response`: empty if the response was streamed, if not streamed, this will contain the full response
To calculate how fast the response is generated in tokens per second (token/s), divide `eval_count` / `eval_duration`.
@@ -87,6 +88,7 @@ To calculate how fast the response is generated in tokens per second (token/s),
{
"model": "llama2:7b",
"created_at": "2023-08-04T19:22:45.499127Z",
"response": "",
"context": [1, 2, 3],
"done": true,
"total_duration": 5589157167,
@@ -112,6 +114,7 @@ Create a model from a [`Modelfile`](./modelfile.md)
- `name`: name of the model to create
- `path`: path to the Modelfile
- `stream`: (optional) if `false` the response will be be returned as a single response object, rather than a stream of objects
### Request
@@ -179,7 +182,7 @@ Show details about a model including modelfile, template, parameters, license, a
### Request
```shell
```shell
curl http://localhost:11434/api/show -d '{
"name": "llama2:7b"
}'
@@ -189,10 +192,10 @@ curl http://localhost:11434/api/show -d '{
```json
{
"license": "<contents of license block>",
"modelfile": "# Modelfile generated by \"ollama show\"\n# To build a new Modelfile based on this one, replace the FROM line with:\n# FROM llama2:latest\n\nFROM /Users/username/.ollama/models/blobs/sha256:8daa9615cce30c259a9555b1cc250d461d1bc69980a274b44d7eda0be78076d8\nTEMPLATE \"\"\"[INST] {{ if and .First .System }}<<SYS>>{{ .System }}<</SYS>>\n\n{{ end }}{{ .Prompt }} [/INST] \"\"\"\nSYSTEM \"\"\"\"\"\"\nPARAMETER stop [INST]\nPARAMETER stop [/INST]\nPARAMETER stop <<SYS>>\nPARAMETER stop <</SYS>>\n",
"parameters": "stop [INST]\nstop [/INST]\nstop <<SYS>>\nstop <</SYS>>",
"template": "[INST] {{ if and .First .System }}<<SYS>>{{ .System }}<</SYS>>\n\n{{ end }}{{ .Prompt }} [/INST] "
"license": "<contents of license block>",
"modelfile": "# Modelfile generated by \"ollama show\"\n# To build a new Modelfile based on this one, replace the FROM line with:\n# FROM llama2:latest\n\nFROM /Users/username/.ollama/models/blobs/sha256:8daa9615cce30c259a9555b1cc250d461d1bc69980a274b44d7eda0be78076d8\nTEMPLATE \"\"\"[INST] {{ if and .First .System }}<<SYS>>{{ .System }}<</SYS>>\n\n{{ end }}{{ .Prompt }} [/INST] \"\"\"\nSYSTEM \"\"\"\"\"\"\nPARAMETER stop [INST]\nPARAMETER stop [/INST]\nPARAMETER stop <<SYS>>\nPARAMETER stop <</SYS>>\n",
"parameters": "stop [INST]\nstop [/INST]\nstop <<SYS>>\nstop <</SYS>>",
"template": "[INST] {{ if and .First .System }}<<SYS>>{{ .System }}<</SYS>>\n\n{{ end }}{{ .Prompt }} [/INST] "
}
```
@@ -245,6 +248,7 @@ Download a model from the ollama library. Cancelled pulls are resumed from where
- `name`: name of the model to pull
- `insecure`: (optional) allow insecure connections to the library. Only use this if you are pulling from your own library during development.
- `stream`: (optional) if `false` the response will be be returned as a single response object, rather than a stream of objects
### Request
@@ -275,7 +279,8 @@ Upload a model to a model library. Requires registering for ollama.ai and adding
### Parameters
- `name`: name of the model to push in the form of `<namespace>/<model>:<tag>`
- `insecure`: (optional) allow insecure connections to the library. Only use this if you are pushing to your library during development.
- `insecure`: (optional) allow insecure connections to the library. Only use this if you are pushing to your library during development.
- `stream`: (optional) if `false` the response will be be returned as a single response object, rather than a stream of objects
### Request
@@ -290,15 +295,16 @@ curl -X POST http://localhost:11434/api/push -d '{
Streaming response that starts with:
```json
{"status":"retrieving manifest"}
{ "status": "retrieving manifest" }
```
and then:
```json
{
"status":"starting upload","digest":"sha256:bc07c81de745696fdf5afca05e065818a8149fb0c77266fb584d9b2cba3711ab",
"total":1928429856
"status": "starting upload",
"digest": "sha256:bc07c81de745696fdf5afca05e065818a8149fb0c77266fb584d9b2cba3711ab",
"total": 1928429856
}
```
@@ -306,9 +312,10 @@ Then there is a series of uploading responses:
```json
{
"status":"starting upload",
"digest":"sha256:bc07c81de745696fdf5afca05e065818a8149fb0c77266fb584d9b2cba3711ab",
"total":1928429856}
"status": "starting upload",
"digest": "sha256:bc07c81de745696fdf5afca05e065818a8149fb0c77266fb584d9b2cba3711ab",
"total": 1928429856
}
```
Finally, when the upload is complete:
@@ -352,4 +359,5 @@ curl -X POST http://localhost:11434/api/embeddings -d '{
0.5670403838157654, 0.009260174818336964, 0.23178744316101074, -0.2916173040866852, -0.8924556970596313,
0.8785552978515625, -0.34576427936553955, 0.5742510557174683, -0.04222835972905159, -0.137906014919281
]
}```
}
```

View File

@@ -10,25 +10,25 @@ Install required tools:
- go version 1.20 or higher
- gcc version 11.4.0 or higher
```
```bash
brew install go cmake gcc
```
Get the required libraries:
```
```bash
go generate ./...
```
Then build ollama:
```
```bash
go build .
```
Now you can run `ollama`:
```
```bash
./ollama
```

View File

@@ -2,13 +2,13 @@
## How can I expose the Ollama server?
```
```bash
OLLAMA_HOST=0.0.0.0:11435 ollama serve
```
By default, Ollama allows cross origin requests from `127.0.0.1` and `0.0.0.0`. To support more origins, you can use the `OLLAMA_ORIGINS` environment variable:
```
```bash
OLLAMA_ORIGINS=http://192.168.1.1:*,https://example.com ollama serve
```
@@ -16,4 +16,3 @@ OLLAMA_ORIGINS=http://192.168.1.1:*,https://example.com ollama serve
* macOS: Raw model data is stored under `~/.ollama/models`.
* Linux: Raw model data is stored under `/usr/share/ollama/.ollama/models`

View File

@@ -2,7 +2,7 @@
> Note: A one line installer for Ollama is available by running:
>
> ```
> ```bash
> curl https://ollama.ai/install.sh | sh
> ```
@@ -10,7 +10,7 @@
Ollama is distributed as a self-contained binary. Download it to a directory in your PATH:
```
```bash
sudo curl -L https://ollama.ai/download/ollama-linux-amd64 -o /usr/bin/ollama
sudo chmod +x /usr/bin/ollama
```
@@ -19,13 +19,13 @@ sudo chmod +x /usr/bin/ollama
Start Ollama by running `ollama serve`:
```
```bash
ollama serve
```
Once Ollama is running, run a model in another terminal session:
```
```bash
ollama run llama2
```
@@ -35,7 +35,7 @@ ollama run llama2
Verify that the drivers are installed by running the following command, which should print details about your GPU:
```
```bash
nvidia-smi
```
@@ -43,7 +43,7 @@ nvidia-smi
Create a user for Ollama:
```
```bash
sudo useradd -r -s /bin/false -m -d /usr/share/ollama ollama
```
@@ -68,7 +68,7 @@ WantedBy=default.target
Then start the service:
```
```bash
sudo systemctl daemon-reload
sudo systemctl enable ollama
```
@@ -77,7 +77,7 @@ sudo systemctl enable ollama
To view logs of Ollama running as a startup service, run:
```
```bash
journalctl -u ollama
```

View File

@@ -1,6 +1,6 @@
# Ollama Model File
> Note: this model file syntax is in development
> Note: this `Modelfile` syntax is in development
A model file is the blueprint to create and share models with Ollama.
@@ -24,7 +24,7 @@ A model file is the blueprint to create and share models with Ollama.
## Format
The format of the Modelfile:
The format of the `Modelfile`:
```modelfile
# comment
@@ -42,9 +42,9 @@ INSTRUCTION arguments
## Examples
An example of a model file creating a mario blueprint:
An example of a `Modelfile` creating a mario blueprint:
```
```modelfile
FROM llama2
# sets the temperature to 1 [higher is more creative, lower is more coherent]
PARAMETER temperature 1
@@ -57,9 +57,9 @@ 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`
1. Save it as a file (e.g. `Modelfile`)
2. `ollama create choose-a-model-name -f <location of the file e.g. ./Modelfile>'`
3. `ollama run choose-a-model-name`
4. Start using the model!
More examples are available in the [examples directory](../examples).
@@ -68,34 +68,34 @@ More examples are available in the [examples directory](../examples).
### FROM (Required)
The FROM instruction defines the base model to use when creating a model.
The `FROM` instruction defines the base model to use when creating a model.
```
```modelfile
FROM <model name>:<tag>
```
#### Build from llama2
```
```modelfile
FROM llama2
```
A list of available base models:
<https://github.com/jmorganca/ollama#model-library>
#### Build from a bin file
#### Build from a `bin` file
```
```modelfile
FROM ./ollama-model.bin
```
This bin file location should be specified as an absolute path or relative to the Modelfile location.
This bin file location should be specified as an absolute path or relative to the `Modelfile` location.
### EMBED
The EMBED instruction is used to add embeddings of files to a model. This is useful for adding custom data that the model can reference when generating an answer. Note that currently only text files are supported, formatted with each line as one embedding.
The `EMBED` instruction is used to add embeddings of files to a model. This is useful for adding custom data that the model can reference when generating an answer. Note that currently only text files are supported, formatted with each line as one embedding.
```
```modelfile
FROM <model name>:<tag>
EMBED <file path>.txt
EMBED <different file path>.txt
@@ -106,7 +106,7 @@ EMBED <path to directory>/*.txt
The `PARAMETER` instruction defines a parameter that can be set when the model is run.
```
```modelfile
PARAMETER <parameter> <parametervalue>
```
@@ -124,6 +124,7 @@ PARAMETER <parameter> <parametervalue>
| 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 |
| seed | Sets the random number seed to use for generation. Setting this to a specific number will make the model generate the same text for the same prompt. | int | seed 42 |
| stop | Sets the stop sequences 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 |
| num_predict | Maximum number of tokens to predict when generating text. (Default: 128, -1 = infinite generation, -2 = fill context) | int | num_predict 42 |
@@ -132,7 +133,7 @@ PARAMETER <parameter> <parametervalue>
### 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` 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. You can usually find the template for a given model in the readme for that model.
#### Template Variables
@@ -142,7 +143,7 @@ PARAMETER <parameter> <parametervalue>
| `{{ .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. |
```
```modelfile
TEMPLATE """
{{- if .First }}
### System:
@@ -162,7 +163,7 @@ SYSTEM """<system message>"""
The `SYSTEM` instruction specifies the system prompt to be used in the template, if applicable.
```
```modelfile
SYSTEM """<system message>"""
```
@@ -170,7 +171,7 @@ SYSTEM """<system message>"""
The `ADAPTER` instruction specifies the LoRA adapter to apply to the base model. The value of this instruction should be an absolute path or a path relative to the Modelfile and the file must be in a GGML file format. The adapter should be tuned from the base model otherwise the behaviour is undefined.
```
```modelfile
ADAPTER ./ollama-lora.bin
```
@@ -178,7 +179,7 @@ ADAPTER ./ollama-lora.bin
The `LICENSE` instruction allows you to specify the legal license under which the model used with this Modelfile is shared or distributed.
```
```modelfile
LICENSE """
<license text>
"""
@@ -186,5 +187,5 @@ LICENSE """
## Notes
- the **modelfile is not case sensitive**. In the examples, we use uppercase for instructions to make it easier to distinguish it from arguments.
- 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.

111
docs/quantize.md Normal file
View File

@@ -0,0 +1,111 @@
# How to Quantize a Model
Sometimes the model you want to work with is not available at [https://ollama.ai/library](https://ollama.ai/library).
## Figure out if we can run the model?
Not all models will work with Ollama. There are a number of factors that go into whether we are able to work with the next cool model. First it has to work with llama.cpp. Then we have to have implemented the features of llama.cpp that it requires. And then, sometimes, even with both of those, the model might not work...
1. What is the model you want to convert and upload?
2. Visit the model's page on HuggingFace.
3. Switch to the **Files and versions** tab.
4. Click on the **config.json** file. If there is no config.json file, it may not work.
5. Take note of the **architecture** list in the json file.
6. Does any entry in the list match one of the following architectures?
1. LlamaForCausalLM
2. MistralForCausalLM
3. RWForCausalLM
4. FalconForCausalLM
5. GPTNeoXForCausalLM
6. GPTBigCodeForCausalLM
7. If the answer is yes, then there is a good chance the model will run after being converted and quantized.
8. An alternative to this process is to visit [https://caniquant.tvl.st](https://caniquant.tvl.st) and enter the org/modelname in the box and submit.
At this point there are two processes you can use. You can either use a Docker container to convert and quantize, OR you can manually run the scripts. The Docker container is the easiest way to do it, but it requires you to have Docker installed on your machine. If you don't have Docker installed, you can follow the manual process.
## Convert and Quantize with Docker
Run `docker run --rm -v /path/to/model/repo:/repo ollama/quantize -q quantlevel /repo`. For instance, if you have downloaded the latest Mistral 7B model, then clone it to your machine. Then change into that directory and you can run:
```shell
docker run --rm -v .:/repo ollama/quantize -q q4_0 /repo
```
You can find the different quantization levels below under **Quantize the Model**.
This will output two files into the directory. First is a f16.bin file that is the model converted to GGUF. The second file is a q4_0.bin file which is the model quantized to a 4 bit quantization. You should rename it to something more descriptive.
You can find the repository for the Docker container here: [https://github.com/mxyng/quantize](https://github.com/mxyng/quantize)
For instance, if you wanted to convert the Mistral 7B model to a Q4 quantized model, then you could go through the following steps:
1. First verify the model will potentially work.
2. Now clone Mistral 7B to your machine. You can find the command to run when you click the three vertical dots button on the model page, then click **Clone Repository**.
1. For this repo, the command is:
```shell
git lfs install
git clone https://huggingface.co/mistralai/Mistral-7B-v0.1
```
2. Navigate into the new directory and run `docker run --rm -v .:/repo ollama/quantize -q q4_0 /repo`
3. Now you can create a modelfile using the q4_0.bin file that was created.
## Convert and Quantize Manually
### Clone llama.cpp to your machine
If we know the model has a chance of working, then we need to convert and quantize. This is a matter of running two separate scripts in the llama.cpp project.
1. Decide where you want the llama.cpp repository on your machine.
2. Navigate to that location and then run:
[`git clone https://github.com/ggerganov/llama.cpp.git`](https://github.com/ggerganov/llama.cpp.git)
1. If you don't have git installed, download this zip file and unzip it to that location: https://github.com/ggerganov/llama.cpp/archive/refs/heads/master.zip
3. Install the Python dependencies: `pip install torch transformers sentencepiece`
4. Run 'make' to build the project and the quantize executable.
### Convert the model to GGUF
1. Decide on the right convert script to run. What was the model architecture you found in the first section.
1. LlamaForCausalLM or MistralForCausalLM:
run `python3 convert.py <modelfilename>`
No need to specify fp16 or fp32.
2. FalconForCausalLM or RWForCausalLM:
run `python3 convert-falcon-hf-to-gguf.py <modelfilename> <fpsize>`
fpsize depends on the weight size. 1 for fp16, 0 for fp32
3. GPTNeoXForCausalLM:
run `python3 convert-gptneox-hf-to-gguf.py <modelfilename> <fpsize>`
fpsize depends on the weight size. 1 for fp16, 0 for fp32
4. GPTBigCodeForCausalLM:
run `python3 convert-starcoder-hf-to-gguf.py <modelfilename> <fpsize>`
fpsize depends on the weight size. 1 for fp16, 0 for fp32
### Quantize the model
If the model converted successfully, there is a good chance it will also quantize successfully. Now you need to decide on the quantization to use. We will always try to create all the quantizations and upload them to the library. You should decide which level is more important to you and quantize accordingly.
The quantization options are as follows. Note that some architectures such as Falcon do not support K quants.
- Q4_0
- Q4_1
- Q5_0
- Q5_1
- Q2_K
- Q3_K
- Q3_K_S
- Q3_K_M
- Q3_K_L
- Q4_K
- Q4_K_S
- Q4_K_M
- Q5_K
- Q5_K_S
- Q5_K_M
- Q6_K
- Q8_0
Run the following command `quantize <converted model from above> <output file> <quantization type>`
## Now Create the Model
Now you can create the Ollama model. Refer to the [modelfile](./modelfile.md) doc for more information on doing that.

171
examples/.gitignore vendored Normal file
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node_modules
# OSX
.DS_STORE
# Models
models/
# Local Chroma db
.chroma/
db/
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
# C extensions
*.so
# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST
# PyInstaller
# Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec
# Installer logs
pip-log.txt
pip-delete-this-directory.txt
# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
*.py,cover
.hypothesis/
.pytest_cache/
cover/
# Translations
*.mo
*.pot
# Django stuff:
*.log
local_settings.py
db.sqlite3
db.sqlite3-journal
# Flask stuff:
instance/
.webassets-cache
# Scrapy stuff:
.scrapy
# Sphinx documentation
docs/_build/
# PyBuilder
.pybuilder/
target/
# Jupyter Notebook
.ipynb_checkpoints
# IPython
profile_default/
ipython_config.py
# pyenv
# For a library or package, you might want to ignore these files since the code is
# intended to run in multiple environments; otherwise, check them in:
# .python-version
# pipenv
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
# However, in case of collaboration, if having platform-specific dependencies or dependencies
# having no cross-platform support, pipenv may install dependencies that don't work, or not
# install all needed dependencies.
#Pipfile.lock
# poetry
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
# This is especially recommended for binary packages to ensure reproducibility, and is more
# commonly ignored for libraries.
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
#poetry.lock
# pdm
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
#pdm.lock
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
# in version control.
# https://pdm.fming.dev/#use-with-ide
.pdm.toml
# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
__pypackages__/
# Celery stuff
celerybeat-schedule
celerybeat.pid
# SageMath parsed files
*.sage.py
# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/
# Spyder project settings
.spyderproject
.spyproject
# Rope project settings
.ropeproject
# mkdocs documentation
/site
# mypy
.mypy_cache/
.dmypy.json
dmypy.json
# Pyre type checker
.pyre/
# pytype static type analyzer
.pytype/
# Cython debug symbols
cython_debug/
# PyCharm
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
# and can be added to the global gitignore or merged into this file. For a more nuclear
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
#.idea/

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@@ -1,15 +1,3 @@
# Examples
This directory contains different examples of using Ollama
To create a model:
```
ollama create example -f <example file>
```
To run a model:
```
ollama run example
```
This directory contains different examples of using Ollama.

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@@ -0,0 +1,27 @@
package main
import (
"bytes"
"fmt"
"net/http"
"os"
"io"
"log"
)
func main() {
body := []byte(`{"model":"mistral"}`)
resp, err := http.Post("http://localhost:11434/api/generate", "application/json", bytes.NewBuffer(body))
if err != nil {
fmt.Print(err.Error())
os.Exit(1)
}
responseData, err := io.ReadAll(resp.Body)
if err != nil {
log.Fatal(err)
}
fmt.Println(string(responseData))
}

View File

@@ -0,0 +1,21 @@
# LangChain
This example is a basic "hello world" of using LangChain with Ollama using Node.js and Typescript.
## Setup
```shell
npm install
```
## Run
```shell
ts-node main.ts
```
Running this example will print the response for "hello":
```plaintext
Hello! It's nice to meet you. hopefully you are having a great day! Is there something I can help you with or would you like to chat?
```

View File

@@ -0,0 +1,15 @@
import { Ollama} from 'langchain/llms/ollama';
async function main() {
const ollama = new Ollama({
model: 'mistral'
// other parameters can be found at https://js.langchain.com/docs/api/llms_ollama/classes/Ollama
})
const stream = await ollama.stream("Hello");
for await (const chunk of stream) {
process.stdout.write(chunk);
}
}
main();

View File

@@ -0,0 +1,997 @@
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"node_modules/retry": {
"version": "0.13.1",
"resolved": "https://registry.npmjs.org/retry/-/retry-0.13.1.tgz",
"integrity": "sha512-XQBQ3I8W1Cge0Seh+6gjj03LbmRFWuoszgK9ooCpwYIrhhoO80pfq4cUkU5DkknwfOfFteRwlZ56PYOGYyFWdg==",
"engines": {
"node": ">= 4"
}
},
"node_modules/tr46": {
"version": "0.0.3",
"resolved": "https://registry.npmjs.org/tr46/-/tr46-0.0.3.tgz",
"integrity": "sha512-N3WMsuqV66lT30CrXNbEjx4GEwlow3v6rr4mCcv6prnfwhS01rkgyFdjPNBYd9br7LpXV1+Emh01fHnq2Gdgrw=="
},
"node_modules/typescript": {
"version": "5.2.2",
"resolved": "https://registry.npmjs.org/typescript/-/typescript-5.2.2.tgz",
"integrity": "sha512-mI4WrpHsbCIcwT9cF4FZvr80QUeKvsUsUvKDoR+X/7XHQH98xYD8YHZg7ANtz2GtZt/CBq2QJ0thkGJMHfqc1w==",
"dev": true,
"bin": {
"tsc": "bin/tsc",
"tsserver": "bin/tsserver"
},
"engines": {
"node": ">=14.17"
}
},
"node_modules/uuid": {
"version": "9.0.1",
"resolved": "https://registry.npmjs.org/uuid/-/uuid-9.0.1.tgz",
"integrity": "sha512-b+1eJOlsR9K8HJpow9Ok3fiWOWSIcIzXodvv0rQjVoOVNpWMpxf1wZNpt4y9h10odCNrqnYp1OBzRktckBe3sA==",
"funding": [
"https://github.com/sponsors/broofa",
"https://github.com/sponsors/ctavan"
],
"bin": {
"uuid": "dist/bin/uuid"
}
},
"node_modules/web-streams-polyfill": {
"version": "4.0.0-beta.3",
"resolved": "https://registry.npmjs.org/web-streams-polyfill/-/web-streams-polyfill-4.0.0-beta.3.tgz",
"integrity": "sha512-QW95TCTaHmsYfHDybGMwO5IJIM93I/6vTRk+daHTWFPhwh+C8Cg7j7XyKrwrj8Ib6vYXe0ocYNrmzY4xAAN6ug==",
"engines": {
"node": ">= 14"
}
},
"node_modules/webidl-conversions": {
"version": "3.0.1",
"resolved": "https://registry.npmjs.org/webidl-conversions/-/webidl-conversions-3.0.1.tgz",
"integrity": "sha512-2JAn3z8AR6rjK8Sm8orRC0h/bcl/DqL7tRPdGZ4I1CjdF+EaMLmYxBHyXuKL849eucPFhvBoxMsflfOb8kxaeQ=="
},
"node_modules/whatwg-url": {
"version": "5.0.0",
"resolved": "https://registry.npmjs.org/whatwg-url/-/whatwg-url-5.0.0.tgz",
"integrity": "sha512-saE57nupxk6v3HY35+jzBwYa0rKSy0XR8JSxZPwgLr7ys0IBzhGviA1/TUGJLmSVqs8pb9AnvICXEuOHLprYTw==",
"dependencies": {
"tr46": "~0.0.3",
"webidl-conversions": "^3.0.0"
}
},
"node_modules/yaml": {
"version": "2.3.2",
"resolved": "https://registry.npmjs.org/yaml/-/yaml-2.3.2.tgz",
"integrity": "sha512-N/lyzTPaJasoDmfV7YTrYCI0G/3ivm/9wdG0aHuheKowWQwGTsK0Eoiw6utmzAnI6pkJa0DUVygvp3spqqEKXg==",
"engines": {
"node": ">= 14"
}
},
"node_modules/zod": {
"version": "3.22.4",
"resolved": "https://registry.npmjs.org/zod/-/zod-3.22.4.tgz",
"integrity": "sha512-iC+8Io04lddc+mVqQ9AZ7OQ2MrUKGN+oIQyq1vemgt46jwCwLfhq7/pwnBnNXXXZb8VTVLKwp9EDkx+ryxIWmg==",
"funding": {
"url": "https://github.com/sponsors/colinhacks"
}
},
"node_modules/zod-to-json-schema": {
"version": "3.21.4",
"resolved": "https://registry.npmjs.org/zod-to-json-schema/-/zod-to-json-schema-3.21.4.tgz",
"integrity": "sha512-fjUZh4nQ1s6HMccgIeE0VP4QG/YRGPmyjO9sAh890aQKPEk3nqbfUXhMFaC+Dr5KvYBm8BCyvfpZf2jY9aGSsw==",
"peerDependencies": {
"zod": "^3.21.4"
}
}
}
}

View File

@@ -0,0 +1,8 @@
{
"devDependencies": {
"typescript": "^5.2.2"
},
"dependencies": {
"langchain": "^0.0.165"
}
}

View File

@@ -1,8 +0,0 @@
# 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.
"""

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@@ -0,0 +1,23 @@
# Ten Tweets Modelfile
This is a simple modelfile that generates ten tweets based off any topic.
```bash
ollama create tentweets
ollama run tentweets
>>> underwater basketweaving
Great! Here are ten creative tweets about underwater basketweaving:
1. "Just discovered the ultimate stress-reliever: Underwater basketweaving! 🌊🧵 #UnderwaterBasketweaving #StressRelief"
2. "Who needs meditation when you can do underwater basketweaving? 😴👀 #PeacefulDistraction #UnderwaterBasketweaving"
3. "Just spent an hour in the pool and still managed to knot my basket. Goal: untangle it before next session. 💪🏽 #ChallengeAccepted #UnderwaterBasketweaving"
4. "When life gives you lemons, make underwater basketweaving! 🍋🧵 #LemonadeLife #UnderwaterBasketweaving"
5. "Just realized my underwater basketweaving skills could come in handy during a zombie apocalypse. 😂🧡 #SurvivalTips #UnderwaterBasketweaving"
6. "I'm not lazy, I'm just conserving energy for my next underwater basketweaving session. 😴💤 #LazyDay #UnderwaterBasketweaving"
7. "Just found my inner peace while doing underwater basketweaving. It's like meditation, but with knots! 🙏🧵 #Mindfulness #UnderwaterBasketweaving"
8. "Why study for exams when you can do underwater basketweaving and forget all your worries? 😜🧵 #ProcrastinationStation #UnderwaterBasketweaving"
9. "Just had to cut my underwater basketweaving session short due to a sudden urge to breathe. 🤯🌊 #AquaticAdventures #UnderwaterBasketweaving"
10. "I'm not sure what's more impressive: my underwater basketweaving skills or the fact that I didn't drown trying to make this tweet. 😅🧵 #Accomplishment
#UnderwaterBasketweaving"
```

View File

@@ -1,7 +1,7 @@
# 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
FROM mistral
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

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@@ -0,0 +1,40 @@
# DevOps Engineer Modelfile
This is a simple modelfile that takes will respond to any questions that a senior DevOps engineer should know how to solve.
````text
ollama create devopsengineer
ollama run devopsengineer
>>> how can i proxy all connections from inside the office through a single server that caches large files. Provide a config file for nginx to achieve this?
Here is an example configuration file for Nginx that can be used to proxy all connections from inside the office network to a centralized cache server:
```perl
http {
upstream cache_server {
server <cache_server_ip>;
server <cache_server_ip>;
server <cache_server_ip>;
}
server {
listen 80;
server_name localhost;
location / {
proxy_pass http://cache_server;
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
}
}
}
```
In this configuration, we define an `upstream` block that lists the IP addresses of the cache servers. We then define a server block that listens on port 80 and routes all
traffic to the `/` location to the cache servers using the `proxy_pass` directive. The `proxy_set_header` directives are used to preserve the source IP address of the client
request when forwarding it to the cache server.
To use this configuration, you would need to replace the placeholder `<cache_server_ip>` with the actual IP addresses of your cache servers. You would also need to make sure
that the cache servers are configured to accept incoming connections from the Nginx server and handle requests for files.
````

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# 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 zephyr
PARAMETER temperature 0.8
PARAMETER top_k 500
PARAMETER top_p 0.9
SYSTEM """
Embrace your role as a creative illustrator. Based on a concept provided, you must produce a single paragraph with a multifaceted description of an image, ensuring significant details of the concept and more is represented in your instructions. You do not need to write complete sentences but rather short concepts with the following information: the level of detail that should be represented, an artistic style and maybe a specific name of a painter or illustrator, the ideal color pallete, lighting, mood, perspective, the setting, time of day, weather, the season, the time period, location, materials, the textures, patterns, lines, brushstrokes, techniques, the medium, the genre, the rendering style. Don't include everything and keep the description length under 250 words.
"""

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@@ -0,0 +1,11 @@
# Midjourney Prompt Generator Modelfile
This simple modelfile will help create a prompt to feed to Midjourney.
```text
ollama create midjourney
ollama run midjourney
>>> a sports car in the mountains.
A sleek, high-performance automobile cuts through a serpentine mountain landscape. The concept is a classic illustration of speed and power, depicted in the style of pop art by Andy Warhol. The color palette is dominated by bold, primary hues of red, blue, and yellow, with striking accent colors of white, black, and metallic shades. The lighting is bright and focused, casting sharp shadows on the rugged terrain. A sense of excitement and anticipation permeates throughout the scene, as the car navigates a treacherous course through the winding road. The perspective is low, allowing for a full view of the vehicle's sleek lines and intricate details. The setting takes place in the afternoon during a sunny day in autumn, as evidenced by the vibrant foliage on the mountainside. The time period is modern, with nods to classic car design. The materials are primarily digital, allowing for smooth curves and sharp contrasts. The textures are sleek and polished, with meticulously detailed lines and brushstrokes that accentuate the car's aerodynamic design. The patterns consist of geometric shapes and bold stripes, adding to the car's dynamic appeal. The genre is modern realism, with a focus on precision and detail. The rendering style is highly technical, capturing the nuances and subtleties of the vehicle and its surroundings in breathtaking detail.
```

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@@ -0,0 +1,20 @@
# Recipe Maker Modelfile
Simple modelfile to generate a recipe from a short list of ingredients.
```
ollama create recipemaker
ollama run recipemaker
>>> chilli pepper, white chocolate, kale
Ingredients:
- 1 small chili pepper
- 4 squares of white chocolate
- handful of kale leaves
Instructions:
1. In a blender or food processor, puree the chilies and white chocolate until smooth.
2. Add the chopped kale leaves to the blender and pulse until well combined.
3. Serve immediately as a dip for crackers or use it as an ingredient in your favorite recipe. The mixture of spicy chili pepper with sweet white chocolate and nutritious
kale will make your taste buds dance with delight!
```

View File

@@ -1,4 +1,4 @@
FROM llama2
FROM mistral
SYSTEM """
You are an experienced Devops engineer focused on docker. When given specifications for a particular need or application you know the best way to host that within a docker container. For instance if someone tells you they want an nginx server to host files located at /web you will answer as follows

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@@ -0,0 +1,2 @@
node_modules
package-lock.json

View File

@@ -0,0 +1,21 @@
# Ask the Mentors
This example demonstrates how one would create a set of 'mentors' you can have a conversation with. The mentors are generated using the `character-generator.ts` file. This will use **Stable Beluga 70b** to create a bio and list of verbal ticks and common phrases used by each person. Then `mentors.ts` will take a question, and choose three of the 'mentors' and start a conversation with them. Occasionally, they will talk to each other, and other times they will just deliver a set of monologues. It's fun to see what they do and say.
## Usage
```bash
ts-node ./character-generator.ts "Lorne Greene"
```
This will create `lornegreene/Modelfile`. Now you can create a model with this command:
```bash
ollama create lornegreene -f lornegreene/Modelfile
```
If you want to add your own mentors, you will have to update the code to look at your namespace instead of **mattw**. Also set the list of mentors to include yours.
```bash
ts-node ./mentors.ts "What is a Jackalope?"
```

View File

@@ -0,0 +1,26 @@
import { Ollama } from 'ollama-node'
import fs from 'fs';
import path from 'path';
async function characterGenerator() {
const character = process.argv[2];
console.log(`You are creating a character for ${character}.`);
const foldername = character.replace(/\s/g, '').toLowerCase();
const directory = path.join(__dirname, foldername);
if (!fs.existsSync(directory)) {
fs.mkdirSync(directory, { recursive: true });
}
const ollama = new Ollama();
ollama.setModel("stablebeluga2:70b-q4_K_M");
const bio = await ollama.generate(`create a bio of ${character} in a single long paragraph. Instead of saying '${character} is...' or '${character} was...' use language like 'You are...' or 'You were...'. Then create a paragraph describing the speaking mannerisms and style of ${character}. Don't include anything about how ${character} looked or what they sounded like, just focus on the words they said. Instead of saying '${character} would say...' use language like 'You should say...'. If you use quotes, always use single quotes instead of double quotes. If there are any specific words or phrases you used a lot, show how you used them. `);
const thecontents = `FROM llama2\nSYSTEM """\n${bio.response.replace(/(\r\n|\n|\r)/gm, " ").replace('would', 'should')} All answers to questions should be related back to what you are most known for.\n"""`;
fs.writeFile(path.join(directory, 'Modelfile'), thecontents, (err: any) => {
if (err) throw err;
console.log('The file has been saved!');
});
}
characterGenerator();

View File

@@ -0,0 +1,59 @@
import { Ollama } from 'ollama-node';
const mentorCount = 3;
const ollama = new Ollama();
function getMentors(): string[] {
const mentors = ['Gary Vaynerchuk', 'Kanye West', 'Martha Stewart', 'Neil deGrasse Tyson', 'Owen Wilson', 'Ronald Reagan', 'Donald Trump', 'Barack Obama', 'Jeff Bezos'];
const chosenMentors: string[] = [];
for (let i = 0; i < mentorCount; i++) {
const mentor = mentors[Math.floor(Math.random() * mentors.length)];
chosenMentors.push(mentor);
mentors.splice(mentors.indexOf(mentor), 1);
}
return chosenMentors;
}
function getMentorFileName(mentor: string): string {
const model = mentor.toLowerCase().replace(/\s/g, '');
return `mattw/${model}`;
}
async function getSystemPrompt(mentor: string, isLast: boolean, question: string): Promise<string> {
ollama.setModel(getMentorFileName(mentor));
const info = await ollama.showModelInfo()
let SystemPrompt = info.system || '';
SystemPrompt += ` You should continue the conversation as if you were ${mentor} and acknowledge the people before you in the conversation. You should adopt their mannerisms and tone, but also not use language they wouldn't use. If they are not known to know about the concept in the question, don't offer an answer. Your answer should be no longer than 1 paragraph. And definitely try not to sound like anyone else. Don't repeat any slang or phrases already used. And if it is a question the original ${mentor} wouldn't have know the answer to, just say that you don't know, in the style of ${mentor}. And think about the time the person lived. Don't use terminology that they wouldn't have used.`
if (isLast) {
SystemPrompt += ` End your answer with something like I hope our answers help you out`;
} else {
SystemPrompt += ` Remember, this is a conversation, so you don't need a conclusion, but end your answer with a question related to the first question: "${question}".`;
}
return SystemPrompt;
}
async function main() {
const mentors = getMentors();
const question = process.argv[2];
let theConversation = `Here is the conversation so far.\nYou: ${question}\n`
for await (const mentor of mentors) {
const SystemPrompt = await getSystemPrompt(mentor, mentor === mentors[mentorCount - 1], question);
ollama.setModel(getMentorFileName(mentor));
ollama.setSystemPrompt(SystemPrompt);
let output = '';
process.stdout.write(`\n${mentor}: `);
for await (const chunk of ollama.streamingGenerate(theConversation + `Continue the conversation as if you were ${mentor} on the question "${question}".`)) {
if (chunk.response) {
output += chunk.response;
process.stdout.write(chunk.response);
} else {
process.stdout.write('\n');
}
}
theConversation += `${mentor}: ${output}\n\n`
}
}
main();

View File

@@ -0,0 +1,7 @@
{
"dependencies": {
"fs": "^0.0.1-security",
"ollama-node": "^0.0.3",
"path": "^0.12.7"
}
}

16
format/bytes.go Normal file
View File

@@ -0,0 +1,16 @@
package format
import "fmt"
func HumanBytes(b int64) string {
switch {
case b > 1000*1000*1000:
return fmt.Sprintf("%d GB", b/1000/1000/1000)
case b > 1000*1000:
return fmt.Sprintf("%d MB", b/1000/1000)
case b > 1000:
return fmt.Sprintf("%d KB", b/1000)
default:
return fmt.Sprintf("%d B", b)
}
}

View File

@@ -7,26 +7,14 @@ import (
"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 {
// humanDuration returns a human-readable approximation of a
// duration (eg. "About a minute", "4 hours ago", etc.).
func humanDuration(d time.Duration) string {
seconds := int(d.Seconds())
switch {
case seconds < 1:
if useCaps {
return "Less than a second"
}
return "less than a second"
return "Less than a second"
case seconds == 1:
return "1 second"
case seconds < 60:
@@ -36,10 +24,7 @@ func HumanDurationWithCase(d time.Duration, useCaps bool) string {
minutes := int(d.Minutes())
switch {
case minutes == 1:
if useCaps {
return "About a minute"
}
return "about a minute"
return "About a minute"
case minutes < 60:
return fmt.Sprintf("%d minutes", minutes)
}
@@ -47,10 +32,7 @@ func HumanDurationWithCase(d time.Duration, useCaps bool) string {
hours := int(math.Round(d.Hours()))
switch {
case hours == 1:
if useCaps {
return "About an hour"
}
return "about an hour"
return "About an hour"
case hours < 48:
return fmt.Sprintf("%d hours", hours)
case hours < 24*7*2:
@@ -65,77 +47,22 @@ func HumanDurationWithCase(d time.Duration, useCaps bool) string {
}
func HumanTime(t time.Time, zeroValue string) string {
return humanTimeWithCase(t, zeroValue, true)
return humanTime(t, zeroValue)
}
func HumanTimeLower(t time.Time, zeroValue string) string {
return humanTimeWithCase(t, zeroValue, false)
return strings.ToLower(humanTime(t, zeroValue))
}
func humanTimeWithCase(t time.Time, zeroValue string, useCaps bool) string {
func humanTime(t time.Time, zeroValue string) string {
if t.IsZero() {
return zeroValue
}
delta := time.Since(t)
if delta < 0 {
return HumanDurationWithCase(-delta, useCaps) + " from now"
return humanDuration(-delta) + " 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())
return humanDuration(delta) + " ago"
}

View File

@@ -11,92 +11,25 @@ func assertEqual(t *testing.T, a interface{}, b interface{}) {
}
}
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))
t.Run("soon", func(t *testing.T) {
v := now.Add(800*time.Millisecond)
assertEqual(t, HumanTime(v, ""), "Less than a second from now")
})
}

1
go.mod
View File

@@ -10,6 +10,7 @@ require (
github.com/olekukonko/tablewriter v0.0.5
github.com/pdevine/readline v1.5.2
github.com/spf13/cobra v1.7.0
golang.org/x/sync v0.3.0
)
require github.com/rivo/uniseg v0.2.0 // indirect

2
go.sum
View File

@@ -125,6 +125,8 @@ golang.org/x/exp v0.0.0-20230817173708-d852ddb80c63/go.mod h1:0v4NqG35kSWCMzLaMe
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/sync v0.3.0 h1:ftCYgMx6zT/asHUrPw8BLLscYtGznsLAnjq5RH9P66E=
golang.org/x/sync v0.3.0/go.mod h1:FU7BRWz2tNW+3quACPkgCx/L+uEAv1htQ0V83Z9Rj+Y=
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=

View File

@@ -1,7 +1,5 @@
package llm
const ModelFamilyFalcon = "falcon"
const (
falconModelType7B = 32
falconModelType40B = 60
@@ -17,6 +15,6 @@ func falconModelType(numLayer uint32) string {
case 80:
return "180B"
default:
return "Unknown"
return "unknown"
}
}

View File

@@ -69,7 +69,7 @@ func fileType(fileType uint32) string {
case fileTypeQ6_K:
return "Q6_K"
default:
return "Unknown"
return "unknown"
}
}

View File

@@ -109,9 +109,13 @@ func (llm *ggufModel) ModelType() string {
if blocks, ok := llm.kv["falcon.block_count"].(uint32); ok {
return falconModelType(blocks)
}
case "starcoder":
if blocks, ok := llm.kv["starcoder.block_count"].(uint32); ok {
return starCoderModelType(blocks)
}
}
return "Unknown"
return "unknown"
}
func (llm *ggufModel) FileType() string {
@@ -120,7 +124,7 @@ func (llm *ggufModel) FileType() string {
return fileType(t)
}
return "Unknown"
return "unknown"
}
func (llm *ggufModel) Decode(r io.Reader) error {

View File

@@ -9,8 +9,10 @@ package llm
//go:generate git -C ggml apply ../patches/0004-metal-add-missing-barriers-for-mul-mat-2699.patch
//go:generate cmake -S ggml -B ggml/build/cpu -DLLAMA_ACCELERATE=on -DLLAMA_K_QUANTS=on -DCMAKE_SYSTEM_PROCESSOR=x86_64 -DCMAKE_OSX_ARCHITECTURES=x86_64 -DCMAKE_OSX_DEPLOYMENT_TARGET=11.0
//go:generate cmake --build ggml/build/cpu --target server --config Release
//go:generate mv ggml/build/cpu/bin/server ggml/build/cpu/bin/ollama-runner
//go:generate git submodule update --force gguf
//go:generate git -C gguf apply ../patches/0001-remove-warm-up-logging.patch
//go:generate cmake -S gguf -B gguf/build/cpu -DLLAMA_ACCELERATE=on -DLLAMA_K_QUANTS=on -DCMAKE_SYSTEM_PROCESSOR=x86_64 -DCMAKE_OSX_ARCHITECTURES=x86_64 -DCMAKE_OSX_DEPLOYMENT_TARGET=11.0
//go:generate cmake --build gguf/build/cpu --target server --config Release
//go:generate mv gguf/build/cpu/bin/server gguf/build/cpu/bin/ollama-runner

View File

@@ -9,8 +9,10 @@ package llm
//go:generate git -C ggml apply ../patches/0004-metal-add-missing-barriers-for-mul-mat-2699.patch
//go:generate cmake -S ggml -B ggml/build/metal -DLLAMA_METAL=on -DLLAMA_ACCELERATE=on -DLLAMA_K_QUANTS=on -DCMAKE_SYSTEM_PROCESSOR=arm64 -DCMAKE_OSX_ARCHITECTURES=arm64 -DCMAKE_OSX_DEPLOYMENT_TARGET=11.0
//go:generate cmake --build ggml/build/metal --target server --config Release
//go:generate mv ggml/build/metal/bin/server ggml/build/metal/bin/ollama-runner
//go:generate git submodule update --force gguf
//go:generate git -C gguf apply ../patches/0001-remove-warm-up-logging.patch
//go:generate cmake -S gguf -B gguf/build/metal -DLLAMA_METAL=on -DLLAMA_ACCELERATE=on -DLLAMA_K_QUANTS=on -DCMAKE_SYSTEM_PROCESSOR=arm64 -DCMAKE_OSX_ARCHITECTURES=arm64 -DCMAKE_OSX_DEPLOYMENT_TARGET=11.0
//go:generate cmake --build gguf/build/metal --target server --config Release
//go:generate mv gguf/build/metal/bin/server gguf/build/metal/bin/ollama-runner

View File

@@ -9,14 +9,18 @@ package llm
//go:generate git -C ggml apply ../patches/0001-copy-cuda-runtime-libraries.patch
//go:generate cmake -S ggml -B ggml/build/cpu -DLLAMA_K_QUANTS=on
//go:generate cmake --build ggml/build/cpu --target server --config Release
//go:generate mv ggml/build/cpu/bin/server ggml/build/cpu/bin/ollama-runner
//go:generate git submodule update --force gguf
//go:generate git -C gguf apply ../patches/0001-copy-cuda-runtime-libraries.patch
//go:generate git -C gguf apply ../patches/0001-remove-warm-up-logging.patch
//go:generate cmake -S gguf -B gguf/build/cpu -DLLAMA_K_QUANTS=on
//go:generate cmake --build gguf/build/cpu --target server --config Release
//go:generate mv gguf/build/cpu/bin/server gguf/build/cpu/bin/ollama-runner
//go:generate cmake -S ggml -B ggml/build/cuda -DLLAMA_CUBLAS=on -DLLAMA_ACCELERATE=on -DLLAMA_K_QUANTS=on
//go:generate cmake --build ggml/build/cuda --target server --config Release
//go:generate mv ggml/build/cuda/bin/server ggml/build/cuda/bin/ollama-runner
//go:generate cmake -S gguf -B gguf/build/cuda -DLLAMA_CUBLAS=on -DLLAMA_ACCELERATE=on -DLLAMA_K_QUANTS=on
//go:generate cmake --build gguf/build/cuda --target server --config Release
//go:generate mv gguf/build/cuda/bin/server gguf/build/cuda/bin/ollama-runner

View File

@@ -7,8 +7,10 @@ package llm
//go:generate git -C ggml apply ../patches/0002-34B-model-support.patch
//go:generate cmake -S ggml -B ggml/build/cpu -DLLAMA_K_QUANTS=on
//go:generate cmake --build ggml/build/cpu --target server --config Release
//go:generate cmd /c move ggml\build\cpu\bin\Release\server.exe ggml\build\cpu\bin\Release\ollama-runner.exe
//go:generate git submodule update --force gguf
//go:generate git -C gguf apply ../patches/0001-remove-warm-up-logging.patch
//go:generate cmake -S gguf -B gguf/build/cpu -DLLAMA_K_QUANTS=on
//go:generate cmake --build gguf/build/cpu --target server --config Release
//go:generate cmd /c move gguf\build\cpu\bin\Release\server.exe gguf\build\cpu\bin\Release\ollama-runner.exe

View File

@@ -20,6 +20,7 @@ import (
"runtime"
"strconv"
"strings"
"sync"
"time"
"github.com/jmorganca/ollama/api"
@@ -41,23 +42,23 @@ func chooseRunners(workDir, runnerType string) []ModelRunner {
switch runtime.GOOS {
case "darwin":
runners = []string{
path.Join(buildPath, "metal", "bin", "server"),
path.Join(buildPath, "cpu", "bin", "server"),
path.Join(buildPath, "metal", "bin", "ollama-runner"),
path.Join(buildPath, "cpu", "bin", "ollama-runner"),
}
case "linux":
runners = []string{
path.Join(buildPath, "cuda", "bin", "server"),
path.Join(buildPath, "cpu", "bin", "server"),
path.Join(buildPath, "cuda", "bin", "ollama-runner"),
path.Join(buildPath, "cpu", "bin", "ollama-runner"),
}
case "windows":
// TODO: select windows GPU runner here when available
runners = []string{
path.Join(buildPath, "cpu", "bin", "Release", "server.exe"),
path.Join(buildPath, "cpu", "bin", "Release", "ollama-runner.exe"),
}
default:
log.Printf("unknown OS, running on CPU: %s", runtime.GOOS)
runners = []string{
path.Join(buildPath, "cpu", "bin", "server"),
path.Join(buildPath, "cpu", "bin", "ollama-runner"),
}
}
@@ -143,7 +144,7 @@ func llamaModelType(numLayer uint32) string {
case 80:
return "65B"
default:
return "Unknown"
return "unknown"
}
}
@@ -177,9 +178,12 @@ type llamaHyperparameters struct {
}
type Running struct {
Port int
Cmd *exec.Cmd
Cancel context.CancelFunc
Port int
Cmd *exec.Cmd
Cancel context.CancelFunc
exitOnce sync.Once
exitCh chan error // channel to receive the exit status of the subprocess
exitErr error // error returned by the subprocess
}
type llama struct {
@@ -191,7 +195,7 @@ var errNoGPU = errors.New("nvidia-smi command failed")
// CheckVRAM returns the available VRAM in MiB on Linux machines with NVIDIA GPUs
func CheckVRAM() (int64, error) {
cmd := exec.Command("nvidia-smi", "--query-gpu=memory.total", "--format=csv,noheader,nounits")
cmd := exec.Command("nvidia-smi", "--query-gpu=memory.free", "--format=csv,noheader,nounits")
var stdout bytes.Buffer
cmd.Stdout = &stdout
err := cmd.Run()
@@ -199,7 +203,7 @@ func CheckVRAM() (int64, error) {
return 0, errNoGPU
}
var total int64
var free int64
scanner := bufio.NewScanner(&stdout)
for scanner.Scan() {
line := scanner.Text()
@@ -208,17 +212,16 @@ func CheckVRAM() (int64, error) {
return 0, fmt.Errorf("failed to parse available VRAM: %v", err)
}
total += vram
free += vram
}
return total, nil
return free, nil
}
func NumGPU(numLayer, fileSizeBytes int64, opts api.Options) int {
if opts.NumGPU != -1 {
return opts.NumGPU
}
n := 1 // default to enable metal on macOS
if runtime.GOOS == "linux" {
vramMib, err := CheckVRAM()
if err != nil {
@@ -229,21 +232,41 @@ func NumGPU(numLayer, fileSizeBytes int64, opts api.Options) int {
return 0
}
totalVramBytes := int64(vramMib) * 1024 * 1024 // 1 MiB = 1024^2 bytes
freeVramBytes := int64(vramMib) * 1024 * 1024 // 1 MiB = 1024^2 bytes
// Calculate bytes per layer
// TODO: this is a rough heuristic, better would be to calculate this based on number of layers and context size
bytesPerLayer := fileSizeBytes / numLayer
// set n to the max number of layers we can fit in VRAM
return int(totalVramBytes / bytesPerLayer)
// max number of layers we can fit in VRAM, subtract 5% to prevent consuming all available VRAM and running out of memory
layers := int(freeVramBytes/bytesPerLayer) * 95 / 100
log.Printf("%d MiB VRAM available, loading up to %d GPU layers", vramMib, layers)
log.Printf("%d MiB VRAM available, loading up to %d GPU layers", vramMib, n)
return layers
}
// default to enable metal on macOS
return 1
}
// StatusWriter is a writer that captures error messages from the llama runner process
type StatusWriter struct {
ErrCh chan error
}
func NewStatusWriter() *StatusWriter {
return &StatusWriter{
ErrCh: make(chan error, 1),
}
}
func (w *StatusWriter) Write(b []byte) (int, error) {
if _, after, ok := bytes.Cut(b, []byte("error:")); ok {
err := fmt.Errorf("llama runner: %s", after)
w.ErrCh <- err
}
return os.Stderr.Write(b)
}
func newLlama(model string, adapters []string, runners []ModelRunner, numLayers int64, opts api.Options) (*llama, error) {
fileInfo, err := os.Stat(model)
if err != nil {
@@ -290,6 +313,8 @@ func newLlama(model string, adapters []string, runners []ModelRunner, numLayers
params = append(params, "--numa")
}
var runnerErr error
// start the llama.cpp server with a retry in case the port is already in use
for _, runner := range runners {
if _, err := os.Stat(runner.Path); err != nil {
@@ -306,9 +331,10 @@ func newLlama(model string, adapters []string, runners []ModelRunner, numLayers
)
cmd.Env = append(os.Environ(), fmt.Sprintf("LD_LIBRARY_PATH=%s", filepath.Dir(runner.Path)))
cmd.Stdout = os.Stderr
cmd.Stderr = os.Stderr
statusWriter := NewStatusWriter()
cmd.Stderr = statusWriter
llm := &llama{Options: opts, Running: Running{Port: port, Cmd: cmd, Cancel: cancel}}
llm := &llama{Options: opts, Running: Running{Port: port, Cmd: cmd, Cancel: cancel, exitCh: make(chan error)}}
log.Print("starting llama runner")
if err := llm.Cmd.Start(); err != nil {
@@ -316,19 +342,30 @@ func newLlama(model string, adapters []string, runners []ModelRunner, numLayers
continue
}
// monitor the command, it is blocking, so if it exits we need to capture that
// monitor the llama runner process and signal when it exits
go func() {
err := llm.Cmd.Wait() // this will block until the command exits
if err != nil {
log.Printf("llama runner exited with error: %v", err)
} else {
log.Printf("llama runner exited")
}
err := llm.Cmd.Wait()
llm.exitErr = err
// llm.Cmd.Wait() can only be called once, use this exit channel to signal that the process has exited
llm.exitOnce.Do(func() {
close(llm.exitCh)
})
}()
if err := waitForServer(llm); err != nil {
log.Printf("error starting llama runner: %v", err)
llm.Close()
// default the runnerErr to the error returned by the most recent llama runner process
runnerErr = err
// capture the error directly from the runner process, if any
select {
case runnerErr = <-statusWriter.ErrCh:
default:
// the runner process probably timed out
}
// try again
continue
}
@@ -337,37 +374,54 @@ func newLlama(model string, adapters []string, runners []ModelRunner, numLayers
return llm, nil
}
if runnerErr != nil {
// this is the error returned from the llama runner process that failed most recently
return nil, runnerErr
}
return nil, fmt.Errorf("failed to start a llama runner")
}
func waitForServer(llm *llama) error {
// wait for the server to start responding
start := time.Now()
expiresAt := time.Now().Add(2 * time.Minute) // be generous with timeout, large models can take a while to load
expiresAt := time.Now().Add(3 * time.Minute) // be generous with timeout, large models can take a while to load
ticker := time.NewTicker(200 * time.Millisecond)
defer ticker.Stop()
log.Print("waiting for llama runner to start responding")
for range ticker.C {
if time.Now().After(expiresAt) {
return fmt.Errorf("llama runner did not start within alloted time, retrying")
}
// check if the server process has terminated
if llm.Cmd.ProcessState != nil && llm.Cmd.ProcessState.Exited() {
for {
select {
case <-llm.exitCh:
// failed to start subprocess
return fmt.Errorf("llama runner process has terminated")
}
case <-ticker.C:
if time.Now().After(expiresAt) {
// timeout
return fmt.Errorf("timed out waiting for llama runner to start")
}
if err := llm.Ping(context.Background()); err == nil {
break
if err := llm.Ping(context.Background()); err == nil {
// success
log.Printf("llama runner started in %f seconds", time.Since(start).Seconds())
return nil
}
}
}
log.Printf("llama runner started in %f seconds", time.Since(start).Seconds())
return nil
}
func (llm *llama) Close() {
// signal the sub-process to terminate
llm.Cancel()
// wait for the command to exit to prevent race conditions with the next run
<-llm.exitCh
err := llm.exitErr
if err != nil {
log.Printf("llama runner stopped with error: %v", err)
} else {
log.Print("llama runner stopped successfully")
}
}
func (llm *llama) SetOptions(opts api.Options) {
@@ -417,30 +471,29 @@ type Prediction struct {
}
type PredictRequest struct {
Stream bool `json:"stream"`
NPredict int `json:"n_predict,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"`
RepeatLastN int `json:"repeat_last_n,omitempty"`
Temperature float32 `json:"temperature,omitempty"`
RepeatPenalty float32 `json:"repeat_penalty,omitempty"`
PresencePenalty float32 `json:"presence_penalty,omitempty"`
FrequencyPenalty float32 `json:"frequency_penalty,omitempty"`
Mirostat int `json:"mirostat,omitempty"`
MirostatTau float32 `json:"mirostat_tau,omitempty"`
MirostatEta float32 `json:"mirostat_eta,omitempty"`
PenalizeNl bool `json:"penalize_nl,omitempty"`
NKeep int `json:"n_keep,omitempty"`
Seed int `json:"seed,omitempty"`
Prompt string `json:"prompt,omitempty"`
NProbs int `json:"n_probs,omitempty"`
LogitBias map[int]float32 `json:"logit_bias,omitempty"`
IgnoreEos bool `json:"ignore_eos,omitempty"`
Stop []string `json:"stop,omitempty"`
Prompt string `json:"prompt"`
Stream bool `json:"stream"`
NPredict int `json:"n_predict"`
NKeep int `json:"n_keep"`
Temperature float32 `json:"temperature"`
TopK int `json:"top_k"`
TopP float32 `json:"top_p"`
TfsZ float32 `json:"tfs_z"`
TypicalP float32 `json:"typical_p"`
RepeatLastN int `json:"repeat_last_n"`
RepeatPenalty float32 `json:"repeat_penalty"`
PresencePenalty float32 `json:"presence_penalty"`
FrequencyPenalty float32 `json:"frequency_penalty"`
Mirostat int `json:"mirostat"`
MirostatTau float32 `json:"mirostat_tau"`
MirostatEta float32 `json:"mirostat_eta"`
PenalizeNl bool `json:"penalize_nl"`
Seed int `json:"seed"`
Stop []string `json:"stop,omitempty"`
}
const maxBufferSize = 512 * 1000 // 512KB
func (llm *llama) Predict(ctx context.Context, prevContext []int, prompt string, fn func(api.GenerateResponse)) error {
prevConvo, err := llm.Decode(ctx, prevContext)
if err != nil {
@@ -470,8 +523,10 @@ func (llm *llama) Predict(ctx context.Context, prevContext []int, prompt string,
MirostatTau: llm.MirostatTau,
MirostatEta: llm.MirostatEta,
PenalizeNl: llm.PenalizeNewline,
Seed: llm.Seed,
Stop: llm.Stop,
}
data, err := json.Marshal(predReq)
if err != nil {
return fmt.Errorf("error marshaling data: %v", err)
@@ -499,6 +554,9 @@ func (llm *llama) Predict(ctx context.Context, prevContext []int, prompt string,
}
scanner := bufio.NewScanner(resp.Body)
// increase the buffer size to avoid running out of space
buf := make([]byte, 0, maxBufferSize)
scanner.Buffer(buf, maxBufferSize)
for scanner.Scan() {
select {
case <-ctx.Done():

View File

@@ -5,6 +5,7 @@ import (
"fmt"
"log"
"os"
"runtime"
"github.com/pbnjay/memory"
@@ -37,53 +38,55 @@ func New(workDir, model string, adapters []string, opts api.Options) (LLM, error
return nil, err
}
switch ggml.FileType() {
case "Q8_0":
if ggml.Name() != "gguf" && opts.NumGPU != 0 {
// GGML Q8_0 do not support Metal API and will
// cause the runner to segmentation fault so disable GPU
log.Printf("WARNING: GPU disabled for F32, Q5_0, Q5_1, and Q8_0")
opts.NumGPU = 0
}
case "F32", "Q5_0", "Q5_1":
if opts.NumGPU != 0 {
// F32, Q5_0, Q5_1, and Q8_0 do not support Metal API and will
// cause the runner to segmentation fault so disable GPU
log.Printf("WARNING: GPU disabled for F32, Q5_0, Q5_1, and Q8_0")
opts.NumGPU = 0
if runtime.GOOS == "darwin" {
switch ggml.FileType() {
case "Q8_0":
if ggml.Name() != "gguf" && opts.NumGPU != 0 {
// GGML Q8_0 do not support Metal API and will
// cause the runner to segmentation fault so disable GPU
log.Printf("WARNING: GPU disabled for F32, Q5_0, Q5_1, and Q8_0")
opts.NumGPU = 0
}
case "F32", "Q5_0", "Q5_1":
if opts.NumGPU != 0 {
// F32, Q5_0, Q5_1, and Q8_0 do not support Metal API and will
// cause the runner to segmentation fault so disable GPU
log.Printf("WARNING: GPU disabled for F32, Q5_0, Q5_1, and Q8_0")
opts.NumGPU = 0
}
}
}
totalResidentMemory := memory.TotalMemory()
switch ggml.ModelType() {
case "3B", "7B":
if ggml.FileType() == "F16" && totalResidentMemory < 16*1024*1024 {
return nil, fmt.Errorf("F16 model requires at least 16GB of memory")
} else if totalResidentMemory < 8*1024*1024 {
return nil, fmt.Errorf("model requires at least 8GB of memory")
if ggml.FileType() == "F16" && totalResidentMemory < 16*1000*1000 {
return nil, fmt.Errorf("F16 model requires at least 16 GB of memory")
} else if totalResidentMemory < 8*1000*1000 {
return nil, fmt.Errorf("model requires at least 8 GB of memory")
}
case "13B":
if ggml.FileType() == "F16" && totalResidentMemory < 32*1024*1024 {
return nil, fmt.Errorf("F16 model requires at least 32GB of memory")
} else if totalResidentMemory < 16*1024*1024 {
return nil, fmt.Errorf("model requires at least 16GB of memory")
if ggml.FileType() == "F16" && totalResidentMemory < 32*1000*1000 {
return nil, fmt.Errorf("F16 model requires at least 32 GB of memory")
} else if totalResidentMemory < 16*1000*1000 {
return nil, fmt.Errorf("model requires at least 16 GB of memory")
}
case "30B", "34B", "40B":
if ggml.FileType() == "F16" && totalResidentMemory < 64*1024*1024 {
return nil, fmt.Errorf("F16 model requires at least 64GB of memory")
} else if totalResidentMemory < 32*1024*1024 {
return nil, fmt.Errorf("model requires at least 32GB of memory")
if ggml.FileType() == "F16" && totalResidentMemory < 64*1000*1000 {
return nil, fmt.Errorf("F16 model requires at least 64 GB of memory")
} else if totalResidentMemory < 32*1000*1000 {
return nil, fmt.Errorf("model requires at least 32 GB of memory")
}
case "65B", "70B":
if ggml.FileType() == "F16" && totalResidentMemory < 128*1024*1024 {
return nil, fmt.Errorf("F16 model requires at least 128GB of memory")
} else if totalResidentMemory < 64*1024*1024 {
return nil, fmt.Errorf("model requires at least 64GB of memory")
if ggml.FileType() == "F16" && totalResidentMemory < 128*1000*1000 {
return nil, fmt.Errorf("F16 model requires at least 128 GB of memory")
} else if totalResidentMemory < 64*1000*1000 {
return nil, fmt.Errorf("model requires at least 64 GB of memory")
}
case "180B":
if ggml.FileType() == "F16" && totalResidentMemory < 512*1024*1024 {
if ggml.FileType() == "F16" && totalResidentMemory < 512*1000*1000 {
return nil, fmt.Errorf("F16 model requires at least 512GB of memory")
} else if totalResidentMemory < 128*1024*1024 {
} else if totalResidentMemory < 128*1000*1000 {
return nil, fmt.Errorf("model requires at least 128GB of memory")
}
}

23
llm/starcoder.go Normal file
View File

@@ -0,0 +1,23 @@
package llm
const (
starCoderModelType1B = 24
starCoderModelType3B = 36
starCoderModelType7B = 42
starCoderModelType15B = 40
)
func starCoderModelType(numLayer uint32) string {
switch numLayer {
case 24:
return "1B"
case 36:
return "3B"
case 42:
return "7B"
case 40:
return "15B"
default:
return "unknown"
}
}

0
scripts/build_docker.sh Normal file → Executable file
View File

View File

@@ -2,38 +2,309 @@ package server
import (
"context"
"encoding/json"
"errors"
"fmt"
"io"
"log"
"net/http"
"net/url"
"os"
"path/filepath"
"strconv"
"strings"
"sync"
"sync/atomic"
"time"
"golang.org/x/sync/errgroup"
"github.com/jmorganca/ollama/api"
"github.com/jmorganca/ollama/format"
)
type FileDownload struct {
Digest string
FilePath string
var blobDownloadManager sync.Map
type blobDownload struct {
Name string
Digest string
Total int64
Completed int64
Completed atomic.Int64
Parts []*blobDownloadPart
context.CancelFunc
done bool
err error
references atomic.Int32
}
var inProgress sync.Map // map of digests currently being downloaded to their current download progress
type blobDownloadPart struct {
N int
Offset int64
Size int64
Completed int64
*blobDownload `json:"-"`
}
const (
numDownloadParts = 64
minDownloadPartSize int64 = 32 * 1000 * 1000
maxDownloadPartSize int64 = 256 * 1000 * 1000
)
func (p *blobDownloadPart) Name() string {
return strings.Join([]string{
p.blobDownload.Name, "partial", strconv.Itoa(p.N),
}, "-")
}
func (p *blobDownloadPart) StartsAt() int64 {
return p.Offset + p.Completed
}
func (p *blobDownloadPart) StopsAt() int64 {
return p.Offset + p.Size
}
func (b *blobDownload) Prepare(ctx context.Context, requestURL *url.URL, opts *RegistryOptions) error {
partFilePaths, err := filepath.Glob(b.Name + "-partial-*")
if err != nil {
return err
}
for _, partFilePath := range partFilePaths {
part, err := b.readPart(partFilePath)
if err != nil {
return err
}
b.Total += part.Size
b.Completed.Add(part.Completed)
b.Parts = append(b.Parts, part)
}
if len(b.Parts) == 0 {
resp, err := makeRequest(ctx, "HEAD", requestURL, nil, nil, opts)
if err != nil {
return err
}
defer resp.Body.Close()
if resp.StatusCode >= http.StatusBadRequest {
body, _ := io.ReadAll(resp.Body)
return fmt.Errorf("registry responded with code %d: %v", resp.StatusCode, string(body))
}
b.Total, _ = strconv.ParseInt(resp.Header.Get("Content-Length"), 10, 64)
var size = b.Total / numDownloadParts
switch {
case size < minDownloadPartSize:
size = minDownloadPartSize
case size > maxDownloadPartSize:
size = maxDownloadPartSize
}
var offset int64
for offset < b.Total {
if offset+size > b.Total {
size = b.Total - offset
}
if err := b.newPart(offset, size); err != nil {
return err
}
offset += size
}
}
log.Printf("downloading %s in %d %s part(s)", b.Digest[7:19], len(b.Parts), format.HumanBytes(b.Parts[0].Size))
return nil
}
func (b *blobDownload) Run(ctx context.Context, requestURL *url.URL, opts *RegistryOptions) {
b.err = b.run(ctx, requestURL, opts)
}
func (b *blobDownload) run(ctx context.Context, requestURL *url.URL, opts *RegistryOptions) error {
defer blobDownloadManager.Delete(b.Digest)
ctx, b.CancelFunc = context.WithCancel(ctx)
file, err := os.OpenFile(b.Name+"-partial", os.O_CREATE|os.O_RDWR, 0644)
if err != nil {
return err
}
defer file.Close()
file.Truncate(b.Total)
g, inner := errgroup.WithContext(ctx)
g.SetLimit(numDownloadParts)
for i := range b.Parts {
part := b.Parts[i]
if part.Completed == part.Size {
continue
}
i := i
g.Go(func() error {
for try := 0; try < maxRetries; try++ {
w := io.NewOffsetWriter(file, part.StartsAt())
err := b.downloadChunk(inner, requestURL, w, part, opts)
switch {
case errors.Is(err, context.Canceled):
return err
case err != nil:
log.Printf("%s part %d attempt %d failed: %v, retrying", b.Digest[7:19], i, try, err)
continue
default:
return nil
}
}
return errors.New("max retries exceeded")
})
}
if err := g.Wait(); err != nil {
return err
}
// explicitly close the file so we can rename it
if err := file.Close(); err != nil {
return err
}
for i := range b.Parts {
if err := os.Remove(file.Name() + "-" + strconv.Itoa(i)); err != nil {
return err
}
}
if err := os.Rename(file.Name(), b.Name); err != nil {
return err
}
b.done = true
return nil
}
func (b *blobDownload) downloadChunk(ctx context.Context, requestURL *url.URL, w io.Writer, part *blobDownloadPart, opts *RegistryOptions) error {
headers := make(http.Header)
headers.Set("Range", fmt.Sprintf("bytes=%d-%d", part.StartsAt(), part.StopsAt()-1))
resp, err := makeRequest(ctx, "GET", requestURL, headers, nil, opts)
if err != nil {
return err
}
defer resp.Body.Close()
n, err := io.Copy(w, io.TeeReader(resp.Body, b))
if err != nil && !errors.Is(err, context.Canceled) {
// rollback progress
b.Completed.Add(-n)
return err
}
part.Completed += n
if err := b.writePart(part.Name(), part); err != nil {
return err
}
// return nil or context.Canceled
return err
}
func (b *blobDownload) newPart(offset, size int64) error {
part := blobDownloadPart{blobDownload: b, Offset: offset, Size: size, N: len(b.Parts)}
if err := b.writePart(part.Name(), &part); err != nil {
return err
}
b.Parts = append(b.Parts, &part)
return nil
}
func (b *blobDownload) readPart(partName string) (*blobDownloadPart, error) {
var part blobDownloadPart
partFile, err := os.Open(partName)
if err != nil {
return nil, err
}
defer partFile.Close()
if err := json.NewDecoder(partFile).Decode(&part); err != nil {
return nil, err
}
part.blobDownload = b
return &part, nil
}
func (b *blobDownload) writePart(partName string, part *blobDownloadPart) error {
partFile, err := os.OpenFile(partName, os.O_CREATE|os.O_RDWR|os.O_TRUNC, 0644)
if err != nil {
return err
}
defer partFile.Close()
return json.NewEncoder(partFile).Encode(part)
}
func (b *blobDownload) Write(p []byte) (n int, err error) {
n = len(p)
b.Completed.Add(int64(n))
return n, nil
}
func (b *blobDownload) acquire() {
b.references.Add(1)
}
func (b *blobDownload) release() {
if b.references.Add(-1) == 0 {
b.CancelFunc()
}
}
func (b *blobDownload) Wait(ctx context.Context, fn func(api.ProgressResponse)) error {
b.acquire()
defer b.release()
ticker := time.NewTicker(60 * time.Millisecond)
for {
select {
case <-ticker.C:
case <-ctx.Done():
return ctx.Err()
}
fn(api.ProgressResponse{
Status: fmt.Sprintf("downloading %s", b.Digest),
Digest: b.Digest,
Total: b.Total,
Completed: b.Completed.Load(),
})
if b.done || b.err != nil {
return b.err
}
}
}
type downloadOpts struct {
mp ModelPath
digest string
regOpts *RegistryOptions
fn func(api.ProgressResponse)
retry int // track the number of retries on this download
}
const maxRetry = 3
const maxRetries = 3
// downloadBlob downloads a blob from the registry and stores it in the blobs directory
func downloadBlob(ctx context.Context, opts downloadOpts) error {
@@ -42,9 +313,14 @@ func downloadBlob(ctx context.Context, opts downloadOpts) error {
return err
}
if fi, _ := os.Stat(fp); fi != nil {
// we already have the file, so return
fi, err := os.Stat(fp)
switch {
case errors.Is(err, os.ErrNotExist):
case err != nil:
return err
default:
opts.fn(api.ProgressResponse{
Status: fmt.Sprintf("downloading %s", opts.digest),
Digest: opts.digest,
Total: fi.Size(),
Completed: fi.Size(),
@@ -53,185 +329,18 @@ func downloadBlob(ctx context.Context, opts downloadOpts) error {
return nil
}
fileDownload := &FileDownload{
Digest: opts.digest,
FilePath: fp,
Total: 1, // dummy value to indicate that we don't know the total size yet
Completed: 0,
}
_, downloading := inProgress.LoadOrStore(opts.digest, fileDownload)
if downloading {
// this is another client requesting the server to download the same blob concurrently
return monitorDownload(ctx, opts, fileDownload)
}
if err := doDownload(ctx, opts, fileDownload); err != nil {
if errors.Is(err, errDownload) && opts.retry < maxRetry {
opts.retry++
log.Print(err)
log.Printf("retrying download of %s", opts.digest)
return downloadBlob(ctx, opts)
}
return err
}
return nil
}
var downloadMu sync.Mutex // mutex to check to resume a download while monitoring
// monitorDownload monitors the download progress of a blob and resumes it if it is interrupted
func monitorDownload(ctx context.Context, opts downloadOpts, f *FileDownload) error {
tick := time.NewTicker(time.Second)
for range tick.C {
done, resume, err := func() (bool, bool, error) {
downloadMu.Lock()
defer downloadMu.Unlock()
val, downloading := inProgress.Load(f.Digest)
if !downloading {
// check once again if the download is complete
if fi, _ := os.Stat(f.FilePath); fi != nil {
// successful download while monitoring
opts.fn(api.ProgressResponse{
Digest: f.Digest,
Total: fi.Size(),
Completed: fi.Size(),
})
return true, false, nil
}
// resume the download
inProgress.Store(f.Digest, f) // store the file download again to claim the resume
return false, true, nil
}
f, ok := val.(*FileDownload)
if !ok {
return false, false, fmt.Errorf("invalid type for in progress download: %T", val)
}
opts.fn(api.ProgressResponse{
Status: fmt.Sprintf("downloading %s", f.Digest),
Digest: f.Digest,
Total: f.Total,
Completed: f.Completed,
})
return false, false, nil
}()
if err != nil {
data, ok := blobDownloadManager.LoadOrStore(opts.digest, &blobDownload{Name: fp, Digest: opts.digest})
download := data.(*blobDownload)
if !ok {
requestURL := opts.mp.BaseURL()
requestURL = requestURL.JoinPath("v2", opts.mp.GetNamespaceRepository(), "blobs", opts.digest)
if err := download.Prepare(ctx, requestURL, opts.regOpts); err != nil {
blobDownloadManager.Delete(opts.digest)
return err
}
if done {
// done downloading
return nil
}
if resume {
return doDownload(ctx, opts, f)
}
go download.Run(context.Background(), requestURL, opts.regOpts)
}
return nil
}
var (
chunkSize int64 = 1024 * 1024 // 1 MiB in bytes
errDownload = fmt.Errorf("download failed")
)
// doDownload downloads a blob from the registry and stores it in the blobs directory
func doDownload(ctx context.Context, opts downloadOpts, f *FileDownload) error {
defer inProgress.Delete(f.Digest)
var size int64
fi, err := os.Stat(f.FilePath + "-partial")
switch {
case errors.Is(err, os.ErrNotExist):
// noop, file doesn't exist so create it
case err != nil:
return fmt.Errorf("stat: %w", err)
default:
size = fi.Size()
// Ensure the size is divisible by the chunk size by removing excess bytes
size -= size % chunkSize
err := os.Truncate(f.FilePath+"-partial", size)
if err != nil {
return fmt.Errorf("truncate: %w", err)
}
}
requestURL := opts.mp.BaseURL()
requestURL = requestURL.JoinPath("v2", opts.mp.GetNamespaceRepository(), "blobs", f.Digest)
headers := make(http.Header)
headers.Set("Range", fmt.Sprintf("bytes=%d-", size))
resp, err := makeRequest(ctx, "GET", requestURL, headers, nil, opts.regOpts)
if err != nil {
log.Printf("couldn't download blob: %v", err)
return fmt.Errorf("%w: %w", errDownload, err)
}
defer resp.Body.Close()
if resp.StatusCode >= http.StatusBadRequest {
body, _ := io.ReadAll(resp.Body)
return fmt.Errorf("%w: on download registry responded with code %d: %v", errDownload, resp.StatusCode, string(body))
}
err = os.MkdirAll(filepath.Dir(f.FilePath), 0o700)
if err != nil {
return fmt.Errorf("make blobs directory: %w", err)
}
remaining, _ := strconv.ParseInt(resp.Header.Get("Content-Length"), 10, 64)
f.Completed = size
f.Total = remaining + f.Completed
inProgress.Store(f.Digest, f)
out, err := os.OpenFile(f.FilePath+"-partial", os.O_CREATE|os.O_APPEND|os.O_WRONLY, 0o644)
if err != nil {
return fmt.Errorf("open file: %w", err)
}
defer out.Close()
outerLoop:
for {
select {
case <-ctx.Done():
// handle client request cancellation
inProgress.Delete(f.Digest)
return nil
default:
opts.fn(api.ProgressResponse{
Status: fmt.Sprintf("downloading %s", f.Digest),
Digest: f.Digest,
Total: f.Total,
Completed: f.Completed,
})
if f.Completed >= f.Total {
if err := out.Close(); err != nil {
return err
}
if err := os.Rename(f.FilePath+"-partial", f.FilePath); err != nil {
opts.fn(api.ProgressResponse{
Status: fmt.Sprintf("error renaming file: %v", err),
Digest: f.Digest,
Total: f.Total,
Completed: f.Completed,
})
return err
}
break outerLoop
}
}
n, err := io.CopyN(out, resp.Body, chunkSize)
if err != nil && !errors.Is(err, io.EOF) {
return fmt.Errorf("%w: %w", errDownload, err)
}
f.Completed += n
inProgress.Store(f.Digest, f)
}
log.Printf("success getting %s\n", f.Digest)
return nil
return download.Wait(ctx, opts.fn)
}

View File

@@ -30,8 +30,6 @@ import (
"github.com/jmorganca/ollama/version"
)
const MaxRetries = 3
type RegistryOptions struct {
Insecure bool
Username string
@@ -374,6 +372,7 @@ func CreateModel(ctx context.Context, workDir, name string, path string, fn func
}
if mf != nil {
fn(api.ProgressResponse{Status: "reading model metadata"})
sourceBlobPath, err := GetBlobsPath(mf.Config.Digest)
if err != nil {
return err
@@ -831,7 +830,7 @@ func formatParams(params map[string][]string) (map[string]interface{}, error) {
return nil, fmt.Errorf("invalid int value %s", vals)
}
out[key] = int(intVal)
out[key] = intVal
case reflect.Bool:
boolVal, err := strconv.ParseBool(vals[0])
if err != nil {
@@ -1417,7 +1416,7 @@ func checkBlobExistence(ctx context.Context, mp ModelPath, digest string, regOpt
func makeRequestWithRetry(ctx context.Context, method string, requestURL *url.URL, headers http.Header, body io.ReadSeeker, regOpts *RegistryOptions) (*http.Response, error) {
var status string
for try := 0; try < MaxRetries; try++ {
for try := 0; try < maxRetries; try++ {
resp, err := makeRequest(ctx, method, requestURL, headers, body, regOpts)
if err != nil {
log.Printf("couldn't start upload: %v", err)
@@ -1487,13 +1486,14 @@ func makeRequest(ctx context.Context, method string, requestURL *url.URL, header
req.ContentLength = contentLength
}
client := &http.Client{
CheckRedirect: func(req *http.Request, via []*http.Request) error {
if len(via) >= 10 {
return fmt.Errorf("too many redirects")
}
log.Printf("redirected to: %s\n", req.URL)
return nil
proxyURL, err := http.ProxyFromEnvironment(req)
if err != nil {
return nil, err
}
client := http.Client{
Transport: &http.Transport{
Proxy: http.ProxyURL(proxyURL),
},
}

View File

@@ -3,8 +3,10 @@ package server
import (
"context"
"encoding/json"
"errors"
"fmt"
"io"
"io/fs"
"log"
"net"
"net/http"
@@ -66,7 +68,6 @@ func load(ctx context.Context, workDir string, model *Model, reqOpts map[string]
}
if err := opts.FromMap(reqOpts); err != nil {
log.Printf("could not merge model options: %v", err)
return err
}
@@ -170,6 +171,11 @@ func GenerateHandler(c *gin.Context) {
model, err := GetModel(req.Model)
if err != nil {
var pErr *fs.PathError
if errors.As(err, &pErr) {
c.JSON(http.StatusNotFound, gin.H{"error": fmt.Sprintf("model '%s' not found, try pulling it first", req.Model)})
return
}
c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
return
}
@@ -179,6 +185,10 @@ func GenerateHandler(c *gin.Context) {
// TODO: set this duration from the request if specified
sessionDuration := defaultSessionDuration
if err := load(c.Request.Context(), workDir, model, req.Options, sessionDuration); err != nil {
if errors.Is(err, api.ErrInvalidOpts) {
c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
return
}
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
@@ -233,6 +243,23 @@ func GenerateHandler(c *gin.Context) {
}
}()
if req.Stream != nil && !*req.Stream {
var response api.GenerateResponse
generated := ""
for resp := range ch {
if r, ok := resp.(api.GenerateResponse); ok {
generated += r.Response
response = r
} else {
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
return
}
}
response.Response = generated
c.JSON(http.StatusOK, response)
return
}
streamResponse(c, ch)
}
@@ -302,6 +329,11 @@ func PullModelHandler(c *gin.Context) {
}
}()
if req.Stream != nil && !*req.Stream {
waitForStream(c, ch)
return
}
streamResponse(c, ch)
}
@@ -329,6 +361,11 @@ func PushModelHandler(c *gin.Context) {
}
}()
if req.Stream != nil && !*req.Stream {
waitForStream(c, ch)
return
}
streamResponse(c, ch)
}
@@ -356,6 +393,11 @@ func CreateModelHandler(c *gin.Context) {
}
}()
if req.Stream != nil && !*req.Stream {
waitForStream(c, ch)
return
}
streamResponse(c, ch)
}
@@ -596,6 +638,31 @@ func Serve(ln net.Listener, allowOrigins []string) error {
return s.Serve(ln)
}
func waitForStream(c *gin.Context, ch chan interface{}) {
c.Header("Content-Type", "application/json")
for resp := range ch {
switch r := resp.(type) {
case api.ProgressResponse:
if r.Status == "success" {
c.JSON(http.StatusOK, r)
return
}
case gin.H:
if errorMsg, ok := r["error"].(string); ok {
c.JSON(http.StatusInternalServerError, gin.H{"error": errorMsg})
return
} else {
c.JSON(http.StatusInternalServerError, gin.H{"error": "unexpected error format in progress response"})
return
}
default:
c.JSON(http.StatusInternalServerError, gin.H{"error": "unexpected progress response"})
return
}
}
c.JSON(http.StatusInternalServerError, gin.H{"error": "unexpected end of progress response"})
}
func streamResponse(c *gin.Context, ch chan any) {
c.Header("Content-Type", "application/x-ndjson")
c.Stream(func(w io.Writer) bool {

View File

@@ -10,6 +10,7 @@ import (
"net/url"
"os"
"strconv"
"sync"
"github.com/jmorganca/ollama/api"
)
@@ -138,7 +139,7 @@ func uploadBlobChunk(ctx context.Context, method string, requestURL *url.URL, r
headers.Set("Content-Range", fmt.Sprintf("%d-%d", offset, offset+sectionReader.Size()-1))
}
for try := 0; try < MaxRetries; try++ {
for try := 0; try < maxRetries; try++ {
resp, err := makeRequest(ctx, method, requestURL, headers, io.TeeReader(sectionReader, pw), opts)
if err != nil && !errors.Is(err, io.EOF) {
return nil, err
@@ -191,9 +192,13 @@ type ProgressWriter struct {
completed int64
total int64
fn func(api.ProgressResponse)
mu sync.Mutex
}
func (pw *ProgressWriter) Write(b []byte) (int, error) {
pw.mu.Lock()
defer pw.mu.Unlock()
n := len(b)
pw.bucket += int64(n)