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11 Commits

Author SHA1 Message Date
Blake Mizerany
348effebf9 server: fix race conditions during download
This fixes various data races scattered throughout the download/pull
client where the client was accessing the download state concurrently.

This commit is mostly a hot-fix and will be replaced by a new client one
day soon.
2024-07-26 13:41:08 -07:00
Blake Mizerany
903d9b1a41 server: remove unnecessary opts argument from downloadChunk 2024-07-25 20:49:21 -07:00
Jeffrey Morgan
f5e3939220 Update api.md (#5968) 2024-07-25 23:10:18 -04:00
Jeffrey Morgan
ae27d9dcfd Update openai.md 2024-07-25 20:27:33 -04:00
Michael Yang
37096790a7 Merge pull request #5552 from ollama/mxyng/messages-docs
docs
2024-07-25 16:26:19 -07:00
Michael Yang
997c903884 Update docs/template.md
Co-authored-by: Jeffrey Morgan <jmorganca@gmail.com>
2024-07-25 16:23:40 -07:00
Blake Mizerany
c8af3c2d96 server: reuse original download URL for images (#5962)
This changes the registry client to reuse the original download URL
it gets on the first redirect response for all subsequent requests,
preventing thundering herd issues when hot new LLMs are released.
2024-07-25 15:58:30 -07:00
Jeffrey Morgan
455e61170d Update openai.md 2024-07-25 18:34:47 -04:00
royjhan
4de1370a9d openai tools doc (#5617) 2024-07-25 18:34:06 -04:00
Michael Yang
9b60a038e5 update api.md 2024-07-22 13:49:51 -07:00
Michael Yang
83a0cb8d88 docs 2024-07-22 13:38:09 -07:00
7 changed files with 410 additions and 32 deletions

View File

@@ -64,7 +64,8 @@ Here are some example models that can be downloaded:
| LLaVA | 7B | 4.5GB | `ollama run llava` |
| Solar | 10.7B | 6.1GB | `ollama run solar` |
> Note: You should have at least 8 GB of RAM available to run the 7B models, 16 GB to run the 13B models, and 32 GB to run the 33B models.
> [!NOTE]
> You should have at least 8 GB of RAM available to run the 7B models, 16 GB to run the 13B models, and 32 GB to run the 33B models.
## Customize a model

View File

@@ -40,6 +40,7 @@ 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
- `suffix`: the text after the model response
- `images`: (optional) a list of base64-encoded images (for multimodal models such as `llava`)
Advanced parameters (optional):
@@ -57,7 +58,8 @@ Advanced parameters (optional):
Enable JSON mode by setting the `format` parameter to `json`. This will structure the response as a valid JSON object. See the JSON mode [example](#request-json-mode) below.
> Note: it's important to instruct the model to use JSON in the `prompt`. Otherwise, the model may generate large amounts whitespace.
> [!IMPORTANT]
> It's important to instruct the model to use JSON in the `prompt`. Otherwise, the model may generate large amounts whitespace.
### Examples
@@ -148,8 +150,44 @@ If `stream` is set to `false`, the response will be a single JSON object:
}
```
#### Request (with suffix)
##### Request
```shell
curl http://localhost:11434/api/generate -d '{
"model": "codellama:code",
"prompt": "def compute_gcd(a, b):",
"suffix": " return result",
"options": {
"temperature": 0
},
"stream": false
}'
```
##### Response
```json
{
"model": "codellama:code",
"created_at": "2024-07-22T20:47:51.147561Z",
"response": "\n if a == 0:\n return b\n else:\n return compute_gcd(b % a, a)\n\ndef compute_lcm(a, b):\n result = (a * b) / compute_gcd(a, b)\n",
"done": true,
"done_reason": "stop",
"context": [...],
"total_duration": 1162761250,
"load_duration": 6683708,
"prompt_eval_count": 17,
"prompt_eval_duration": 201222000,
"eval_count": 63,
"eval_duration": 953997000
}
```
#### Request (JSON mode)
> [!IMPORTANT]
> When `format` is set to `json`, the output will always be a well-formed JSON object. It's important to also instruct the model to respond in JSON.
##### Request
@@ -380,12 +418,14 @@ Generate the next message in a chat with a provided model. This is a streaming e
- `model`: (required) the [model name](#model-names)
- `messages`: the messages of the chat, this can be used to keep a chat memory
- `tools`: tools for the model to use if supported. Requires `stream` to be set to `false`
The `message` object has the following fields:
- `role`: the role of the message, either `system`, `user` or `assistant`
- `role`: the role of the message, either `system`, `user`, `assistant`, or `tool`
- `content`: the content of the message
- `images` (optional): a list of images to include in the message (for multimodal models such as `llava`)
- `tool_calls` (optional): a list of tools the model wants to use
Advanced parameters (optional):
@@ -622,6 +662,79 @@ curl http://localhost:11434/api/chat -d '{
}
```
#### Chat request (with tools)
##### Request
```
curl http://localhost:11434/api/chat -d '{
"model": "mistral",
"messages": [
{
"role": "user",
"content": "What is the weather today in Paris?"
}
],
"stream": false,
"tools": [
{
"type": "function",
"function": {
"name": "get_current_weather",
"description": "Get the current weather for a location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The location to get the weather for, e.g. San Francisco, CA"
},
"format": {
"type": "string",
"description": "The format to return the weather in, e.g. 'celsius' or 'fahrenheit'",
"enum": ["celsius", "fahrenheit"]
}
},
"required": ["location", "format"]
}
}
}
]
}'
```
##### Response
```json
{
"model": "mistral:7b-instruct-v0.3-q4_K_M",
"created_at": "2024-07-22T20:33:28.123648Z",
"message": {
"role": "assistant",
"content": "",
"tool_calls": [
{
"function": {
"name": "get_current_weather",
"arguments": {
"format": "celsius",
"location": "Paris, FR"
}
}
}
]
},
"done_reason": "stop",
"done": true,
"total_duration": 885095291,
"load_duration": 3753500,
"prompt_eval_count": 122,
"prompt_eval_duration": 328493000,
"eval_count": 33,
"eval_duration": 552222000
}
```
## Create a Model
```shell
@@ -1173,4 +1286,4 @@ curl http://localhost:11434/api/embeddings -d '{
0.8785552978515625, -0.34576427936553955, 0.5742510557174683, -0.04222835972905159, -0.137906014919281
]
}
```
```

View File

@@ -1,6 +1,7 @@
# Ollama Model File
> Note: `Modelfile` syntax is in development
> [!NOTE]
> `Modelfile` syntax is in development
A model file is the blueprint to create and share models with Ollama.

View File

@@ -78,8 +78,8 @@ curl http://localhost:11434/v1/chat/completions \
- [x] Streaming
- [x] JSON mode
- [x] Reproducible outputs
- [x] Tools (streaming support coming soon)
- [ ] Vision
- [ ] Function calling
- [ ] Logprobs
#### Supported request fields
@@ -97,9 +97,9 @@ curl http://localhost:11434/v1/chat/completions \
- [x] `temperature`
- [x] `top_p`
- [x] `max_tokens`
- [ ] `logit_bias`
- [ ] `tools`
- [x] `tools`
- [ ] `tool_choice`
- [ ] `logit_bias`
- [ ] `user`
- [ ] `n`

173
docs/template.md Normal file
View File

@@ -0,0 +1,173 @@
# Template
Ollama provides a powerful templating engine backed by Go's built-in templating engine to construct prompts for your large language model. This feature is a valuable tool to get the most out of your models.
## Basic Template Structure
A basic Go template consists of three main parts:
* **Layout**: The overall structure of the template.
* **Variables**: Placeholders for dynamic data that will be replaced with actual values when the template is rendered.
* **Functions**: Custom functions or logic that can be used to manipulate the template's content.
Here's an example of a simple chat template:
```gotmpl
{{- range .Messages }}
{{ .Role }}: {{ .Content }}
{{- end }}
```
In this example, we have:
* A basic messages structure (layout)
* Three variables: `Messages`, `Role`, and `Content` (variables)
* A custom function (action) that iterates over an array of items (`range .Messages`) and displays each item
## Adding templates to your model
By default, models imported into Ollama have a default template of `{{ .Prompt }}`, i.e. user inputs are sent verbatim to the LLM. This is appropriate for text or code completion models but lacks essential markers for chat or instruction models.
Omitting a template in these models puts the responsibility of correctly templating input onto the user. Adding a template allows users to easily get the best results from the model.
To add templates in your model, you'll need to add a `TEMPLATE` command to the Modelfile. Here's an example using Meta's Llama 3.
```dockerfile
FROM llama3
TEMPLATE """{{- if .System }}<|start_header_id|>system<|end_header_id|>
{{ .System }}<|eot_id|>
{{- end }}
{{- range .Messages }}<|start_header_id|>{{ .Role }}<|end_header_id|>
{{ .Content }}<|eot_id|>
{{- end }}<|start_header_id|>assistant<|end_header_id|>
"""
```
## Variables
`System` (string): system prompt
`Prompt` (string): user prompt
`Response` (string): assistant response
`Suffix` (string): text inserted after the assistant's response
`Messages` (list): list of messages
`Messages[].Role` (string): role which can be one of `system`, `user`, `assistant`, or `tool`
`Messages[].Content` (string): message content
`Messages[].ToolCalls` (list): list of tools the model wants to call
`Messages[].ToolCalls[].Function` (object): function to call
`Messages[].ToolCalls[].Function.Name` (string): function name
`Messages[].ToolCalls[].Function.Arguments` (map): mapping of argument name to argument value
`Tools` (list): list of tools the model can access
`Tools[].Type` (string): schema type. `type` is always `function`
`Tools[].Function` (object): function definition
`Tools[].Function.Name` (string): function name
`Tools[].Function.Description` (string): function description
`Tools[].Function.Parameters` (object): function parameters
`Tools[].Function.Parameters.Type` (string): schema type. `type` is always `object`
`Tools[].Function.Parameters.Required` (list): list of required properties
`Tools[].Function.Parameters.Properties` (map): mapping of property name to property definition
`Tools[].Function.Parameters.Properties[].Type` (string): property type
`Tools[].Function.Parameters.Properties[].Description` (string): property description
`Tools[].Function.Parameters.Properties[].Enum` (list): list of valid values
## Tips and Best Practices
Keep the following tips and best practices in mind when working with Go templates:
* **Be mindful of dot**: Control flow structures like `range` and `with` changes the value `.`
* **Out-of-scope variables**: Use `$.` to reference variables not currently in scope, starting from the root
* **Whitespace control**: Use `-` to trim leading (`{{-`) and trailing (`-}}`) whitespace
## Examples
### Example Messages
#### ChatML
ChatML is a popular template format. It can be used for models such as Databrick's DBRX, Intel's Neural Chat, and Microsoft's Orca 2.
```gotmpl
{{- if .System }}<|im_start|>system
{{ .System }}<|im_end|>
{{ end }}
{{- range .Messages }}<|im_start|>{{ .Role }}
{{ .Content }}<|im_end|>
{{ end }}<|im_start|>assistant
{{ else }}
{{ if .System }}<|im_start|>system
{{ .System }}<|im_end|>
```
### Example Tools
Tools support can be added to a model by adding a `{{ .Tools }}` node to the template. This feature is useful for models trained to call external tools and can a powerful tool for retrieving real-time data or performing complex tasks.
#### Mistral
Mistral v0.3 and Mixtral 8x22B supports tool calling.
```gotmpl
{{- range $index, $_ := .Messages }}
{{- if eq .Role "user" }}
{{- if and (le (len (slice $.Messages $index)) 2) $.Tools }}[AVAILABLE_TOOLS] {{ json $.Tools }}[/AVAILABLE_TOOLS]
{{- end }}[INST] {{ if and (eq (len (slice $.Messages $index)) 1) $.System }}{{ $.System }}
{{ end }}{{ .Content }}[/INST]
{{- else if eq .Role "assistant" }}
{{- if .Content }} {{ .Content }}</s>
{{- else if .ToolCalls }}[TOOL_CALLS] [
{{- range .ToolCalls }}{"name": "{{ .Function.Name }}", "arguments": {{ json .Function.Arguments }}}
{{- end }}]</s>
{{- end }}
{{- else if eq .Role "tool" }}[TOOL_RESULTS] {"content": {{ .Content }}}[/TOOL_RESULTS]
{{- end }}
{{- end }}
```
### Example Fill-in-Middle
Fill-in-middle support can be added to a model by adding a `{{ .Suffix }}` node to the template. This feature is useful for models that are trained to generate text in the middle of user input, such as code completion models.
#### CodeLlama
CodeLlama [7B](https://ollama.com/library/codellama:7b-code) and [13B](https://ollama.com/library/codellama:13b-code) code completion models support fill-in-middle.
```gotmpl
<PRE> {{ .Prompt }} <SUF>{{ .Suffix }} <MID>
```
> [!NOTE]
> CodeLlama 34B and 70B code completion and all instruct and Python fine-tuned models do not support fill-in-middle.
#### Codestral
Codestral [22B](https://ollama.com/library/codestral:22b) supports fill-in-middle.
```gotmpl
[SUFFIX]{{ .Suffix }}[PREFIX] {{ .Prompt }}
```

View File

@@ -8,6 +8,7 @@ import (
"io"
"log/slog"
"math"
"math/rand/v2"
"net/http"
"net/url"
"os"
@@ -43,17 +44,19 @@ type blobDownload struct {
context.CancelFunc
done bool
done chan struct{}
err error
references atomic.Int32
}
type blobDownloadPart struct {
N int
Offset int64
Size int64
Completed int64
lastUpdated time.Time
N int
Offset int64
Size int64
Completed atomic.Int64
lastUpdatedMu sync.Mutex
lastUpdated time.Time
*blobDownload `json:"-"`
}
@@ -71,7 +74,7 @@ func (p *blobDownloadPart) Name() string {
}
func (p *blobDownloadPart) StartsAt() int64 {
return p.Offset + p.Completed
return p.Offset + p.Completed.Load()
}
func (p *blobDownloadPart) StopsAt() int64 {
@@ -81,7 +84,9 @@ func (p *blobDownloadPart) StopsAt() int64 {
func (p *blobDownloadPart) Write(b []byte) (n int, err error) {
n = len(b)
p.blobDownload.Completed.Add(int64(n))
p.lastUpdatedMu.Lock()
p.lastUpdated = time.Now()
p.lastUpdatedMu.Unlock()
return n, nil
}
@@ -91,6 +96,8 @@ func (b *blobDownload) Prepare(ctx context.Context, requestURL *url.URL, opts *r
return err
}
b.done = make(chan struct{})
for _, partFilePath := range partFilePaths {
part, err := b.readPart(partFilePath)
if err != nil {
@@ -98,7 +105,7 @@ func (b *blobDownload) Prepare(ctx context.Context, requestURL *url.URL, opts *r
}
b.Total += part.Size
b.Completed.Add(part.Completed)
b.Completed.Add(part.Completed.Load())
b.Parts = append(b.Parts, part)
}
@@ -138,9 +145,36 @@ func (b *blobDownload) Prepare(ctx context.Context, requestURL *url.URL, opts *r
}
func (b *blobDownload) Run(ctx context.Context, requestURL *url.URL, opts *registryOptions) {
defer close(b.done)
b.err = b.run(ctx, requestURL, opts)
}
func newBackoff(maxBackoff time.Duration) func(ctx context.Context) error {
var n int
return func(ctx context.Context) error {
if ctx.Err() != nil {
return ctx.Err()
}
n++
// n^2 backoff timer is a little smoother than the
// common choice of 2^n.
d := min(time.Duration(n*n)*10*time.Millisecond, maxBackoff)
// Randomize the delay between 0.5-1.5 x msec, in order
// to prevent accidental "thundering herd" problems.
d = time.Duration(float64(d) * (rand.Float64() + 0.5))
t := time.NewTimer(d)
defer t.Stop()
select {
case <-ctx.Done():
return ctx.Err()
case <-t.C:
return nil
}
}
}
func (b *blobDownload) run(ctx context.Context, requestURL *url.URL, opts *registryOptions) error {
defer blobDownloadManager.Delete(b.Digest)
ctx, b.CancelFunc = context.WithCancel(ctx)
@@ -153,11 +187,57 @@ func (b *blobDownload) run(ctx context.Context, requestURL *url.URL, opts *regis
_ = file.Truncate(b.Total)
directURL, err := func() (*url.URL, error) {
ctx, cancel := context.WithTimeout(ctx, 30*time.Second)
defer cancel()
backoff := newBackoff(10 * time.Second)
for {
// shallow clone opts to be used in the closure
// without affecting the outer opts.
newOpts := new(registryOptions)
*newOpts = *opts
newOpts.CheckRedirect = func(req *http.Request, via []*http.Request) error {
if len(via) > 10 {
return errors.New("maxium redirects exceeded (10) for directURL")
}
// if the hostname is the same, allow the redirect
if req.URL.Hostname() == requestURL.Hostname() {
return nil
}
// stop at the first redirect that is not
// the same hostname as the original
// request.
return http.ErrUseLastResponse
}
resp, err := makeRequestWithRetry(ctx, http.MethodGet, requestURL, nil, nil, newOpts)
if err != nil {
slog.Warn("failed to get direct URL; backing off and retrying", "err", err)
if err := backoff(ctx); err != nil {
return nil, err
}
continue
}
defer resp.Body.Close()
if resp.StatusCode != http.StatusTemporaryRedirect {
return nil, fmt.Errorf("unexpected status code %d", resp.StatusCode)
}
return resp.Location()
}
}()
if err != nil {
return err
}
g, inner := errgroup.WithContext(ctx)
g.SetLimit(numDownloadParts)
for i := range b.Parts {
part := b.Parts[i]
if part.Completed == part.Size {
if part.Completed.Load() == part.Size {
continue
}
@@ -165,7 +245,7 @@ func (b *blobDownload) run(ctx context.Context, requestURL *url.URL, opts *regis
var err error
for try := 0; try < maxRetries; try++ {
w := io.NewOffsetWriter(file, part.StartsAt())
err = b.downloadChunk(inner, requestURL, w, part, opts)
err = b.downloadChunk(inner, directURL, w, part)
switch {
case errors.Is(err, context.Canceled), errors.Is(err, syscall.ENOSPC):
// return immediately if the context is canceled or the device is out of space
@@ -206,29 +286,31 @@ func (b *blobDownload) run(ctx context.Context, requestURL *url.URL, opts *regis
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 {
func (b *blobDownload) downloadChunk(ctx context.Context, requestURL *url.URL, w io.Writer, part *blobDownloadPart) error {
g, ctx := errgroup.WithContext(ctx)
g.Go(func() error {
headers := make(http.Header)
headers.Set("Range", fmt.Sprintf("bytes=%d-%d", part.StartsAt(), part.StopsAt()-1))
resp, err := makeRequestWithRetry(ctx, http.MethodGet, requestURL, headers, nil, opts)
req, err := http.NewRequestWithContext(ctx, "GET", requestURL.String(), nil)
if err != nil {
return err
}
req.Header.Set("Range", fmt.Sprintf("bytes=%d-%d", part.StartsAt(), part.StopsAt()-1))
resp, err := http.DefaultClient.Do(req)
if err != nil {
return err
}
defer resp.Body.Close()
n, err := io.CopyN(w, io.TeeReader(resp.Body, part), part.Size-part.Completed)
n, err := io.CopyN(w, io.TeeReader(resp.Body, part), part.Size-part.Completed.Load())
if err != nil && !errors.Is(err, context.Canceled) && !errors.Is(err, io.ErrUnexpectedEOF) {
// rollback progress
b.Completed.Add(-n)
return err
}
part.Completed += n
part.Completed.Add(n)
if err := b.writePart(part.Name(), part); err != nil {
return err
}
@@ -242,15 +324,21 @@ func (b *blobDownload) downloadChunk(ctx context.Context, requestURL *url.URL, w
for {
select {
case <-ticker.C:
if part.Completed >= part.Size {
if part.Completed.Load() >= part.Size {
return nil
}
if !part.lastUpdated.IsZero() && time.Since(part.lastUpdated) > 5*time.Second {
part.lastUpdatedMu.Lock()
lastUpdated := part.lastUpdated
part.lastUpdatedMu.Unlock()
if !lastUpdated.IsZero() && time.Since(lastUpdated) > 5*time.Second {
const msg = "%s part %d stalled; retrying. If this persists, press ctrl-c to exit, then 'ollama pull' to find a faster connection."
slog.Info(fmt.Sprintf(msg, b.Digest[7:19], part.N))
// reset last updated
part.lastUpdatedMu.Lock()
part.lastUpdated = time.Time{}
part.lastUpdatedMu.Unlock()
return errPartStalled
}
case <-ctx.Done():
@@ -315,6 +403,8 @@ func (b *blobDownload) Wait(ctx context.Context, fn func(api.ProgressResponse))
ticker := time.NewTicker(60 * time.Millisecond)
for {
select {
case <-b.done:
return b.err
case <-ticker.C:
fn(api.ProgressResponse{
Status: fmt.Sprintf("pulling %s", b.Digest[7:19]),
@@ -322,10 +412,6 @@ func (b *blobDownload) Wait(ctx context.Context, fn func(api.ProgressResponse))
Total: b.Total,
Completed: b.Completed.Load(),
})
if b.done || b.err != nil {
return b.err
}
case <-ctx.Done():
return ctx.Err()
}

View File

@@ -54,6 +54,8 @@ type registryOptions struct {
Username string
Password string
Token string
CheckRedirect func(req *http.Request, via []*http.Request) error
}
type Model struct {
@@ -1131,7 +1133,9 @@ func makeRequest(ctx context.Context, method string, requestURL *url.URL, header
req.ContentLength = contentLength
}
resp, err := http.DefaultClient.Do(req)
resp, err := (&http.Client{
CheckRedirect: regOpts.CheckRedirect,
}).Do(req)
if err != nil {
return nil, err
}