565 lines
13 KiB
Markdown
565 lines
13 KiB
Markdown
# API
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## Endpoints
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- [Generate a completion](#generate-a-completion)
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- [Create a Model](#create-a-model)
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- [List Local Models](#list-local-models)
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- [Show Model Information](#show-model-information)
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- [Copy a Model](#copy-a-model)
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- [Delete a Model](#delete-a-model)
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- [Pull a Model](#pull-a-model)
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- [Push a Model](#push-a-model)
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- [Generate Embeddings](#generate-embeddings)
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## Conventions
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### Model names
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Model names follow a `model:tag` format. Some examples are `orca-mini:3b-q4_1` and `llama2:70b`. The tag is optional and, if not provided, will default to `latest`. The tag is used to identify a specific version.
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### Durations
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All durations are returned in nanoseconds.
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### Streaming responses
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Certain endpoints stream responses as JSON objects delineated with the newline (`\n`) character.
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## Generate a completion
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```shell
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POST /api/generate
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```
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Generate a response for a given prompt with a provided model. This is a streaming endpoint, so will be a series of responses. The final response object will include statistics and additional data from the request.
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### Parameters
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- `model`: (required) the [model name](#model-names)
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- `prompt`: the prompt to generate a response for
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Advanced parameters (optional):
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- `options`: additional model parameters listed in the documentation for the [Modelfile](./modelfile.md#valid-parameters-and-values) such as `temperature`
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- `system`: system prompt to (overrides what is defined in the `Modelfile`)
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- `template`: the full prompt or prompt template (overrides what is defined in the `Modelfile`)
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- `context`: the context parameter returned from a previous request to `/generate`, this can be used to keep a short conversational memory
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- `stream`: if `false` the response will be returned as a single response object, rather than a stream of objects
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- `raw`: if `true` no formatting will be applied to the prompt and no context will be returned. You may choose to use the `raw` parameter if you are specifying a full templated prompt in your request to the API, and are managing history yourself.
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### Examples
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#### Request
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```shell
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curl -X POST http://localhost:11434/api/generate -d '{
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"model": "llama2:7b",
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"prompt": "Why is the sky blue?"
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}'
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```
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#### Response
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A stream of JSON objects is returned:
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```json
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{
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"model": "llama2:7b",
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"created_at": "2023-08-04T08:52:19.385406455-07:00",
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"response": "The",
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"done": false
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}
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```
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The final response in the stream also includes additional data about the generation:
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- `total_duration`: time spent generating the response
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- `load_duration`: time spent in nanoseconds loading the model
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- `sample_count`: number of samples generated
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- `sample_duration`: time spent generating samples
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- `prompt_eval_count`: number of tokens in the prompt
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- `prompt_eval_duration`: time spent in nanoseconds evaluating the prompt
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- `eval_count`: number of tokens the response
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- `eval_duration`: time in nanoseconds spent generating the response
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- `context`: an encoding of the conversation used in this response, this can be sent in the next request to keep a conversational memory
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- `response`: empty if the response was streamed, if not streamed, this will contain the full response
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To calculate how fast the response is generated in tokens per second (token/s), divide `eval_count` / `eval_duration`.
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```json
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{
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"model": "llama2:7b",
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"created_at": "2023-08-04T19:22:45.499127Z",
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"response": "",
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"context": [1, 2, 3],
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"done": true,
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"total_duration": 5589157167,
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"load_duration": 3013701500,
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"sample_count": 114,
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"sample_duration": 81442000,
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"prompt_eval_count": 46,
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"prompt_eval_duration": 1160282000,
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"eval_count": 113,
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"eval_duration": 1325948000
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}
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```
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#### Request
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```shell
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curl -X POST http://localhost:11434/api/generate -d '{
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"model": "llama2:7b",
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"prompt": "Why is the sky blue?",
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"stream": false
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}'
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```
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#### Response
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If `stream` is set to `false`, the response will be a single JSON object:
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```json
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{
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"model": "llama2:7b",
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"created_at": "2023-08-04T19:22:45.499127Z",
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"response": "The sky is blue because it is the color of the sky.",
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"context": [1, 2, 3],
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"done": true,
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"total_duration": 5589157167,
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"load_duration": 3013701500,
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"sample_count": 114,
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"sample_duration": 81442000,
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"prompt_eval_count": 46,
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"prompt_eval_duration": 1160282000,
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"eval_count": 13,
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"eval_duration": 1325948000
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}
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```
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#### Request
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In some cases you may wish to bypass the templating system and provide a full prompt. In this case, you can use the `raw` parameter to disable formatting and context.
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```shell
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curl -X POST http://localhost:11434/api/generate -d '{
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"model": "mistral",
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"prompt": "[INST] why is the sky blue? [/INST]",
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"raw": true,
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"stream": false
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}'
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```
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#### Response
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```json
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{
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"model": "mistral",
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"created_at": "2023-11-03T15:36:02.583064Z",
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"response": " The sky appears blue because of a phenomenon called Rayleigh scattering.",
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"done": true,
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"total_duration": 14648695333,
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"load_duration": 3302671417,
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"prompt_eval_count": 14,
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"prompt_eval_duration": 286243000,
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"eval_count": 129,
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"eval_duration": 10931424000
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}
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```
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#### Request
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If you want to set custom options for the model at runtime rather than in the Modelfile, you can do so with the `options` parameter. This example sets every available option, but you can set any of them individually and omit the ones you do not want to override.
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```shell
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curl -X POST http://localhost:11434/api/generate -d '{
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"model": "llama2:7b",
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"prompt": "Why is the sky blue?",
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"stream": false,
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"options": {
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"num_keep": 5,
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"seed": 42,
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"num_predict": 100,
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"top_k": 20,
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"top_p": 0.9,
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"tfs_z": 0.5,
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"typical_p": 0.7,
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"repeat_last_n": 33,
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"temperature": 0.8,
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"repeat_penalty": 1.2,
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"presence_penalty": 1.5,
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"frequency_penalty": 1.0,
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"mirostat": 1,
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"mirostat_tau": 0.8,
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"mirostat_eta": 0.6,
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"penalize_newline": true,
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"stop": ["\n", "user:"],
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"numa": false,
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"num_ctx": 4,
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"num_batch": 2,
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"num_gqa": 1,
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"num_gpu": 1,
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"main_gpu": 0,
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"low_vram": false,
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"f16_kv": true,
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"logits_all": false,
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"vocab_only": false,
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"use_mmap": true,
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"use_mlock": false,
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"embedding_only": false,
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"rope_frequency_base": 1.1,
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"rope_frequency_scale": 0.8,
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"num_thread": 8
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}
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}'
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```
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#### Response
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```json
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{
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"model": "llama2:7b",
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"created_at": "2023-08-04T19:22:45.499127Z",
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"response": "The sky is blue because it is the color of the sky.",
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"context": [1, 2, 3],
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"done": true,
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"total_duration": 5589157167,
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"load_duration": 3013701500,
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"sample_count": 114,
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"sample_duration": 81442000,
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"prompt_eval_count": 46,
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"prompt_eval_duration": 1160282000,
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"eval_count": 13,
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"eval_duration": 1325948000
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}
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```
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## Create a Model
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```shell
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POST /api/create
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```
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Create a model from a [`Modelfile`](./modelfile.md)
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### Parameters
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- `name`: name of the model to create
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- `path`: path to the Modelfile
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- `stream`: (optional) if `false` the response will be returned as a single response object, rather than a stream of objects
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### Examples
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#### Request
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```shell
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curl -X POST http://localhost:11434/api/create -d '{
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"name": "mario",
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"path": "~/Modelfile"
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}'
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```
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#### Response
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A stream of JSON objects. When finished, `status` is `success`.
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```json
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{
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"status": "parsing modelfile"
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}
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```
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## List Local Models
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```shell
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GET /api/tags
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```
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List models that are available locally.
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### Examples
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#### Request
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```shell
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curl http://localhost:11434/api/tags
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```
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#### Response
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A single JSON object will be returned.
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```json
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{
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"models": [
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{
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"name": "llama2:7b",
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"modified_at": "2023-08-02T17:02:23.713454393-07:00",
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"size": 3791730596
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},
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{
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"name": "llama2:13b",
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"modified_at": "2023-08-08T12:08:38.093596297-07:00",
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"size": 7323310500
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}
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]
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}
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```
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## Show Model Information
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```shell
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POST /api/show
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```
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Show details about a model including modelfile, template, parameters, license, and system prompt.
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### Parameters
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- `name`: name of the model to show
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### Examples
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#### Request
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```shell
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curl http://localhost:11434/api/show -d '{
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"name": "llama2:7b"
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}'
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```
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#### Response
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```json
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{
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"license": "<contents of license block>",
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"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",
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"parameters": "stop [INST]\nstop [/INST]\nstop <<SYS>>\nstop <</SYS>>",
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"template": "[INST] {{ if and .First .System }}<<SYS>>{{ .System }}<</SYS>>\n\n{{ end }}{{ .Prompt }} [/INST] "
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}
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```
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## Copy a Model
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```shell
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POST /api/copy
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```
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Copy a model. Creates a model with another name from an existing model.
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### Examples
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#### Request
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```shell
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curl http://localhost:11434/api/copy -d '{
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"source": "llama2:7b",
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"destination": "llama2-backup"
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}'
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```
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#### Response
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The only response is a 200 OK if successful.
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## Delete a Model
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```shell
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DELETE /api/delete
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```
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Delete a model and its data.
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### Parameters
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- `name`: model name to delete
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### Examples
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#### Request
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```shell
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curl -X DELETE http://localhost:11434/api/delete -d '{
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"name": "llama2:13b"
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}'
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```
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#### Response
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If successful, the only response is a 200 OK.
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## Pull a Model
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```shell
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POST /api/pull
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```
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Download a model from the ollama library. Cancelled pulls are resumed from where they left off, and multiple calls will share the same download progress.
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### Parameters
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- `name`: name of the model to pull
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- `insecure`: (optional) allow insecure connections to the library. Only use this if you are pulling from your own library during development.
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- `stream`: (optional) if `false` the response will be returned as a single response object, rather than a stream of objects
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### Examples
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#### Request
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```shell
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curl -X POST http://localhost:11434/api/pull -d '{
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"name": "llama2:7b"
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}'
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```
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#### Response
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If `stream` is not specified, or set to `true`, a stream of JSON objects is returned:
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The first object is the manifest:
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```json
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{
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"status": "pulling manifest"
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}
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```
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Then there is a series of downloading responses. Until any of the download is completed, the `completed` key may not be included. The number of files to be downloaded depends on the number of layers specified in the manifest.
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```json
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{
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"status": "downloading digestname",
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"digest": "digestname",
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"total": 2142590208,
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"completed": 241970
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}
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```
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After all the files are downloaded, the final responses are:
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```json
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{
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"status": "verifying sha256 digest"
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}
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{
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"status": "writing manifest"
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}
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{
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"status": "removing any unused layers"
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}
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{
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"status": "success"
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}
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```
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if `stream` is set to false, then the response is a single JSON object:
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```json
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{
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"status": "success"
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}
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```
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## Push a Model
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```shell
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POST /api/push
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```
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Upload a model to a model library. Requires registering for ollama.ai and adding a public key first.
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### Parameters
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- `name`: name of the model to push in the form of `<namespace>/<model>:<tag>`
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- `insecure`: (optional) allow insecure connections to the library. Only use this if you are pushing to your library during development.
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- `stream`: (optional) if `false` the response will be returned as a single response object, rather than a stream of objects
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### Examples
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#### Request
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```shell
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curl -X POST http://localhost:11434/api/push -d '{
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"name": "mattw/pygmalion:latest"
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}'
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```
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#### Response
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If `stream` is not specified, or set to `true`, a stream of JSON objects is returned:
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```json
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{ "status": "retrieving manifest" }
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```
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and then:
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```json
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{
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"status": "starting upload",
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"digest": "sha256:bc07c81de745696fdf5afca05e065818a8149fb0c77266fb584d9b2cba3711ab",
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"total": 1928429856
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}
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```
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Then there is a series of uploading responses:
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```json
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{
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"status": "starting upload",
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"digest": "sha256:bc07c81de745696fdf5afca05e065818a8149fb0c77266fb584d9b2cba3711ab",
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"total": 1928429856
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}
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```
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Finally, when the upload is complete:
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```json
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{"status":"pushing manifest"}
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{"status":"success"}
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```
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If `stream` is set to `false`, then the response is a single JSON object:
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```json
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{ "status": "success" }
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```
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## Generate Embeddings
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```shell
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POST /api/embeddings
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```
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Generate embeddings from a model
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### Parameters
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- `model`: name of model to generate embeddings from
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- `prompt`: text to generate embeddings for
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Advanced parameters:
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- `options`: additional model parameters listed in the documentation for the [Modelfile](./modelfile.md#valid-parameters-and-values) such as `temperature`
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### Examples
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#### Request
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```shell
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curl -X POST http://localhost:11434/api/embeddings -d '{
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"model": "llama2:7b",
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"prompt": "Here is an article about llamas..."
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}'
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```
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#### Response
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```json
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{
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"embedding": [
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0.5670403838157654, 0.009260174818336964, 0.23178744316101074, -0.2916173040866852, -0.8924556970596313,
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0.8785552978515625, -0.34576427936553955, 0.5742510557174683, -0.04222835972905159, -0.137906014919281
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]
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}
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```
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