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25d4cf1c1d
* docs(files_endpoints.md): add doc on litellm managed files * refactor: separate litellm managed file docs from `/files` docs clearer * docs(litellm_managed_files.md): add architecture diagram explaining managed files
186 lines
3.3 KiB
Markdown
186 lines
3.3 KiB
Markdown
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import TabItem from '@theme/TabItem';
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import Tabs from '@theme/Tabs';
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# Provider Files Endpoints
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Files are used to upload documents that can be used with features like Assistants, Fine-tuning, and Batch API.
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Use this to call the provider's `/files` endpoints directly, in the OpenAI format.
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## Quick Start
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- Upload a File
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- List Files
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- Retrieve File Information
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- Delete File
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- Get File Content
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<Tabs>
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<TabItem value="proxy" label="LiteLLM PROXY Server">
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1. Setup config.yaml
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```
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# for /files endpoints
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files_settings:
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- custom_llm_provider: azure
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api_base: https://exampleopenaiendpoint-production.up.railway.app
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api_key: fake-key
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api_version: "2023-03-15-preview"
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- custom_llm_provider: openai
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api_key: os.environ/OPENAI_API_KEY
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```
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2. Start LiteLLM PROXY Server
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```bash
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litellm --config /path/to/config.yaml
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## RUNNING on http://0.0.0.0:4000
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```
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3. Use OpenAI's /files endpoints
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Upload a File
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```python
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from openai import OpenAI
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client = OpenAI(
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api_key="sk-...",
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base_url="http://0.0.0.0:4000/v1"
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)
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client.files.create(
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file=wav_data,
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purpose="user_data",
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extra_body={"custom_llm_provider": "openai"}
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)
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```
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List Files
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```python
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from openai import OpenAI
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client = OpenAI(
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api_key="sk-...",
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base_url="http://0.0.0.0:4000/v1"
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)
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files = client.files.list(extra_body={"custom_llm_provider": "openai"})
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print("files=", files)
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```
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Retrieve File Information
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```python
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from openai import OpenAI
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client = OpenAI(
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api_key="sk-...",
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base_url="http://0.0.0.0:4000/v1"
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)
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file = client.files.retrieve(file_id="file-abc123", extra_body={"custom_llm_provider": "openai"})
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print("file=", file)
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```
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Delete File
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```python
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from openai import OpenAI
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client = OpenAI(
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api_key="sk-...",
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base_url="http://0.0.0.0:4000/v1"
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)
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response = client.files.delete(file_id="file-abc123", extra_body={"custom_llm_provider": "openai"})
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print("delete response=", response)
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```
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Get File Content
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```python
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from openai import OpenAI
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client = OpenAI(
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api_key="sk-...",
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base_url="http://0.0.0.0:4000/v1"
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)
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content = client.files.content(file_id="file-abc123", extra_body={"custom_llm_provider": "openai"})
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print("content=", content)
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```
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</TabItem>
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<TabItem value="sdk" label="SDK">
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**Upload a File**
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```python
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from litellm
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import os
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os.environ["OPENAI_API_KEY"] = "sk-.."
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file_obj = await litellm.acreate_file(
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file=open("mydata.jsonl", "rb"),
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purpose="fine-tune",
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custom_llm_provider="openai",
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)
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print("Response from creating file=", file_obj)
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```
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**List Files**
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```python
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files = await litellm.alist_files(
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custom_llm_provider="openai",
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limit=10
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)
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print("files=", files)
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```
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**Retrieve File Information**
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```python
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file = await litellm.aretrieve_file(
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file_id="file-abc123",
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custom_llm_provider="openai"
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)
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print("file=", file)
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```
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**Delete File**
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```python
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response = await litellm.adelete_file(
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file_id="file-abc123",
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custom_llm_provider="openai"
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)
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print("delete response=", response)
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```
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**Get File Content**
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```python
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content = await litellm.afile_content(
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file_id="file-abc123",
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custom_llm_provider="openai"
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)
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print("file content=", content)
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```
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</TabItem>
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</Tabs>
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## **Supported Providers**:
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### [OpenAI](#quick-start)
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### [Azure OpenAI](./providers/azure#azure-batches-api)
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### [Vertex AI](./providers/vertex#batch-apis)
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## [Swagger API Reference](https://litellm-api.up.railway.app/#/files)
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