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docs(proxy_server): doc cleanup

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Krrish Dholakia 2023-10-07 17:28:55 -07:00
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3
.gitignore vendored
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@ -3,4 +3,5 @@
litellm_uuid.txt
__pycache__/
bun.lockb
**/.DS_Store
**/.DS_Store
.aider*

151
docs/my-website/docs/proxy_server.md
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@ -3,38 +3,25 @@ import TabItem from '@theme/TabItem';
# OpenAI Proxy Server
CLI Tool to create a LLM Proxy Server to translate openai api calls to any non-openai model (e.g. Huggingface, TogetherAI, Ollama, etc.) 100+ models [Provider List](https://docs.litellm.ai/docs/providers).
A local, fast, and lightweight OpenAI-compatible server to call 100+ LLM APIs.
## Quick start
Call Ollama models through your OpenAI proxy.
### Start Proxy
## usage
```shell
$ pip install litellm
pip install litellm
```
```shell
$ litellm --model ollama/llama2
$ litellm --model ollama/codellama
#INFO: Uvicorn running on http://0.0.0.0:8000
#INFO: Ollama running on http://0.0.0.0:8000
```
This will host a local proxy api at: **http://0.0.0.0:8000**
### test
In a new shell, run:
```shell
$ litellm --test
```
Let's see if it works
```shell
$ curl --location 'http://0.0.0.0:8000/chat/completions' \
--header 'Content-Type: application/json' \
--data '{
"messages": [
{
"role": "user",
"content": "what do you know?"
}
],
}'
```
### Replace OpenAI Base
### replace openai base
```python
import openai
@ -145,6 +132,81 @@ $ litellm --model command-nightly
[**Jump to Code**](https://github.com/BerriAI/litellm/blob/fef4146396d5d87006259e00095a62e3900d6bb4/litellm/proxy.py#L36)
## [tutorial]: Use with Aider/AutoGen/Continue-Dev
Here's how to use the proxy to test codellama/mistral/etc. models for different github repos
```shell
pip install litellm
```
```shell
$ ollama pull codellama # OUR Local CodeLlama
$ litellm --model ollama/codellama --temperature 0.3 --max_tokens 2048
```
Implementation for different repos
<Tabs>
<TabItem value="aider" label="Aider">
```shell
$ pip install aider
$ aider --openai-api-base http://0.0.0.0:8000 --openai-api-key fake-key
```
</TabItem>
<TabItem value="continue-dev" label="ContinueDev">
Continue-Dev brings ChatGPT to VSCode. See how to [install it here](https://continue.dev/docs/quickstart).
In the [config.py](https://continue.dev/docs/reference/Models/openai) set this as your default model.
```python
default=OpenAI(
api_key="IGNORED",
model="fake-model-name",
context_length=2048,
api_base="http://your_litellm_hostname:8000"
),
```
Credits [@vividfog](https://github.com/jmorganca/ollama/issues/305#issuecomment-1751848077) for this tutorial.
</TabItem>
<TabItem value="autogen" label="AutoGen">
```python
pip install pyautogen
```
```python
from autogen import AssistantAgent, UserProxyAgent, oai
config_list=[
{
"model": "my-fake-model",
"api_base": "http://localhost:8000/v1", #litellm compatible endpoint
"api_type": "open_ai",
"api_key": "NULL", # just a placeholder
}
]
response = oai.Completion.create(config_list=config_list, prompt="Hi")
print(response) # works fine
assistant = AssistantAgent("assistant")
user_proxy = UserProxyAgent("user_proxy")
user_proxy.initiate_chat(assistant, message="Plot a chart of META and TESLA stock price change YTD.", config_list=config_list)
# fails with the error: openai.error.AuthenticationError: No API key provided.
```
Credits [@victordibia](https://github.com/microsoft/autogen/issues/45#issuecomment-1749921972) for this tutorial.
</TabItem>
</Tabs>
:::note
**Contribute** Using this server with a project? Contribute your tutorial here!
:::
## Configure Model
To save api keys and/or customize model prompt, run:
@ -207,44 +269,3 @@ This will host a ChatCompletions API at: https://api.litellm.ai/44508ad4
</TabItem>
</Tabs>
## Tutorial - using HuggingFace LLMs with aider
[Aider](https://github.com/paul-gauthier/aider) is an AI pair programming in your terminal.
But it only accepts OpenAI API Calls.
In this tutorial we'll use Aider with WizardCoder (hosted on HF Inference Endpoints).
[NOTE]: To learn how to deploy a model on Huggingface
### Step 1: Install aider and litellm
```shell
$ pip install aider-chat litellm
```
### Step 2: Spin up local proxy
Save your huggingface api key in your local environment (can also do this via .env)
```shell
$ export HUGGINGFACE_API_KEY=my-huggingface-api-key
```
Point your local proxy to your model endpoint
```shell
$ litellm \
--model huggingface/WizardLM/WizardCoder-Python-34B-V1.0 \
--api_base https://my-endpoint.huggingface.com
```
This will host a local proxy api at: **http://0.0.0.0:8000**
### Step 3: Replace openai api base in Aider
Aider lets you set the openai api base. So lets point it to our proxy instead.
```shell
$ aider --openai-api-base http://0.0.0.0:8000
```
And that's it!

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litellm/proxy/proxy_server.py
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@ -1,4 +1,4 @@
import sys, os
import sys, os, platform
sys.path.insert(
0, os.path.abspath("../..")
) # Adds the parent directory to the system path
@ -19,7 +19,7 @@ print()
import litellm
from fastapi import FastAPI, Request
from fastapi.routing import APIRouter
from fastapi.responses import StreamingResponse
from fastapi.responses import StreamingResponse, FileResponse
import json
app = FastAPI()
@ -203,4 +203,19 @@ async def chat_completion(request: Request):
print_verbose(f"response: {response}")
return response
@router.get("/ollama_logs")
async def retrieve_server_log(request: Request):
filepath = os.path.expanduser('~/.ollama/logs/server.log')
return FileResponse(filepath)
# @router.get("/ollama_logs")
# async def chat_completion(request: Request):
# if platform.system() == "Darwin":
# print("This is a MacOS system.")
# elif platform.system() == "Linux":
# print("This is a Linux system.")
# else:
# print("This is an unknown operating system.")
app.include_router(router)