🚅 LiteLLM
Call all LLM APIs using the OpenAI format [Anthropic, Huggingface, Cohere, TogetherAI, Azure, OpenAI, etc.]
LiteLLM manages
- Translating inputs to the provider's completion and embedding endpoints
- Guarantees [consistent output](https://docs.litellm.ai/docs/completion/output), text responses will always be available at `['choices'][0]['message']['content']`
- Exception mapping - common exceptions across providers are mapped to the OpenAI exception types
# Usage
```
pip install litellm
```
```python
from litellm import completion
import os
## set ENV variables
os.environ["OPENAI_API_KEY"] = "your-openai-key"
os.environ["COHERE_API_KEY"] = "your-cohere-key"
messages = [{ "content": "Hello, how are you?","role": "user"}]
# openai call
response = completion(model="gpt-3.5-turbo", messages=messages)
# cohere call
response = completion(model="command-nightly", messages=messages)
print(response)
```
## Streaming ([Docs](https://docs.litellm.ai/docs/completion/stream))
liteLLM supports streaming the model response back, pass `stream=True` to get a streaming iterator in response.
Streaming is supported for OpenAI, Azure, Anthropic, Huggingface models
```python
response = completion(model="gpt-3.5-turbo", messages=messages, stream=True)
for chunk in response:
print(chunk['choices'][0]['delta'])
# claude 2
result = completion('claude-2', messages, stream=True)
for chunk in result:
print(chunk['choices'][0]['delta'])
```
## Caching ([Docs](https://docs.litellm.ai/docs/caching/))
LiteLLM supports caching `completion()` and `embedding()` calls for all LLMs. [Hosted Cache LiteLLM API](https://docs.litellm.ai/docs/caching/caching_api)
```python
import litellm
from litellm.caching import Cache
import os
litellm.cache = Cache()
os.environ['OPENAI_API_KEY'] = ""
# add to cache
response1 = litellm.completion(
model="gpt-3.5-turbo",
messages=[{"role": "user", "content": "why is LiteLLM amazing?"}],
caching=True
)
# returns cached response
response2 = litellm.completion(
model="gpt-3.5-turbo",
messages=[{"role": "user", "content": "why is LiteLLM amazing?"}],
caching=True
)
print(f"response1: {response1}")
print(f"response2: {response2}")
```
## OpenAI Proxy Server ([Docs](https://docs.litellm.ai/docs/proxy_server))
Spin up a local server to translate openai api calls to any non-openai model (e.g. Huggingface, TogetherAI, Ollama, etc.)
This works for async + streaming as well.
```python
litellm --model
```
Running your model locally or on a custom endpoint ? Set the `--api-base` parameter [see how](https://docs.litellm.ai/docs/proxy_server)
## Supported Provider ([Docs](https://docs.litellm.ai/docs/providers))
| Provider | [Completion](https://docs.litellm.ai/docs/#basic-usage) | [Streaming](https://docs.litellm.ai/docs/completion/stream#streaming-responses) | [Async Completion](https://docs.litellm.ai/docs/completion/stream#async-completion) | [Async Streaming](https://docs.litellm.ai/docs/completion/stream#async-streaming) |
| ------------- | ------------- | ------------- | ------------- | ------------- |
| [openai](https://docs.litellm.ai/docs/providers/openai) | ✅ | ✅ | ✅ | ✅ |
| [cohere](https://docs.litellm.ai/docs/providers/cohere) | ✅ | ✅ | ✅ | ✅ |
| [anthropic](https://docs.litellm.ai/docs/providers/anthropic) | ✅ | ✅ | ✅ | ✅ |
| [replicate](https://docs.litellm.ai/docs/providers/replicate) | ✅ | ✅ | ✅ | ✅ |
| [huggingface](https://docs.litellm.ai/docs/providers/huggingface) | ✅ | ✅ | ✅ | ✅ |
| [together_ai](https://docs.litellm.ai/docs/providers/togetherai) | ✅ | ✅ | ✅ | ✅ |
| [openrouter](https://docs.litellm.ai/docs/providers/openrouter) | ✅ | ✅ | ✅ | ✅ |
| [vertex_ai](https://docs.litellm.ai/docs/providers/vertex) | ✅ | ✅ | ✅ | ✅ |
| [palm](https://docs.litellm.ai/docs/providers/palm) | ✅ | ✅ | ✅ | ✅ |
| [ai21](https://docs.litellm.ai/docs/providers/ai21) | ✅ | ✅ | ✅ | ✅ |
| [baseten](https://docs.litellm.ai/docs/providers/baseten) | ✅ | ✅ | ✅ | ✅ |
| [azure](https://docs.litellm.ai/docs/providers/azure) | ✅ | ✅ | ✅ | ✅ |
| [sagemaker](https://docs.litellm.ai/docs/providers/aws_sagemaker) | ✅ | ✅ | ✅ | ✅ |
| [bedrock](https://docs.litellm.ai/docs/providers/bedrock) | ✅ | ✅ | ✅ | ✅ |
| [vllm](https://docs.litellm.ai/docs/providers/vllm) | ✅ | ✅ | ✅ | ✅ |
| [nlp_cloud](https://docs.litellm.ai/docs/providers/nlp_cloud) | ✅ | ✅ | ✅ | ✅ |
| [aleph alpha](https://docs.litellm.ai/docs/providers/aleph_alpha) | ✅ | ✅ | ✅ | ✅ |
| [petals](https://docs.litellm.ai/docs/providers/petals) | ✅ | ✅ | ✅ | ✅ |
| [ollama](https://docs.litellm.ai/docs/providers/ollama) | ✅ | ✅ | ✅ | ✅ |
| [deepinfra](https://docs.litellm.ai/docs/providers/deepinfra) | ✅ | ✅ | ✅ | ✅ |
[**Read the Docs**](https://docs.litellm.ai/docs/)
# Contributing
To contribute: Clone the repo locally -> Make a change -> Submit a PR with the change.
Here's how to modify the repo locally:
Step 1: Clone the repo
```
git clone https://github.com/BerriAI/litellm.git
```
Step 2: Navigate into the project, and install dependencies:
```
cd litellm
poetry install
```
Step 3: Test your change:
```
cd litellm/tests # pwd: Documents/litellm/litellm/tests
pytest .
```
Step 4: Submit a PR with your changes! 🚀
- push your fork to your github repo
- submit a PR from there
[Learn more on how to make a PR](https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/proposing-changes-to-your-work-with-pull-requests/creating-a-pull-request)
# Support / talk with founders
- [Schedule Demo 👋](https://calendly.com/d/4mp-gd3-k5k/berriai-1-1-onboarding-litellm-hosted-version)
- [Community Discord 💭](https://discord.gg/wuPM9dRgDw)
- Our numbers 📞 +1 (770) 8783-106 / +1 (412) 618-6238
- Our emails ✉️ ishaan@berri.ai / krrish@berri.ai
# Why did we build this
- **Need for simplicity**: Our code started to get extremely complicated managing & translating calls between Azure, OpenAI, Cohere
# Contributors
