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75 lines
3.1 KiB
Markdown
75 lines
3.1 KiB
Markdown
# *🚅 litellm*
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[](https://pypi.org/project/litellm/)
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[](https://pypi.org/project/litellm/0.1.1/)
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[](https://dl.circleci.com/status-badge/redirect/gh/BerriAI/litellm/tree/main)
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[](https://github.com/BerriAI/litellm)
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[](https://discord.gg/wuPM9dRgDw)
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a light package to simplify calling OpenAI, Azure, Cohere, Anthropic, Huggingface API Endpoints. It manages:
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- translating inputs to the provider's completion and embedding endpoints
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- guarantees [consistent output](https://litellm.readthedocs.io/en/latest/output/), text responses will always be available at `['choices'][0]['message']['content']`
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- exception mapping - common exceptions across providers are mapped to the [OpenAI exception types](https://help.openai.com/en/articles/6897213-openai-library-error-types-guidance)
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# usage
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Demo - https://litellm.ai/ \
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Read the docs - https://docs.litellm.ai/docs/
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## quick start
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```
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pip install litellm
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```
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```python
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from litellm import completion
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import os
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# set API keys
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os.environ['OPENAI_API_KEY'] = "<your key>"
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messages = [{ "content": "Hello, how are you?","role": "user"}]
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# openai call
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response = completion(model="gpt-3.5-turbo", messages=messages)
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# cohere call
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response = completion("command-nightly", messages)
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# azure openai call
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response = completion("chatgpt-test", messages, azure=True)
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# hugging face call
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response = completion(model="stabilityai/stablecode-completion-alpha-3b-4k", messages=messages, hugging_face=True)
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# openrouter call
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response = completion("google/palm-2-codechat-bison", messages)
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```
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Code Sample: [Getting Started Notebook](https://colab.research.google.com/drive/1gR3pY-JzDZahzpVdbGBtrNGDBmzUNJaJ?usp=sharing)
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Stable version
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```
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pip install litellm==0.1.345
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```
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## Streaming Queries
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liteLLM supports streaming the model response back, pass `stream=True` to get a streaming iterator in response.
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Streaming is supported for OpenAI, Azure, Anthropic models
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```python
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response = completion(model="gpt-3.5-turbo", messages=messages, stream=True)
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for chunk in response:
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print(chunk['choices'][0]['delta'])
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# claude 2
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result = completion('claude-2', messages, stream=True)
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for chunk in result:
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print(chunk['choices'][0]['delta'])
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```
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# support / talk with founders
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- [Our calendar 👋](https://calendly.com/d/4mp-gd3-k5k/berriai-1-1-onboarding-litellm-hosted-version)
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- [Community Discord 💭](https://discord.gg/wuPM9dRgDw)
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- Our numbers 📞 +1 (770) 8783-106 / +1 (412) 618-6238
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- Our emails ✉️ ishaan@berri.ai / krrish@berri.ai
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# why did we build this
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- **Need for simplicity**: Our code started to get extremely complicated managing & translating calls between Azure, OpenAI, Cohere
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