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PathFinder is a simple prompting library with support for parsing and regex.

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PathFinder

The pathfinder library is a prompting library, that wraps around the most common LLM inference backends (OpenAI, Azure OpenAI, Anthropic, Mistral, OpenRouter, transformers library and vllm) and allows for easy inference with LLMs.

Development Notes

I'm building this library to be as modular as possible, so that it can be easily extended to support new models and new backends. Currently the supported models are hardcode in pathfinder/library/loader.py, but I'm planning to remove this and make the library more dynamic.

This is a work in progress, so expect breaking changes in the way a model is initialized. Nevertheless, this library helped me a lot in my research, especially in GovSim (Governance of the Commons Simulation), so I'm sharing it as separate project in the hope that it can help others as well.

Supported LLMs

In principle, any LLM model can be used. We support the following families of models:

APIs:

  • OpenAI: gpt-4-turbo-2024-04-09, gpt-3.5-turbo-0125, gpt-4o-2024-05-13
  • Anthropic: claude-3-opus-20240229, claude-3-sonnet-20240229, claude-3-haiku-20240307
  • Mistral (API):

Open-weights models:

  • Mistral: mistralai/Mistral-7B-Instruct-v0.2, mistralai/Mixtral-8x7B-Instruct-v0.1
  • Llama-2: meta-llama/Llama-2-7b-chat-hf, meta-llama/Llama-2-13b-chat-hf, meta-llama/Llama-2-70b-chat-hf
  • Llama-3: meta-llama/Meta-Llama-3-8B-Instruct, meta-llama/Meta-Llama-3-70B-Instruct
  • Qwen-1.5: Qwen/Qwen1.5-72B-Chat-GPTQ-Int4, Qwen/Qwen1.5-110B-Chat-GPTQ-Int4
  • Phi-3: microsoft/Phi-3-medium-4k-instruct
  • Vicuna
  • Cohere

Documentation

More documentation & examples coming soon.

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PathFinder is a simple prompting library with support for parsing and regex.

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