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Nice this made me go back and check up on the Gorilla LLM project [1] to see whats they are doing with API and if they have applied their fine tuning to any of
by jimmySixDOF 3y ago
Nice this made me go back and check up on the Gorilla LLM project [1] to see whats they are doing with API and if they have applied their fine tuning to any of the newer foundation models but looks like things have slowed down since they launched (?) or maybe development is happening elsewhere on some invisible discord channel but I hope the intersection of API calling and LLM as a logic processing function keep getting focus it's an important direction for interop across the web.
[1] https://github.com/ShishirPatil/gorilla https://github.com/ShishirPatil/gorilla
- quan 3y agoI open sourced this tool that takes OpenAPI spec and let you control API using natural language https://github.com/mquan/api2ai https://github.com/mquan/api2ai Let me know if you have any questions or feature request
- ushakov 3y agoHow is this different from what LangChain already offers with their OpenAPI chain? https://python.langchain.com/docs/use_cases/apis https://python.langchain.com/docs/use_cases/apis
- quan 3y agoafaik, the langchain solution loads entire openAPI spec which consumes a lot of token and won't work for many large API. For efficient token usage, api2ai divides the task into two steps: api planning and params parsing. First step takes a summarization of all the endpoints. Once the endpoint is known, we parse params using the schema of the selected endpoint.