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View Code? Open in Web Editor NEWText to Python Objects via a LLM Function Call
License: Apache License 2.0
Text to Python Objects via a LLM Function Call
License: Apache License 2.0
Check and confirm if the GPT4 tokeniser is same as gpt2? From what I recall, this is wrong. The tokeniser depends on the LLM.
Originally posted by @NirantK in #8 (comment)
See this gist for sample implementations
Reference for how they are used: https://colab.research.google.com/drive/14M4F4FP4NNmSMLOK8aOxfm3MYgj5vNv5?usp=sharing
#6 depends on this
Use: https://github.com/Unstructured-IO/unstructured
For reference, look at how SQLite Utils are organised. These are optional and someone not using them — never needs to care about them
Desired Workflow: Someone points to a pdf file → we read it → chunk it with context → convert to a JSON/Python object
Problem Motivation: Albus
Remember to mark this as an optional dependency in pyproject.toml
We should default to infinite max_history_tokens
to be backward compatible.
Originally posted by @NirantK in #8 (comment)
Hey, Nirant,
I ran the following as pr the README.md file:
from agentai.api import chat_complete, chat_complete_execute_fn
from agentai.openai_function import tool, ToolRegistry
from agentai.conversation import Conversation
from enum import Enum
weather_registry = ToolRegistry()
Looks like openai_function is not found. This could be because in the updated agentai folder, there is no module named openai_function. Please look into that. Thanks
I believe the openai_function has been moved to annotations from which tool and tool registry can be imported as per the google colab notebook.
In addition to unstructured, have Azure Form Recognizer as an optional dependency. That has great pdf extraction and something I'd like to use more often
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