mirror of
https://github.com/hwchase17/langchain
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83 lines
3.1 KiB
Python
83 lines
3.1 KiB
Python
from __future__ import annotations
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from typing import TYPE_CHECKING, Optional
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from langchain_core.callbacks import BaseCallbackHandler
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from langchain_community.callbacks.streamlit.streamlit_callback_handler import (
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LLMThoughtLabeler as LLMThoughtLabeler,
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)
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from langchain_community.callbacks.streamlit.streamlit_callback_handler import (
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StreamlitCallbackHandler as _InternalStreamlitCallbackHandler,
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)
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if TYPE_CHECKING:
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from streamlit.delta_generator import DeltaGenerator
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def StreamlitCallbackHandler(
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parent_container: DeltaGenerator,
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*,
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max_thought_containers: int = 4,
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expand_new_thoughts: bool = True,
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collapse_completed_thoughts: bool = True,
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thought_labeler: Optional[LLMThoughtLabeler] = None,
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) -> BaseCallbackHandler:
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"""Callback Handler that writes to a Streamlit app.
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This CallbackHandler is geared towards
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use with a LangChain Agent; it displays the Agent's LLM and tool-usage "thoughts"
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inside a series of Streamlit expanders.
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Parameters
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----------
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parent_container
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The `st.container` that will contain all the Streamlit elements that the
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Handler creates.
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max_thought_containers
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The max number of completed LLM thought containers to show at once. When this
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threshold is reached, a new thought will cause the oldest thoughts to be
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collapsed into a "History" expander. Defaults to 4.
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expand_new_thoughts
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Each LLM "thought" gets its own `st.expander`. This param controls whether that
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expander is expanded by default. Defaults to True.
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collapse_completed_thoughts
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If True, LLM thought expanders will be collapsed when completed.
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Defaults to True.
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thought_labeler
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An optional custom LLMThoughtLabeler instance. If unspecified, the handler
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will use the default thought labeling logic. Defaults to None.
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Returns
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-------
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A new StreamlitCallbackHandler instance.
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Note that this is an "auto-updating" API: if the installed version of Streamlit
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has a more recent StreamlitCallbackHandler implementation, an instance of that class
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will be used.
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"""
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# If we're using a version of Streamlit that implements StreamlitCallbackHandler,
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# delegate to it instead of using our built-in handler. The official handler is
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# guaranteed to support the same set of kwargs.
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try:
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from streamlit.external.langchain import (
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StreamlitCallbackHandler as OfficialStreamlitCallbackHandler,
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)
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return OfficialStreamlitCallbackHandler(
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parent_container,
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max_thought_containers=max_thought_containers,
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expand_new_thoughts=expand_new_thoughts,
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collapse_completed_thoughts=collapse_completed_thoughts,
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thought_labeler=thought_labeler,
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)
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except ImportError:
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return _InternalStreamlitCallbackHandler(
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parent_container,
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max_thought_containers=max_thought_containers,
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expand_new_thoughts=expand_new_thoughts,
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collapse_completed_thoughts=collapse_completed_thoughts,
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thought_labeler=thought_labeler,
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)
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