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48 lines
1.4 KiB
Python
48 lines
1.4 KiB
Python
import sqlite3
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from typing import Annotated, Optional
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from langchain_core.runnables import (
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RunnableConfig,
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)
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from langgraph.checkpoint.sqlite import SqliteSaver
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from langgraph.graph import END, START, StateGraph
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from langgraph.graph.message import add_messages
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from typing_extensions import TypedDict
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from open_notebook.config import LANGGRAPH_CHECKPOINT_FILE
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from open_notebook.domain.notebook import Notebook
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from open_notebook.graphs.utils import provision_langchain_model
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from open_notebook.prompter import Prompter
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class ThreadState(TypedDict):
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messages: Annotated[list, add_messages]
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notebook: Optional[Notebook]
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context: Optional[str]
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context_config: Optional[dict]
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def call_model_with_messages(state: ThreadState, config: RunnableConfig) -> dict:
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system_prompt = Prompter(prompt_template="chat").render(data=state)
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payload = [system_prompt] + state.get("messages", [])
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model = provision_langchain_model(
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str(payload),
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config.get("configurable", {}).get("model_id"),
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"chat",
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max_tokens=2000,
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)
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ai_message = model.invoke(payload)
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return {"messages": ai_message}
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conn = sqlite3.connect(
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LANGGRAPH_CHECKPOINT_FILE,
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check_same_thread=False,
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)
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memory = SqliteSaver(conn)
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agent_state = StateGraph(ThreadState)
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agent_state.add_node("agent", call_model_with_messages)
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agent_state.add_edge(START, "agent")
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agent_state.add_edge("agent", END)
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graph = agent_state.compile(checkpointer=memory)
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