mirror of
https://github.com/lfnovo/open-notebook.git
synced 2026-05-04 14:20:36 +00:00
d7b0fff954
Creates the API layer for Open Notebook Creates a services API gateway for the Streamlit front-end Migrates the SurrealDB SDK to the official one Change all database calls to async New podcast framework supporting multiple speaker configurations Implement the surreal-commands library for async processing Improve docker image and docker-compose configurations
50 lines
1.6 KiB
Python
50 lines
1.6 KiB
Python
import asyncio
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import sqlite3
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from typing import Annotated, Optional
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from ai_prompter import Prompter
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from langchain_core.messages import SystemMessage
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from langchain_core.runnables import RunnableConfig
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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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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 = [SystemMessage(content=system_prompt)] + state.get("messages", [])
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model = asyncio.run(
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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=10000,
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)
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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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