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| """React Agent - A simple LangChain ReAct agent for querying the podcast knowledge base. | |
| This agent uses the tools (Chroma vector search, Neo4j knowledge graph) | |
| to answer questions about the Future of Education podcast episodes. | |
| The agent includes conversation memory via a SQLite checkpointer | |
| (`.checkpoints/react_agent.sqlite`, gitignored). Pass a thread_id in config | |
| so the same conversation survives process restart: | |
| result = await react_agent.ainvoke( | |
| {"messages": [HumanMessage(content="...")]}, | |
| config={"configurable": {"thread_id": "my-thread"}} | |
| ) | |
| """ | |
| from src.react_agent.graph import get_react_agent | |
| from src.react_agent.checkpointer import get_sqlite_checkpointer | |
| from src.react_agent.configuration import Configuration | |
| from src.react_agent.tools import ( | |
| tools, | |
| search_knowledge_base, | |
| search_knowledge_base_structured, | |
| query_knowledge_graph, | |
| inspect_graph_schema, | |
| ) | |
| __all__ = [ | |
| "react_agent", | |
| "get_react_agent", | |
| "get_sqlite_checkpointer", | |
| "memory", | |
| "Configuration", | |
| "tools", | |
| "search_knowledge_base", | |
| "search_knowledge_base_structured", | |
| "query_knowledge_graph", | |
| "inspect_graph_schema", | |
| ] | |
| def __getattr__(name: str): | |
| if name in ("react_agent", "memory"): | |
| from src.react_agent import graph as _graph | |
| return getattr(_graph, name) | |
| raise AttributeError(f"module {__name__!r} has no attribute {name!r}") | |