55 lines
1.9 KiB
Python
55 lines
1.9 KiB
Python
"""Интерактивный RAG-агент (Qdrant + Ollama + LangChain)."""
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from __future__ import annotations
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from agent_app import build_agent, build_llm
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from knowledge_base import build_knowledge_base
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from rag_tools import add_to_knowledge_base, get_knowledge_base, search_knowledge_base
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__all__ = [
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"build_agent",
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"build_llm",
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"build_knowledge_base",
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"get_knowledge_base",
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"search_knowledge_base",
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"add_to_knowledge_base",
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"run_interactive_cli",
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]
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def run_interactive_cli() -> None:
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agent = build_agent()
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print("RAG-агент (Qdrant + Ollama). Команды: /add, /search, /quit")
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print(" /add <заголовок> | <текст>")
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print(" /search <запрос>")
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print(" или задайте вопрос агенту\n")
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while True:
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user_input = input("Вы: ").strip()
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if not user_input:
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continue
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if user_input.lower() in ("/quit", "exit", "quit", "q"):
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print("До встречи!")
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break
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if user_input.startswith("/search "):
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query = user_input[len("/search ") :].strip()
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print(search_knowledge_base.invoke({"query": query, "max_results": 5}))
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continue
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if user_input.startswith("/add "):
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payload = user_input[len("/add ") :].strip()
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if "|" not in payload:
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print("Формат: /add <заголовок> | <текст>")
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continue
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title, content = (part.strip() for part in payload.split("|", 1))
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print(add_to_knowledge_base.invoke({"content": content, "title": title}))
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continue
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result = agent.invoke({"messages": [{"role": "human", "content": user_input}]})
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answer = result["messages"][-1]
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print(f"\nАгент: {getattr(answer, 'content', answer)}\n")
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if __name__ == "__main__":
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run_interactive_cli()
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