src/agents/agent_transcript/tools.py

# from langchain_core.tools import tool
# from src.utils.helper import convert_list_context_source_to_str
# from src.utils.logger import logger
# from langchain_core.runnables import RunnableConfig
# from langchain_experimental.utilities import PythonREPL
# from langchain_community.tools import DuckDuckGoSearchRun


# duckduckgo_search = DuckDuckGoSearchRun(max_results=10, output_format="json")

# python_exec = PythonREPL()


# @tool
# def retrieve_document(query: str, config: RunnableConfig):
#     """Ưu tiên truy xuất tài liệu từ vector store nếu câu hỏi liên quan đến vai trò của chatbot.

#     Args:
#         query (str): Câu truy vấn của người dùng bằng tiếng Việt
#     Returns:
#         str: Retrieved documents
#     """
#     configuration = config.get("configurable", {})
#     bot_id = configuration.get("bot_id", None)
#     if not bot_id:
#         logger.error("Bot ID is not found")
#         return {"context_str": "", "selected_documents": [], "selected_ids": []}
#     retriever = test_rag_vector_store.as_retriever(
#         search_type="similarity_score_threshold",
#         search_kwargs={"k": 5, "score_threshold": 0.3},
#     )
#     documents = retriever.invoke(query, filter={"bot_id": bot_id})
#     selected_documents = [doc.__dict__ for doc in documents]
#     selected_ids = [doc["id"] for doc in selected_documents]
#     context_str = convert_list_context_source_to_str(documents)

#     return {
#         "context_str": context_str,
#         "selected_documents": selected_documents,
#         "selected_ids": selected_ids,
#     }


# @tool
# def python_repl(code: str):
#     """
#     A Python shell. Use this to execute python commands. Input should be a valid python command. If you want to see the output of a value, you should print it out with `print(...)`.

#     Args:
#         code (str): Python code to execute
#     Returns:
#         str: Output of the Python code
#     """
#     return python_exec.run(code)