Jeremy Live
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0e57fc2
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Parent(s):
e41b0d8
Revert "memory1"
Browse filesThis reverts commit 08978902f6e581f2dfd9fa1ab8057890d1e3a0a5.
app.py
CHANGED
@@ -291,10 +291,8 @@ def create_agent(llm, db_connection, *, run_test: bool = True):
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# test_result = agent.run(test_query)
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# logger.info(f"Agent test query successful: {str(test_result)[:200]}...")
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# except Exception as e:
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# logger.warning(
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#
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# )
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# Continue even if test fails, as it might be due to model limitations
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logger.info("SQL agent created successfully")
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return agent, ""
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@@ -490,7 +488,6 @@ def convert_to_messages_format(chat_history):
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return []
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messages = []
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-
prev_messages = []
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# If the first element is a list, assume it's in the old format
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if isinstance(chat_history[0], list):
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@@ -525,13 +522,9 @@ async def stream_agent_response(question: str, chat_history: List[List[str]], se
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# Add previous chat history in the correct format for the agent
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for msg_pair in chat_history:
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if len(msg_pair) >= 1 and msg_pair[0]: # User message
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-
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messages.append(hm)
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prev_messages.append(hm)
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if len(msg_pair) >= 2 and msg_pair[1]: # Assistant message
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-
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messages.append(am)
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prev_messages.append(am)
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# Add current user's question
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user_message = HumanMessage(content=question)
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@@ -571,11 +564,7 @@ async def stream_agent_response(question: str, chat_history: List[List[str]], se
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# Execute the agent with proper error handling
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try:
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# Let the agent use its memory; don't pass raw chat_history
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-
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response = await active_agent.ainvoke({
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"input": question,
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"chat_history": prev_messages,
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})
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logger.info(f"Agent response type: {type(response)}")
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logger.info(f"Agent response content: {str(response)[:500]}...")
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@@ -665,10 +654,7 @@ async def stream_agent_response(question: str, chat_history: List[List[str]], se
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"Devuelve SOLO la consulta SQL en un bloque ```sql``` para responder a: "
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f"{question}. No incluyas explicaci贸n ni texto adicional."
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)
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sql_only_resp = await active_agent.ainvoke({
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"input": sql_only_prompt,
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"chat_history": prev_messages,
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})
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sql_only_text = str(sql_only_resp)
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sql_query2 = extract_sql_query(sql_only_text)
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if sql_query2 and looks_like_sql(sql_query2):
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# test_result = agent.run(test_query)
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# logger.info(f"Agent test query successful: {str(test_result)[:200]}...")
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# except Exception as e:
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# logger.warning(f"Agent test query failed (this might be expected): {str(e)}")
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# # Continue even if test fails, as it might be due to model limitations
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logger.info("SQL agent created successfully")
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return agent, ""
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return []
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messages = []
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# If the first element is a list, assume it's in the old format
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if isinstance(chat_history[0], list):
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# Add previous chat history in the correct format for the agent
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for msg_pair in chat_history:
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if len(msg_pair) >= 1 and msg_pair[0]: # User message
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messages.append(HumanMessage(content=msg_pair[0]))
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if len(msg_pair) >= 2 and msg_pair[1]: # Assistant message
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messages.append(AIMessage(content=msg_pair[1]))
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# Add current user's question
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user_message = HumanMessage(content=question)
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# Execute the agent with proper error handling
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try:
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# Let the agent use its memory; don't pass raw chat_history
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response = await active_agent.ainvoke({"input": question})
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logger.info(f"Agent response type: {type(response)}")
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logger.info(f"Agent response content: {str(response)[:500]}...")
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"Devuelve SOLO la consulta SQL en un bloque ```sql``` para responder a: "
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f"{question}. No incluyas explicaci贸n ni texto adicional."
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)
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sql_only_resp = await active_agent.ainvoke({"input": sql_only_prompt})
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sql_only_text = str(sql_only_resp)
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sql_query2 = extract_sql_query(sql_only_text)
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if sql_query2 and looks_like_sql(sql_query2):
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