Delete csvanswer.py

csvanswer.py

@@ -1,59 +0,0 @@
-import os
-import pandas as pd
-
-from langchain_openai import ChatOpenAI
-
-from langchain.agents import AgentExecutor
-from langchain.agents.agent_types import AgentType
-from langchain_experimental.agents.agent_toolkits import create_pandas_dataframe_agent, create_csv_agent
-
-import chainlit as cl
-
-from deep_translator import GoogleTranslator
-
-async def create_agent(filename: str):
-    """
-    Create an agent that can access and use a large language model (LLM).
-
-    Args:
-        filename: The path to the CSV file that contains the data.
-
-    Returns:
-        An agent that can access and use the LLM.
-    """
-
-    # Create an OpenAI object.
-    os.environ['OPENAI_API_KEY'] = os.environ['OPENAI_API_KEY']
-    llm = ChatOpenAI(temperature=0, model="gpt-4o-2024-05-13")
-
-    # Read the CSV file into a Pandas DataFrame.
-    df = pd.read_csv(filename)
-
-    # Create a Pandas DataFrame agent.
-    return create_csv_agent(llm, filename, verbose=False, allow_dangerous_code=True, handle_parsing_errors=True, agent_type=AgentType.OPENAI_FUNCTIONS)
-
-
-async def LLMAnswer(msg):
-    agent = await create_agent("./public/surveyia.csv")
-    cb = cl.AsyncLangchainCallbackHandler()
-    try:
-        res = await agent.acall("Réponds en langue française à la question suivante : " + msg, callbacks=[cb])
-        await cl.Message(author="COPILOT",content=GoogleTranslator(source='auto', target='fr').translate(res['output'])).send()
-    except ValueError as e:
-        res = str(e)
-        resArray = res.split(":")
-        ans = ''
-        if str(res).find('parsing') != -1:
-            for i in range(2,len(resArray)):
-                ans += resArray[i]
-            await cl.Message(author="COPILOT",content=ans.replace("`","")).send()
-        else:
-            await cl.Message(author="COPILOT",content="Reformulez votre requête, s'il vous plait 😃").send()
-    # Query the agent.
-    #response = query_agent(agent=agent, query=message.content)
-    # Decode the response.
-    #decoded_response = decode_response(response)
-
-    # Write the response to the Streamlit app.
-    #result = write_response(decoded_response)   
-    #await cl.Message(author="COPILOT",content=GoogleTranslator(source='auto', target='fr').translate(result)).send()