Create csvanswer.py

csvanswer.py

@@ -0,0 +1,59 @@
+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
+
+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():
+    agent = create_agent("./public/surveyia.csv")
+    cb = cl.AsyncLangchainCallbackHandler()
+    try:
+        res = await agent.acall("Réponds en langue française à la question suivante : " + message.content, 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()