Update app.py

app.py

@@ -1,40 +1,49 @@
+import os
+
 import streamlit as st
 import yfinance as yf
 import pandas as pd
-from langchain.agents.agent_toolkits.pandas.base import create_pandas_dataframe_agent
+from langchain.agents import create_csv_agent, AgentType
 import re
 import sqlite3
+from langchain.chat_models import ChatOpenAI
 from htmlTemplates import css, user_template, bot_template
-from typing import Optional, List, Mapping, Any
-from langchain.llms.base import LLM
-import g4f
-
-
-
-
-
-class FinLLM(LLM):
-
-    @property
-    def _llm_type(self) -> str:
-        return "custom"
-
-    def _call(self, prompt: str, stop: Optional[List[str]] = None) -> str:
-        out = g4f.ChatCompletion.create(
-            model="gpt-3.5-turbo",
-            messages=[{"role": "user", "content": prompt}],
-            temperature=0.5,  # You can adjust parameters as needed
-            max_tokens=350  # Adjust the token limit as needed
-        )  #
-        if stop:
-            stop_indexes = (out.find(s) for s in stop if s in out)
-            min_stop = min(stop_indexes, default=-1)
-            if min_stop > -1:
-                out = out[:min_stop]
-        return out
-
-
-llm = FinLLM()
+import openai
+
+# openai.api_key = os.environ("OPENAI_API_KEY")  # vLLM server is not authenticated
+os.environ['OPENAI_API_KEY'] = OPENAI_API_KEY
+
+
+llm = ChatOpenAI(
+    model='gpt-3.5-turbo',
+    max_tokens=500,
+    temperature=0.7,
+)
+
+
+#
+# class FinLLM(LLM):
+#
+#     @property
+#     def _llm_type(self) -> str:
+#         return "custom"
+#
+#     def _call(self, prompt: str, stop: Optional[List[str]] = None) -> str:
+#         out = g4f.ChatCompletion.create(
+#             model="gpt-3.5-turbo",
+#             messages=[{"role": "user", "content": prompt}],
+#             temperature=0.5,  # You can adjust parameters as needed
+#             max_tokens=350  # Adjust the token limit as needed
+#         )  #
+#         if stop:
+#             stop_indexes = (out.find(s) for s in stop if s in out)
+#             min_stop = min(stop_indexes, default=-1)
+#             if min_stop > -1:
+#                 out = out[:min_stop]
+#         return out
+#
+#
+# llm = FinLLM()
 
 def create_users_db():
     with sqlite3.connect('MASTER.db') as conn:
@@ -197,10 +206,13 @@ def main():
             if st.button("Execute") and query:
                 with st.spinner('Generating response...'):
                     try:
-                        agent = create_pandas_dataframe_agent(
+                        DF = pd.DataFrame(df)
+                        DF.to_csv('data.csv')
+                        agent = create_csv_agent(
                             llm,
-                            pd.DataFrame(df),
-                            verbose=True
+                            'data.csv',
+                            verbose=True,
+                            agent_type=AgentType.OPENAI_FUNCTIONS,
                         )
 
                         answer = agent.run(chat_prompt)