Create demo2.py

demo2.py

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+import pandas as pd
+
+import os
+import gradio as gr
+import io
+from langchain.chains.question_answering import load_qa_chain
+from langchain import PromptTemplate, LLMChain
+from langchain_experimental.agents.agent_toolkits import create_pandas_dataframe_agent
+from langchain.chat_models import ChatOpenAI
+from langchain.agents.agent_types import AgentType
+from langchain.chat_models import ChatOpenAI
+import pandas as pd
+from langchain.llms import OpenAI
+from dotenv import load_dotenv
+import google.generativeai as palm
+from langchain.llms import GooglePalm
+
+def questiondocument(user_question):
+    load_dotenv()
+    #
+    df = pd.read_excel("tour_op2.xlsx")
+    #df['Profit'] = df['Profit'].apply(lambda x: "R{:.1f}".format((x)))
+    #df['Revenue'] = df['Revenue'].apply(lambda x: "R{:.1f}".format((x)))
+    #llm = ChatOpenAI(model_name='gpt-3.5-turbo-0613', temperature=0, openai_api_key=os.getenv('OPENAI_API_KEY'))
+    llm = GooglePalm(temperature=0, google_api_key=os.environ['PALM'])
+    #agent = create_pandas_dataframe_agent(llm, df, verbose=True, agent_type=AgentType.OPENAI_FUNCTIONS)
+    agent = create_pandas_dataframe_agent(llm, df, agent="structured_chat-zero-shot-react-description", verbose=True)
+    response = agent.run(user_question)
+    return response
+
+demo = gr.Interface(
+
+    fn=questiondocument,
+    inputs=["text"],
+    outputs=["text"],
+    title="Ask BuzyHelper",
+)
+demo.launch(share=True)