Delete app2.py

app2.py

@@ -1,72 +0,0 @@
-#!/usr/bin/env python3
-
-import os
-import gradio as gr
-from dotenv import load_dotenv
-import s3fs
-
-load_dotenv('myenvfile.env')
-
-os.environ['OPENAI_API_KEY'] = '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'
-os.environ['AWS_ACCESS_KEY_ID']="AKIAZOU6TJIYU64BCGHE"
-os.environ['AWS_SECRET_ACCESS_KEY']="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"
-from llama_index import GPTListIndex, GPTSimpleVectorIndex
-from langchain.agents import load_tools, Tool, initialize_agent
-from langchain.llms import OpenAI
-from langchain.agents import ZeroShotAgent, Tool, AgentExecutor
-from langchain.agents import initialize_agent, Tool
-from langchain import OpenAI, LLMChain
-from llama_index import GPTSimpleVectorIndex, SimpleDirectoryReader
-
-
-fs = s3fs.S3FileSystem(
-		key="AKIAZOU6TJIYU64BCGHE",
-		secret="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"
-	)
-
-# download the index file from S3
-with fs.open('notesinendocrinology/index.json', 'rb') as f:
-	index_data = f.read()
-	
-import json
-
-# Decode the bytes to a string using UTF-8 encoding
-index_str = index_data.decode('utf-8')
-
-# Load the JSON data into a dictionary
-index_dict = json.loads(index_str)
-
-# create a new index object and load the saved index from the downloaded file
-index = GPTSimpleVectorIndex.load_from_string(index_str)
-
-
-def querying_db(query: str):
-	response = index.query(query)
-	return response
-
-
-tools = [
-	Tool(
-		name="QueryingDB",
-		func=querying_db,
-		description="This function takes a query string as input and returns the most relevant answer from the documentation as output"
-	)
-]
-
-llm = OpenAI(temperature=0)
-
-
-def get_answer(query_string):
-	agent = initialize_agent(tools, llm, agent="zero-shot-react-description")
-	result = agent.run(query_string)
-	return result
-
-
-def qa_app(query):
-	answer = get_answer(query)
-	return answer
-
-
-inputs = gr.inputs.Textbox(label="Enter your question:")
-output = gr.outputs.Textbox(label="Answer:")
-gr.Interface(fn=qa_app, inputs=inputs, outputs=output, title="Query Answering App").launch()