Create app.py

app.py

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+# Import standard libraries
+import os
+import re
+import json
+import getpass
+import logging
+
+# Import third-party libraries for web scraping, API interactions, and data processing
+import requests
+import pandas as pd
+from bs4 import BeautifulSoup
+
+# Import libraries for interacting with OpenAI and other language models
+import openai
+import llama_index
+from llama_index.llms import OpenAI
+from llama_index.embeddings import OpenAIEmbedding
+from llama_index.llms import (
+    CustomLLM,
+    CompletionResponse,
+    CompletionResponseGen,
+    LLMMetadata,
+)
+
+# Import for creating web interfaces
+import gradio as gr
+
+# Import specific utilities for news feed parsing and query processing
+from RAG_utils import NewsFeedParser, HybridRetriever, NewsQueryEngine
+
+with open('config.json') as config_file:
+    config = json.load(config_file)
+    
+# Setup logging
+logging.basicConfig(level=logging.INFO)
+openai.api_key = config['OPENAI_API_KEY']
+os.environ['OPENAI_API_KEY'] = openai.api_key
+
+
+llm = OpenAI(model="gpt-4", temperature=0.1, max_tokens=512)
+embed_model = OpenAIEmbedding()
+
+
+def chatbot(input_text):
+    # Create an instance of NewsFeedParser and process query
+    news_parser = NewsFeedParser()
+    documents = news_parser.process_and_chunk_articles(input_text)
+
+    # Initialize the query engine with the processed documents
+    pdf_query_engine = NewsQueryEngine(documents, llm, embed_model)
+    query_engine = pdf_query_engine.setup_query_engine()
+
+    # Process the query using the query engine
+    response = query_engine.query(input_text)
+    return response
+
+# Gradio interface setup
+iface = gr.Interface(
+    fn=chatbot,
+    inputs=gr.components.Textbox(lines=3, label="Enter your text:"),
+    outputs=gr.components.Textbox(lines=20, label="Answer:"),
+    title="FinWise Explorer"
+)
+
+# Launch the Gradio interface
+iface.launch(share=True)