Update app.py

app.py

@@ -1,9 +1,6 @@
 import gradio as gr
-import chromadb
-from langchain.document_loaders import PyPDFLoader
-from langchain.text_splitter import RecursiveCharacterTextSplitter
-from uuid import uuid4
 import google.generativeai as genai
+import upload_pdf
 import re
 import os
 
@@ -14,31 +11,6 @@ GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
 genai.configure(api_key=GOOGLE_API_KEY)
 model = genai.GenerativeModel('gemini-pro')  # Load the model
 
-# Necessary imports for Gradio
-
-text_splitter = RecursiveCharacterTextSplitter(
-    chunk_size=800,
-    chunk_overlap=50
-)
-client = chromadb.PersistentClient("test")
-collection = client.create_collection("test_data")
-
-def upload_pdf(file_path):
-    loader = PyPDFLoader(file_path)
-    pages = loader.load()
-    documents = []
-    for page in pages:
-        docs = text_splitter.split_text(page.page_content)
-        for doc in docs:
-            documents.append({
-                "text": docs, "meta_data": page.metadata,
-            })
-    collection.add(
-        ids=[str(uuid4()) for _ in range(len(documents))],
-        documents=[doc['text'][0] for doc in documents],
-        metadatas=[doc['meta_data'] for doc in documents]
-    )
-    return f"PDF Uploaded Successfully. {collection.count()} chunks stored in ChromaDB"
 
 
 
@@ -58,27 +30,16 @@ def get_Answer(query):
     answer = model.generate_content(prompt).text
     return answer
 
-# # Define the Gradio interface
-# iface = gr.Interface(
-#     fn=get_Answer,
-#     inputs=gr.Textbox(lines=5, placeholder="Ask a question"),  # Textbox for query
-#     outputs="textbox",  # Display the generated answer in a textbox
-#     title="Answer Questions with Gemini-Pro",
-#     description="Ask a question and get an answer based on context from a ChromaDB collection.",
-# )
-
-# # Launch the Gradio app
-# iface.launch(debug=True,share=True)
-
-
 # Define the Gradio interface
 iface = gr.Interface(
-    fn=upload_pdf,
-    inputs=["file"],  # Specify a file input component
-    outputs="textbox",  # Display the output text in a textbox
-    title="Upload PDF to ChromaDB",
-    description="Upload a PDF file and store its text chunks in ChromaDB.",
+    fn=get_Answer,
+    inputs=gr.Textbox(lines=5, placeholder="Ask a question"),  # Textbox for query
+    outputs="textbox",  # Display the generated answer in a textbox
+    title="Answer Questions with Gemini-Pro",
+    description="Ask a question and get an answer based on context from a ChromaDB collection.",
 )
 
 # Launch the Gradio app
 iface.launch(debug=True,share=True)
+
+