Update app.py

app.py

@@ -36,6 +36,33 @@ pc = Pinecone(api_key=os.environ['PINECONE_API_KEY'])
 # Define index name and parameters
 index_name = "italy-kg"
 vectorstore = PineconeVectorStore(index_name=index_name, embedding=embeddings)
+
+#Dynamic Pinecone Creation
+
+# Function to initialize Pinecone dynamically and create index if it doesn't exist
+def init_pinecone(api_key, index_name):
+    pinecone.init(api_key=api_key, environment="us-east-1")
+    pc = Pinecone(api_key=api_key)
+    
+    # Check if index exists, create if not
+    if index_name not in pc.list_indexes():
+        pc.create_index(
+            name=index_name,
+            dimension=1536,
+            metric="cosine",
+            spec=ServerlessSpec(
+                cloud="aws",
+                region="us-east-1"
+            ),
+            deletion_protection="disabled"
+        )
+    vectorstore = PineconeVectorStore(index_name=index_name, embedding=embeddings)
+    return vectorstore
+
+
+
+
+
 llm=OpenAI(temperature=0,openai_api_key=openai_api_key)
 
 
@@ -179,10 +206,15 @@ def process_pdf(pdf_file, uploaded_documents):
     return table_data, f"Uploaded {len(chunks)} chunks to the vector database."
 
 # Gradio Interface
-with gr.Blocks() as demo:
-    gr.Markdown("# PDF Uploader to Pinecone with Query Response")
-    
+with gr.Blocks() as demo:    
     with gr.Row():
+        with gr.Column():
+            # Add Pinecone Index and API Key fields side by side
+            pinecone_index_input = gr.Textbox(label="Pinecone Index Name", placeholder="Enter Pinecone Index Name")
+        with gr.Column():
+            pinecone_api_key_input = gr.Textbox(label="Pinecone API Key", placeholder="Enter Pinecone API Key")
+            
+    with gr.Row():         
         with gr.Column():
             response_output = gr.Textbox(label="Response:", lines=10, max_lines=10)
             query_input = gr.Textbox(label="Enter your query:")