Create app.py

app.py

@@ -0,0 +1,69 @@
+# app.py
+import os
+import logging
+import gradio as gr
+from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, StorageContext
+from llama_index.vector_stores.pinecone import PineconeVectorStore
+from pinecone import Pinecone, ServerlessSpec
+
+# Logging setup
+logging.basicConfig(level=logging.INFO)
+
+
+api_key = os.environ["PINECONE_API_KEY"]
+
+# Initialize Pinecone
+pc = Pinecone(api_key=api_key)
+index_name = "quickstart"
+dimension = 1536
+
+# Delete index if exists (optional)
+if index_name in [idx['name'] for idx in pc.list_indexes()]:
+    pc.delete_index(index_name)
+
+# Create new index
+pc.create_index(
+    name=index_name,
+    dimension=dimension,
+    metric="euclidean",
+    spec=ServerlessSpec(cloud="aws", region="us-east-1"),
+)
+
+pinecone_index = pc.Index(index_name)
+
+# Download data if not exists
+os.makedirs("data/paul_graham", exist_ok=True)
+file_path = "data/paul_graham/paul_graham_essay.txt"
+if not os.path.exists(file_path):
+    import urllib.request
+    urllib.request.urlretrieve(
+        "https://raw.githubusercontent.com/run-llama/llama_index/main/docs/docs/examples/data/paul_graham/paul_graham_essay.txt",
+        file_path
+    )
+
+# Load documents
+documents = SimpleDirectoryReader("data/paul_graham/").load_data()
+
+# Build vector index
+vector_store = PineconeVectorStore(pinecone_index=pinecone_index)
+storage_context = StorageContext.from_defaults(vector_store=vector_store)
+index = VectorStoreIndex.from_documents(documents, storage_context=storage_context)
+
+query_engine = index.as_query_engine()
+
+# Gradio UI function
+def query_doc(prompt):
+    try:
+        response = query_engine.query(prompt)
+        return str(response)
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Launch Gradio app
+gr.Interface(
+    fn=query_doc,
+    inputs=gr.Textbox(label="Ask a question about the document"),
+    outputs=gr.Textbox(label="Answer"),
+    title="Paul Graham Document QA (LlamaIndex + Pinecone)",
+    description="Ask questions based on the indexed Paul Graham essay. Powered by LlamaIndex & Pinecone."
+).launch()