# app.py — Insurance Q&A (RAG) with Omantel logo from GitHub URL (centered top) # Minimal changes; logic preserved. Uses Pinecone + LlamaIndex + OpenAI. import os import logging import gradio as gr from pinecone import Pinecone, ServerlessSpec from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, StorageContext, Settings from llama_index.vector_stores.pinecone import PineconeVectorStore from llama_index.embeddings.openai import OpenAIEmbedding from llama_index.llms.openai import OpenAI # ===== CONFIG ===== PINECONE_API_KEY = os.getenv("PINECONE_API_KEY") OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") PINECONE_INDEX_NAME = os.getenv("PINECONE_INDEX_NAME", "dds-insurance-index") PINECONE_REGION = os.getenv("PINECONE_REGION", "us-east-1") PINECONE_CLOUD = os.getenv("PINECONE_CLOUD", "aws") EMBED_MODEL = os.getenv("EMBED_MODEL", "text-embedding-3-small") # 1536-dim LLM_MODEL = os.getenv("LLM_MODEL", "gpt-4o-mini") DATA_DIR = "data" DEFAULT_TOP_K = 4 # internal similarity_top_k (no UI control) # Omantel logo (raw GitHub URL so it renders directly) LOGO_URL = "https://raw.githubusercontent.com/Decoding-Data-Science/Omantel/main/Omantel_Logo%20(1).png" if not PINECONE_API_KEY: raise RuntimeError("Missing PINECONE_API_KEY (set it in your Space → Settings → Variables).") if not OPENAI_API_KEY: raise RuntimeError("Missing OPENAI_API_KEY (set it in your Space → Settings → Variables).") logging.basicConfig(level=logging.INFO) log = logging.getLogger("dds-space") # ===== LlamaIndex / Pinecone ===== Settings.embed_model = OpenAIEmbedding(model=EMBED_MODEL, api_key=OPENAI_API_KEY) Settings.llm = OpenAI(model=LLM_MODEL, api_key=OPENAI_API_KEY) pc = Pinecone(api_key=PINECONE_API_KEY) def ensure_index(name: str, dim: int = 1536): names = [i["name"] for i in pc.list_indexes()] if name not in names: log.info(f"Creating Pinecone index '{name}' (dim={dim})...") pc.create_index( name=name, dimension=dim, metric="cosine", spec=ServerlessSpec(cloud=PINECONE_CLOUD, region=PINECONE_REGION), ) return pc.Index(name) pinecone_index = ensure_index(PINECONE_INDEX_NAME, dim=1536) vector_store = PineconeVectorStore(pinecone_index=pinecone_index) def bootstrap_index(): if not os.path.isdir(DATA_DIR): raise RuntimeError("No 'data/' directory found. Commit your documents to data/ in the Space repo.") log.info("Loading documents from ./data ...") docs = SimpleDirectoryReader(DATA_DIR).load_data() if not docs: raise RuntimeError("No documents found in data/. Add e.g., data/insurance.pdf") log.info(f"Docs loaded: {len(docs)}. Upserting into Pinecone…") storage_ctx = StorageContext.from_defaults(vector_store=vector_store) VectorStoreIndex.from_documents(docs, storage_context=storage_ctx, show_progress=True) log.info("Index upsert complete.") bootstrap_index() def answer(query: str) -> str: if not query or not query.strip(): return "Please enter a question (or select one from the FAQ list)." index = VectorStoreIndex.from_vector_store(vector_store) engine = index.as_query_engine(similarity_top_k=DEFAULT_TOP_K) resp = engine.query(query) return str(resp) FAQS = [ "", "What benefits are covered under the policy?", "How do I file a claim and what documents are required?", "What are the exclusions and limitations?", "Is pre-authorization needed for hospitalization?", "What is the reimbursement timeline?", "How are outpatient vs inpatient services handled?", "How can I check my network hospitals/clinics?", "What is the co-pay or deductible policy?", ] def use_faq(selected_faq: str, free_text: str): prompt = (selected_faq or "").strip() or (free_text or "").strip() if not prompt: return "", "Please select a FAQ or type your question." return prompt, answer(prompt) # ===== UI ===== CSS = """ .header { text-align:center; } .header img { max-height:80px; height:auto; } .title { text-align:center; font-weight:700; font-size:1.4rem; margin:6px 0 0 0; } .subnote { text-align:center; margin-top:-2px; opacity:0.8; } """ with gr.Blocks(css=CSS, theme=gr.themes.Soft()) as demo: # Centered logo + title gr.Markdown( f"""
Ask about coverage, claims, exclusions, and more — powered by LlamaIndex + Pinecone
""" ) with gr.Row(): with gr.Column(scale=1): gr.Markdown("### Ask from Frequently Asked Questions") faq = gr.Dropdown(choices=FAQS, value=FAQS[0], label="Select a common question") gr.Markdown("### Or type your question") user_q = gr.Textbox( label="Your question", placeholder="e.g., What is covered under outpatient benefits?", lines=2 ) ask_btn = gr.Button("Ask", variant="primary") with gr.Column(scale=1): chosen_prompt = gr.Textbox(label="Query sent", interactive=False) answer_box = gr.Markdown() ask_btn.click(use_faq, inputs=[faq, user_q], outputs=[chosen_prompt, answer_box]) if __name__ == "__main__": demo.launch()