app.py

import gradio as gr
import os
from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, Settings
from llama_index.embeddings.huggingface import HuggingFaceEmbedding

# ✅ Access OpenAI API Key
openai_api_key = os.environ.get("OPENAI_API_KEY")
if not openai_api_key:
    raise ValueError("❌ OPENAI_API_KEY not found. Add it in Space settings > Secrets.")
os.environ["OPENAI_API_KEY"] = openai_api_key

# ✅ Set Hugging Face Embedding globally
embed_model = HuggingFaceEmbedding(model_name="sentence-transformers/all-MiniLM-L6-v2")
Settings.embed_model = embed_model

# ✅ Load and filter documents
def load_filtered_docs(folder):
    try:
        docs = SimpleDirectoryReader(folder).load_data()
        return [doc for doc in docs if doc.text and doc.text.strip()]
    except Exception as e:
        print(f"❌ Error loading docs from {folder}: {e}")
        return []

# ✅ Load predefined document sets
pg_docs = load_filtered_docs("data/paul")
pg_index = VectorStoreIndex.from_documents(pg_docs)
pg_engine = pg_index.as_query_engine()

ins_docs = load_filtered_docs("data/insurance")
ins_index = VectorStoreIndex.from_documents(ins_docs)
ins_engine = ins_index.as_query_engine()

# ✅ Query functions
def query_pg(query):
    if not query.strip():
        return "❌ Please enter a valid question before submitting."
    try:
        return str(pg_engine.query(query))
    except Exception as e:
        return f"❌ Error: {str(e)}"

def query_ins(query):
    if not query.strip():
        return "❌ Please enter a valid question before submitting."
    try:
        return str(ins_engine.query(query))
    except Exception as e:
        return f"❌ Error: {str(e)}"

# ✅ Predefined questions
paul_questions = [
    "What is the main purpose of writing, according to Paul Graham?",
    "Why do students often struggle with writing in school?",
    "How does Paul Graham describe the relationship between writing and thinking?",
    "What is one reason Paul Graham gives for why school essays feel boring?",
    "What does Paul Graham suggest writers should focus on first?",
    "What is the link between curiosity and writing?",
    "How can one write more clearly according to Paul Graham?"
]

insurance_questions = [
    "What is insurance and why is it important?",
    "What should you check before buying insurance?",
    "What are the primary types of insurance?",
    "What is health insurance and what does it cover?",
    "How does life insurance differ from term insurance?",
    "What is the difference between premium and coverage?",
    "How is insurance regulated?"
]

# ✅ Gradio interface
def launch_interface():
    with gr.Blocks(
        title="RAG App",
        css="""
        .gradio-container {
            background-color: #e6fff7 !important;
        }
        #header-text {
            text-align: center;
            color: #2b6777;
        }
        """
    ) as demo:

        gr.Markdown("""<div id='header-text'><h1>RAG Bot with LlamaIndex (PDF + TXT)</h1></div>""")

        with gr.Tabs():
            # ✅ Tab 1: Paul Graham
            with gr.Tab("Paul Graham"):
                if os.path.exists("data/logo.png"):
                    gr.Image("data/logo.png", show_label=False, container=False, height=120)

                gr.Markdown("""
                    <div id='header-text'>
                        <h2>Paul Graham: Writing and Thinking</h2>
                        <p>Select a question or ask your own based on the essay.</p>
                    </div>
                """)

                dropdown_pg = gr.Dropdown(label="Pick a Question", choices=[""] + paul_questions, interactive=True)
                textbox_pg = gr.Textbox(label="Ask Anything", placeholder="Type your question...", lines=2)
                output_pg = gr.Textbox(label="Response", lines=10)
                submit_pg = gr.Button("Submit")
                clear_pg = gr.Button("Clear")

                def handle_pg_submit(drop_value, text_value):
                    final_query = drop_value if drop_value else text_value
                    if not final_query.strip():
                        return "❌ Please select or enter a question."
                    return query_pg(final_query)

                def handle_pg_clear():
                    return "", "", ""

                submit_pg.click(handle_pg_submit, inputs=[dropdown_pg, textbox_pg], outputs=output_pg)
                clear_pg.click(fn=handle_pg_clear, outputs=[dropdown_pg, textbox_pg, output_pg])

            # ✅ Tab 2: Insurance
            with gr.Tab("Insurance"):
                gr.Markdown("""
                    <div id='header-text'>
                        <h2>Understanding Insurance</h2>
                        <p>Explore key insurance concepts or ask your own questions.</p>
                    </div>
                """)

                dropdown_ins = gr.Dropdown(label="Pick a Question", choices=[""] + insurance_questions, interactive=True)
                textbox_ins = gr.Textbox(label="Ask Anything", placeholder="Type your question...", lines=2)
                output_ins = gr.Textbox(label="Response", lines=10)
                submit_ins = gr.Button("Submit")
                clear_ins = gr.Button("Clear")

                def handle_ins_submit(drop_value, text_value):
                    final_query = drop_value if drop_value else text_value
                    if not final_query.strip():
                        return "❌ Please select or enter a question."
                    return query_ins(final_query)

                def handle_ins_clear():
                    return "", "", ""

                submit_ins.click(handle_ins_submit, inputs=[dropdown_ins, textbox_ins], outputs=output_ins)
                clear_ins.click(fn=handle_ins_clear, outputs=[dropdown_ins, textbox_ins, output_ins])

            # ✅ Tab 3: Upload & Ask
            with gr.Tab("Upload & Ask"):
                gr.Markdown("""
                    <div id='header-text'>
                        <h2>Upload Your Document and Ask Questions</h2>
                        <p>Supported formats: PDF, TXT</p>
                    </div>
                """)

                upload_input = gr.File(label="Upload a document", file_types=[".pdf", ".txt"])
                user_question = gr.Textbox(label="Ask a question", placeholder="Type your question here", lines=2)
                upload_output = gr.Textbox(label="Response", lines=10)
                upload_submit = gr.Button("Submit")
                upload_clear = gr.Button("Clear")

                def handle_upload_question(file, query):
                    if not file or not query.strip():
                        return "❌ Please upload a file and enter a valid question."
                    try:
                        reader = SimpleDirectoryReader(input_files=[file.name])
                        docs = reader.load_data()
                        temp_index = VectorStoreIndex.from_documents(docs)
                        temp_engine = temp_index.as_query_engine()
                        return str(temp_engine.query(query))
                    except Exception as e:
                        return f"❌ Error: {str(e)}"

                def handle_upload_clear():
                    return None, "", ""

                upload_submit.click(fn=handle_upload_question, inputs=[upload_input, user_question], outputs=upload_output)
                upload_clear.click(fn=handle_upload_clear, outputs=[upload_input, user_question, upload_output])

    demo.launch()

# ✅ Launch app
launch_interface()