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Patelcoder commited on Jul 11

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+<!DOCTYPE html>
+<html>
+<head>
+    <meta charset="utf-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <title>Story RAG Assistant (Gradio-Lite)</title>
+    <script type="module" crossorigin src="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.js"></script>
+    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@gradio/lite/dist/lite.css" />
+    <style>
+        body {
+            background-color: #0f172a;
+            color: #f8fafc;
+            font-family: 'Inter', system-ui, -apple-system, sans-serif;
+            margin: 0;
+            padding: 20px;
+        }
+    </style>
+</head>
+<body>
+    <gradio-lite>
+        <gradio-code>
+import gradio as gr
+import json
+from pyodide.http import pyfetch
+async def make_post_request(url, headers, body_dict):
+    response = await pyfetch(
+        url,
+        method="POST",
+        headers=headers,
+        body=json.dumps(body_dict)
+    )
+    if response.status != 200:
+        err_msg = await response.string()
+        raise Exception(f"Request failed with status {response.status}: {err_msg}")
+    return await response.json()
+async def get_pinecone_host(api_key, index_name):
+    # Route control plane through corsproxy.io because Pinecone blocks browser CORS
+    url = f"https://corsproxy.io/?url=https://api.pinecone.io/indexes/{index_name}"
+    response = await pyfetch(
+        url,
+        method="GET",
+        headers={
+            "Api-Key": api_key,
+            "Accept": "application/json"
+        }
+    )
+    if response.status != 200:
+        err_msg = await response.string()
+        raise Exception(f"Failed to get Pinecone index info: {err_msg}")
+    data = await response.json()
+    return data["host"]
+async def query_pinecone(api_key, host, namespace, text, top_k=4):
+    # Route data plane through corsproxy.io
+    url = f"https://corsproxy.io/?url=https://{host}/query"
+    headers = {
+        "Api-Key": api_key,
+        "Content-Type": "application/json",
+        "Accept": "application/json"
+    }
+    body = {
+        "namespace": namespace,
+        "topK": top_k,
+        "inputs": {
+            "text": text
+        },
+        "includeMetadata": True
+    }
+    data = await make_post_request(url, headers, body)
+    matches = data.get("matches", [])
+    chunks = [m["metadata"].get("chunk_text", "") for m in matches if "metadata" in m]
+    return chunks
+async def call_gemini(api_key, model_name, contents):
+    # Gemini API natively supports CORS, so we do not need a proxy for it
+    url = f"https://generativelanguage.googleapis.com/v1beta/models/{model_name}:generateContent?key={api_key}"
+    headers = {
+        "Content-Type": "application/json"
+    }
+    body = {
+        "contents": contents,
+        "generationConfig": {
+            "temperature": 0.1
+        }
+    }
+    data = await make_post_request(url, headers, body)
+    try:
+        text = data["candidates"][0]["content"]["parts"][0]["text"]
+        return text
+    except (KeyError, IndexError):
+        raise Exception(f"Failed to parse Gemini response: {json.dumps(data)}")
+async def respond(message, history, google_key, pinecone_key, pinecone_index, pinecone_ns, google_model):
+    if not google_key or not pinecone_key:
+        history.append({"role": "user", "content": message})
+        history.append({"role": "assistant", "content": "❌ Please provide both Google and Pinecone API keys in the configuration panel on the left."})
+        return "", history
+    try:
+        # 1. Fetch Pinecone Host
+        host = await get_pinecone_host(pinecone_key, pinecone_index)
+        # 2. Search Pinecone for context
+        chunks = await query_pinecone(pinecone_key, host, pinecone_ns, message)
+        # 3. Format prompt
+        sources_text = "\n\n".join(f"Source {i+1}:\n{text}" for i, text in enumerate(chunks)) if chunks else "No relevant sources found."
+        system_prompt = (
+            "You are an educational assistant answering questions about stories in uploaded documents.\n"
+            "Rules:\n"
+            "- Use ONLY facts from the retrieved sources. Never invent details.\n"
+            "- Give a direct answer in 2-4 sentences. Do not repeat the question or show your reasoning.\n"
+            "- If multiple stories appear, answer about the one most relevant to the question.\n"
+            "- If the sources do not contain the answer, say you could not find it in the document."
+        )
+        augmented_prompt = (
+            f"{system_prompt}\n\n"
+            f"Retrieved sources (answer using ONLY these):\n{sources_text}\n\n"
+            f"Question: {message}"
+        )
+        # 4. Construct conversation contents for Gemini
+        contents = []
+        for turn in history[-8:]:
+            role = "user" if turn["role"] == "user" else "model"
+            contents.append({
+                "role": role,
+                "parts": [{"text": turn["content"]}]
+            })
+        contents.append({
+            "role": "user",
+            "parts": [{"text": augmented_prompt}]
+        })
+        # 5. Call Gemini
+        response_text = await call_gemini(google_key, google_model, contents)
+        history.append({"role": "user", "content": message})
+        history.append({"role": "assistant", "content": response_text})
+        return "", history
+    except Exception as e:
+        history.append({"role": "user", "content": message})
+        history.append({"role": "assistant", "content": f"❌ Error: {str(e)}"})
+        return "", history
+# Custom WebAssembly Theme and Styling
+with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="indigo")) as demo:
+    gr.Markdown("# 📚 Static RAG Story Assistant (Gradio-Lite)")
+    gr.Markdown(
+        "This application runs **entirely inside your browser** via WebAssembly (Pyodide). "
+        "No backend server is required, and your API keys never leave your browser session (except to call Pinecone and Gemini)."
+    )
+    with gr.Row():
+        with gr.Column(scale=1):
+            gr.Markdown("### 🔑 API Configuration")
+            google_key_input = gr.Textbox(label="Google API Key", type="password", placeholder="AIzaSy...")
+            pinecone_key_input = gr.Textbox(label="Pinecone API Key", type="password", placeholder="pcsk_...")
+            pinecone_index_input = gr.Textbox(label="Pinecone Index Name", value="story-llama")
+            pinecone_ns_input = gr.Textbox(label="Pinecone Namespace", value="default")
+            google_model_input = gr.Textbox(label="Google Model", value="gemini-2.0-flash")
+        with gr.Column(scale=2):
+            chatbot = gr.Chatbot(type="messages", height=450)
+            msg_input = gr.Textbox(placeholder="Ask a question about the story...", label="Your Question")
+            with gr.Row():
+                submit_btn = gr.Button("Send", variant="primary")
+                clear_btn = gr.Button("Clear Chat")
+    submit_btn.click(
+        respond,
+        inputs=[msg_input, chatbot, google_key_input, pinecone_key_input, pinecone_index_input, pinecone_ns_input, google_model_input],
+        outputs=[msg_input, chatbot]
+    )
+    msg_input.submit(
+        respond,
+        inputs=[msg_input, chatbot, google_key_input, pinecone_key_input, pinecone_index_input, pinecone_ns_input, google_model_input],
+        outputs=[msg_input, chatbot]
+    )
+    clear_btn.click(lambda: [], None, chatbot)
+demo.launch()
+        </gradio-code>
+    </gradio-lite>
+</body>
+</html>