Create app2.py

app2.py

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+# AYesha — DDS Enterprise HR Chatbot (Hugging Face Space / Render)
+# !pip install -U "gradio>=6.28" spaces pinecone llama-index llama-index-vector-stores-pinecone llama-index-readers-file pypdf llama-index-llms-openai llama-index-embeddings-openai
+
+# --- Imports ---
+import logging
+import os
+import sys
+
+import gradio as gr
+import spaces
+
+from pinecone import Pinecone, ServerlessSpec
+from llama_index.core import (
+    VectorStoreIndex,
+    SimpleDirectoryReader,
+    StorageContext,
+    Settings,
+    PromptTemplate,
+)
+from llama_index.vector_stores.pinecone import PineconeVectorStore
+from llama_index.readers.file import PDFReader
+from llama_index.llms.openai import OpenAI
+from llama_index.embeddings.openai import OpenAIEmbedding
+
+# --- Logging ---
+logging.basicConfig(stream=sys.stdout, level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+# --- Keys (set these in Space Settings -> Variables and secrets) ---
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+PINECONE_API_KEY = os.getenv("PINECONE_API_KEY")
+
+if not OPENAI_API_KEY:
+    raise RuntimeError("OPENAI_API_KEY is not set. Add it under Settings -> Variables and secrets.")
+if not PINECONE_API_KEY:
+    raise RuntimeError("PINECONE_API_KEY is not set. Add it under Settings -> Variables and secrets.")
+
+# --- LlamaIndex global settings ---
+Settings.llm = OpenAI(model="gpt-4o-mini", temperature=0.2)
+Settings.embed_model = OpenAIEmbedding(model="text-embedding-ada-002")
+Settings.chunk_size = 600
+Settings.chunk_overlap = 200
+
+SYSTEM_PROMPT = """You are AYesha, the Decoding Data Science (DDS) Enterprise HR Chatbot. Answer questions exclusively using the attached DDS HR Handbook. Base all responses on the most up-to-date information available in the handbook. Only respond to queries directly related to DDS HR policies as outlined in the handbook.
+Important instructions:
+- Only answer questions directly supported by the latest DDS HR handbook.
+- Decline politely and redirect to the provided email address for any questions outside scope or for confidential information.
+- Always reason before concluding. Only present the answer after checking scope and source.
+Remember: As AYesha, the DDS HR Enterprise Chatbot, you must never provide information outside authorized HR handbook content and always respond respectfully according to these constraints.
+"""
+
+# LlamaIndex's query engine doesn't accept a `system_prompt=` kwarg — that param only
+# exists on as_chat_engine(). The equivalent for a query engine is a custom QA prompt
+# template, which is what actually enforces AYesha's scope/persona.
+QA_TEMPLATE = PromptTemplate(
+    SYSTEM_PROMPT
+    + "\n\nContext information is below.\n---------------------\n{context_str}\n---------------------\n"
+    "Given the context information and not prior knowledge, answer the query.\n"
+    "Query: {query_str}\nAnswer: "
+)
+
+# --- Initialize Pinecone ---
+pc = Pinecone(api_key=PINECONE_API_KEY)
+INDEX_NAME = "quickstart"
+DIMENSION = 1536
+
+existing_indexes = [idx["name"] for idx in pc.list_indexes()]
+
+if INDEX_NAME not in existing_indexes:
+    # Only create the index the first time. Deleting + recreating on every
+    # restart re-embeds every PDF (real API cost) and risks a race if two
+    # cold starts overlap — so we only build the index when it doesn't exist yet.
+    pc.create_index(
+        name=INDEX_NAME,
+        dimension=DIMENSION,
+        metric="euclidean",
+        spec=ServerlessSpec(cloud="aws", region="us-east-1"),
+    )
+
+pinecone_index = pc.Index(INDEX_NAME)
+vector_store = PineconeVectorStore(pinecone_index=pinecone_index)
+
+# If the index is already populated (from a prior run), just attach to it.
+# Otherwise load the PDFs and build it now.
+stats = pinecone_index.describe_index_stats()
+if stats.get("total_vector_count", 0) > 0:
+    index = VectorStoreIndex.from_vector_store(vector_store)
+else:
+    documents = SimpleDirectoryReader(
+        input_dir="Data",  # folder name is case-sensitive — must match exactly what you upload
+        required_exts=[".pdf"],
+        file_extractor={".pdf": PDFReader()},
+    ).load_data()
+
+    if not documents:
+        raise ValueError(
+            "No PDF documents were loaded from the 'Data' folder. "
+            "Make sure a folder named exactly 'Data' with your PDF(s) is uploaded alongside app.py."
+        )
+
+    storage_context = StorageContext.from_defaults(vector_store=vector_store)
+    index = VectorStoreIndex.from_documents(documents, storage_context=storage_context)
+
+query_engine = index.as_query_engine(text_qa_template=QA_TEMPLATE)
+
+
+# --- Query function (logic unchanged) ---
+@spaces.GPU
+def query_doc(prompt):
+    try:
+        response = query_engine.query(prompt)
+        return str(response)
+    except Exception as e:
+        logger.exception("Query failed")
+        return f"Error: {str(e)}"
+
+
+# =====================================================================
+# UI LAYER — everything below is presentation only.
+# Every answer still comes from query_doc(prompt) exactly as before.
+# =====================================================================
+
+DDS_LOGO_URL = (
+    "https://raw.githubusercontent.com/Decoding-Data-Science/airesidency/main/"
+    "DDS%20HIGH%20RES%20Logo%20%20copywhite.png"
+)
+
+# FAQ groups shown in the sidebar. Edit these to mirror the sections of your handbook.
+FAQ_GROUPS = {
+    "Leave & time off": [
+        "How many days of annual leave am I entitled to?",
+        "What is the process for applying for sick leave?",
+        "What public holidays does DDS observe?",
+    ],
+    "Working at DDS": [
+        "What are the standard working hours?",
+        "What is the policy on remote or hybrid work?",
+        "How long is the probation period for new employees?",
+    ],
+    "Policies & process": [
+        "What is the notice period for resignation?",
+        "How do I raise a grievance or workplace concern?",
+        "What does the code of conduct cover?",
+    ],
+}
+
+
+def add_user_message(message, history):
+    """Show the user's question in the chat immediately and stash it for the answer step."""
+    message = (message or "").strip()
+    history = list(history or [])
+    if not message:
+        return "", history, ""
+    history.append({"role": "user", "content": message})
+    return "", history, message
+
+
+def add_bot_answer(pending_question, history):
+    """Run the unchanged query_doc() and append AYesha's answer."""
+    history = list(history or [])
+    if not pending_question:
+        return history
+    answer = query_doc(pending_question)
+    history.append({"role": "assistant", "content": answer})
+    return history
+
+
+def clear_chat():
+    return [], "", ""
+
+
+# --- Theme: DDS Futuristic palette ---
+dds_theme = gr.themes.Base(
+    primary_hue=gr.themes.colors.cyan,
+    secondary_hue=gr.themes.colors.violet,
+    neutral_hue=gr.themes.colors.slate,
+    font=[gr.themes.GoogleFont("Inter"), "system-ui", "sans-serif"],
+    font_mono=[gr.themes.GoogleFont("JetBrains Mono"), "ui-monospace", "monospace"],
+    radius_size=gr.themes.sizes.radius_md,
+).set(
+    body_background_fill="#070b14",
+    body_background_fill_dark="#070b14",
+    body_text_color="#e2e8f0",
+    body_text_color_dark="#e2e8f0",
+    body_text_color_subdued="#94a3b8",
+    body_text_color_subdued_dark="#94a3b8",
+    background_fill_primary="#0c1322",
+    background_fill_primary_dark="#0c1322",
+    background_fill_secondary="#0a101d",
+    background_fill_secondary_dark="#0a101d",
+    block_background_fill="#0c1322",
+    block_background_fill_dark="#0c1322",
+    block_border_color="#1e293b",
+    block_border_color_dark="#1e293b",
+    block_border_width="1px",
+    block_label_text_color="#94a3b8",
+    block_label_text_color_dark="#94a3b8",
+    border_color_primary="#1e293b",
+    border_color_primary_dark="#1e293b",
+    input_background_fill="#0a101d",
+    input_background_fill_dark="#0a101d",
+    input_border_color="#243049",
+    input_border_color_dark="#243049",
+    input_border_color_focus="#22d3ee",
+    input_border_color_focus_dark="#22d3ee",
+    button_primary_background_fill="#22d3ee",
+    button_primary_background_fill_dark="#22d3ee",
+    button_primary_background_fill_hover="#67e8f9",
+    button_primary_background_fill_hover_dark="#67e8f9",
+    button_primary_text_color="#04111a",
+    button_primary_text_color_dark="#04111a",
+    button_secondary_background_fill="#111a2c",
+    button_secondary_background_fill_dark="#111a2c",
+    button_secondary_background_fill_hover="#16213a",
+    button_secondary_background_fill_hover_dark="#16213a",
+    button_secondary_text_color="#cbd5e1",
+    button_secondary_text_color_dark="#cbd5e1",
+    button_secondary_border_color="#243049",
+    button_secondary_border_color_dark="#243049",
+    color_accent_soft="#132238",
+    color_accent_soft_dark="#132238",
+)
+
+CUSTOM_CSS = """
+@import url('https://fonts.googleapis.com/css2?family=Space+Grotesk:wght@500;600;700&display=swap');
+
+.gradio-container {
+    max-width: 1240px !important;
+    margin: 0 auto !important;
+    padding: 24px 20px 12px !important;
+}
+
+/* ---------- Header ---------- */
+#dds-header {
+    display: flex;
+    align-items: center;
+    justify-content: space-between;
+    gap: 24px;
+    flex-wrap: wrap;
+    padding: 22px 28px;
+    border: 1px solid #1e293b;
+    border-top: 3px solid #22d3ee;
+    border-radius: 14px;
+    background:
+        radial-gradient(900px 220px at 100% 0%, rgba(139, 92, 246, 0.16), transparent 60%),
+        #0a101d;
+}
+#dds-header .brand {
+    display: flex;
+    align-items: center;
+    gap: 22px;
+}
+#dds-header .brand img {
+    height: 76px;
+    width: auto;
+    display: block;
+}
+#dds-header .divider {
+    width: 1px;
+    height: 48px;
+    background: #243049;
+}
+#dds-header h1 {
+    font-family: 'Space Grotesk', 'Inter', sans-serif;
+    font-size: 30px;
+    font-weight: 700;
+    letter-spacing: -0.02em;
+    margin: 0;
+    color: #f8fafc;
+    line-height: 1.1;
+}
+#dds-header p {
+    margin: 4px 0 0;
+    font-size: 14px;
+    color: #94a3b8;
+    max-width: 560px;
+}
+#dds-header .status {
+    display: flex;
+    align-items: center;
+    gap: 8px;
+    font-size: 13px;
+    color: #cbd5e1;
+    padding: 8px 14px;
+    border: 1px solid #243049;
+    border-radius: 999px;
+    background: #0c1322;
+}
+#dds-header .dot {
+    width: 8px;
+    height: 8px;
+    border-radius: 50%;
+    background: #22d3ee;
+    box-shadow: 0 0 0 4px rgba(34, 211, 238, 0.15);
+}
+
+/* ---------- Panels ---------- */
+.dds-panel {
+    border: 1px solid #1e293b !important;
+    border-radius: 14px !important;
+    background: #0a101d !important;
+    padding: 18px !important;
+}
+.dds-panel-title h3 {
+    font-family: 'Space Grotesk', 'Inter', sans-serif;
+    font-size: 16px;
+    font-weight: 600;
+    color: #f1f5f9;
+    margin: 0 0 2px;
+}
+.dds-panel-title p {
+    font-size: 13px;
+    color: #94a3b8;
+    margin: 0;
+}
+.faq-group-label p {
+    font-size: 12px;
+    font-weight: 600;
+    color: #f5a623;
+    margin: 14px 0 6px !important;
+}
+
+/* FAQ buttons read like list items, not CTAs */
+.faq-btn {
+    justify-content: flex-start !important;
+    text-align: left !important;
+    white-space: normal !important;
+    font-weight: 400 !important;
+    font-size: 13.5px !important;
+    line-height: 1.4 !important;
+    padding: 10px 12px !important;
+    border-left: 2px solid #243049 !important;
+}
+.faq-btn:hover {
+    border-left-color: #22d3ee !important;
+    color: #f8fafc !important;
+}
+
+.scope-note {
+    margin-top: 16px;
+    padding: 12px 14px;
+    border: 1px solid #2a2140;
+    border-left: 3px solid #8b5cf6;
+    border-radius: 10px;
+    background: #0f0c1d;
+    font-size: 13px;
+    color: #c4b5fd;
+    line-height: 1.5;
+}
+
+/* ---------- Chat ---------- */
+#dds-chat {
+    border: 1px solid #1e293b !important;
+    border-radius: 12px !important;
+    background: #070b14 !important;
+}
+#dds-input textarea {
+    font-size: 15px !important;
+}
+#send-btn {
+    font-weight: 600 !important;
+    min-height: 44px;
+}
+
+/* ---------- Footer ---------- */
+#dds-footer {
+    text-align: center;
+    font-size: 12.5px;
+    color: #64748b;
+    padding: 18px 0 4px;
+    border-top: 1px solid #1e293b;
+    margin-top: 8px;
+}
+#dds-footer a {
+    color: #22d3ee;
+    text-decoration: none;
+}
+
+footer { display: none !important; }
+
+@media (max-width: 768px) {
+    #dds-header { padding: 18px; }
+    #dds-header .divider { display: none; }
+    #dds-header .brand { flex-direction: column; align-items: flex-start; gap: 12px; }
+    #dds-header h1 { font-size: 24px; }
+}
+"""
+
+HEADER_HTML = f"""
+<div id="dds-header">
+  <div class="brand">
+    <img src="{DDS_LOGO_URL}" alt="Decoding Data Science">
+    <div class="divider"></div>
+    <div>
+      <h1>AYesha</h1>
+      <p>The DDS Enterprise HR assistant. Answers come only from the current DDS HR Handbook.</p>
+    </div>
+  </div>
+  <div class="status"><span class="dot"></span>Handbook connected</div>
+</div>
+"""
+
+FOOTER_HTML = """
+<div id="dds-footer">
+  Built by <a href="https://decodingdatascience.com" target="_blank" rel="noopener">Decoding Data Science</a>
+  &nbsp;|&nbsp; Answers are generated from the DDS HR Handbook. Always confirm critical decisions with HR.
+</div>
+"""
+
+CHAT_PLACEHOLDER = """
+<div style="text-align:center; padding: 40px 16px;">
+  <h3 style="font-family:'Space Grotesk',Inter,sans-serif; font-size:20px; color:#f1f5f9; margin:0 0 8px;">
+    Ask AYesha about DDS HR policy
+  </h3>
+  <p style="color:#94a3b8; font-size:14px; margin:0;">
+    Type a question below, or pick one from the common questions on the left.
+  </p>
+</div>
+"""
+
+
+with gr.Blocks(title="AYesha | DDS Enterprise HR Chatbot", fill_height=False) as demo:
+    pending_question = gr.State("")
+
+    gr.HTML(HEADER_HTML)
+
+    with gr.Row(equal_height=False):
+        # ---------- Sidebar: FAQ ----------
+        with gr.Column(scale=4, min_width=280, elem_classes="dds-panel"):
+            gr.Markdown(
+                "### Common questions\nClick any question to ask it instantly.",
+                elem_classes="dds-panel-title",
+            )
+            faq_buttons = []
+            for group_name, questions in FAQ_GROUPS.items():
+                gr.Markdown(group_name, elem_classes="faq-group-label")
+                for q in questions:
+                    faq_buttons.append(
+                        gr.Button(q, variant="secondary", size="sm", elem_classes="faq-btn")
+                    )
+            gr.HTML(
+                '<div class="scope-note">AYesha only answers from the DDS HR Handbook. '
+                "For confidential matters or anything the handbook does not cover, "
+                "please contact the DDS HR team directly.</div>"
+            )
+
+        # ---------- Main: Chat ----------
+        with gr.Column(scale=8, min_width=360, elem_classes="dds-panel"):
+            chatbot = gr.Chatbot(
+                elem_id="dds-chat",
+                label="Conversation",
+                show_label=False,
+                height=520,
+                placeholder=CHAT_PLACEHOLDER,
+                buttons=["copy"],
+                feedback_options=None,
+                layout="bubble",
+            )
+            with gr.Row(equal_height=True):
+                msg = gr.Textbox(
+                    elem_id="dds-input",
+                    placeholder="e.g. How many days of annual leave do I get?",
+                    show_label=False,
+                    lines=1,
+                    max_lines=4,
+                    scale=8,
+                    autofocus=True,
+                )
+                send_btn = gr.Button("Ask AYesha", variant="primary", scale=2, elem_id="send-btn")
+            with gr.Row():
+                gr.HTML("")
+                clear_btn = gr.Button("Clear conversation", variant="secondary", size="sm", scale=0, min_width=180)
+
+    gr.HTML(FOOTER_HTML)
+
+    # ---------- Events ----------
+    # Step 1 shows the question instantly; step 2 calls query_doc() for the answer.
+    for trigger in (msg.submit, send_btn.click):
+        trigger(
+            add_user_message,
+            inputs=[msg, chatbot],
+            outputs=[msg, chatbot, pending_question],
+            queue=False,
+        ).then(
+            add_bot_answer,
+            inputs=[pending_question, chatbot],
+            outputs=[chatbot],
+        )
+
+    # A button passed as an input sends its own label, i.e. the FAQ question text.
+    for btn in faq_buttons:
+        btn.click(
+            add_user_message,
+            inputs=[btn, chatbot],
+            outputs=[msg, chatbot, pending_question],
+            queue=False,
+        ).then(
+            add_bot_answer,
+            inputs=[pending_question, chatbot],
+            outputs=[chatbot],
+        )
+
+    clear_btn.click(clear_chat, outputs=[chatbot, msg, pending_question], queue=False)
+
+
+if __name__ == "__main__":
+    # Gradio 6: theme and css are passed to launch(), not to gr.Blocks().
+    # PORT is read so the same file runs on Hugging Face Spaces (7860) and Render ($PORT).
+    demo.queue().launch(
+        server_name="0.0.0.0",
+        server_port=int(os.getenv("PORT", 7860)),
+        theme=dds_theme,
+        css=CUSTOM_CSS,
+        favicon_path=None,
+    )