ksunamprusty/Maker_Lab_1

1import os2import gradio as gr3 4from huggingface_hub import InferenceClient5 6from langchain_text_splitters import RecursiveCharacterTextSplitter7from langchain_community.embeddings import HuggingFaceEmbeddings8from langchain_community.vectorstores import FAISS9from langchain_community.document_loaders import TextLoader10from pathlib import Path11 12import re13 14# =====================================================15# 0. Config16# =====================================================17 18HF_TOKEN = os.environ.get("Token_Key")19 20MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"  # Much better for RAG21 22# =====================================================23# 1. Load + Build Knowledge Base24# =====================================================25 26print("🔄 Reading knowledge base...")27 28folder_path = "knowledge_base"29 30documents = []31 32for file in Path(folder_path).glob("*.txt"):33    loader = TextLoader(str(file))34    documents.extend(loader.load())35 36 37print("✂️ Splitting documents...")38 39splitter = RecursiveCharacterTextSplitter(40    chunk_size=600,41    chunk_overlap=80,42)43 44documents = splitter.split_documents(documents)45 46 47print("🧠 Building embeddings...")48 49embeddings = HuggingFaceEmbeddings(50    model_name="sentence-transformers/all-mpnet-base-v2"51)52 53 54print("📦 Building vector store...")55 56db = FAISS.from_documents(documents, embeddings)57 58retriever = db.as_retriever(59    search_type="mmr",60    search_kwargs={61        "k": 2,62        "fetch_k": 863    }64)65 66 67print("✅ Knowledge base is ready!")68 69 70# =====================================================71# 2. Prompt Builder72# =====================================================73 74def clean_context(text):75    # Remove entire QUESTION/ANSWER blocks fully76    text = re.sub(r"QUESTION:.*?(?=QUESTION:|$)", "", text, flags=re.DOTALL)77 78    # Remove leftover labels if any79    text = text.replace("QUESTION:", "")80    text = text.replace("ANSWER:", "")81 82    return text.strip()83 84def build_prompt(question, docs):85 86    context = "\n\n".join(87        clean_context(d.page_content)88        for d in docs89    )90 91    prompt = f"""92You are Sunam's AI twin.93 94IMPORTANT RULES:95- Be concise, sharp, and specific.96- Answer ONLY the user's current question.97- Do NOT generate additional questions.98- Do NOT repeat information.99- Do NOT use QUESTION/ANSWER labels.100- Provide a single focused response (max 4–5 sentences).101- Use bullet points only if helpful.102- If the answer is not in context, say "I don't know."103 104CONTEXT:105{context}106 107User Question:108{question}109 110Respond below:111"""112 113    return prompt.strip()114 115 116# =====================================================117# 3. LLM Client118# =====================================================119 120client = InferenceClient(121    model=MODEL_NAME,122    token=HF_TOKEN123)124 125 126# =====================================================127# 4. Chat Function (Fixed Retriever API)128# =====================================================129 130def chat(message, history):131 132    # New LangChain API133    docs = retriever.invoke(message)134    135    prompt = build_prompt(message, docs)136 137    messages = [138        {"role": "user", "content": prompt}139    ]140 141    response = ""142 143    for chunk in client.chat_completion(144        messages=messages,145        max_tokens=500,146        temperature=0.1,147        stream=True,148    ):149 150        if chunk.choices[0].delta.content:151            token = chunk.choices[0].delta.content152            response += token153            yield response154 155 156# =====================================================157# 5. Minimal Dark UI158# =====================================================159 160custom_css = """161.header-container {162    text-align: center;163    margin-bottom: 30px;164}165 166.header-container h1 {167    font-size: 42px;168    font-weight: 700;169    color: #d97706;  /* warm orange */170    margin-bottom: 8px;171}172 173.header-container p {174    font-size: 18px;175    color: #7c2d12;  /* soft brownish orange */176    opacity: 0.85;177}178body {179    background: #0f172a !important;180}181.gradio-container {182    max-width: 900px !important;183    margin: auto !important;184}185h1 {186    color: #e5e7eb;187    text-align: center;188}189.subtitle {190    text-align: center;191    color: #9ca3af;192    margin-bottom: 20px;193}194footer {195    display: none !important;196}197/* Style the textbox */198textarea,199input[type="text"] {200    height: 52px !important;201    border-radius: 12px !important;202    padding: 12px 16px !important;203    font-size: 16px !important;204}205 206/* Style the Clear button */207button {208    height: 52px !important;209    border-radius: 12px !important;210    font-size: 16px !important;211    font-weight: 600 !important;212}213/* ===== Examples Section ===== */214 215.examples-section {216    margin-top: 25px;217    margin-bottom: 10px;218}219 220.examples-title {221    font-size: 18px;222    font-weight: 600;223    color: #b45309;224    margin-bottom: 12px;225    text-align: left;226}227 228/* Style example buttons */229.examples-section + div button,230.gradio-container .examples button {231    background-color: #fb923c !important;232    border-radius: 20px !important;233    padding: 8px 16px !important;234    font-weight: 500 !important;235    border: none !important;236    transition: all 0.2s ease-in-out !important;237}238 239/* Hover effect */240.examples-section + div button:hover,241.gradio-container .examples button:hover {242    background-color: #ea580c !important;243    transform: translateY(-2px);244    box-shadow: 0 4px 10px rgba(234, 88, 12, 0.3);245}246"""247 248 249# =====================================================250# 6. App251# =====================================================252 253with gr.Blocks(254    theme=gr.themes.Soft(255        primary_hue="amber",256        neutral_hue="orange",257    ),258    css="""259    body {260        background: linear-gradient(135deg, #FFF7ED, #FFEDD5);261    }262    263    /* Main container */264    .container {265        max-width: 850px;266        margin: auto;267        padding-top: 40px;268    }269    270    /* Title */271    .title {272        text-align: center;273        font-size: 30px;274        font-weight: 700;275        margin-bottom: 5px;276        color: #C2410C;277    }278    279    /* Subtitle */280    .subtitle {281        text-align: center;282        font-size: 15px;283        color: #7C2D12;284        margin-bottom: 25px;285    }286    287    /* Chatbox card */288    .chatbox {289        border-radius: 18px;290        box-shadow: 0px 8px 25px rgba(249, 115, 22, 0.15);291        background: #ffffff;292    }293    294    /* Input row spacing */295    .input-row {296        margin-top: 15px;297    }298    299    /* Example buttons styling */300    .gradio-examples .example {301        border: 1px solid #FDBA74 !important;302        background-color: #FFEDD5 !important;303        color: #7C2D12 !important;304        border-radius: 10px !important;305        transition: all 0.2s ease-in-out !important;306    }307    308    /* Hover effect */309    .gradio-examples .example:hover {310        background-color: #F97316 !important;311        color: white !important;312        border-color: #F97316 !important;313        transform: translateY(-2px);314    }315    316    /* Clear button */317    .input-row button {318        height: 52px !important;319        padding: 0 24px !important;320        display: flex !important;321        align-items: center !important;322        justify-content: center !important;323        border-radius: 12px !important;324        background-color: #F97316 !important;325        color: white !important;326        border: none !important;327    }328    329    .input-row button:hover {330        background-color: #EA580C !important;331    }332    333    footer {display:none !important;}334    """335 336) as demo:337 338    with gr.Column(elem_classes="container"):339 340        gr.HTML(341            """342            <div class="header-container">343                <h1>Sunam's AI Twin</h1>344                <p>Ask anything about Sunam’s experience, skills, achievements or education.</p>345            </div>346            """347        )348 349        chatbot = gr.Chatbot(350            height=450,351            bubble_full_width=False,352            elem_classes="chatbox",353        )354 355        with gr.Row(elem_classes="input-row"):356            msg = gr.Textbox(357                placeholder="Type your question here...",358                show_label=False,359                scale=8360            )361 362            clear = gr.Button("Clear", scale=1)363 364        # Optional: Example prompts365        gr.Examples(366            examples=[367                "What are my skills?",368                "What projects have I done?",369                "What are my interests?",370                "What roles suit me?"371            ],372            inputs=msg373        )374 375        def user(user_message, history):376            return "", history + [[user_message, None]]377 378        def bot(history):379            user_message = history[-1][0]380            history[-1][1] = ""381 382            for chunk in chat(user_message, history):383                history[-1][1] = chunk384                yield history385 386        msg.submit(387            user,388            [msg, chatbot],389            [msg, chatbot],390            queue=False,391        ).then(392            bot,393            chatbot,394            chatbot,395        )396 397        clear.click(lambda: [], None, chatbot)398 399 400# =====================================================401# 7. Launch402# =====================================================403 404if __name__ == "__main__":405    demo.launch()