Create app.py

app.py

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+import os
+import faiss
+import numpy as np
+import requests
+import gradio as gr
+
+from openai import OpenAI
+from pypdf import PdfReader
+from sentence_transformers import SentenceTransformer
+
+# =========================
+# INIT
+# =========================
+embed_model = SentenceTransformer("all-MiniLM-L6-v2")
+index = None
+chunks = []
+
+client = OpenAI(
+    api_key=os.getenv("GROQ_API_KEY"),
+    base_url="https://api.groq.com/openai/v1",
+)
+
+# =========================
+# TELEKOM THEME LOGO
+# =========================
+LOGO_URL = "https://www.telekom.com/resource/image/1037468/landscape_ratio16x9/1920/1080/0a6b8d7f3d9f6f0c5f4c8b9c2c1b2d3e/telekom-logo.jpg"
+
+# =========================
+# DRIVE LINK HANDLER
+# =========================
+def convert_drive_link(link):
+    try:
+        file_id = link.split("/d/")[1].split("/")[0]
+        return f"https://drive.google.com/uc?id={file_id}"
+    except:
+        return link
+
+# =========================
+# LOAD PDF
+# =========================
+def load_pdf_from_link(link):
+    global index, chunks
+
+    url = convert_drive_link(link)
+    pdf_path = "temp.pdf"
+
+    r = requests.get(url)
+    with open(pdf_path, "wb") as f:
+        f.write(r.content)
+
+    reader = PdfReader(pdf_path)
+
+    texts = []
+    for page in reader.pages:
+        text = page.extract_text()
+        if text:
+            texts.append(text)
+
+    chunks = []
+    for t in texts:
+        words = t.split()
+        for i in range(0, len(words), 500):
+            chunks.append(" ".join(words[i:i+500]))
+
+    embeddings = embed_model.encode(chunks)
+    dim = embeddings.shape[1]
+
+    index = faiss.IndexFlatL2(dim)
+    index.add(np.array(embeddings))
+
+    return f"✅ PDF Loaded | Chunks: {len(chunks)}"
+
+# =========================
+# RETRIEVAL
+# =========================
+def retrieve(query, k=3):
+    q_emb = embed_model.encode([query])
+    _, indices = index.search(np.array(q_emb), k)
+    return [chunks[i] for i in indices[0]]
+
+# =========================
+# GENERATION
+# =========================
+def generate_answer(query):
+    if index is None:
+        return "⚠️ Load a PDF first"
+
+    context = "\n\n".join(retrieve(query))
+
+    prompt = f"""
+You are a professional AI assistant.
+Answer ONLY from context.
+
+Context:
+{context}
+
+Question:
+{query}
+"""
+
+    res = client.responses.create(
+        model="openai/gpt-oss-20b",
+        input=prompt
+    )
+
+    return res.output_text
+
+# =========================
+# CHAT
+# =========================
+def chat(msg, history):
+    ans = generate_answer(msg)
+    history.append((msg, ans))
+    return history, history
+
+# =========================
+# CSS (BOTPRESS + TELEKOM STYLE)
+# =========================
+css = """
+body {
+    background-color: #0b0b10;
+    color: white;
+    font-family: 'Inter', sans-serif;
+}
+
+.gradio-container {
+    max-width: 1100px !important;
+}
+
+h1 {
+    text-align: center;
+    color: #e20074; /* Telekom pink */
+    font-weight: 700;
+}
+
+.chatbot {
+    background: #11131a !important;
+    border-radius: 15px;
+    border: 1px solid #2a2d3a;
+}
+
+button {
+    background: linear-gradient(90deg, #e20074, #ff4da6) !important;
+    border-radius: 10px !important;
+    color: white !important;
+    font-weight: bold;
+    transition: 0.3s;
+}
+
+button:hover {
+    transform: scale(1.03);
+    box-shadow: 0 0 15px #e20074;
+}
+
+input {
+    background: #1a1d26 !important;
+    border: 1px solid #2a2d3a !important;
+    color: white !important;
+    border-radius: 10px !important;
+}
+
+.card {
+    background: #11131a;
+    padding: 15px;
+    border-radius: 15px;
+    border: 1px solid #2a2d3a;
+}
+"""
+
+# =========================
+# UI
+# =========================
+with gr.Blocks(css=css, theme=gr.themes.Soft()) as app:
+
+    gr.Image(LOGO_URL, height=80)
+    gr.Markdown("# 📊 Telekom AI RAG Chatbot")
+
+    with gr.Row():
+        pdf_link = gr.Textbox(label="📎 PDF Link (Google Drive supported)")
+        load_btn = gr.Button("Load Document")
+
+    status = gr.Textbox()
+
+    chatbot = gr.Chatbot()
+    state = gr.State([])
+
+    msg = gr.Textbox(label="Ask Anything")
+
+    load_btn.click(load_pdf_from_link, inputs=pdf_link, outputs=status)
+    msg.submit(chat, inputs=[msg, state], outputs=[chatbot, state])
+
+app.launch()