Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Load small + free LLM
+generator = pipeline("text2text-generation", model="google/flan-t5-small")
+
+# --- Agent 1: Summarizer + Knowledge Graph Builder ---
+def doc_agent(user_text):
+    # Step 1: Summarize
+    summary_prompt = f"Summarize this in 3 lines: {user_text}"
+    summary = generator(summary_prompt, max_length=80, do_sample=False)[0]['generated_text']
+
+    # Step 2: Build a "mini knowledge graph" (keywords as nodes)
+    keyword_prompt = f"Extract 5 important keywords from this text: {user_text}"
+    keywords = generator(keyword_prompt, max_length=40, do_sample=False)[0]['generated_text']
+    graph_nodes = [kw.strip() for kw in keywords.split(",") if kw.strip()]
+    graph_repr = " → ".join(graph_nodes) if graph_nodes else "No graph generated."
+
+    return f"📄 Summary:\n{summary}\n\n🕸️ Knowledge Graph:\n{graph_repr}"
+
+# --- Agent 2: Career Skill Recommender ---
+def career_agent(user_goal):
+    # Step 1: Analyze career intent
+    analysis_prompt = f"Identify skill gap for this career goal: {user_goal}"
+    analysis = generator(analysis_prompt, max_length=50, do_sample=False)[0]['generated_text']
+
+    # Step 2: Recommend roadmap
+    roadmap_prompt = f"Suggest a 3-step learning roadmap for: {user_goal}"
+    roadmap = generator(roadmap_prompt, max_length=80, do_sample=False)[0]['generated_text']
+
+    return f"🔍 Gap Analysis:\n{analysis}\n\n🛠️ Skill Roadmap:\n{roadmap}"
+
+# --- Combined Agent Controller ---
+def agentic_ai(user_input, mode):
+    if mode == "Document Insight":
+        return doc_agent(user_input)
+    elif mode == "Career Roadmap":
+        return career_agent(user_input)
+    else:
+        return "⚠️ Please choose a valid mode."
+
+# --- Demo UI ---
+demo = gr.Interface(
+    fn=agentic_ai,
+    inputs=[
+        gr.Textbox(lines=4, placeholder="Enter text or career goal..."),
+        gr.Radio(["Document Insight", "Career Roadmap"], label="Choose Mode")
+    ],
+    outputs="text",
+    title="🌐 Mini Agentic AI MVP",
+    description="""
+    This smallest MVP demonstrates:
+    - 📄 Document Summarization
+    - 🕸️ Knowledge Graph (mini keyword graph)
+    - 🧑‍💻 Career Skill Gap Analysis
+    - 🛠️ Personalized 3-step Roadmap
+
+    Built with free Hugging Face + Gradio. Optimized for AI Research use cases.
+    """
+)
+
+if __name__ == "__main__":
+    demo.launch()