Create app.py

app.py

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+import gradio as gr
+import os
+from langchain_google_genai import ChatGoogleGenerativeAI
+
+llm = None  # Global Gemini model
+
+# Set up Gemini model
+def setup_gemini(api_key):
+    try:
+        os.environ["GOOGLE_API_KEY"] = api_key
+        global llm
+        llm = ChatGoogleGenerativeAI(model="gemini-pro", temperature=0.2)
+        return "✅ Gemini model is ready!"
+    except Exception as e:
+        return f"❌ Error: {str(e)}"
+
+# Ask question using Chain of Thought prompting
+def solve_step_by_step(question):
+    if not llm:
+        return "⚠️ Please initialize Gemini first."
+    
+    prompt = question.strip()
+    if not prompt.endswith("Let's think step by step."):
+        prompt += " Let's think step by step."
+    
+    try:
+        return llm.invoke(prompt)
+    except Exception as e:
+        return f"❌ Error: {str(e)}"
+
+# Gradio UI
+with gr.Blocks(title="Chain of Thought with Gemini") as demo:
+    gr.Markdown("## 🤖 Chain of Thought Prompting (Gemini)")
+    
+    api_key = gr.Textbox(label="🔑 Gemini API Key", type="password", placeholder="Paste your Gemini key")
+    status = gr.Textbox(label="Status", interactive=False)
+
+    setup_btn = gr.Button("⚙️ Initialize Gemini")
+
+    question = gr.Textbox(label="❓ Your Question", placeholder="e.g., What is 15 * 4?")
+    answer = gr.Textbox(label="🧠 Gemini's Reasoning", lines=10)
+
+    ask_btn = gr.Button("🔍 Think Step by Step")
+
+    setup_btn.click(fn=setup_gemini, inputs=[api_key], outputs=[status])
+    ask_btn.click(fn=solve_step_by_step, inputs=[question], outputs=[answer])
+
+demo.launch()