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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-1.5-flash-latest", 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()
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