.

app.py

@@ -0,0 +1,48 @@
+import gradio as gr
+import google.generativeai as genai
+import os
+
+# Set up Gemini API key (use environment variable on Hugging Face)
+API_KEY = os.getenv("GEMINI_API_KEY")  # Set this in Hugging Face secrets
+genai.configure(api_key=API_KEY)
+
+# Use Gemini 1.5 Flash (free-tier accessible)
+model = genai.GenerativeModel("gemini-1.5-flash")
+
+def chatbot(prompt, history=[]):
+    """Generates a chatbot response using the free-tier Gemini API."""
+    try:
+        response = model.generate_content(prompt)
+        return response.text
+    except Exception as e:
+        return f"Error: {e}"
+
+def vqa(image, question):
+    """Performs Visual Question Answering (VQA) using the Gemini API."""
+    try:
+        response = model.generate_content([question, image])
+        return response.text
+    except Exception as e:
+        return f"Error: {e}"
+
+# Create Gradio interfaces
+chat_interface = gr.ChatInterface(
+    chatbot,
+    title="Free Gemini API Chatbot",
+    description="Ae chatbot powered by the free-tier Google Gemini API."
+)
+
+vqa_interface = gr.Interface(
+    fn=vqa,
+    inputs=[gr.Image(type="filepath"), gr.Textbox(label="Question")],
+    outputs=gr.Textbox(label="Answer"),
+    title="Visual Question Answering (VQA)",
+    description="Upload an image and ask a question about it."
+)
+
+# Combine interfaces
+with gr.Blocks() as demo:
+    gr.TabbedInterface([chat_interface, vqa_interface], ["Chatbot", "VQA"])
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+google-generativeai
+gradio