| import base64 | |
| import os | |
| import gradio as gr | |
| from google import genai | |
| from google.genai import types | |
| def generate(prompt): | |
| client = genai.Client(api_key=os.environ.get("GEMINI_API_KEY")) | |
| model = "gemini-2.5-pro-exp-03-25" | |
| contents = [ | |
| types.Content( | |
| role="user", | |
| parts=[types.Part.from_text(text=prompt)], | |
| ), | |
| ] | |
| generate_content_config = types.GenerateContentConfig( | |
| temperature=2, | |
| response_mime_type="text/plain", | |
| ) | |
| response_text = "" | |
| for chunk in client.models.generate_content_stream( | |
| model=model, contents=contents, config=generate_content_config | |
| ): | |
| response_text += chunk.text | |
| return response_text | |
| demo = gr.Interface( | |
| fn=generate, | |
| inputs=gr.Textbox(lines=2, placeholder="Enter your prompt here..."), | |
| outputs="text", | |
| title="Gemini 2.5 Pro Generator", | |
| description="Enter a prompt and get AI-generated text.", | |
| ) | |
| demo.launch() | |