import os import time from typing import List, Tuple, Optional import google.generativeai as genai import gradio as gr from PIL import Image print("google-generativeai:", genai.__version__) GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY") TITLE = """

🕹ī¸ Google Gemini Playground đŸ”Ĩ

""" SUBTITLE = """

Play with Gemini Text and Vision Model API 🖇ī¸

""" DUPLICATE = """
Duplicate Space Duplicate the Space and run securely with your GOOGLE API KEY.
""" IMAGE_WIDTH = 512 def preprocess_stop_sequences(stop_sequences: str) -> Optional[List[str]]: return [seq.strip() for seq in stop_sequences.split(",")] if stop_sequences else None def preprocess_image(image: Image.Image) -> Image.Image: image_height = int(image.height * IMAGE_WIDTH / image.width) return image.resize((IMAGE_WIDTH, image_height)) def user(text_prompt: str, chatbot: List[Tuple[str, str]]): return "", chatbot + [[text_prompt, None]] def bot( google_key: str, model_name: str, image_prompt: Optional[Image.Image], temperature: float, max_output_tokens: int, stop_sequences: str, top_k: int, top_p: float, chatbot: List[Tuple[str, str]] ): google_key = google_key or GOOGLE_API_KEY if not google_key: raise ValueError("GOOGLE_API_KEY is not set. Please set it up.") text_prompt = chatbot[-1][0] genai.configure(api_key=google_key) generation_config = genai.types.GenerationConfig( temperature=temperature, max_output_tokens=max_output_tokens, stop_sequences=preprocess_stop_sequences(stop_sequences), top_k=top_k, top_p=top_p ) model = genai.GenerativeModel(model_name if image_prompt is None else 'gemini-pro-vision') inputs = [text_prompt] if image_prompt is None else [text_prompt, preprocess_image(image_prompt)] response = model.generate_content(inputs, stream=True, generation_config=generation_config) response.resolve() chatbot[-1][1] = "" for chunk in response: for i in range(0, len(chunk.text), 10): chatbot[-1][1] += chunk.text[i:i + 10] time.sleep(0.01) yield chatbot google_key_component = gr.Textbox( label="GOOGLE API KEY", type="password", placeholder="...", visible=GOOGLE_API_KEY is None ) image_prompt_component = gr.Image(type="pil", label="Image") model_selection = gr.Dropdown(["gemini-1.0-pro", "gemini-pro-vision", "gemini-1.5-flash-latest", "gemini-1.5-pro-latest", "gemini-1.0-pro-001"], label="Select Gemini Model", value="gemini-1.0-pro") chatbot_component = gr.Chatbot(label='Gemini', bubble_full_width=False) text_prompt_component = gr.Textbox(placeholder="Hi there!", label="Ask me anything and press Enter") run_button_component = gr.Button("Run") temperature_component = gr.Slider(minimum=0, maximum=1.0, value=0.4, step=0.05, label="Temperature") max_output_tokens_component = gr.Slider(minimum=1, maximum=2048, value=1024, step=1, label="Token limit") stop_sequences_component = gr.Textbox(label="Add stop sequence", placeholder="STOP, END") top_k_component = gr.Slider(minimum=1, maximum=40, value=32, step=1, label="Top-K") top_p_component = gr.Slider(minimum=0, maximum=1, value=1, step=0.01, label="Top-P") user_inputs = [text_prompt_component, chatbot_component] bot_inputs = [google_key_component, model_selection, image_prompt_component, temperature_component, max_output_tokens_component, stop_sequences_component, top_k_component, top_p_component, chatbot_component] with gr.Blocks() as demo: gr.HTML(TITLE) gr.HTML(SUBTITLE) gr.HTML(DUPLICATE) with gr.Column(): google_key_component.render() with gr.Row(): image_prompt_component.render() model_selection.render() chatbot_component.render() text_prompt_component.render() run_button_component.render() with gr.Accordion("Parameters", open=False): temperature_component.render() max_output_tokens_component.render() stop_sequences_component.render() with gr.Accordion("Advanced", open=False): top_k_component.render() top_p_component.render() run_button_component.click(fn=user, inputs=user_inputs, outputs=[text_prompt_component, chatbot_component], queue=False).then(fn=bot, inputs=bot_inputs, outputs=[chatbot_component]) text_prompt_component.submit(fn=user, inputs=user_inputs, outputs=[text_prompt_component, chatbot_component], queue=False).then(fn=bot, inputs=bot_inputs, outputs=[chatbot_component]) demo.launch()