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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 = """<h1 align="center">🕹️ Google Gemini Chatbot 🔥</h1>""" | |
SUBTITLE = """<h2 align="center">🎨Create with Multimodal Gemini</h2>""" | |
DUPLICATE = """ | |
<div style="text-align: center; display: flex; justify-content: center; align-items: center;"> | |
<a href="https://huggingface.co/spaces/Rahatara/build_with_gemini/blob/main/allgemapp.py?duplicate=true"> | |
<img src="https://bit.ly/3gLdBN6" alt="Duplicate Space" style="margin-right: 10px;"> | |
</a> | |
<span>Duplicate the Space and run securely with your | |
<a href="https://makersuite.google.com/app/apikey">GOOGLE API KEY</a>. | |
</span> | |
</div> | |
""" | |
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, | |
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, | |
#instructions = "You are an expert stylist" | |
) | |
model_name = "gemini-1.5-pro-latest" | |
model = genai.GenerativeModel(model_name) | |
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") | |
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, 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() | |
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() | |