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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 advocate against gender-based discrimination "
)
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 = "Analyze this for any instances of gender-based discrimination. Consider both explicit and implicit biases, stereotypes, and unequal treatment. Provide specific examples from the text to support your analysis"
run_button_component = gr.Button("Check Discrimantion")
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()
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