Spaces:
Running
Running
File size: 2,739 Bytes
29ffd49 b3355ef 953b1da 3e18d30 b3355ef 29ffd49 b3355ef 29ffd49 b3355ef 29ffd49 3e18d30 29ffd49 3e18d30 29ffd49 b3355ef 3e18d30 29ffd49 b3355ef 29ffd49 3e18d30 29ffd49 b3355ef 29ffd49 3e18d30 29ffd49 b3355ef 3e18d30 b3355ef a4be152 3e18d30 b3355ef 3e18d30 b3355ef 29ffd49 3e18d30 b3355ef 3e18d30 b3355ef 3e18d30 b3355ef 3e18d30 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 |
import os
import time
from typing import List, Tuple, Optional
import google.generativeai as genai
import gradio as gr
from PIL import Image
# Environment variable for Google API Key
GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY")
# Constants for image processing
IMAGE_WIDTH = 512
# Helper functions
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))
# Function to trigger model invocation
def bot(
google_key: str,
image_prompt: Optional[Image.Image],
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.")
# Fixed text prompt for analyzing gender-based discrimination
text_prompt = "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."
genai.configure(api_key=google_key)
generation_config = genai.types.GenerationConfig(
temperature=0.4,
max_output_tokens=1024,
stop_sequences=preprocess_stop_sequences("STOP, END"),
top_k=32,
top_p=1.0,
)
model_name = "gemini-1.5-pro-latest"
model = genai.GenerativeModel(model_name)
inputs = [text_prompt, preprocess_image(image_prompt)] if image_prompt else [text_prompt]
response = model.generate_content(inputs, stream=True, generation_config=generation_config)
response.resolve()
chatbot[-1][1] = ""
for chunk in response:
chatbot[-1][1] += chunk.text
time.sleep(0.01)
return chatbot
# Gradio Interface Components
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")
chatbot_component = gr.Chatbot(label='Gemini', bubble_full_width=False)
run_button_component = gr.Button("Check Discrimination")
# Layout and Interaction
with gr.Blocks() as demo:
with gr.Column():
google_key_component.render()
image_prompt_component.render()
run_button_component.render()
chatbot_component.render()
# Connect button to the bot function
run_button_component.click(
fn=bot,
inputs=[google_key_component, image_prompt_component, chatbot_component],
outputs=[chatbot_component]
)
# Launch the app
demo.launch()
|