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import gradio as gr
from openai import OpenAI
# Function to initialize the client with the provided API key
def initialize_client(api_key):
client = OpenAI(
base_url="https://openrouter.ai/api/v1",
api_key=api_key
)
return client
# Function to analyze environmental impact using Gemini 2.5 Pro
def analyze_environmental_impact(api_key, image=None, location=None, product_info=None):
client = initialize_client(api_key) # Initialize client with the user's API key
messages = []
if image:
messages.append({
"role": "user",
"content": [
{"type": "text", "text": "Analyze the environmental impact of this image."},
{"type": "image_url", "image_url": {"url": image}}
]
})
if location:
messages.append({
"role": "user",
"content": [{"type": "text", "text": f"Analyze the environmental impact of {location}."}]
})
if product_info:
messages.append({
"role": "user",
"content": [{"type": "text", "text": f"Analyze the environmental impact of this product: {product_info}."}]
})
# Call the model for environmental analysis
try:
completion = client.chat.completions.create(
extra_headers={
"HTTP-Referer": "<YOUR_SITE_URL>", # Optional
"X-Title": "<YOUR_SITE_NAME>", # Optional
},
model="google/gemini-2.5-pro-exp-03-25:free",
messages=messages
)
response = completion.choices[0].message.content
return response
except Exception as e:
return f"Error: {str(e)}"
# Gradio interface
def gradio_interface(api_key, image, location, product_info):
image_url = image if image else None # For filepath, Gradio returns the path of the uploaded image
result = analyze_environmental_impact(api_key, image_url=image_url, location=location, product_info=product_info)
return result
# Create Gradio inputs and outputs
api_key_input = gr.Textbox(label="Enter Your OpenRouter API Key", type="password")
image_input = gr.Image(label="Upload an Image (Optional)", type="filepath") # Fix: Changed to 'filepath'
location_input = gr.Textbox(label="Enter Location for Environmental Impact (Optional)", type="text")
product_info_input = gr.Textbox(label="Enter Product Information (Optional)", type="text")
output = gr.Textbox(label="Environmental Impact Analysis Output", lines=10)
# Create Gradio interface
app = gr.Interface(
fn=gradio_interface,
inputs=[api_key_input, image_input, location_input, product_info_input],
outputs=output,
title="Smart Environmental Impact Analyzer",
description="Analyze environmental impact based on images, location, or product information. Please provide your OpenRouter API key."
)
# Launch the Gradio app
app.launch() |