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import gradio as gr
from openai import OpenAI
import base64
import io
def solve_stem_problem(api_key, image, subject="math"):
# Initialize OpenAI client with user-provided API key
client = OpenAI(
base_url="https://openrouter.ai/api/v1",
api_key=api_key,
)
# Define detective based on subject
detectives = {
"math": "Algebra Ace",
"physics": "Physics Phantom",
"chemistry": "Chemistry Clue-finder",
"coding": "Code Cracker"
}
detective = detectives.get(subject, "Algebra Ace")
# Encode the uploaded image to base64
try:
# Convert the image to bytes
img_byte_arr = io.BytesIO()
image.save(img_byte_arr, format='PNG')
img_byte_arr = img_byte_arr.getvalue()
# Encode to base64
encoded_image = base64.b64encode(img_byte_arr).decode('utf-8')
image_url_data = f"data:image/png;base64,{encoded_image}"
except Exception as e:
return f"Error encoding image: {str(e)}"
# Call the Gemini model
try:
completion = client.chat.completions.create(
extra_headers={
"HTTP-Referer": "https://stem-sleuth.example.com",
"X-Title": "STEM Sleuth",
},
model="google/gemini-2.0-flash-exp:free",
messages=[
{
"role": "user",
"content": [
{
"type": "text",
"text": f"Act as {detective} and solve this {subject} problem step-by-step with a detective narrative."
},
{
"type": "image_url",
"image_url": {"url": image_url_data}
}
]
}
]
)
# Check for valid response
if completion.choices and len(completion.choices) > 0 and completion.choices[0].message:
solution = completion.choices[0].message.content
else:
solution = "Could not retrieve a solution from the API."
except Exception as e:
solution = f"Error calling API: {str(e)}"
return solution
# Create Gradio interface
with gr.Blocks() as app:
gr.Markdown("# STEM Sleuth Problem Solver")
gr.Markdown("Upload an image of a STEM problem, select the subject, and provide your API key to get a step-by-step solution.")
with gr.Row():
api_key_input = gr.Textbox(label="OpenRouter API Key", type="password", placeholder="Enter your API key")
subject_input = gr.Dropdown(
choices=["math", "physics", "chemistry", "coding"],
label="Subject",
value="math"
)
image_input = gr.Image(type="pil", label="Upload Problem Image")
solve_button = gr.Button("Solve Problem")
output = gr.Textbox(label="Solution", lines=10)
solve_button.click(
fn=solve_stem_problem,
inputs=[api_key_input, image_input, subject_input],
outputs=output
)
# Launch the app
app.launch() |