Update app.py

app.py

@@ -1,12 +1,16 @@
 import gradio as gr
+from openai import OpenAI
 import base64
 import io
-import requests
-
-def solve_stem_problem(api_key, image, subject):
-    if not api_key.strip():
-        return "❌ Error: API key is required."
 
+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",
@@ -14,27 +18,29 @@ def solve_stem_problem(api_key, image, subject):
         "coding": "Code Cracker"
     }
     detective = detectives.get(subject, "Algebra Ace")
-
+    
+    # Encode the uploaded image to base64
     try:
-        # Convert image to base64 string
-        buffered = io.BytesIO()
-        image.save(buffered, format="PNG")
-        encoded_image = base64.b64encode(buffered.getvalue()).decode('utf-8')
+        # 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)}"
-
+        return f"Error encoding image: {str(e)}"
+    
+    # Call the Gemini model
     try:
-        headers = {
-            "Authorization": f"Bearer {api_key}",
-            "Content-Type": "application/json",
-            "HTTP-Referer": "https://stem-sleuth.example.com",
-            "X-Title": "STEM Sleuth"
-        }
-
-        payload = {
-            "model": "google/gemini-2.0-flash-exp:free",
-            "messages": [
+        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": [
@@ -44,42 +50,45 @@ def solve_stem_problem(api_key, image, subject):
                         },
                         {
                             "type": "image_url",
-                            "image_url": {
-                                "url": image_url_data
-                            }
+                            "image_url": {"url": image_url_data}
                         }
                     ]
                 }
             ]
-        }
-
-        response = requests.post("https://openrouter.ai/api/v1/chat/completions", headers=headers, json=payload)
-
-        if response.status_code != 200:
-            return f"❌ API Error {response.status_code}: {response.text}"
-
-        completion = response.json()
-        message = completion.get("choices", [{}])[0].get("message", {}).get("content")
-
-        if not message:
-            return "⚠️ No response content received. Try another image or check the model output."
-
-        return message
-
+        )
+        
+        # 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:
-        return f"❌ API call failed: {str(e)}"
+        solution = f"Error calling API: {str(e)}"
+    
+    return solution
 
-# Launch Gradio Interface
-iface = gr.Interface(
-    fn=solve_stem_problem,
-    inputs=[
-        gr.Textbox(label="🔐 OpenRouter API Key", type="password"),
-        gr.Image(label="🖼️ Upload STEM Problem Image", type="pil"),
-        gr.Dropdown(["math", "physics", "chemistry", "coding"], label="📚 Select Subject")
-    ],
-    outputs=gr.Textbox(label="🕵️‍♂️ Detective's Solution"),
-    title="🧠 STEM Sleuth Solver",
-    description="Upload a math, physics, chemistry, or coding problem image and solve it with a detective twist using OpenRouter Gemini model."
-)
+# 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
+    )
 
-iface.launch()
+# Launch the app
+app.launch()