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README.md

@@ -1,33 +1,33 @@
----
-title: Math Solution Classifier
-emoji: 🧮
-colorFrom: blue
-colorTo: purple
-sdk: gradio
-sdk_version: 4.44.0
-app_file: app.py
-pinned: false
----
-
-# Math Solution Classifier
-
-This application classifies math solutions into three categories:
-- **Correct**: Solution is mathematically sound
-- **Conceptually Flawed**: Wrong approach or understanding  
-- **Computationally Flawed**: Right approach, calculation errors
-
-## Usage
-
-1. Enter a math question
-2. Enter the proposed solution
-3. Click "Classify Solution"
-4. Get instant feedback on the solution quality
-
-Built with Gradio and your custom trained model.
-
-# requirements.txt
-gradio==4.44.0
-torch==2.1.0
-transformers==4.35.0
-peft==0.7.1
+---
+title: Math Solution Classifier
+emoji: 🧮
+colorFrom: blue
+colorTo: purple
+sdk: gradio
+sdk_version: 4.44.0
+app_file: app.py
+pinned: false
+---
+
+# Math Solution Classifier
+
+This application classifies math solutions into three categories:
+- **Correct**: Solution is mathematically sound
+- **Conceptually Flawed**: Wrong approach or understanding  
+- **Computationally Flawed**: Right approach, calculation errors
+
+## Usage
+
+1. Enter a math question
+2. Enter the proposed solution
+3. Click "Classify Solution"
+4. Get instant feedback on the solution quality
+
+Built with Gradio and your custom trained model.
+
+# requirements.txt
+gradio==4.44.0
+torch==2.1.0
+transformers==4.35.0
+peft==0.7.1
 accelerate==0.25.0

app.py

@@ -18,6 +18,8 @@ import re
 import math
 import time
 
+DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
 # Set up logging
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
@@ -322,10 +324,10 @@ classifier_tokenizer = None
 
 def load_model():
     """Load your trained model here"""
-    global gemma_model, gemma_tokenizer, classifier_model, classifier_tokenizer
+    global gemma_model, gemma_tokenizer, classifier_model, classifier_tokenizer, DEVICE
     
     try:
-        device = "cuda" if torch.cuda.is_available() else "cpu"
+        device = DEVICE
 
         # --- Model 1: Equation Extractor (Gemma-3 with Unsloth) ---
         extractor_adapter_repo = "arvindsuresh-math/gemma-3-1b-equation-extractor-lora"
@@ -392,6 +394,8 @@ def load_model():
     except Exception as e:
         logger.error(f"Error loading model: {e}")
         return f"Error loading model: {e}"
+def models_ready():
+    return all([gemma_model, gemma_tokenizer, classifier_model, classifier_tokenizer])
 
 @spaces.GPU
 def analyze_single(math_question: str, proposed_solution: str, debug: bool = False):
@@ -401,6 +405,8 @@ def analyze_single(math_question: str, proposed_solution: str, debug: bool = Fal
     Stage 2: conceptual/correct check via Phi-4 classifier.
     Returns: {"classification": "...", "confidence": "...", "explanation": "..."}
     """
+    global DEVICE
+    device = DEVICE
     # -----------------------------
     # STAGE 1: COMPUTATIONAL CHECK
     # -----------------------------
@@ -506,13 +512,13 @@ def classify_solution(question: str, solution: str):
     if not question.strip() or not solution.strip():
         return "Please fill in both fields", 0.0, ""
     
-    if not model or not tokenizer:
-        return "Model not loaded", 0.0, ""
+    if not models_ready():
+        return "Models not loaded", 0.0, ""
     
     try:
         res = analyze_single(question, solution)
         
-        return list(res.values())
+        return res["classification"], res["confidence"], res["explanation"]
     except Exception:
         logger.exception("inference failed")
         

deployment_files.py

@@ -1,49 +1,49 @@
-# requirements.txt
-fastapi==0.104.1
-uvicorn==0.24.0
-torch==2.1.0
-transformers==4.35.0
-python-multipart==0.0.6
-pydantic==2.5.0
-
-# README.md for your Hugging Face Space
----
-title: Math Solution Classifier
-emoji: 🧮
-colorFrom: blue
-colorTo: purple
-sdk: gradio
-sdk_version: 4.7.1
-app_file: app.py
-pinned: false
----
-
-# Math Solution Classifier
-
-This application classifies math solutions into three categories:
-- **Correct**: Solution is mathematically sound
-- **Conceptually Flawed**: Wrong approach or understanding  
-- **Computationally Flawed**: Right approach, calculation errors
-
-## Usage
-
-1. Enter a math question
-2. Enter the proposed solution
-3. Click "Classify Solution"
-4. Get instant feedback on the solution quality
-
-Built with FastAPI and your custom trained model.
-
-# Dockerfile (optional, for other hosting platforms)
-FROM python:3.9-slim
-
-WORKDIR /app
-
-COPY requirements.txt .
-RUN pip install --no-cache-dir -r requirements.txt
-
-COPY . .
-
-EXPOSE 7860
-
+# requirements.txt
+fastapi==0.104.1
+uvicorn==0.24.0
+torch==2.1.0
+transformers==4.35.0
+python-multipart==0.0.6
+pydantic==2.5.0
+
+# README.md for your Hugging Face Space
+---
+title: Math Solution Classifier
+emoji: 🧮
+colorFrom: blue
+colorTo: purple
+sdk: gradio
+sdk_version: 4.7.1
+app_file: app.py
+pinned: false
+---
+
+# Math Solution Classifier
+
+This application classifies math solutions into three categories:
+- **Correct**: Solution is mathematically sound
+- **Conceptually Flawed**: Wrong approach or understanding  
+- **Computationally Flawed**: Right approach, calculation errors
+
+## Usage
+
+1. Enter a math question
+2. Enter the proposed solution
+3. Click "Classify Solution"
+4. Get instant feedback on the solution quality
+
+Built with FastAPI and your custom trained model.
+
+# Dockerfile (optional, for other hosting platforms)
+FROM python:3.9-slim
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+EXPOSE 7860
+
 CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

requirements.txt

@@ -4,8 +4,4 @@ transformers
 peft
 accelerate
 spaces
-unsloth
-json
-re
-math
-time
+unsloth

webapp_TODO.md

@@ -0,0 +1,4 @@
+- [] update prompt given to the model (before the actual question/answer) to match prompt used in training
+- [] figure out how to merge lora adapter and classifier head with base model
+- [] add new examples
+- [] update interface so that one can select types of problems from the examples