Update tinyllama_inference.py with DeepSeek integration and debug logging

tinyllama_inference.py

@@ -9,7 +9,7 @@ def load_model():
     global tokenizer, model
     if tokenizer is None or model is None:
         # Use a DeepSeek model for code evaluation.
-        model_name = "deepseek-ai/deepseek-coder-1.3b"  # Adjust to your chosen DeepSeek model
+        model_name = "deepseek-ai/deepseek-coder-1.3b"  # Adjust to your chosen DeepSeek model if needed
         tokenizer = AutoTokenizer.from_pretrained(model_name)
         model = AutoModelForCausalLM.from_pretrained(model_name)
     return tokenizer, model
@@ -37,12 +37,10 @@ Solution: "{code}"
         do_sample=False
     )
     response_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    
-    # Debug: Uncomment the following line to print raw output if needed
-    # print("Raw model response:", response_text)
-    
+    print("Raw model response:", response_text)  # Debug output
+
     # Use regex to extract the JSON object from the response
-    match = re.search(r'\{.*\}', response_text)
+    match = re.search(r'\{.*?\}', response_text)
     if match:
         json_text = match.group(0)
         try: