Update app/predictor.py

app/predictor.py

@@ -4,7 +4,6 @@ import torch
 import torch.nn.functional as F
 from transformers import AutoModel, AutoTokenizer
 
-# Resilient import handling for AIReviewerService across different project layouts
 try:
     from app.services.reviewer_service import AIReviewerService
 except ImportError:
@@ -24,7 +23,6 @@ class CodeClassifier:
     """
     def __init__(self):
         logger.info("⏳ Initializing CodeBERT AI Service...")
-
         self.device = "cuda" if torch.cuda.is_available() else "cpu"
         if torch.backends.mps.is_available():
             self.device = "mps"
@@ -74,7 +72,6 @@ class CodeClassifier:
         Returns: { "label": str, "confidence": float, "embedding": List[float] }
         """
         path = file_path.lower()
-
         try:
             text_to_analyze = content[:1000] if content else file_path
             target_embedding_tensor = self._get_embedding(text_to_analyze)
@@ -207,8 +204,6 @@ class GuideGenerator:
         detected = {"languages": set(), "frameworks": set(), "tools": set()}
         for file in files:
             path = file.lower()
-
-            # Languages
             if path.endswith(".ts") or path.endswith(".tsx"):
                 detected["languages"].add("TypeScript")
             elif path.endswith(".js") or path.endswith(".jsx"):
@@ -224,12 +219,10 @@ class GuideGenerator:
             elif path.endswith(".kt") or path.endswith(".kts"):
                 detected["languages"].add("Kotlin")
 
-            # Frameworks
             for framework, indicators in self.tech_stacks.items():
                 if any(ind in path for ind in indicators):
                     detected["frameworks"].add(framework)
 
-            # Tools & Libraries
             for tool, indicators in self.tools.items():
                 if any(ind in path for ind in indicators):
                     detected["tools"].add(tool)
@@ -260,7 +253,6 @@ class GuideGenerator:
         total_files = len(files) if files else 1
         primary_layer = max(stats, key=stats.get)
 
-        # Cross-file logical couplings analysis
         couplings = []
         try:
             sample_paths = list(file_embeddings.keys())[:50]
@@ -306,7 +298,6 @@ class GuideGenerator:
             run_cmd = "go run main.go"
             test_cmd = "go test ./..."
 
-        # Assemble Markdown Document
         md = f"# {repo_name} Developer Guide\n\n"
         md += "## AI Codebase Insights\n"
         md += "Analysis powered by **CodeBERT** semantic vector embeddings.\n\n"
@@ -373,7 +364,7 @@ class GuideGenerator:
         md += "\n### Installation & Setup\n"
         md += "1. Clone the repository:\n"
         md += "   ```bash\n"
-        md += f"   git clone [https://github.com/OWNER/](https://github.com/OWNER/){repo_name}.git\n"
+        md += f"   git clone https://github.com/OWNER/{repo_name}.git\n"
         md += f"   cd {repo_name}\n"
         md += "   ```\n\n"
         md += "2. Install dependencies:\n"
@@ -492,7 +483,6 @@ class GuideGenerator:
         return "\n".join(lines[:60])
 
 
-# Global Singleton Instances
 classifier = CodeClassifier()
 guide_generator = GuideGenerator()