Update app/main.py

app/main.py

@@ -12,7 +12,6 @@ from pydantic import BaseModel
 import uvicorn
 
 load_dotenv()
-
 from app.predictor import classifier, guide_generator, reviewer
 from app.core.model_loader import llm_engine
 
@@ -22,7 +21,7 @@ logger = logging.getLogger(__name__)
 app = FastAPI(title="GitGud AI Service")
 
 REPO_CACHE: Dict[str, Dict[str, List[float]]] = {}
-executor = ThreadPoolExecutor(max_workers=2)
+executor = ThreadPoolExecutor(max_workers=10)
 
 class FileRequest(BaseModel):
     fileName: str
@@ -47,9 +46,9 @@ class ChatRequest(BaseModel):
     repoName: str
 
 def calculate_repo_health(total_vulns: int, avg_maint: float) -> int:
-    base_score = avg_maint * 10
-    penalty = total_vulns * 8
-    return int(max(10, min(100, base_score - penalty)))
+    base_score = avg_maint * 10.0
+    penalty = total_vulns * 8.0
+    return int(max(10.0, min(100.0, base_score - penalty)))
 
 def sync_review_worker(file_list: List[FileRequest]):
     logger.info(f"--- [DEBUG] Processing {len(file_list)} files for code review ---")
@@ -141,7 +140,7 @@ async def get_dashboard_stats(request: BatchReviewRequest):
                     found_apis.add(f"/{match}")
 
         num_files = len(maint_scores)
-        avg_maint = (sum(maint_scores) / num_files) if num_files > 0 else 0
+        avg_maint = (sum(maint_scores) / num_files) if num_files > 0 else 0.0
         health_score = calculate_repo_health(total_vulns, avg_maint)
 
         return {
@@ -214,6 +213,7 @@ async def generate_guide(request: GuideRequest):
     try:
         markdown = guide_generator.generate_markdown(request.repoName, request.filePaths)
         tree_match = re.search(r"Project Structure\n\n(.*?)(?=\n\n|$)", markdown, re.S)
+
         structured_tree = []
         if tree_match:
             structured_tree = parse_tree_to_list(tree_match.group(1))