Update app/main.py

app/main.py

@@ -4,7 +4,7 @@ import logging
 import traceback
 import time
 import asyncio
-from typing import List, Optional, Dict
+from typing import List, Optional, Dict, Any
 from concurrent.futures import ThreadPoolExecutor
 from dotenv import load_dotenv
 from fastapi import FastAPI, HTTPException, status
@@ -12,8 +12,11 @@ from pydantic import BaseModel
 import uvicorn
 
 load_dotenv()
+
 from app.predictor import classifier, guide_generator, reviewer
 from app.core.model_loader import llm_engine
+from app.services.danger_zone_service import DangerZoneService
+from app.services.convention_service import convention_service
 
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
@@ -23,33 +26,60 @@ app = FastAPI(title="GitGud AI Service")
 REPO_CACHE: Dict[str, Dict[str, List[float]]] = {}
 executor = ThreadPoolExecutor(max_workers=10)
 
+
+# ──────────────────────────────────────────────
+# Pydantic Models
+# ──────────────────────────────────────────────
+
 class FileRequest(BaseModel):
     fileName: str
     content: Optional[str] = None
     repoName: Optional[str] = None
 
+
 class BatchReviewRequest(BaseModel):
     files: List[FileRequest]
 
+
 class GuideRequest(BaseModel):
     repoName: str
     filePaths: List[str]
 
+
 class SearchRequest(BaseModel):
     query: str
     embeddings: Optional[Dict[str, List[float]]] = None
     repoName: Optional[str] = None
 
+
 class ChatRequest(BaseModel):
     query: str
     context: List[Dict[str, str]]
     repoName: str
 
+
+class DestructiveActionRequest(BaseModel):
+    repoOwner: str
+    repoName: str
+    action: str                      # "hard_reset" | "force_push"
+    targetRef: str                   # e.g. "origin/main" or a SHA
+    currentLocalCommits: Optional[List[str]] = None
+
+
+class ReviewRequest(BaseModel):
+    files: List[FileRequest]
+
+
+# ──────────────────────────────────────────────
+# Helpers
+# ──────────────────────────────────────────────
+
 def calculate_repo_health(total_vulns: int, avg_maint: float) -> int:
     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 ---")
     try:
@@ -59,15 +89,14 @@ def sync_review_worker(file_list: List[FileRequest]):
         logger.error(f"--- [ERROR] Exception during review processing: {e} ---", exc_info=True)
         raise e
 
+
 def parse_tree_to_list(raw_tree: str):
     nodes = []
     for line in raw_tree.strip().split('\n'):
         if line.startswith("```") or not line.strip():
             continue
         level = line.count('|') + (line.count(' ') // 2)
-        # Strip tree connectors
         name = re.sub(r'[|└├─]', '', line).strip()
-        # Strip AI layer annotations like [Backend] or [Frontend]
         name = re.sub(r'\[.*?\]', '', name).strip()
         if name:
             nodes.append({
@@ -77,6 +106,11 @@ def parse_tree_to_list(raw_tree: str):
             })
     return nodes
 
+
+# ──────────────────────────────────────────────
+# Core Endpoints
+# ──────────────────────────────────────────────
+
 @app.get("/")
 def health_check():
     return {
@@ -86,10 +120,12 @@ def health_check():
         "cached_repos": list(REPO_CACHE.keys()),
     }
 
+
 @app.get("/usage")
 def get_usage():
     return llm_engine.get_usage_stats()
 
+
 @app.post("/classify")
 async def classify_file(request: FileRequest):
     try:
@@ -108,6 +144,7 @@ async def classify_file(request: FileRequest):
         logger.error(f"Classify failed: {e}")
         raise HTTPException(status_code=500, detail=str(e))
 
+
 @app.post("/review-batch-code")
 async def review_batch_code(request: BatchReviewRequest):
     try:
@@ -119,6 +156,7 @@ async def review_batch_code(request: BatchReviewRequest):
         logger.error(f"Batch review critical failure: {traceback.format_exc()}")
         raise HTTPException(status_code=500, detail="Internal processing error")
 
+
 @app.post("/repo-dashboard-stats")
 async def get_dashboard_stats(request: BatchReviewRequest):
     try:
@@ -126,23 +164,28 @@ async def get_dashboard_stats(request: BatchReviewRequest):
         raw_reviews = await loop.run_in_executor(executor, sync_review_worker, request.files)
         if not isinstance(raw_reviews, list):
             raw_reviews = [raw_reviews]
+
         total_vulns = 0
         maint_scores = []
         found_apis = set()
         api_regex = re.compile(r'(?:get|post|put|delete|patch)\([\'"]\/(.*?)[\'"]', re.IGNORECASE)
+
         for i, current_review in enumerate(raw_reviews):
             vulns = current_review.get("vulnerabilities", [])
             total_vulns += len(vulns)
             m_score = current_review.get("metrics", {}).get("maintainability", 8.0)
             maint_scores.append(m_score)
+
             content = request.files[i].content if i < len(request.files) else None
             if content:
                 matches = api_regex.findall(content)
                 for match in matches:
                     found_apis.add(f"/{match}")
+
         num_files = len(maint_scores)
         avg_maint = (sum(maint_scores) / num_files) if num_files > 0 else 0.0
         health_score = calculate_repo_health(total_vulns, avg_maint)
+
         return {
             "repo_health": health_score,
             "health_label": "Excellent" if health_score > 85 else "Good" if health_score > 60 else "Critical",
@@ -156,6 +199,7 @@ async def get_dashboard_stats(request: BatchReviewRequest):
         logger.error(f"Stats failed: {e}")
         raise HTTPException(status_code=500, detail="Failed to aggregate metrics")
 
+
 @app.post("/analyze-file")
 async def analyze_file(request: FileRequest):
     try:
@@ -174,6 +218,7 @@ async def analyze_file(request: FileRequest):
             raise HTTPException(status_code=429, detail="Limit Reached")
         raise HTTPException(status_code=500, detail=str(e))
 
+
 @app.post("/semantic-search")
 async def semantic_search(request: SearchRequest):
     try:
@@ -187,16 +232,19 @@ async def semantic_search(request: SearchRequest):
     except Exception as e:
         raise HTTPException(status_code=500, detail=str(e))
 
+
 @app.post("/chat")
 async def chat(request: ChatRequest):
     try:
         context_str = ""
         for item in request.context:
             context_str += f"--- FILE: {item['fileName']} ---\n{item['content']}\n\n"
+
         prompt = f"""You are "GitGud AI", an expert software architect.
 Repository: "{request.repoName}"
 CONTEXT: {context_str if request.context else "(NO CODE PROVIDED)"}
 USER QUESTION: {request.query}"""
+
         response = llm_engine.generate_text(prompt)
         return {"response": response, "status": "success"}
     except Exception as e:
@@ -204,6 +252,7 @@ USER QUESTION: {request.query}"""
             return {"response": "⚠️ Daily limit reached. Try again in a bit!", "status": "quota_error"}
         raise HTTPException(status_code=500, detail=str(e))
 
+
 @app.post("/generate-guide")
 async def generate_guide(request: GuideRequest):
     try:
@@ -222,6 +271,71 @@ async def generate_guide(request: GuideRequest):
             raise HTTPException(status_code=429, detail="AI Quota Exceeded")
         raise HTTPException(status_code=500, detail=str(e))
 
+
+# ──────────────────────────────────────────────
+# Sandbox / Danger Zone Endpoints (new)
+# ──────────────────────────────────────────────
+
+@app.post("/sandbox/simulate-destructive-action")
+async def simulate_danger(request: DestructiveActionRequest):
+    try:
+        result = DangerZoneService.simulate_destructive_action(
+            owner=request.repoOwner,
+            repo_name=request.repoName,
+            action=request.action,
+            target_ref=request.targetRef,
+            current_local_shas=request.currentLocalCommits or [],
+        )
+        return result
+    except Exception as e:
+        logger.error(f"Danger zone simulation failed: {e}", exc_info=True)
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@app.post("/sandbox/review-practice-pr")
+async def review_practice(request: ReviewRequest):
+    """
+    Reuses the exact same AIReviewerService that powers /review-batch-code.
+    """
+    try:
+        loop = asyncio.get_running_loop()
+        results = await loop.run_in_executor(executor, sync_review_worker, request.files)
+        if not isinstance(results, list):
+            results = [results]
+
+        # One-sentence overall verdict
+        verdict_prompt = (
+            f"Give a single short sentence verdict on this practice PR. "
+            f"Be encouraging but honest. Results summary: {str(results)[:600]}"
+        )
+        try:
+            summary = llm_engine.generate(verdict_prompt, max_tokens=60)
+        except Exception:
+            summary = "Practice review completed."
+
+        return {
+            "results": results,
+            "isPractice": True,
+            "summary": summary.strip() if isinstance(summary, str) else "Practice review completed."
+        }
+    except Exception as e:
+        logger.error(f"Practice PR review failed: {e}", exc_info=True)
+        raise HTTPException(status_code=500, detail="Practice review failed")
+
+
+@app.get("/sandbox/repo-conventions")
+async def get_repo_conventions(owner: str, repo: str):
+    try:
+        return await convention_service.get_conventions(owner, repo)
+    except Exception as e:
+        logger.error(f"Conventions failed: {e}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+# ──────────────────────────────────────────────
+# Entry point
+# ──────────────────────────────────────────────
+
 if __name__ == "__main__":
     port = int(os.environ.get("PORT", 7860))
     uvicorn.run(app, host="0.0.0.0", port=port)