inegrated the ai agent

app/routers/code_scan.py

@@ -0,0 +1,91 @@
+import logging
+import uuid
+import json
+from fastapi import APIRouter, HTTPException
+from typing import Dict, Any
+
+from app.schemas.code_scan import CodeScanRequest, CodeScanResponse, CodeChatRequest, CodeChatResponse
+from app.services.code_scanner.orchestrator import CodeScanOrchestrator, client
+from app.config import settings
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(tags=["code-scan"])
+
+# In-memory store for scan results to support chat context.
+# In a real production app, this would be stored in the database.
+scan_store: Dict[str, CodeScanResponse] = {}
+
+@router.post("/code-scan/analyze", response_model=CodeScanResponse)
+async def analyze_codebase(request: CodeScanRequest):
+    logger.info(f"Starting code scan for {request.repo_url}")
+    
+    try:
+        orchestrator = CodeScanOrchestrator(
+            repo_url=request.repo_url,
+            github_token=request.github_token,
+            branch=request.branch or "main"
+        )
+        
+        # 1. Fetch repo structure
+        all_files = await orchestrator.github.get_repo_tree(request.repo_url, request.branch or "main")
+        
+        # 2. Triage files
+        triaged_files = await orchestrator.triage_files(all_files)
+        logger.info(f"Triaged {len(triaged_files)} files out of {len(all_files)}.")
+        
+        # 3. Analyze triaged files
+        vulnerabilities = await orchestrator.analyze_files(triaged_files)
+        
+        # 4. Generate Summary
+        summary = await orchestrator.generate_summary(vulnerabilities)
+        
+        scan_id = str(uuid.uuid4())
+        
+        response = CodeScanResponse(
+            scan_id=scan_id,
+            repo_url=request.repo_url,
+            summary=summary,
+            issues=vulnerabilities
+        )
+        
+        # Save to in-memory store for the chat feature
+        scan_store[scan_id] = response
+        
+        return response
+    except Exception as e:
+        logger.error(f"Code scan failed: {str(e)}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+@router.post("/code-scan/chat", response_model=CodeChatResponse)
+async def chat_with_scan(request: CodeChatRequest):
+    if not settings.openai_api_key:
+        raise HTTPException(status_code=400, detail="AI Chat is disabled because OPENAI_API_KEY is not configured.")
+        
+    scan_data = scan_store.get(request.scan_id)
+    if not scan_data:
+        raise HTTPException(status_code=404, detail="Scan ID not found or expired.")
+        
+    system_prompt = (
+        "You are SecureLens AI, an expert application security assistant. "
+        "You are helping a developer understand a security scan report for their codebase. "
+        f"Here is the context of the scan for the repository {scan_data.repo_url}:\n"
+        f"Summary: {scan_data.summary}\n"
+        f"Vulnerabilities: {json.dumps([v.model_dump() for v in scan_data.issues])}\n\n"
+        "Answer the user's questions clearly, concisely, and professionally. Provide code fixes if requested."
+    )
+
+    try:
+        response = await client.chat.completions.create(
+            model="gpt-3.5-turbo",
+            messages=[
+                {"role": "system", "content": system_prompt},
+                {"role": "user", "content": request.message}
+            ],
+            temperature=0.5,
+        )
+        reply = response.choices[0].message.content or "No response from AI."
+        return CodeChatResponse(reply=reply)
+    except Exception as e:
+        logger.error(f"AI Chat Error: {str(e)}")
+        raise HTTPException(status_code=500, detail="I encountered an error trying to process your request.")