winning commit we are comming to banglore be prepared meta

pyproject.toml

@@ -14,6 +14,7 @@ dependencies = [
     "openai>=1.76.0",
     "openenv-core[core]>=0.2.2",
     "pytest>=8.0.0",
+    "streamlit>=1.44.0",
     "torch>=2.2.0",
     "transformers>=4.45.0",
     "uvicorn>=0.30.0",
@@ -34,5 +35,12 @@ packages = [
     "python_env.server",
     "python_env.tasks",
     "python_env.graders",
+    "python_env.api",
+    "python_env.app",
+    "python_env.analyzers",
+    "python_env.models",
+    "python_env.schemas",
+    "python_env.services",
+    "python_env.utils",
 ]
-package-dir = { "python_env" = ".", "python_env.server" = "server", "python_env.tasks" = "tasks", "python_env.graders" = "graders" }
+package-dir = { "python_env" = ".", "python_env.server" = "server", "python_env.tasks" = "tasks", "python_env.graders" = "graders", "python_env.api" = "api", "python_env.app" = "app", "python_env.analyzers" = "analyzers", "python_env.models" = "models", "python_env.schemas" = "schemas", "python_env.services" = "services", "python_env.utils" = "utils" }

services/analysis_service.py

@@ -79,8 +79,18 @@ class AnalysisService:
             combined_scores[domain] = round((0.6 * model_score) + (0.4 * heuristic_score), 4)
 
         detected_domain = request.domain_hint if request.domain_hint != "auto" else max(combined_scores, key=combined_scores.get)
-        analyzer = self._analyzers.get(detected_domain, analyze_dsa_code if detected_domain == "dsa" else analyze_web_code)
-        domain_analysis = analyzer(request.code, parsed, complexity) if detected_domain in self._analyzers else DomainAnalysis(domain="general", domain_score=0.6, issues=[], suggestions=["Add stronger domain-specific context for deeper analysis."], highlights={})
+        analyzer = self._analyzers.get(detected_domain)
+        domain_analysis = (
+            analyzer(request.code, parsed, complexity)
+            if analyzer is not None
+            else DomainAnalysis(
+                domain="general",
+                domain_score=0.6,
+                issues=[],
+                suggestions=["Add stronger domain-specific context for deeper analysis."],
+                highlights={},
+            )
+        )
 
         lint_score = _lint_score(parsed)
         score_breakdown = self.reward_service.compute(