Merge dev into main

.github/workflows/ci.yml

@@ -38,7 +38,7 @@ jobs:
         run: black --check src/
 
       - name: Type check
-        run: mypy src/ || true
+        run: mypy src/
 
       - name: Run tests
         run: pytest

pyproject.toml

@@ -39,3 +39,13 @@ python_version = "3.11"
 warn_return_any = true
 warn_unused_configs = true
 
+[[tool.mypy.overrides]]
+module = [
+    "boto3",
+    "botocore.exceptions",
+    "torch",
+    "httpx",
+    "ollama",
+]
+ignore_missing_imports = true
+

src/deepiri_modelkit/contracts/models.py

@@ -112,7 +112,7 @@ def validate_aimodel(value: Any) -> Any:
 
             return value
 
-        def serialize_aimodel(value: Any) -> Dict[str, Any]:
+        def serialize_aimodel(value: Any) -> Optional[Dict[str, Any]]:
             """Serialize AIModel instance to dict"""
             if value is None:
                 return None

src/deepiri_modelkit/contracts/services.py

@@ -2,7 +2,7 @@
 Service contracts and interfaces
 """
 
-from typing import Protocol, Dict, Any, Optional
+from typing import Any, Callable, Dict, Optional, Protocol
 from pydantic import BaseModel
 
 
@@ -38,7 +38,10 @@ def publish(self, topic: str, event: Dict[str, Any]) -> bool:
         ...
 
     def subscribe(
-        self, topic: str, callback: callable, consumer_group: Optional[str] = None
+        self,
+        topic: str,
+        callback: Callable[[Dict[str, Any]], Any],
+        consumer_group: Optional[str] = None,
     ) -> None:
         """Subscribe to topic with callback"""
         ...

src/deepiri_modelkit/data/monitoring.py

@@ -35,7 +35,7 @@ def __init__(self, log_dir: str = "./logs/dataset_monitoring"):
         self.alerts_file = self.log_dir / "alerts.jsonl"
 
         # In-memory metrics for quick access
-        self.current_metrics = {
+        self.current_metrics: Dict[str, Any] = {
             "total_versions_created": 0,
             "total_datasets_tracked": 0,
             "average_version_creation_time": 0,
@@ -159,7 +159,7 @@ def get_usage_analytics(self, days: int = 30) -> Dict[str, Any]:
         """Get usage analytics for the specified period."""
         cutoff_date = datetime.utcnow() - timedelta(days=days)
 
-        analytics = {
+        analytics: Dict[str, Any] = {
             "period_days": days,
             "version_creations": [],
             "training_runs": [],

src/deepiri_modelkit/data/validation.py

@@ -93,7 +93,7 @@ def validate_dataset(self, data_path: Path) -> Dict[str, Any]:
             "Starting dataset validation", path=str(data_path), type=self.dataset_type
         )
 
-        results = {
+        results: Dict[str, Any] = {
             "is_valid": True,
             "errors": [],
             "warnings": [],

src/deepiri_modelkit/ml/semantic.py

@@ -48,7 +48,7 @@ def __init__(
     ):
         self.ollama_base_url = ollama_base_url
         self.model = model
-        self._cache = {}  # Cache for semantic analysis results
+        self._cache: dict[str, list[str]] = {}  # Cache for semantic analysis results
 
     def _call_ollama(
         self, prompt: str, timeout: float = 15.0
@@ -66,7 +66,7 @@ def _call_ollama(
                         "num_predict": 100,  # Reduced from 200 for faster responses
                     },
                 )
-                return response.get("response", "").strip()
+                return str(response.get("response", "")).strip()
             except Exception:
                 # Fall back to HTTP
                 pass
@@ -93,7 +93,7 @@ def _call_ollama(
                 if response.status_code == 200:
                     result = response.json()
                     logger.debug("Ollama HTTP call succeeded")
-                    return result.get("response", "").strip()
+                    return str(result.get("response", "")).strip()
                 else:
                     logger.debug(
                         f"Ollama HTTP call failed: HTTP {response.status_code}"
@@ -118,7 +118,7 @@ def _call_ollama(
                 if response.status_code == 200:
                     result = response.json()
                     logger.debug("Ollama HTTP call succeeded")
-                    return result.get("response", "").strip()
+                    return str(result.get("response", "")).strip()
                 else:
                     logger.debug(
                         f"Ollama HTTP call failed: HTTP {response.status_code}"
@@ -305,7 +305,9 @@ def analyze_semantic_structure(self, text: str) -> Dict:
             try:
                 json_match = re.search(r"\{.*?\}", response, re.DOTALL)
                 if json_match:
-                    return json.loads(json_match.group())
+                    parsed = json.loads(json_match.group())
+                    if isinstance(parsed, dict):
+                        return parsed
             except Exception:
                 pass
 
@@ -333,10 +335,10 @@ def check_ollama_available(self) -> bool:
         try:
             if HAS_HTTPX:
                 response = httpx.get(f"{self.ollama_base_url}/api/tags", timeout=5.0)
-                return response.status_code == 200
+                return bool(response.status_code == 200)
             elif HAS_REQUESTS:
                 response = requests.get(f"{self.ollama_base_url}/api/tags", timeout=5.0)
-                return response.status_code == 200
+                return bool(response.status_code == 200)
         except Exception:
             pass
 
@@ -349,8 +351,10 @@ def get_semantic_analyzer(
     """
     Factory function to get semantic analyzer
     """
-    base_url = ollama_base_url or os.getenv("OLLAMA_BASE_URL", "http://localhost:11434")
-    model_name = model or os.getenv("OLLAMA_MODEL", "llama3:8b")
+    base_url = (
+        ollama_base_url or os.getenv("OLLAMA_BASE_URL") or "http://localhost:11434"
+    )
+    model_name = model or os.getenv("OLLAMA_MODEL") or "llama3:8b"
 
     analyzer = SemanticAnalyzer(ollama_base_url=base_url, model=model_name)