fixes

repos/generation_repo.py

@@ -65,6 +65,8 @@ class GenerationRepo:
             args["status"] = status
         if created_by is not None:
             args["created_by"] = created_by
+            if project_id is None:
+                args["project_id"] = None
         if project_id is not None:
             args["project_id"] = project_id
         if idea_id is not None:
@@ -92,6 +94,121 @@ class GenerationRepo:
     async def update_generation(self, generation: Generation, ):
         res = await self.collection.update_one({"_id": ObjectId(generation.id)}, {"$set": generation.model_dump()})
 
+    async def get_usage_stats(self, created_by: Optional[str] = None, project_id: Optional[str] = None) -> dict:
+        """
+        Calculates usage statistics (runs, tokens, cost) using MongoDB aggregation.
+        """
+        pipeline = []
+        
+        # 1. Match active done generations
+        match_stage = {"is_deleted": False, "status": GenerationStatus.DONE}
+        if created_by:
+            match_stage["created_by"] = created_by
+        if project_id:
+            match_stage["project_id"] = project_id
+            
+        pipeline.append({"$match": match_stage})
+        
+        # 2. Group by null (total)
+        pipeline.append({
+            "$group": {
+                "_id": None,
+                "total_runs": {"$sum": 1},
+                "total_tokens": {
+                    "$sum": {
+                        "$cond": [
+                            {"$and": [{"$gt": ["$input_token_usage", 0]}, {"$gt": ["$output_token_usage", 0]}]},
+                            {"$add": ["$input_token_usage", "$output_token_usage"]},
+                            {"$ifNull": ["$token_usage", 0]}
+                        ]
+                    }
+                },
+                "total_input_tokens": {"$sum": {"$ifNull": ["$input_token_usage", 0]}},
+                "total_output_tokens": {"$sum": {"$ifNull": ["$output_token_usage", 0]}},
+                "total_cost": {
+                    "$sum": {
+                        "$add": [
+                            {"$multiply": [{"$ifNull": ["$input_token_usage", 0]}, 0.000002]},
+                            {"$multiply": [{"$ifNull": ["$output_token_usage", 0]}, 0.00012]}
+                        ]
+                    }
+                }
+            }
+        })
+        
+        cursor = self.collection.aggregate(pipeline)
+        res = await cursor.to_list(1)
+        
+        if not res:
+            return {
+                "total_runs": 0,
+                "total_tokens": 0,
+                "total_input_tokens": 0,
+                "total_output_tokens": 0,
+                "total_cost": 0.0
+            }
+            
+        result = res[0]
+        result.pop("_id")
+        result["total_cost"] = round(result["total_cost"], 4)
+        return result
+
+    async def get_usage_breakdown(self, group_by: str = "created_by", project_id: Optional[str] = None, created_by: Optional[str] = None) -> List[dict]:
+        """
+        Returns usage statistics grouped by user or project.
+        """
+        pipeline = []
+        
+        match_stage = {"is_deleted": False, "status": GenerationStatus.DONE}
+        if project_id:
+            match_stage["project_id"] = project_id
+        if created_by:
+            match_stage["created_by"] = created_by
+            
+        pipeline.append({"$match": match_stage})
+        
+        pipeline.append({
+            "$group": {
+                "_id": f"${group_by}",
+                "total_runs": {"$sum": 1},
+                "total_tokens": {
+                    "$sum": {
+                        "$cond": [
+                            {"$and": [{"$gt": ["$input_token_usage", 0]}, {"$gt": ["$output_token_usage", 0]}]},
+                            {"$add": ["$input_token_usage", "$output_token_usage"]},
+                            {"$ifNull": ["$token_usage", 0]}
+                        ]
+                    }
+                },
+                "total_input_tokens": {"$sum": {"$ifNull": ["$input_token_usage", 0]}},
+                "total_output_tokens": {"$sum": {"$ifNull": ["$output_token_usage", 0]}},
+                "total_cost": {
+                    "$sum": {
+                        "$add": [
+                            {"$multiply": [{"$ifNull": ["$input_token_usage", 0]}, 0.000002]},
+                            {"$multiply": [{"$ifNull": ["$output_token_usage", 0]}, 0.00012]}
+                        ]
+                    }
+                }
+            }
+        })
+        
+        pipeline.append({"$sort": {"total_cost": -1}})
+        
+        cursor = self.collection.aggregate(pipeline)
+        res = await cursor.to_list(None)
+        
+        results = []
+        for item in res:
+            entity_id = item.pop("_id")
+            item["total_cost"] = round(item["total_cost"], 4)
+            results.append({
+                "entity_id": str(entity_id) if entity_id else "unknown",
+                "stats": item
+            })
+            
+        return results
+
     async def get_generations_by_group(self, group_id: str) -> List[Generation]:
         res = await self.collection.find({"generation_group_id": group_id, "is_deleted": False}).sort("created_at", 1).to_list(None)
         generations: List[Generation] = []