feat(evidence): contribute to semantic stages (#42)

harness/tht/adapters/vector/qdrant.py

@@ -143,7 +143,13 @@ class QdrantVectorStore:
         filter_must.append(self._semantic_kind_filter(allowed_record_kinds))
         filter_must.append({"key": "record_kind", "match": {"any": allowed_record_kinds}})
         if metadata_filter is not None:
-            if set(metadata_filter) != {"vector_generation", "document_ids", "workspace_id"}:
+            allowed_filters = {
+                "vector_generation", "document_ids", "workspace_id", "purpose",
+                "required_kinds", "required_concepts", "required_tables", "required_columns",
+            }
+            if not {"vector_generation", "document_ids", "workspace_id"} <= set(metadata_filter) or (
+                set(metadata_filter) - allowed_filters
+            ):
                 raise VectorStoreError("Unsupported vector metadata filter")
             generation = metadata_filter["vector_generation"]
             document_ids = metadata_filter["document_ids"]
@@ -160,6 +166,25 @@ class QdrantVectorStore:
                 {"key": "vector_generation", "match": {"value": generation}},
                 {"key": "document_id", "match": {"any": document_ids}},
             ])
+            purpose = metadata_filter.get("purpose")
+            if purpose is not None:
+                if not isinstance(purpose, str):
+                    raise VectorStoreError("Invalid vector metadata filter")
+                filter_must.append({"key": "purposes", "match": {"value": purpose}})
+            required_kinds = metadata_filter.get("required_kinds", [])
+            if not isinstance(required_kinds, list) or not all(isinstance(item, str) for item in required_kinds):
+                raise VectorStoreError("Invalid vector metadata filter")
+            if required_kinds:
+                filter_must.append({"key": "evidence_kind", "match": {"any": required_kinds}})
+            for filter_key, payload_key in (
+                ("required_concepts", "scope.concepts"),
+                ("required_tables", "scope.tables"),
+                ("required_columns", "scope.columns"),
+            ):
+                values = metadata_filter.get(filter_key, [])
+                if not isinstance(values, list) or not all(isinstance(item, str) for item in values):
+                    raise VectorStoreError("Invalid vector metadata filter")
+                filter_must.extend({"key": payload_key, "match": {"value": item}} for item in values)
         if query_text is None:
             if allowed_record_kinds == ["evidence"]:
                 raise VectorStoreError("Evidence hybrid query text is required")