Copilot commented on code in PR #351:
URL: https://github.com/apache/hugegraph-ai/pull/351#discussion_r3353258311


##########
hugegraph-llm/src/hugegraph_llm/api/models/graph_extract_requests.py:
##########
@@ -0,0 +1,105 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+import json
+from typing import Any, Dict, List, Literal, Optional, Union
+
+from fastapi import Query
+from pydantic import BaseModel, ConfigDict, Field, field_validator, 
model_validator
+
+
+class GraphExtractClientConfig(BaseModel):
+    model_config = ConfigDict(extra="forbid")
+
+    graph: Optional[str] = None
+    user: Optional[str] = None
+    pwd: Optional[str] = None
+    gs: Optional[str] = None
+
+
+class GraphExtractRequest(BaseModel):
+    model_config = ConfigDict(populate_by_name=True)
+
+    texts: Union[str, List[str]] = Field(..., description="Text or list of 
texts to extract a graph from.")
+    graph_schema: Union[str, Dict[str, Any]] = Field(
+        ...,
+        alias="schema",
+        description="Graph schema as a JSON string/object, or an existing 
graph name.",
+    )
+    example_prompt: Optional[str] = Query(None, description="Optional graph 
extraction prompt header.")
+    extract_type: Literal["property_graph"] = Query("property_graph", 
description="Extraction type.")
+    language: Literal["zh", "en"] = Query("zh", description="Language for 
chunk splitting.")
+    split_type: Literal["document", "paragraph", "sentence"] = 
Query("document", description="Chunk split granularity.")
+    include_meta: bool = Query(False, description="Include vertex/edge/text 
counts in the response.")
+    client_config: Optional[GraphExtractClientConfig] = Field(None, 
description="Request-scoped HugeGraph connection.")
+
+    @field_validator("texts")
+    @classmethod
+    def normalize_texts(cls, v):
+        items = [v] if isinstance(v, str) else list(v)
+        items = [t for t in items if t and t.strip()]
+        if not items:
+            raise ValueError("texts must not be empty.")
+        return items
+
+    @field_validator("graph_schema")
+    @classmethod
+    def normalize_schema(cls, v):
+        def validate_schema_obj(schema_obj):
+            if not isinstance(schema_obj, dict):
+                raise ValueError("schema JSON must be an object.")
+            if "vertexlabels" not in schema_obj or "edgelabels" not in 
schema_obj:
+                raise ValueError("schema must contain 'vertexlabels' and 
'edgelabels'.")
+            if not isinstance(schema_obj["vertexlabels"], list) or not 
isinstance(schema_obj["edgelabels"], list):
+                raise ValueError("'vertexlabels' and 'edgelabels' must be 
lists.")

Review Comment:
   `schema` validation is too shallow: it only checks that 
`vertexlabels`/`edgelabels` exist and are lists, but it does not validate the 
per-label structure (`name`, `properties`, `source_label`, `target_label`, 
etc.). Invalid inline schemas that pass this validator will later be rejected 
by `CheckSchema` in `SchemaNode` and end up as a scheduler/pipeline error (500) 
instead of the intended 422 validation error.



##########
hugegraph-llm/src/hugegraph_llm/state/ai_state.py:
##########
@@ -26,6 +26,8 @@ class WkFlowInput(GParam):
     split_type: Optional[str] = None  # split type used by ChunkSplit Node
     example_prompt: Optional[str] = None  # need by graph information extract
     schema: Optional[str] = None  # Schema information requeired by SchemaNode
+    # Request-scoped HugeGraph connection; None falls back to global 
huge_settings.
+    graph_client_config: Optional[Dict[str, Any]] = None
     data_json: Optional[Dict[str, Any]] = None

Review Comment:
   `WkFlowInput` adds `graph_client_config`, but `reset()` does not clear it. 
If the underlying `pycgraph` runtime reuses `GParam` instances and calls 
`reset()`, this field could retain request-scoped connection info across runs. 
Please update `reset()` to set `self.graph_client_config = None` alongside the 
other cleared fields.



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