imbajin commented on code in PR #301:
URL:
https://github.com/apache/incubator-hugegraph-ai/pull/301#discussion_r2447068104
##########
hugegraph-llm/pyproject.toml:
##########
@@ -85,3 +86,4 @@ allow-direct-references = true
[tool.uv.sources]
hugegraph-python-client = { workspace = true }
+pycgraph = { git = "https://github.com/ChunelFeng/CGraph.git";, subdirectory =
"python", rev = "main", marker = "sys_platform == 'linux'" }
Review Comment:
‼️ **Critical: Platform-specific dependency with insufficient error
handling**
The `pycgraph` dependency is marked with `marker = "sys_platform ==
'linux'"`, meaning it will only install on Linux systems. However, the code
imports and uses `PyCGraph` unconditionally without any platform checks or
error handling.
**Impact:** The application will crash immediately on non-Linux systems
(macOS, Windows) when trying to import modules from `hugegraph_llm.flows`.
**Recommendation:**
1. Add platform compatibility checks and graceful degradation
2. Provide clear error messages for unsupported platforms
3. Consider making CGraph support optional with a feature flag
4. Document platform requirements in README/docs
##########
hugegraph-llm/src/hugegraph_llm/flows/scheduler.py:
##########
@@ -0,0 +1,90 @@
+# 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 threading
+from typing import Dict, Any
+from PyCGraph import GPipelineManager
+from hugegraph_llm.flows.build_vector_index import BuildVectorIndexFlow
+from hugegraph_llm.flows.common import BaseFlow
+from hugegraph_llm.flows.graph_extract import GraphExtractFlow
+from hugegraph_llm.utils.log import log
+
+
+class Scheduler:
+ pipeline_pool: Dict[str, Any] = None
+ max_pipeline: int
+
+ def __init__(self, max_pipeline: int = 10):
+ self.pipeline_pool = {}
+ # pipeline_pool act as a manager of GPipelineManager which used for
pipeline management
+ self.pipeline_pool["build_vector_index"] = {
+ "manager": GPipelineManager(),
+ "flow": BuildVectorIndexFlow(),
+ }
+ self.pipeline_pool["graph_extract"] = {
+ "manager": GPipelineManager(),
+ "flow": GraphExtractFlow(),
+ }
+ self.max_pipeline = max_pipeline
+
+ # TODO: Implement Agentic Workflow
+ def agentic_flow(self):
+ pass
+
+ def schedule_flow(self, flow: str, *args, **kwargs):
Review Comment:
‼️ **Critical: Missing thread safety in pipeline access**
The `schedule_flow` method accesses and modifies the pipeline pool without
proper synchronization. While `SchedulerSingleton` uses a lock for instance
creation, the `schedule_flow` method itself doesn't protect concurrent access
to the shared `pipeline_pool` dictionary.
**Race condition scenarios:**
1. Multiple threads calling `schedule_flow` for the same flow type
2. Concurrent `fetch()` and `release()` operations on the same manager
3. Pipeline state corruption during concurrent runs
**Recommendation:**
Add proper locking around pipeline operations:
```python
def schedule_flow(self, flow: str, *args, **kwargs):
if flow not in self.pipeline_pool:
raise ValueError(f"Unsupported workflow {flow}")
with threading.Lock(): # Add lock here
manager = self.pipeline_pool[flow]["manager"]
# ... rest of the logic
```
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