Bug 1: chat_json() was passing response_format={'type': 'json_object'}
to the LLM, which enforces JSON grammar from token 0. Reasoning
models (Qwen3, DeepSeek-R1, etc.) generate <think>...</think> blocks
before JSON output, causing garbled results. The fix removes the
response_format parameter since the system prompt already requests
JSON output and the existing <think> cleanup handles any remaining
tags.
Bug 2: ontology_generator hardcoded max_tokens=4096, causing
truncation for models with larger context windows. Increased to
16384 to accommodate reasoning model outputs.
Fixes#642
The language instruction was causing LLM to change entity/relation naming
conventions. Now explicitly enforce PascalCase/UPPER_SNAKE_CASE for technical
identifiers while only applying language preference to description fields.
- Updated `run.py` to conditionally print startup information only in the reloader process to avoid duplicate logs in debug mode.
- Modified `__init__.py` to log startup and completion messages based on the reloader process condition.
- Added warnings suppression in `graph_builder.py` for Pydantic v2 regarding Field usage.
- Revised `ontology_generator.py` to enforce strict design guidelines for entity types and relationships, ensuring compliance with new requirements.
- Improved logging behavior in `logger.py` to prevent log propagation to the root logger, avoiding duplicate outputs.
Md_Mushfiqur Rahim
BaiFu
ghostubborn