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docs(README): update ReMe results table and remove unused code
- Update the ReMe results table in README_ZH.md for better readability - Remove unused and outdated code in trajectory_preprocess_op.py
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2 changed files with 6 additions and 35 deletions
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@ -229,10 +229,10 @@ Pass@K 衡量的是在生成的 K 个样本中,至少有一个成功完成任
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我们在 BFCL-V3 multi-turn-base (随机划分50train/150val) 上使用 qwen3-8b 测试 ReMe:
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| 方法 | pass@1 | pass@2 | pass@4 |
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|---------------------|-----------|-------------|-----------|
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| 不使用 ReMe (baseline) | 0.2472 | 0.2733 | 0.2922 |
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| **使用 ReMe** | 0.3061 **(+5.89%)** | 0.3500 **(+7.67%)** | 0.3888 **(+9.66%)** |
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| 方法 | pass@1 | pass@2 | pass@4 |
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|--------------|---------------------|---------------------|---------------------|
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| without Reme | 0.2472 | 0.2733 | 0.2922 |
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| with Reme | 0.3061 **(+5.89%)** | 0.3500 **(+7.67%)** | 0.3888 **(+9.66%)** |
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## 📚 相关资源
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@ -1,4 +1,3 @@
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import json
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from typing import List, Dict
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from flowllm import C, BaseOp
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@ -14,15 +13,7 @@ class TrajectoryPreprocessOp(BaseOp):
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def execute(self):
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"""Preprocess trajectories: validate and classify"""
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trajectories: list = self.context.get("trajectories", [])
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# trajectories: List[Trajectory] = [Trajectory(**x) if isinstance(x, dict) else x for x in trajectories]
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new_trajectories: List[Trajectory] = []
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for x in trajectories:
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if isinstance(x, dict):
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x["messages"] = self._modify_tool_calls(x["messages"])
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new_trajectories.append(Trajectory(**x))
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else:
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new_trajectories.append(x)
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trajectories = new_trajectories
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trajectories: List[Trajectory] = [Trajectory(**x) if isinstance(x, dict) else x for x in trajectories]
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# Classify trajectories
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classified = self._classify_trajectories(trajectories)
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@ -53,24 +44,4 @@ class TrajectoryPreprocessOp(BaseOp):
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'success': success_trajectories,
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'failure': failure_trajectories,
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'all': trajectories
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}
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def _modify_tool_calls(self, messages: List[Dict]) -> List[Dict]:
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new_messages = []
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for msg in messages:
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if 'tool_calls' in msg:
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processed_tool_calls = []
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for tool_call in msg['tool_calls']:
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tool_type = tool_call.get("type", "function")
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nested_data = tool_call.get(tool_type, {})
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tool_call.update({
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"arguments": json.loads(nested_data.get("arguments", "")),
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"name": nested_data.get("name", "")
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})
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tool_call.pop(tool_type)
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processed_tool_calls.append(tool_call)
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msg['tool_calls'] = processed_tool_calls
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new_messages.append(msg)
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return new_messages
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}
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