From 99b8a119b082298b15d8677ef333115558b98d34 Mon Sep 17 00:00:00 2001
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Date: Sat, 25 Jul 2026 06:35:10 +0800
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Model: MaliDDD/openai_us4_500_8B
Source: Original Platform
---
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 tokenizer.json                                |   3 +
 tokenizer_config.json                         |  73 ++++
 train_raw_trace.jsonl                         | 400 ++++++++++++++++++
 420 files changed, 2990 insertions(+)
 create mode 100644 .gitattributes
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 create mode 100644 config.json
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 create mode 100644 grpo_full/config.json
 create mode 100644 grpo_full/fail_buffer.jsonl
 create mode 100644 grpo_full/generation_config.json
 create mode 100644 grpo_full/manager_run_config.json
 create mode 100644 grpo_full/tokenizer.json
 create mode 100644 grpo_full/tokenizer_config.json
 create mode 100644 grpo_full/train_raw_trace.jsonl
 create mode 100644 manager_run_config.json
 create mode 100644 model.safetensors
 create mode 100644 tokenizer.json
 create mode 100644 tokenizer_config.json
 create mode 100644 train_raw_trace.jsonl

diff --git a/.gitattributes b/.gitattributes
new file mode 100644
index 0000000..0986efb
--- /dev/null
+++ b/.gitattributes
@@ -0,0 +1,37 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+grpo_full/tokenizer.json filter=lfs diff=lfs merge=lfs -text
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diff --git a/README.md b/README.md
new file mode 100644
index 0000000..7c0ef40
--- /dev/null
+++ b/README.md
@@ -0,0 +1,67 @@
+---
+base_model: Qwen/Qwen3-8B
+library_name: transformers
+model_name: grpo_full
+tags:
+- generated_from_trainer
+- trl
+- grpo
+licence: license
+---
+
+# Model Card for grpo_full
+
+This model is a fine-tuned version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B).
+It has been trained using [TRL](https://github.com/huggingface/trl).
+
+## Quick start
+
+```python
+from transformers import pipeline
+
+question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
+generator = pipeline("text-generation", model="None", device="cuda")
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
+print(output["generated_text"])
+```
+
+## Training procedure
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/madisonlijingxuan-ucla/agent_routing/runs/vz9kdbdh) 
+
+
+
+This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
+
+### Framework versions
+
+- TRL: 1.5.0
+- Transformers: 5.8.1
+- Pytorch: 2.12.0
+- Datasets: 4.8.5
+- Tokenizers: 0.22.2
+
+## Citations
+
+Cite GRPO as:
+
+```bibtex
+@article{shao2024deepseekmath,
+    title        = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
+    author       = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
+    year         = 2024,
+    eprint       = {arXiv:2402.03300},
+}
+```
+
+Cite TRL as:
+    
+```bibtex
+@software{vonwerra2020trl,
+  title   = {{TRL: Transformers Reinforcement Learning}},
+  author  = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
+  license = {Apache-2.0},
+  url     = {https://github.com/huggingface/trl},
+  year    = {2020}
+}
+```
\ No newline at end of file
diff --git a/chat_template.jinja b/chat_template.jinja
new file mode 100644
index 0000000..01be9b3
--- /dev/null
+++ b/chat_template.jinja
@@ -0,0 +1,89 @@
+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
+        {%- set ns.multi_step_tool = false %}
+        {%- set ns.last_query_index = index %}
+    {%- endif %}
+{%- endfor %}
+{%- for message in messages %}
+    {%- if message.content is string %}
+        {%- set content = message.content %}
+    {%- else %}
+        {%- set content = '' %}
+    {%- endif %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if loop.last or (not loop.last and reasoning_content) %}
+                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
+            {%- else %}
+                {{- '<|im_start|>' + message.role + '\n' + content }}
+            {%- endif %}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- endif %}
+{%- endif %}
\ No newline at end of file
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+{"ts": 1781928496, "example_id": 981, "ground_truth": "A", "pred": "B", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["rule_applier_tool", "reasoner_tool"], "last_assistant_text": "ANSWER_B"}
+{"ts": 1781928496, "example_id": 981, "ground_truth": "A", "pred": "B", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_B"}
+{"ts": 1781928528, "example_id": 817, "ground_truth": "A", "pred": "B", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_B"}
+{"ts": 1781928528, "example_id": 817, "ground_truth": "A", "pred": "B", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_B"}
+{"ts": 1781928609, "example_id": 170, "ground_truth": "C", "pred": "A", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_A"}
+{"ts": 1781928609, "example_id": 170, "ground_truth": "C", "pred": "A", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_A"}
+{"ts": 1781928706, "example_id": 826, "ground_truth": "A", "pred": "D", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_D"}
+{"ts": 1781928706, "example_id": 826, "ground_truth": "A", "pred": "D", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_D"}
+{"ts": 1781928734, "example_id": 1143, "ground_truth": "B", "pred": "C", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_C"}
+{"ts": 1781928734, "example_id": 1143, "ground_truth": "B", "pred": "C", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_C"}
+{"ts": 1781928798, "example_id": 1087, "ground_truth": "A", "pred": "B", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_B"}
+{"ts": 1781928798, "example_id": 1087, "ground_truth": "A", "pred": "B", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_B"}
+{"ts": 1781928832, "example_id": 506, "ground_truth": "A", "pred": "D", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_D"}
+{"ts": 1781928832, "example_id": 506, "ground_truth": "A", "pred": "D", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_D"}
+{"ts": 1781928935, "example_id": 1074, "ground_truth": "C", "pred": "B", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_B"}
+{"ts": 1781928935, "example_id": 1074, "ground_truth": "C", "pred": "B", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_B"}
+{"ts": 1781928999, "example_id": 525, "ground_truth": "B", "pred": "C", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_C"}
+{"ts": 1781928999, "example_id": 525, "ground_truth": "B", "pred": "C", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_C"}
+{"ts": 1781929027, "example_id": 648, "ground_truth": "B", "pred": "A", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_A"}
+{"ts": 1781929027, "example_id": 648, "ground_truth": "B", "pred": "A", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_A"}
+{"ts": 1781929216, "example_id": 553, "ground_truth": "D", "pred": "B", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_B"}
+{"ts": 1781929216, "example_id": 553, "ground_truth": "D", "pred": "B", "valid_format": true, "no_artifacts": true, "no_tc_in_final": true, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "last_assistant_text": "ANSWER_B"}
diff --git a/generation_config.json b/generation_config.json
new file mode 100644
index 0000000..e473d31
--- /dev/null
+++ b/generation_config.json
@@ -0,0 +1,12 @@
+{
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "pad_token_id": 151643,
+  "temperature": 0.6,
+  "top_k": 20,
+  "top_p": 0.95,
+  "transformers_version": "5.8.1"
+}
diff --git a/grpo_full/README.md b/grpo_full/README.md
new file mode 100644
index 0000000..7c0ef40
--- /dev/null
+++ b/grpo_full/README.md
@@ -0,0 +1,67 @@
+---
+base_model: Qwen/Qwen3-8B
+library_name: transformers
+model_name: grpo_full
+tags:
+- generated_from_trainer
+- trl
+- grpo
+licence: license
+---
+
+# Model Card for grpo_full
+
+This model is a fine-tuned version of [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B).
+It has been trained using [TRL](https://github.com/huggingface/trl).
+
+## Quick start
+
+```python
+from transformers import pipeline
+
+question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
+generator = pipeline("text-generation", model="None", device="cuda")
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
+print(output["generated_text"])
+```
+
+## Training procedure
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/madisonlijingxuan-ucla/agent_routing/runs/vz9kdbdh) 
+
+
+
+This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
+
+### Framework versions
+
+- TRL: 1.5.0
+- Transformers: 5.8.1
+- Pytorch: 2.12.0
+- Datasets: 4.8.5
+- Tokenizers: 0.22.2
+
+## Citations
+
+Cite GRPO as:
+
+```bibtex
+@article{shao2024deepseekmath,
+    title        = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
+    author       = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
+    year         = 2024,
+    eprint       = {arXiv:2402.03300},
+}
+```
+
+Cite TRL as:
+    
+```bibtex
+@software{vonwerra2020trl,
+  title   = {{TRL: Transformers Reinforcement Learning}},
+  author  = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
+  license = {Apache-2.0},
+  url     = {https://github.com/huggingface/trl},
+  year    = {2020}
+}
+```
\ No newline at end of file
diff --git a/grpo_full/chat_template.jinja b/grpo_full/chat_template.jinja
new file mode 100644
index 0000000..01be9b3
--- /dev/null
+++ b/grpo_full/chat_template.jinja
@@ -0,0 +1,89 @@
+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
+        {%- set ns.multi_step_tool = false %}
+        {%- set ns.last_query_index = index %}
+    {%- endif %}
+{%- endfor %}
+{%- for message in messages %}
+    {%- if message.content is string %}
+        {%- set content = message.content %}
+    {%- else %}
+        {%- set content = '' %}
+    {%- endif %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if loop.last or (not loop.last and reasoning_content) %}
+                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
+            {%- else %}
+                {{- '<|im_start|>' + message.role + '\n' + content }}
+            {%- endif %}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- endif %}
+{%- endif %}
\ No newline at end of file
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new file mode 100644
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new file mode 100644
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new file mode 100644
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new file mode 100644
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new file mode 100644
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new file mode 100644
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new file mode 100644
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diff --git a/grpo_full/generation_config.json b/grpo_full/generation_config.json
new file mode 100644
index 0000000..e473d31
--- /dev/null
+++ b/grpo_full/generation_config.json
@@ -0,0 +1,12 @@
+{
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "pad_token_id": 151643,
+  "temperature": 0.6,
+  "top_k": 20,
+  "top_p": 0.95,
+  "transformers_version": "5.8.1"
+}
diff --git a/grpo_full/manager_run_config.json b/grpo_full/manager_run_config.json
new file mode 100644
index 0000000..4db8589
--- /dev/null
+++ b/grpo_full/manager_run_config.json
@@ -0,0 +1,15 @@
+{
+  "base_model": "Qwen/Qwen3-8B",
+  "binding_mode": "environment",
+  "n_train_rows": 737,
+  "subagents": [
+    "extractor",
+    "reasoner",
+    "rule_applier"
+  ],
+  "manager_adapter": "/home/yizzhao/5.14-reasearch/outputs/manager/openai_us4_500_8B/sft_evolved",
+  "full_parameter_rl": true,
+  "subagent_server_url": "http://localhost:8000",
+  "routing_efficiency_bonus": 0.0,
+  "tool_use_bonus": 0.2
+}
\ No newline at end of file
diff --git a/grpo_full/tokenizer.json b/grpo_full/tokenizer.json
new file mode 100644
index 0000000..c7afbed
--- /dev/null
+++ b/grpo_full/tokenizer.json
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:be75606093db2094d7cd20f3c2f385c212750648bd6ea4fb2bf507a6a4c55506
+size 11422650
diff --git a/grpo_full/tokenizer_config.json b/grpo_full/tokenizer_config.json
new file mode 100644
index 0000000..0c559cd
--- /dev/null
+++ b/grpo_full/tokenizer_config.json
@@ -0,0 +1,73 @@
+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "is_local": true,
+  "local_files_only": false,
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "response_schema": {
+    "properties": {
+      "content": {
+        "type": "string"
+      },
+      "reasoning_content": {
+        "type": "string"
+      },
+      "role": {
+        "const": "assistant"
+      },
+      "tool_calls": {
+        "items": {
+          "properties": {
+            "function": {
+              "properties": {
+                "arguments": {
+                  "additionalProperties": {},
+                  "type": "object"
+                },
+                "name": {
+                  "type": "string"
+                }
+              },
+              "type": "object"
+            },
+            "type": {
+              "const": "function"
+            }
+          },
+          "type": "object",
+          "x-parser": "json",
+          "x-parser-args": {
+            "transform": "{type: 'function', function: @}"
+          }
+        },
+        "type": "array",
+        "x-regex-iterator": "<tool_call>\\s*(.+?)\\s*</tool_call>"
+      }
+    },
+    "type": "object",
+    "x-regex": "^(?:<think>\\n?(?:(?P<reasoning_content>.*?\\S.*?)\\n?|[\\s]*)</think>\\s*)?(?P<content>(?:(?!<tool_call>)[\\s\\S])*?)(?:\\n(?=<tool_call>))?(?=(?:<tool_call>|<\\|im_end\\|>|$))(?P<tool_calls>(?:<tool_call>(?:(?!</tool_call>)[\\s\\S])+</tool_call>\\s*)+)?\\s*(?:<\\|im_end\\|>|$)"
+  },
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}
diff --git a/grpo_full/train_raw_trace.jsonl b/grpo_full/train_raw_trace.jsonl
new file mode 100644
index 0000000..97cf73e
--- /dev/null
+++ b/grpo_full/train_raw_trace.jsonl
@@ -0,0 +1,400 @@
+{"ts": 1781919776, "example_id": 634, "ground_truth": "C", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "reasoner_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781919776, "example_id": 634, "ground_truth": "C", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781919851, "example_id": 640, "ground_truth": "D", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "reasoner_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781919851, "example_id": 640, "ground_truth": "D", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "reasoner_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781919895, "example_id": 1151, "ground_truth": "C", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "reasoner_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781919895, "example_id": 1151, "ground_truth": "C", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "reasoner_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781919942, "example_id": 1025, "ground_truth": "B", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781919942, "example_id": 1025, "ground_truth": "B", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920004, "example_id": 985, "ground_truth": "D", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920004, "example_id": 985, "ground_truth": "D", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "reasoner_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920048, "example_id": 580, "ground_truth": "D", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920048, "example_id": 580, "ground_truth": "D", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920109, "example_id": 500, "ground_truth": "B", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920109, "example_id": 500, "ground_truth": "B", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920169, "example_id": 552, "ground_truth": "B", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "reasoner_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920169, "example_id": 552, "ground_truth": "B", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920272, "example_id": 841, "ground_truth": "D", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "reasoner_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920272, "example_id": 841, "ground_truth": "D", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920337, "example_id": 1159, "ground_truth": "D", "pred": "D", "reward": 1.2, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["reasoner_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920337, "example_id": 1159, "ground_truth": "D", "pred": "D", "reward": 1.2, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["reasoner_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920391, "example_id": 796, "ground_truth": "B", "pred": "D", "reward": 0.0, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920391, "example_id": 796, "ground_truth": "B", "pred": "D", "reward": 0.0, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920434, "example_id": 617, "ground_truth": "B", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920434, "example_id": 617, "ground_truth": "B", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920515, "example_id": 748, "ground_truth": "B", "pred": "A", "reward": 0.0, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["reasoner_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920515, "example_id": 748, "ground_truth": "B", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920582, "example_id": 1048, "ground_truth": "A", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920582, "example_id": 1048, "ground_truth": "A", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920655, "example_id": 807, "ground_truth": "D", "pred": "A", "reward": 0.0, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920655, "example_id": 807, "ground_truth": "D", "pred": "A", "reward": 0.0, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920693, "example_id": 619, "ground_truth": "B", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920693, "example_id": 619, "ground_truth": "B", "pred": "A", "reward": 0.0, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920755, "example_id": 563, "ground_truth": "B", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["reasoner_tool", "rule_applier_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920755, "example_id": 563, "ground_truth": "B", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["rule_applier_tool", "reasoner_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920797, "example_id": 1125, "ground_truth": "C", "pred": "C", "reward": 1.2, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920797, "example_id": 1125, "ground_truth": "C", "pred": "C", "reward": 1.2, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920875, "example_id": 771, "ground_truth": "B", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920875, "example_id": 771, "ground_truth": "B", "pred": "B", "reward": 1.2, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920927, "example_id": 784, "ground_truth": "D", "pred": "D", "reward": 1.2, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920927, "example_id": 784, "ground_truth": "D", "pred": "D", "reward": 1.2, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920972, "example_id": 994, "ground_truth": "C", "pred": "D", "reward": 0.0, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781920972, "example_id": 994, "ground_truth": "C", "pred": "D", "reward": 0.0, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921020, "example_id": 652, "ground_truth": "B", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921020, "example_id": 652, "ground_truth": "B", "pred": "B", "reward": 1.2, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921091, "example_id": 953, "ground_truth": "B", "pred": "B", "reward": 1.2, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921091, "example_id": 953, "ground_truth": "B", "pred": "C", "reward": 0.0, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921149, "example_id": 709, "ground_truth": "C", "pred": "C", "reward": 1.2, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921149, "example_id": 709, "ground_truth": "C", "pred": "C", "reward": 1.2, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921185, "example_id": 1014, "ground_truth": "D", "pred": "C", "reward": 0.0, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921185, "example_id": 1014, "ground_truth": "D", "pred": "C", "reward": 0.0, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921217, "example_id": 651, "ground_truth": "A", "pred": "C", "reward": 0.0, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921217, "example_id": 651, "ground_truth": "A", "pred": "C", "reward": 0.0, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["reasoner_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921291, "example_id": 749, "ground_truth": "D", "pred": "D", "reward": 1.2, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921291, "example_id": 749, "ground_truth": "D", "pred": "D", "reward": 1.2, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921359, "example_id": 1147, "ground_truth": "A", "pred": null, "reward": 0.0, "tool_calls": 3, "tool_msgs": 2, "tool_names_called": ["rule_applier_tool", "reasoner_tool", "extractor_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921359, "example_id": 1147, "ground_truth": "A", "pred": "A", "reward": 1.2, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921417, "example_id": 630, "ground_truth": "B", "pred": "C", "reward": 0.0, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921417, "example_id": 630, "ground_truth": "B", "pred": "B", "reward": 1.2, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921457, "example_id": 878, "ground_truth": "B", "pred": "B", "reward": 1.2, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921457, "example_id": 878, "ground_truth": "B", "pred": "B", "reward": 1.2, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
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+{"ts": 1781921525, "example_id": 904, "ground_truth": "C", "pred": "B", "reward": 0.0, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921544, "example_id": 701, "ground_truth": "D", "pred": "B", "reward": 0.0, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921544, "example_id": 701, "ground_truth": "D", "pred": "B", "reward": 0.0, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921560, "example_id": 1094, "ground_truth": "B", "pred": "D", "reward": 0.0, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921560, "example_id": 1094, "ground_truth": "B", "pred": "D", "reward": 0.0, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921611, "example_id": 1002, "ground_truth": "D", "pred": "D", "reward": 1.2, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921611, "example_id": 1002, "ground_truth": "D", "pred": "D", "reward": 1.2, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921665, "example_id": 957, "ground_truth": "B", "pred": "B", "reward": 1.2, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921665, "example_id": 957, "ground_truth": "B", "pred": "B", "reward": 1.2, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921700, "example_id": 889, "ground_truth": "C", "pred": null, "reward": 0.0, "tool_calls": 0, "tool_msgs": 0, "tool_names_called": [], "tool_use_bonus": 0.2}
+{"ts": 1781921700, "example_id": 889, "ground_truth": "C", "pred": "B", "reward": 0.0, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["rule_applier_tool", "reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921764, "example_id": 984, "ground_truth": "D", "pred": "D", "reward": 1.2, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921764, "example_id": 984, "ground_truth": "D", "pred": "A", "reward": 0.0, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921812, "example_id": 872, "ground_truth": "C", "pred": "C", "reward": 1.2, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921812, "example_id": 872, "ground_truth": "C", "pred": "C", "reward": 1.2, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921887, "example_id": 906, "ground_truth": "D", "pred": "D", "reward": 1.2, "tool_calls": 1, "tool_msgs": 1, "tool_names_called": ["reasoner_tool"], "tool_use_bonus": 0.2}
+{"ts": 1781921887, "example_id": 906, "ground_truth": "D", "pred": "D", "reward": 1.2, "tool_calls": 2, "tool_msgs": 2, "tool_names_called": ["extractor_tool", "rule_applier_tool"], "tool_use_bonus": 0.2}
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+}
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