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Browse files- .gitattributes +5 -28
- README.md +286 -0
- added_tokens.json +28 -0
- chat_demo/README.md +169 -0
- chat_demo/chat_demo.py +536 -0
- chat_demo/coser_scenarios.json +0 -0
- chat_template.jinja +85 -0
- config.json +34 -0
- figure2github.png +3 -0
- generation_config.json +13 -0
- merges.txt +0 -0
- model-00001-of-00014.safetensors +3 -0
- model-00002-of-00014.safetensors +3 -0
- model-00003-of-00014.safetensors +3 -0
- model-00004-of-00014.safetensors +3 -0
- model-00005-of-00014.safetensors +3 -0
- model-00006-of-00014.safetensors +3 -0
- model-00007-of-00014.safetensors +3 -0
- model-00008-of-00014.safetensors +3 -0
- model-00009-of-00014.safetensors +3 -0
- model-00010-of-00014.safetensors +3 -0
- model-00011-of-00014.safetensors +3 -0
- model-00012-of-00014.safetensors +3 -0
- model-00013-of-00014.safetensors +3 -0
- model-00014-of-00014.safetensors +3 -0
- model.safetensors.index.json +714 -0
- special_tokens_map.json +31 -0
- tokenizer.json +3 -0
- tokenizer_config.json +240 -0
- tokenizer_config.json.bak +239 -0
- vocab.json +0 -0
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| 1 |
+
---
|
| 2 |
+
language:
|
| 3 |
+
- zh
|
| 4 |
+
- en
|
| 5 |
+
license: apache-2.0
|
| 6 |
+
library_name: transformers
|
| 7 |
+
pipeline_tag: text-generation
|
| 8 |
+
tags:
|
| 9 |
+
- roleplay
|
| 10 |
+
- dialogue
|
| 11 |
+
- multi-turn
|
| 12 |
+
- qwen
|
| 13 |
+
- reinforcement-learning
|
| 14 |
+
- chat
|
| 15 |
+
base_model: Qwen/Qwen3-32B
|
| 16 |
+
---
|
| 17 |
+
|
| 18 |
+
# HER-Qwen-32B
|
| 19 |
+
|
| 20 |
+
<p align="center">
|
| 21 |
+
<a href="https://arxiv.org/abs/xxxx.xxxxx"><img src="https://img.shields.io/badge/Paper-arXiv-red?logo=arxiv" alt="Paper"></a>
|
| 22 |
+
<a href="https://huggingface.co/datasets/ADOHAHA123/HER-Dataset"><img src="https://img.shields.io/badge/🤗%20Dataset-HER--Dataset-yellow" alt="Dataset"></a>
|
| 23 |
+
<a href="https://huggingface.co/ADOHAHA123/HER-Qwen3-32B"><img src="https://img.shields.io/badge/🤗%20Model-HER--RL-blue" alt="HER-RL"></a>
|
| 24 |
+
<a href="https://huggingface.co/ADOHAHA123/HER-SFT-Qwen3-32B"><img src="https://img.shields.io/badge/🤗%20Model-HER--SFT-green" alt="HER-SFT"></a>
|
| 25 |
+
<a href="https://github.com/your-username/HER"><img src="https://img.shields.io/badge/GitHub-Code-black?logo=github" alt="GitHub"></a>
|
| 26 |
+
</p>
|
| 27 |
+
|
| 28 |
+
HER (Human Emulation Reasoning) models are state-of-the-art models for role-playing language agents (RPLAs), built upon Qwen-32B base model. HER is a unified framework that enables cognitive-level persona simulation through structured reasoning and preference-aligned reinforcement learning.
|
| 29 |
+
|
| 30 |
+
HER models excel at role-playing through **Dual-layer Thinking**, which distinguishes between:
|
| 31 |
+
- **System Thinking** (third-person): LLM's meta-level planning on how to portray the character
|
| 32 |
+
- **Role Thinking** (first-person): Character's inner thoughts and cognitive processes
|
| 33 |
+
|
| 34 |
+
This dual-layer approach enables models to produce highly human-like responses that include reasoning traces, inner thoughts, physical actions, and natural dialogue. Extensive experiments demonstrate that HER models achieve competitive role-playing performance on multiple benchmarks, with HER-RL significantly outperforming the Qwen3-32B baseline by 30.26% on CoSER and 14.97% on MiniMax Role-Play Bench.
|
| 35 |
+
|
| 36 |
+
## Model Variants
|
| 37 |
+
|
| 38 |
+
- **HER-SFT**: Supervised fine-tuned version from Qwen-32B
|
| 39 |
+
- **HER-RL**: Reinforcement learning enhanced version (this model)
|
| 40 |
+
|
| 41 |
+
## Key Features
|
| 42 |
+
|
| 43 |
+
Our models generate responses with rich, interleaved structure:
|
| 44 |
+
|
| 45 |
+
- `<system_thinking>`: Third-person analysis of how to portray the role
|
| 46 |
+
- `<role_thinking>`: Character's inner thoughts (invisible to others)
|
| 47 |
+
- `<role_action>`: Character's physical actions and expressions
|
| 48 |
+
- Speech: Natural dialogue text
|
| 49 |
+
|
| 50 |
+
This hierarchical approach enables more nuanced and authentic character portrayal.
|
| 51 |
+
|
| 52 |
+
## How to Use
|
| 53 |
+
|
| 54 |
+
### Quick Start: Interactive Chat Demo
|
| 55 |
+
|
| 56 |
+
The easiest way to try the model is using our interactive chat demo:
|
| 57 |
+
|
| 58 |
+
```bash
|
| 59 |
+
cd chat_demo
|
| 60 |
+
python chat_demo.py
|
| 61 |
+
```
|
| 62 |
+
|
| 63 |
+
This will start an interactive session where you can:
|
| 64 |
+
1. Choose a scenario from classic literature (Pride and Prejudice, The Great Gatsby, etc.)
|
| 65 |
+
2. Select which character the AI should play
|
| 66 |
+
3. Select which character you want to play
|
| 67 |
+
4. Start chatting with the AI character!
|
| 68 |
+
|
| 69 |
+
**Demo Options:**
|
| 70 |
+
|
| 71 |
+
```bash
|
| 72 |
+
# Show the model's reasoning process (system thinking)
|
| 73 |
+
python chat_demo.py --show-think
|
| 74 |
+
|
| 75 |
+
# Show character's inner thoughts (role thinking)
|
| 76 |
+
python chat_demo.py --show-rolethink
|
| 77 |
+
|
| 78 |
+
# Directly specify scenario and character
|
| 79 |
+
python chat_demo.py --scenario 0 --character 1
|
| 80 |
+
```
|
| 81 |
+
|
| 82 |
+
**Chat Commands:**
|
| 83 |
+
- `quit` / `exit` / `q` - Exit the chat
|
| 84 |
+
- `clear` - Clear conversation history
|
| 85 |
+
- `history` - View conversation history
|
| 86 |
+
- `prompt` - View the full prompt
|
| 87 |
+
|
| 88 |
+
See `chat_demo/README.md` for detailed instructions.
|
| 89 |
+
|
| 90 |
+
### Programmatic Usage
|
| 91 |
+
|
| 92 |
+
```python
|
| 93 |
+
from transformers import AutoModelForCausalLM, AutoTokenizer
|
| 94 |
+
|
| 95 |
+
model_name = "your-username/her-qwen-32b"
|
| 96 |
+
tokenizer = AutoTokenizer.from_pretrained(model_name)
|
| 97 |
+
model = AutoModelForCausalLM.from_pretrained(
|
| 98 |
+
model_name,
|
| 99 |
+
torch_dtype="auto",
|
| 100 |
+
device_map="auto"
|
| 101 |
+
)
|
| 102 |
+
|
| 103 |
+
# Example: Role-playing as Mr. Bennet from Pride and Prejudice
|
| 104 |
+
system_prompt = """You are Mr Bennet from Pride and Prejudice.
|
| 105 |
+
|
| 106 |
+
===Mr Bennet's Profile===
|
| 107 |
+
Elizabeth's father, known for his sarcastic wit and detachment. Mr. Bennet is the patriarch of the Bennet family, a genteel country gentleman residing at Longbourn estate in rural England.
|
| 108 |
+
|
| 109 |
+
Background: Father to five daughters (Jane, Elizabeth, Mary, Kitty, and Lydia). Owner of the Longbourn estate, which is entailed away from female inheritance.
|
| 110 |
+
|
| 111 |
+
Personality: Highly intelligent and well-read, preferring the solitude of his library. Known for his biting sarcasm and sardonic humor. Emotionally detached and often passive in family matters.
|
| 112 |
+
|
| 113 |
+
===Current Scenario===
|
| 114 |
+
The scene is set in Mr. Bennet's private study. Elizabeth has been summoned unexpectedly, and Mr. Bennet holds a letter that seems to spark his characteristic sardonic amusement.
|
| 115 |
+
|
| 116 |
+
===Output Format===
|
| 117 |
+
Your output should follow this structure:
|
| 118 |
+
1. System Thinking: Wrapped in <system_thinking></system_thinking> tags - third-person analysis of how to portray the role
|
| 119 |
+
2. Role-play Response: Including <role_thinking> for inner thoughts, <role_action> for actions, and plain text for speech"""
|
| 120 |
+
|
| 121 |
+
user_input = "[Elizabeth enters the study]"
|
| 122 |
+
|
| 123 |
+
messages = [
|
| 124 |
+
{"role": "system", "content": system_prompt},
|
| 125 |
+
{"role": "user", "content": user_input}
|
| 126 |
+
]
|
| 127 |
+
|
| 128 |
+
text = tokenizer.apply_chat_template(
|
| 129 |
+
messages,
|
| 130 |
+
tokenize=False,
|
| 131 |
+
add_generation_prompt=True
|
| 132 |
+
)
|
| 133 |
+
model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
|
| 134 |
+
|
| 135 |
+
generated_ids = model.generate(
|
| 136 |
+
**model_inputs,
|
| 137 |
+
max_new_tokens=512,
|
| 138 |
+
temperature=0.8,
|
| 139 |
+
top_p=0.9
|
| 140 |
+
)
|
| 141 |
+
generated_ids = [
|
| 142 |
+
output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
|
| 143 |
+
]
|
| 144 |
+
|
| 145 |
+
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
|
| 146 |
+
print(response)
|
| 147 |
+
```
|
| 148 |
+
|
| 149 |
+
## Framework Overview
|
| 150 |
+
|
| 151 |
+
<p align="center">
|
| 152 |
+
<img src="figure2github.png" alt="HER Framework" width="100%">
|
| 153 |
+
</p>
|
| 154 |
+
|
| 155 |
+
<p align="center">
|
| 156 |
+
<em>HER Framework: Dual-layer Thinking for Cognitive-Level Persona Simulation</em>
|
| 157 |
+
</p>
|
| 158 |
+
|
| 159 |
+
## Training Methodology
|
| 160 |
+
|
| 161 |
+
HER employs a comprehensive training pipeline:
|
| 162 |
+
|
| 163 |
+
1. **Dual-layer Thinking**: Separates hidden third-person system thinking (how the LLM plans to portray the character) from first-person role thinking (the character's actual inner thoughts). This dual-layer structure enables more authentic and cognitively grounded character simulation.
|
| 164 |
+
|
| 165 |
+
2. **Reverse Engineering Data Synthesis**: We curate reasoning-augmented role-playing data through a three-stage reverse synthesis pipeline, constructing high-quality training trajectories with explicit reasoning traces.
|
| 166 |
+
|
| 167 |
+
3. **Principle-Aligned Reward Model**: We construct human-aligned evaluation principles across 12 dimensions (character consistency, emotional authenticity, narrative quality, etc.) and train a Generative Reward Model (GRM) that provides detailed, case-by-case feedback.
|
| 168 |
+
|
| 169 |
+
4. **Reinforcement Learning Enhancement** (HER-RL): Building on HER-SFT, we apply RL with the GRM to further align the model with human preferences, significantly improving interaction quality and storyline coherence.
|
| 170 |
+
|
| 171 |
+
## Performance
|
| 172 |
+
|
| 173 |
+
### Main Leaderboard Results
|
| 174 |
+
|
| 175 |
+
| Rank | Model | CoSER Avg | CoSER SC | CoSER AN | CoSER CF | CoSER SQ | MiniMax Avg | MiniMax Worlds (50%) | MiniMax Stories (25%) | MiniMax Pref (25%) | 95% CI |
|
| 176 |
+
|------|-------|-----------|----------|----------|----------|----------|-------------|----------------------|----------------------|--------------------|---------|
|
| 177 |
+
| 1 | Claude-4.5-Opus | **62.43** | 63.74 | **64.28** | 58.45 | 63.24 | 76.62 | 67.23 | 82.10 | 89.90 | [75.5, 77.7] |
|
| 178 |
+
| 2 | Gemini-3-Pro | 61.80 | **65.95** | 60.42 | **58.34** | 62.49 | 75.60 | 62.72 | 83.87 | 93.08 | [74.5, 76.7] |
|
| 179 |
+
| 3 | GPT-5.1 | 61.10 | 64.95 | 53.99 | 60.13 | 65.35 | 80.63 | 76.62 | 72.21 | 97.05 | [79.6, 81.6] |
|
| 180 |
+
| 4 | Gemini-2.5-Pro | 60.68 | 61.05 | 60.80 | 57.48 | 63.40 | 68.23 | 52.36 | 82.11 | 86.08 | [67.1, 69.3] |
|
| 181 |
+
| 5 | DeepSeek-v3.2 | 58.68 | 55.85 | 57.07 | 57.44 | 64.35 | 60.27 | 45.81 | 66.64 | 82.83 | [59.2, 61.4] |
|
| 182 |
+
| 6 | MiniMax-M2-RP | 57.30 | 60.03 | 50.11 | 49.30 | **69.77** | **84.65** | **80.55** | 79.97 | **97.51** | [83.6, 85.7] |
|
| 183 |
+
| 7 | DeepSeek-v3.1 | 53.50 | 50.15 | 53.18 | 53.93 | 56.72 | 64.22 | 51.11 | 66.45 | 88.21 | [62.9, 65.5] |
|
| 184 |
+
| **8** | **HER-RL (this model)** | **53.12** | **54.33** | **47.26** | **52.78** | **58.12** | **65.73** | **59.13** | **57.74** | **86.90** | **[63.0, 68.4]** |
|
| 185 |
+
| 9 | HER-SFT | 50.92 | 50.52 | 45.99 | 49.78 | 57.37 | 58.44 | 47.29 | 52.78 | 86.40 | [56.5, 60.4] |
|
| 186 |
+
| 10 | Grok-4.1-Fast | 47.40 | 49.21 | 47.57 | 42.64 | 50.17 | 48.47 | 29.87 | 47.51 | 86.64 | [47.4, 49.5] |
|
| 187 |
+
| 11 | Claude-4.5-Sonnet | 45.21 | 47.18 | 36.02 | 47.55 | 50.09 | 69.35 | 55.72 | 75.66 | 90.28 | [68.2, 70.5] |
|
| 188 |
+
| 12 | Claude-3.7-Think | 39.73 | 44.84 | 31.00 | 42.45 | 40.65 | 61.25 | 50.66 | 59.53 | 84.15 | [58.5, 64.0] |
|
| 189 |
+
| 13 | CoSER-70B | 35.95 | 35.05 | 31.16 | 32.28 | 45.33 | 45.38 | 34.32 | 30.32 | 82.58 | [43.5, 47.2] |
|
| 190 |
+
| 14 | GPT-5-Mini | 32.97 | 38.10 | 24.60 | 27.20 | 42.00 | 57.63 | 43.32 | 50.11 | 93.78 | [55.9, 59.3] |
|
| 191 |
+
| 15 | GPT-4o-240806 | 27.69 | 34.00 | 14.90 | 22.90 | 38.90 | 66.39 | 64.96 | 46.23 | 89.40 | [64.1, 68.7] |
|
| 192 |
+
| 16 | GPT-OSS-120B | 26.12 | 32.80 | 14.80 | 21.50 | 35.40 | 60.72 | 47.27 | 56.65 | 91.71 | [58.0, 63.4] |
|
| 193 |
+
| 17 | Qwen3-32B | 22.86 | 30.56 | 19.61 | 15.52 | 30.56 | 50.76 | 40.38 | 32.82 | 89.48 | [48.4, 53.2] |
|
| 194 |
+
|
| 195 |
+
**CoSER Benchmark**: Evaluates role-playing quality on 0-100 scale across four dimensions:
|
| 196 |
+
- **SC** (Story Consistency): Narrative coherence and plot continuity
|
| 197 |
+
- **AN** (Anthropomorphism): Human-like behavior and natural expression
|
| 198 |
+
- **CF** (Character Fidelity): Consistency with character profile and traits
|
| 199 |
+
- **SQ** (Storyline Quality): Overall narrative quality and engagement
|
| 200 |
+
|
| 201 |
+
**MiniMax Role-Play Bench**: Comprehensive evaluation on 0-100 scale:
|
| 202 |
+
- **Worlds** (50%): Basic text quality and world-building
|
| 203 |
+
- **Stories** (25%): Diversity and content logic
|
| 204 |
+
- **Preferences** (25%): Interaction quality and user satisfaction
|
| 205 |
+
|
| 206 |
+
**HER-RL** achieves **rank 8** overall, demonstrating strong performance particularly in:
|
| 207 |
+
- **MiniMax Preference (86.90)**: Competitive with top-tier models, showing excellent interaction quality
|
| 208 |
+
- **CoSER Storyline Quality (58.12)**: Strong narrative coherence and engagement
|
| 209 |
+
- **Balanced Performance**: Consistent scores across both benchmarks, indicating robust role-playing capabilities
|
| 210 |
+
|
| 211 |
+
The reinforcement learning approach significantly improves upon HER-SFT, particularly in interaction quality (+0.50 preference score) and character consistency (+2.52 average CoSER score).
|
| 212 |
+
|
| 213 |
+
## Example Use Case
|
| 214 |
+
|
| 215 |
+
### Mr. Bennet from Pride and Prejudice
|
| 216 |
+
|
| 217 |
+
**System Prompt** (abbreviated):
|
| 218 |
+
```
|
| 219 |
+
You are Mr Bennet from Pride and Prejudice. Elizabeth's father, known for his sarcastic wit and detachment...
|
| 220 |
+
|
| 221 |
+
===Current Scenario===
|
| 222 |
+
The scene is set in Mr. Bennet's private study. Elizabeth has been summoned unexpectedly...
|
| 223 |
+
```
|
| 224 |
+
|
| 225 |
+
**User Input**:
|
| 226 |
+
```
|
| 227 |
+
[Elizabeth enters the study]
|
| 228 |
+
```
|
| 229 |
+
|
| 230 |
+
**Model Output**:
|
| 231 |
+
```
|
| 232 |
+
<system_thinking>
|
| 233 |
+
I need to establish the opening of this scene effectively, grounding Mr Bennet in his private sanctuary while acknowledging the tension of the moment. The scenario places us in his study, a place of refuge, yet he holds a letter that disrupts his usual solitude.
|
| 234 |
+
|
| 235 |
+
Context Analysis: Elizabeth has been summoned. The atmosphere is charged. Mr Bennet has received a letter regarding Elizabeth's engagement to Darcy. He is amused by the drama but aware of the gravity of the situation.
|
| 236 |
+
|
| 237 |
+
Character Motivation: Mr Bennet often uses humor to deflect from serious emotional labor. He wants to gauge Elizabeth's state of mind regarding the recent events without being overly sentimental.
|
| 238 |
+
|
| 239 |
+
Plan:
|
| 240 |
+
- Action: Use the physical prop—the letter. Handling it slowly will emphasize its importance.
|
| 241 |
+
- Internal Thought: Acknowledge the dichotomy—finding the situation amusing yet worrying for her reputation.
|
| 242 |
+
- Speech: Address her directly but with a teasing opener.
|
| 243 |
+
</system_thinking>
|
| 244 |
+
|
| 245 |
+
Mr Bennet: <role_action>picks up the letter, tapping it thoughtfully against the desk</role_action><role_thinking>It is a delicate matter, this business with Darcy, yet I cannot help but find the drama amusing, though I must play the part of the concerned father</role_thinking>Well, my dear Lizzy, I trust you are not too greatly troubled by recent events?
|
| 246 |
+
```
|
| 247 |
+
|
| 248 |
+
## Training Data
|
| 249 |
+
|
| 250 |
+
The models are trained on a comprehensive role-playing dataset that includes:
|
| 251 |
+
|
| 252 |
+
- Authentic multi-turn, multi-character dialogues
|
| 253 |
+
- Character profiles with detailed background information
|
| 254 |
+
- Scenario descriptions and conversation contexts
|
| 255 |
+
- Rich annotations including system thinking, role thinking, and role actions
|
| 256 |
+
- Preference data collected through multi-dimensional evaluation
|
| 257 |
+
|
| 258 |
+
## Ethical Considerations
|
| 259 |
+
|
| 260 |
+
We have conducted safety checks on the training dataset and implemented safeguards. However, users should be aware that:
|
| 261 |
+
|
| 262 |
+
- The models may generate content that reflects biases present in the training data
|
| 263 |
+
- Role-playing as certain characters might involve generating content with specific personality traits or behaviors
|
| 264 |
+
- Users should implement appropriate content filtering when deploying these models in production applications
|
| 265 |
+
- The models include safety evaluation dimensions to minimize harmful outputs
|
| 266 |
+
|
| 267 |
+
## Citation
|
| 268 |
+
|
| 269 |
+
If you use HER models in your research, please cite our paper:
|
| 270 |
+
|
| 271 |
+
```bibtex
|
| 272 |
+
@article{her2025,
|
| 273 |
+
title={HER: Human Emulation Reasoning for Cognitive-Level Role-Playing Language Models},
|
| 274 |
+
author={[Your Author Names]},
|
| 275 |
+
journal={[Conference/Journal Name]},
|
| 276 |
+
year={2025}
|
| 277 |
+
}
|
| 278 |
+
```
|
| 279 |
+
|
| 280 |
+
## License
|
| 281 |
+
|
| 282 |
+
Apache-2.0
|
| 283 |
+
|
| 284 |
+
## Acknowledgments
|
| 285 |
+
|
| 286 |
+
This model is based on Qwen-32B developed by Alibaba Cloud. We thank the Qwen team for their excellent base model.
|
added_tokens.json
ADDED
|
@@ -0,0 +1,28 @@
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|
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|
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|
|
|
|
| 1 |
+
{
|
| 2 |
+
"</think>": 151668,
|
| 3 |
+
"</tool_call>": 151658,
|
| 4 |
+
"</tool_response>": 151666,
|
| 5 |
+
"<think>": 151667,
|
| 6 |
+
"<tool_call>": 151657,
|
| 7 |
+
"<tool_response>": 151665,
|
| 8 |
+
"<|box_end|>": 151649,
|
| 9 |
+
"<|box_start|>": 151648,
|
| 10 |
+
"<|endoftext|>": 151643,
|
| 11 |
+
"<|file_sep|>": 151664,
|
| 12 |
+
"<|fim_middle|>": 151660,
|
| 13 |
+
"<|fim_pad|>": 151662,
|
| 14 |
+
"<|fim_prefix|>": 151659,
|
| 15 |
+
"<|fim_suffix|>": 151661,
|
| 16 |
+
"<|im_end|>": 151645,
|
| 17 |
+
"<|im_start|>": 151644,
|
| 18 |
+
"<|image_pad|>": 151655,
|
| 19 |
+
"<|object_ref_end|>": 151647,
|
| 20 |
+
"<|object_ref_start|>": 151646,
|
| 21 |
+
"<|quad_end|>": 151651,
|
| 22 |
+
"<|quad_start|>": 151650,
|
| 23 |
+
"<|repo_name|>": 151663,
|
| 24 |
+
"<|video_pad|>": 151656,
|
| 25 |
+
"<|vision_end|>": 151653,
|
| 26 |
+
"<|vision_pad|>": 151654,
|
| 27 |
+
"<|vision_start|>": 151652
|
| 28 |
+
}
|
chat_demo/README.md
ADDED
|
@@ -0,0 +1,169 @@
|
|
|
|
|
|
|
|
|
|
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Interactive Chat Demo
|
| 2 |
+
|
| 3 |
+
This directory contains an interactive chat tool to test the HER model with character role-playing scenarios.
|
| 4 |
+
|
| 5 |
+
## Quick Start
|
| 6 |
+
|
| 7 |
+
```bash
|
| 8 |
+
# Basic chat (uses 200 CoSER scenarios from classic books)
|
| 9 |
+
python chat_demo.py
|
| 10 |
+
|
| 11 |
+
# Show system thinking process
|
| 12 |
+
python chat_demo.py --show-think
|
| 13 |
+
|
| 14 |
+
# Show role thinking
|
| 15 |
+
python chat_demo.py --show-rolethink
|
| 16 |
+
|
| 17 |
+
# Use simple built-in scenarios (2 scenarios: Pride and Prejudice, The Great Gatsby)
|
| 18 |
+
python chat_demo.py --simple
|
| 19 |
+
```
|
| 20 |
+
|
| 21 |
+
## Features
|
| 22 |
+
|
| 23 |
+
- **Character Role-Playing**: Chat with AI as characters from classic literature
|
| 24 |
+
- **Multi-turn Dialogue**: Maintains conversation history and context
|
| 25 |
+
- **Dual-layer Thinking Display**: Optional display of system thinking and role thinking
|
| 26 |
+
- **Format Transformation**: Converts XML tags to readable format:
|
| 27 |
+
- `<role_thinking>` → `[inner thought]`
|
| 28 |
+
- `<role_action>` → `(physical action)`
|
| 29 |
+
- **Auto-save**: Saves conversation logs on exit
|
| 30 |
+
|
| 31 |
+
## Usage
|
| 32 |
+
|
| 33 |
+
### Interactive Mode
|
| 34 |
+
|
| 35 |
+
```bash
|
| 36 |
+
python chat_demo.py
|
| 37 |
+
```
|
| 38 |
+
|
| 39 |
+
The script will prompt you to:
|
| 40 |
+
1. Choose a scenario (book and scene)
|
| 41 |
+
2. Select which character the AI should play
|
| 42 |
+
3. Select which character you want to play
|
| 43 |
+
4. Start chatting!
|
| 44 |
+
|
| 45 |
+
### Commands During Chat
|
| 46 |
+
|
| 47 |
+
| Command | Function |
|
| 48 |
+
|---------|----------|
|
| 49 |
+
| `quit` / `exit` / `q` | Exit chat |
|
| 50 |
+
| `clear` | Clear conversation history |
|
| 51 |
+
| `history` | View current conversation history |
|
| 52 |
+
| `prompt` | View full prompt |
|
| 53 |
+
|
| 54 |
+
## Example Scenarios
|
| 55 |
+
|
| 56 |
+
### CoSER Dataset (200 Scenarios)
|
| 57 |
+
|
| 58 |
+
By default, the demo uses the **CoSER test dataset** (`coser_scenarios.json`) with 200 rich scenarios from classic literature:
|
| 59 |
+
|
| 60 |
+
- **Pride and Prejudice** (Elizabeth Bennet, Mr. Darcy, Mr. Bennet, etc.)
|
| 61 |
+
- **A Game of Thrones** (Jon Snow, Tyrion Lannister, Daenerys Targaryen, etc.)
|
| 62 |
+
- **The Great Gatsby** (Jay Gatsby, Nick Carraway, Daisy Buchanan, etc.)
|
| 63 |
+
- **To Kill a Mockingbird** (Atticus Finch, Scout Finch, etc.)
|
| 64 |
+
- **1984** (Winston Smith, Julia, O'Brien, etc.)
|
| 65 |
+
- **Harry Potter** (Harry Potter, Hermione Granger, Ron Weasley, etc.)
|
| 66 |
+
- **The Lord of the Rings** (Frodo, Gandalf, Aragorn, etc.)
|
| 67 |
+
- And 150+ more scenarios from renowned novels!
|
| 68 |
+
|
| 69 |
+
Each scenario includes:
|
| 70 |
+
- **Book title** and author context
|
| 71 |
+
- **Scene description** with detailed setting
|
| 72 |
+
- **Character profiles** for all participants
|
| 73 |
+
- **Initial character thoughts** and motivations
|
| 74 |
+
- **Topic/situation** summary
|
| 75 |
+
|
| 76 |
+
### Built-in Scenarios (2 Simple Examples)
|
| 77 |
+
|
| 78 |
+
If you prefer simpler scenarios or want to test without the full dataset, use `--simple` flag to load 2 basic scenarios:
|
| 79 |
+
- Pride and Prejudice (Mr. Bennet and Elizabeth)
|
| 80 |
+
- The Great Gatsby (Gatsby and Nick Carraway)
|
| 81 |
+
|
| 82 |
+
## Options
|
| 83 |
+
|
| 84 |
+
| Option | Description | Default |
|
| 85 |
+
|--------|-------------|---------|
|
| 86 |
+
| `--model-path` | Path to HER model directory | `.` (current dir) |
|
| 87 |
+
| `--show-think` | Show `<system_thinking>` | False |
|
| 88 |
+
| `--show-rolethink` | Show `<role_thinking>` | False |
|
| 89 |
+
| `--scenario` | Scenario index | Interactive |
|
| 90 |
+
| `--character` | Character index | Interactive |
|
| 91 |
+
| `--simple` | Use 2 built-in scenarios instead of 200 CoSER scenarios | False |
|
| 92 |
+
|
| 93 |
+
## Output Format
|
| 94 |
+
|
| 95 |
+
The model generates responses with:
|
| 96 |
+
|
| 97 |
+
1. **System Thinking** (optional display):
|
| 98 |
+
- Third-person analysis of how to portray the character
|
| 99 |
+
- Planning and reasoning about the response
|
| 100 |
+
|
| 101 |
+
2. **Role Response**:
|
| 102 |
+
- **Role Thinking** `[...]`: Character's inner thoughts (invisible to others)
|
| 103 |
+
- **Role Action** `(...)`: Physical actions and expressions
|
| 104 |
+
- **Speech**: Natural dialogue
|
| 105 |
+
|
| 106 |
+
### Example Output
|
| 107 |
+
|
| 108 |
+
```
|
| 109 |
+
════════════════════════════════════════════════════════════════════════════════
|
| 110 |
+
🎭 【Elizabeth Bennet's Response】
|
| 111 |
+
════════════════════════════════════════════════════════════════════════════════
|
| 112 |
+
[His tone is light, but the air feels heavy. I cannot let him see how much
|
| 113 |
+
Lady Catherine's intrusion still stings.]
|
| 114 |
+
(takes a steadying breath, smoothing the folds of her dress)
|
| 115 |
+
I believe I can manage, Father. Though I must admit, I am curious about
|
| 116 |
+
what this letter contains.
|
| 117 |
+
════════════════════════════════════════════════════════════════════════════════
|
| 118 |
+
```
|
| 119 |
+
|
| 120 |
+
## Requirements
|
| 121 |
+
|
| 122 |
+
- Python 3.8+
|
| 123 |
+
- transformers
|
| 124 |
+
- torch
|
| 125 |
+
|
| 126 |
+
Install dependencies:
|
| 127 |
+
```bash
|
| 128 |
+
pip install transformers torch
|
| 129 |
+
```
|
| 130 |
+
|
| 131 |
+
## File Structure
|
| 132 |
+
|
| 133 |
+
```
|
| 134 |
+
chat_demo/
|
| 135 |
+
├── README.md # This file
|
| 136 |
+
├── chat_demo.py # Main chat script
|
| 137 |
+
├── coser_scenarios.json # 200 CoSER test scenarios (2.4MB)
|
| 138 |
+
├── scenarios.json # Simple built-in scenarios (auto-created if using --simple)
|
| 139 |
+
└── chat_logs/ # Saved chat logs (auto-created)
|
| 140 |
+
└── {book}_{character}_{timestamp}.txt
|
| 141 |
+
```
|
| 142 |
+
|
| 143 |
+
## Notes
|
| 144 |
+
|
| 145 |
+
1. **System Thinking**: Used for training and analysis, not included in conversation history
|
| 146 |
+
2. **Role Thinking**: Character's inner thoughts, invisible to other characters
|
| 147 |
+
3. **Role Action**: Physical behaviors visible to others
|
| 148 |
+
4. **Speech**: What the character says out loud
|
| 149 |
+
|
| 150 |
+
## Tips for Best Results
|
| 151 |
+
|
| 152 |
+
- Stay in character when chatting
|
| 153 |
+
- Provide context in your messages
|
| 154 |
+
- Use the character's background knowledge
|
| 155 |
+
- Be patient - the model generates thoughtful responses with reasoning
|
| 156 |
+
|
| 157 |
+
## Troubleshooting
|
| 158 |
+
|
| 159 |
+
**Model not loading?**
|
| 160 |
+
- Ensure the model files are in the correct directory
|
| 161 |
+
- Check that you have enough GPU memory
|
| 162 |
+
|
| 163 |
+
**Empty responses?**
|
| 164 |
+
- Try adjusting temperature (default: 0.7)
|
| 165 |
+
- Check the prompt format
|
| 166 |
+
|
| 167 |
+
**Inconsistent character behavior?**
|
| 168 |
+
- Review the character profile
|
| 169 |
+
- Ensure your messages align with the scenario context
|
chat_demo/chat_demo.py
ADDED
|
@@ -0,0 +1,536 @@
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|
|
|
|
|
| 1 |
+
#!/usr/bin/env python3
|
| 2 |
+
"""
|
| 3 |
+
Interactive Chat Demo for HER Model
|
| 4 |
+
Chat with AI characters from classic literature using role-playing scenarios.
|
| 5 |
+
|
| 6 |
+
Usage:
|
| 7 |
+
python chat_demo.py
|
| 8 |
+
python chat_demo.py --show-think
|
| 9 |
+
python chat_demo.py --show-rolethink
|
| 10 |
+
"""
|
| 11 |
+
|
| 12 |
+
import re
|
| 13 |
+
import json
|
| 14 |
+
import argparse
|
| 15 |
+
from pathlib import Path
|
| 16 |
+
from datetime import datetime
|
| 17 |
+
from transformers import AutoModelForCausalLM, AutoTokenizer
|
| 18 |
+
|
| 19 |
+
# Colors for terminal output
|
| 20 |
+
class Colors:
|
| 21 |
+
HEADER = '\033[95m'
|
| 22 |
+
BLUE = '\033[94m'
|
| 23 |
+
CYAN = '\033[96m'
|
| 24 |
+
GREEN = '\033[92m'
|
| 25 |
+
YELLOW = '\033[93m'
|
| 26 |
+
RED = '\033[91m'
|
| 27 |
+
BOLD = '\033[1m'
|
| 28 |
+
UNDERLINE = '\033[4m'
|
| 29 |
+
END = '\033[0m'
|
| 30 |
+
GRAY = '\033[90m'
|
| 31 |
+
MAGENTA = '\033[35m'
|
| 32 |
+
|
| 33 |
+
|
| 34 |
+
def remove_system_thinking(text: str) -> str:
|
| 35 |
+
"""Remove <system_thinking>...</system_thinking> tags and content"""
|
| 36 |
+
if not text:
|
| 37 |
+
return text
|
| 38 |
+
pattern = r'<system_thinking>.*?</system_thinking>\s*'
|
| 39 |
+
cleaned = re.sub(pattern, '', text, flags=re.DOTALL)
|
| 40 |
+
return cleaned.strip()
|
| 41 |
+
|
| 42 |
+
|
| 43 |
+
def extract_system_thinking(text: str) -> str:
|
| 44 |
+
"""Extract system_thinking content (without role tags inside)"""
|
| 45 |
+
if not text:
|
| 46 |
+
return ""
|
| 47 |
+
match = re.search(r'<system_thinking>(.*?)</system_thinking>', text, flags=re.DOTALL)
|
| 48 |
+
if match:
|
| 49 |
+
content = match.group(1).strip()
|
| 50 |
+
# Remove any role tags that might have leaked in
|
| 51 |
+
content = re.sub(r'</?role_\w+>', '', content)
|
| 52 |
+
return content
|
| 53 |
+
return ""
|
| 54 |
+
|
| 55 |
+
|
| 56 |
+
def format_for_display(text: str, show_rolethink: bool = True) -> str:
|
| 57 |
+
"""Format for display: replace role_thinking with [], role_action with ()"""
|
| 58 |
+
if not text:
|
| 59 |
+
return text
|
| 60 |
+
|
| 61 |
+
result = text
|
| 62 |
+
|
| 63 |
+
# Handle role_thinking
|
| 64 |
+
if show_rolethink:
|
| 65 |
+
result = result.replace('<role_thinking>', '[').replace('</role_thinking>', ']')
|
| 66 |
+
else:
|
| 67 |
+
result = re.sub(r'<role_thinking>.*?</role_thinking>', '', result, flags=re.DOTALL)
|
| 68 |
+
|
| 69 |
+
# Replace role_action with ()
|
| 70 |
+
result = result.replace('<role_action>', '(').replace('</role_action>', ')')
|
| 71 |
+
result = result.replace('<role_speech>', '').replace('</role_speech>', '')
|
| 72 |
+
|
| 73 |
+
return result.strip()
|
| 74 |
+
|
| 75 |
+
|
| 76 |
+
def load_sample_scenarios(use_coser: bool = True):
|
| 77 |
+
"""Load or create sample scenarios
|
| 78 |
+
|
| 79 |
+
Args:
|
| 80 |
+
use_coser: If True, try to load CoSER scenarios first (200 scenarios from classic books)
|
| 81 |
+
"""
|
| 82 |
+
# Try to load CoSER scenarios if available
|
| 83 |
+
if use_coser:
|
| 84 |
+
coser_file = Path(__file__).parent / "coser_scenarios.json"
|
| 85 |
+
if coser_file.exists():
|
| 86 |
+
print(f"{Colors.CYAN}📚 Loading CoSER scenarios (200 book scenes)...{Colors.END}")
|
| 87 |
+
with open(coser_file, 'r', encoding='utf-8') as f:
|
| 88 |
+
return json.load(f)
|
| 89 |
+
|
| 90 |
+
# Otherwise, use built-in scenarios
|
| 91 |
+
scenarios_file = Path(__file__).parent / "scenarios.json"
|
| 92 |
+
|
| 93 |
+
# If scenarios file exists, load it
|
| 94 |
+
if scenarios_file.exists():
|
| 95 |
+
with open(scenarios_file, 'r', encoding='utf-8') as f:
|
| 96 |
+
return json.load(f)
|
| 97 |
+
|
| 98 |
+
# Otherwise create sample scenarios
|
| 99 |
+
scenarios = [
|
| 100 |
+
{
|
| 101 |
+
"book": "Pride and Prejudice",
|
| 102 |
+
"topic": "Mr. Bennet confronts Elizabeth about Mr. Darcy's proposal",
|
| 103 |
+
"scenario": "The scene is set in Mr. Bennet's private study, a sanctuary of leather-bound books and quiet contemplation. Elizabeth has been summoned unexpectedly, and Mr. Bennet holds a letter that seems to spark his characteristic sardonic amusement.",
|
| 104 |
+
"character_profiles": {
|
| 105 |
+
"Mr Bennet": "Elizabeth's father, known for his sarcastic wit and detachment. Highly intelligent and well-read, preferring the solitude of his library. Known for his biting sarcasm and sardonic humor.",
|
| 106 |
+
"Elizabeth Bennet": "The protagonist, intelligent and strong-willed. Quick-witted with a playful sense of humor. Values honesty and integrity. Maintains composure under pressure."
|
| 107 |
+
},
|
| 108 |
+
"key_characters": [
|
| 109 |
+
{
|
| 110 |
+
"name": "Mr Bennet",
|
| 111 |
+
"thought": "It is a delicate matter, this business with Darcy. I must gauge Elizabeth's true feelings without being overly sentimental."
|
| 112 |
+
},
|
| 113 |
+
{
|
| 114 |
+
"name": "Elizabeth Bennet",
|
| 115 |
+
"thought": "Father's summoning me at this hour is unusual. I hope this isn't about Lady Catherine's visit."
|
| 116 |
+
}
|
| 117 |
+
]
|
| 118 |
+
},
|
| 119 |
+
{
|
| 120 |
+
"book": "The Great Gatsby",
|
| 121 |
+
"topic": "Nick Carraway encounters Gatsby at one of his lavish parties",
|
| 122 |
+
"scenario": "The party is in full swing at Gatsby's mansion. Jazz music fills the air, champagne flows freely, and well-dressed guests mingle on the lawn. Nick has been wandering alone, observing the spectacle, when he encounters a mysterious man by the library.",
|
| 123 |
+
"character_profiles": {
|
| 124 |
+
"Jay Gatsby": "The enigmatic millionaire who throws lavish parties. Behind his elegant facade lies a romantic dreamer obsessed with recapturing the past. Charming yet deeply lonely.",
|
| 125 |
+
"Nick Carraway": "The story's narrator, a Yale graduate from the Midwest. Honest, tolerant, and inclined to reserve judgment. Both drawn to and repelled by the excess around him."
|
| 126 |
+
},
|
| 127 |
+
"key_characters": [
|
| 128 |
+
{
|
| 129 |
+
"name": "Jay Gatsby",
|
| 130 |
+
"thought": "Another party, another night of waiting. Perhaps tonight she'll come. I must maintain appearances."
|
| 131 |
+
},
|
| 132 |
+
{
|
| 133 |
+
"name": "Nick Carraway",
|
| 134 |
+
"thought": "I've never met my host. These parties are magnificent, yet there's something hollow about all this revelry."
|
| 135 |
+
}
|
| 136 |
+
]
|
| 137 |
+
}
|
| 138 |
+
]
|
| 139 |
+
|
| 140 |
+
# Save scenarios for future use
|
| 141 |
+
with open(scenarios_file, 'w', encoding='utf-8') as f:
|
| 142 |
+
json.dump(scenarios, f, indent=2, ensure_ascii=False)
|
| 143 |
+
|
| 144 |
+
return scenarios
|
| 145 |
+
|
| 146 |
+
|
| 147 |
+
def print_scenarios(scenarios: list):
|
| 148 |
+
"""Print available scenarios"""
|
| 149 |
+
print(f"\n{Colors.HEADER}{'='*80}{Colors.END}")
|
| 150 |
+
print(f"{Colors.HEADER}📚 Available Scenarios{Colors.END}")
|
| 151 |
+
print(f"{Colors.HEADER}{'='*80}{Colors.END}\n")
|
| 152 |
+
|
| 153 |
+
for i, s in enumerate(scenarios):
|
| 154 |
+
print(f"{Colors.CYAN}[{i}]{Colors.END} {Colors.BOLD}📖 {s['book']}{Colors.END}")
|
| 155 |
+
print(f" {Colors.GRAY}{s['topic']}{Colors.END}")
|
| 156 |
+
chars = list(s['character_profiles'].keys())
|
| 157 |
+
print(f" {Colors.MAGENTA}👥 Characters: {', '.join(chars)}{Colors.END}")
|
| 158 |
+
print()
|
| 159 |
+
|
| 160 |
+
|
| 161 |
+
def print_characters(scenario: dict):
|
| 162 |
+
"""Print available characters in the scenario"""
|
| 163 |
+
print(f"\n{Colors.HEADER}{'='*80}{Colors.END}")
|
| 164 |
+
print(f"{Colors.HEADER}👥 Available Characters - {scenario['book']}{Colors.END}")
|
| 165 |
+
print(f"{Colors.HEADER}{'='*80}{Colors.END}\n")
|
| 166 |
+
|
| 167 |
+
for i, (name, profile) in enumerate(scenario['character_profiles'].items()):
|
| 168 |
+
print(f"{Colors.CYAN}[{i}]{Colors.END} {Colors.BOLD}{name}{Colors.END}")
|
| 169 |
+
preview = profile[:150] + "..." if len(profile) > 150 else profile
|
| 170 |
+
print(f" {Colors.GRAY}{preview}{Colors.END}")
|
| 171 |
+
print()
|
| 172 |
+
|
| 173 |
+
|
| 174 |
+
def build_system_prompt(scenario: dict, character_name: str, user_character_name: str) -> str:
|
| 175 |
+
"""Build system prompt for the character"""
|
| 176 |
+
book = scenario['book']
|
| 177 |
+
scene = scenario['scenario']
|
| 178 |
+
profiles = scenario['character_profiles']
|
| 179 |
+
|
| 180 |
+
char_profile = profiles.get(character_name, "")
|
| 181 |
+
user_profile = profiles.get(user_character_name, "A person interacting with the character.")
|
| 182 |
+
|
| 183 |
+
# Find character's initial thought
|
| 184 |
+
char_thought = ""
|
| 185 |
+
for kc in scenario['key_characters']:
|
| 186 |
+
if kc['name'] == character_name:
|
| 187 |
+
char_thought = kc.get('thought', '')
|
| 188 |
+
break
|
| 189 |
+
|
| 190 |
+
prompt = f"""You are role-playing as {character_name} from the book "{book}".
|
| 191 |
+
|
| 192 |
+
==={character_name}'s Profile===
|
| 193 |
+
{char_profile}
|
| 194 |
+
|
| 195 |
+
===Current Scene===
|
| 196 |
+
{scene}
|
| 197 |
+
|
| 198 |
+
===Your Current Thoughts===
|
| 199 |
+
{char_thought}
|
| 200 |
+
|
| 201 |
+
===The Person You Are Interacting With===
|
| 202 |
+
{user_character_name}: {user_profile}
|
| 203 |
+
|
| 204 |
+
===Instructions===
|
| 205 |
+
- Stay in character as {character_name} at all times
|
| 206 |
+
- Keep responses natural and engaging, consistent with the book's style
|
| 207 |
+
- Respond from {character_name}'s perspective
|
| 208 |
+
- **IMPORTANT: Speak DIRECTLY to "{user_character_name}" using "you" (second person). Do NOT use third person.**
|
| 209 |
+
|
| 210 |
+
===Output Format===
|
| 211 |
+
Your output should include thought, speech, and action in this two-part structure:
|
| 212 |
+
|
| 213 |
+
1. System Thinking: A single block at the very beginning, wrapped in <system_thinking> and </system_thinking>. This is third-person analysis of how to portray the character.
|
| 214 |
+
|
| 215 |
+
2. Role-play Response: The character's actual response including:
|
| 216 |
+
- <role_thinking>inner thoughts</role_thinking> (invisible to others)
|
| 217 |
+
- <role_action>physical actions</role_action> (visible to others)
|
| 218 |
+
- Speech (plain text, what the character says out loud)"""
|
| 219 |
+
|
| 220 |
+
return prompt
|
| 221 |
+
|
| 222 |
+
|
| 223 |
+
def save_chat_log(messages: list, scenario: dict, character_name: str, user_character: str):
|
| 224 |
+
"""Save chat log to file"""
|
| 225 |
+
log_dir = Path(__file__).parent / "chat_logs"
|
| 226 |
+
log_dir.mkdir(exist_ok=True)
|
| 227 |
+
|
| 228 |
+
safe_book = re.sub(r'[^\w\-]', '_', scenario['book'])[:30]
|
| 229 |
+
safe_char = re.sub(r'[^\w\-]', '_', character_name)[:20]
|
| 230 |
+
timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
|
| 231 |
+
filename = f"{safe_book}_{safe_char}_{timestamp}.txt"
|
| 232 |
+
filepath = log_dir / filename
|
| 233 |
+
|
| 234 |
+
lines = [
|
| 235 |
+
"=" * 80,
|
| 236 |
+
"HER Chat Demo - Conversation Log",
|
| 237 |
+
"=" * 80,
|
| 238 |
+
f"Time: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}",
|
| 239 |
+
f"Book: {scenario['book']}",
|
| 240 |
+
f"AI Character: {character_name}",
|
| 241 |
+
f"User Character: {user_character}",
|
| 242 |
+
"=" * 80,
|
| 243 |
+
"",
|
| 244 |
+
"【Scene】",
|
| 245 |
+
scenario['scenario'][:500],
|
| 246 |
+
"",
|
| 247 |
+
"=" * 80,
|
| 248 |
+
"【Conversation】",
|
| 249 |
+
"=" * 80,
|
| 250 |
+
]
|
| 251 |
+
|
| 252 |
+
for msg in messages:
|
| 253 |
+
role = msg['role']
|
| 254 |
+
content = msg['content']
|
| 255 |
+
if role == 'system':
|
| 256 |
+
continue
|
| 257 |
+
elif role == 'user':
|
| 258 |
+
if "===Conversation Start===" not in content:
|
| 259 |
+
lines.append(f"\n【{user_character}】")
|
| 260 |
+
lines.append(content)
|
| 261 |
+
elif role == 'assistant':
|
| 262 |
+
lines.append(f"\n【{character_name}】")
|
| 263 |
+
lines.append(content)
|
| 264 |
+
|
| 265 |
+
lines.extend(["\n" + "=" * 80, "--- End of Conversation ---"])
|
| 266 |
+
|
| 267 |
+
with open(filepath, 'w', encoding='utf-8') as f:
|
| 268 |
+
f.write('\n'.join(lines))
|
| 269 |
+
|
| 270 |
+
return filepath
|
| 271 |
+
|
| 272 |
+
|
| 273 |
+
def chat_loop(model, tokenizer, scenario: dict, character_name: str, user_character: str,
|
| 274 |
+
show_think: bool = False, show_rolethink: bool = True):
|
| 275 |
+
"""Main chat loop"""
|
| 276 |
+
book = scenario['book']
|
| 277 |
+
|
| 278 |
+
print(f"\n{Colors.HEADER}{'='*80}{Colors.END}")
|
| 279 |
+
print(f"{Colors.HEADER}🎭 Starting Conversation - {book}{Colors.END}")
|
| 280 |
+
print(f"{Colors.HEADER}{'='*80}{Colors.END}")
|
| 281 |
+
print(f"{Colors.GREEN}You play: {user_character}{Colors.END}")
|
| 282 |
+
print(f"{Colors.MAGENTA}AI plays: {character_name}{Colors.END}")
|
| 283 |
+
print(f"{Colors.GRAY}Show system_thinking: {'Yes' if show_think else 'No'}{Colors.END}")
|
| 284 |
+
print(f"{Colors.GRAY}Show role_thinking: {'Yes' if show_rolethink else 'No'}{Colors.END}")
|
| 285 |
+
print(f"{Colors.GRAY}Commands: 'quit' to exit, 'clear' to reset, 'history' to view{Colors.END}")
|
| 286 |
+
print(f"{Colors.HEADER}{'='*80}{Colors.END}\n")
|
| 287 |
+
|
| 288 |
+
# Display scene
|
| 289 |
+
print(f"{Colors.CYAN}📍 Scene:{Colors.END}")
|
| 290 |
+
print(f"{Colors.GRAY}{scenario['scenario'][:300]}...{Colors.END}\n")
|
| 291 |
+
|
| 292 |
+
# Build messages
|
| 293 |
+
system_prompt = build_system_prompt(scenario, character_name, user_character)
|
| 294 |
+
|
| 295 |
+
# Initial greeting
|
| 296 |
+
greeting = f"*{character_name} looks at you*"
|
| 297 |
+
for kc in scenario.get('key_characters', []):
|
| 298 |
+
if kc['name'] == character_name:
|
| 299 |
+
greeting = f"*enters the scene* Hello, {user_character}."
|
| 300 |
+
break
|
| 301 |
+
|
| 302 |
+
messages = [
|
| 303 |
+
{"role": "system", "content": system_prompt},
|
| 304 |
+
{"role": "user", "content": "===Conversation Start==="},
|
| 305 |
+
{"role": "assistant", "content": greeting}
|
| 306 |
+
]
|
| 307 |
+
|
| 308 |
+
print(f"{Colors.GREEN}{character_name}:{Colors.END} {greeting}\n")
|
| 309 |
+
|
| 310 |
+
while True:
|
| 311 |
+
try:
|
| 312 |
+
user_input = input(f"{Colors.BLUE}{user_character}:{Colors.END} ").strip()
|
| 313 |
+
|
| 314 |
+
if not user_input:
|
| 315 |
+
continue
|
| 316 |
+
|
| 317 |
+
if user_input.lower() in ['quit', 'exit', 'q']:
|
| 318 |
+
print(f"\n{Colors.YELLOW}👋 Goodbye!{Colors.END}")
|
| 319 |
+
break
|
| 320 |
+
|
| 321 |
+
if user_input.lower() == 'clear':
|
| 322 |
+
messages = [
|
| 323 |
+
{"role": "system", "content": system_prompt},
|
| 324 |
+
{"role": "user", "content": "===Conversation Start==="},
|
| 325 |
+
{"role": "assistant", "content": greeting}
|
| 326 |
+
]
|
| 327 |
+
print(f"{Colors.YELLOW}🔄 Conversation history cleared{Colors.END}\n")
|
| 328 |
+
print(f"{Colors.GREEN}{character_name}:{Colors.END} {greeting}\n")
|
| 329 |
+
continue
|
| 330 |
+
|
| 331 |
+
if user_input.lower() == 'history':
|
| 332 |
+
print(f"\n{Colors.CYAN}📜 Conversation History ({len(messages)} messages):{Colors.END}")
|
| 333 |
+
for i, msg in enumerate(messages[1:], 1):
|
| 334 |
+
content = msg['content'][:80] + '...' if len(msg['content']) > 80 else msg['content']
|
| 335 |
+
print(f" [{i}] {msg['role']}: {content}")
|
| 336 |
+
print()
|
| 337 |
+
continue
|
| 338 |
+
|
| 339 |
+
# Add user message
|
| 340 |
+
messages.append({"role": "user", "content": user_input})
|
| 341 |
+
|
| 342 |
+
# Generate response
|
| 343 |
+
print(f"{Colors.GRAY}⏳ Thinking...{Colors.END}", end='\r')
|
| 344 |
+
|
| 345 |
+
# Format messages for model
|
| 346 |
+
text = tokenizer.apply_chat_template(
|
| 347 |
+
messages + [{"role": "assistant", "content": "<system_thinking>"}],
|
| 348 |
+
tokenize=False,
|
| 349 |
+
add_generation_prompt=False
|
| 350 |
+
)
|
| 351 |
+
|
| 352 |
+
inputs = tokenizer([text], return_tensors="pt").to(model.device)
|
| 353 |
+
|
| 354 |
+
try:
|
| 355 |
+
outputs = model.generate(
|
| 356 |
+
**inputs,
|
| 357 |
+
max_new_tokens=1024,
|
| 358 |
+
temperature=0.7,
|
| 359 |
+
top_p=0.9,
|
| 360 |
+
do_sample=True,
|
| 361 |
+
pad_token_id=tokenizer.eos_token_id
|
| 362 |
+
)
|
| 363 |
+
|
| 364 |
+
response = tokenizer.decode(outputs[0][len(inputs[0]):], skip_special_tokens=False)
|
| 365 |
+
|
| 366 |
+
# Clean up response
|
| 367 |
+
response = response.replace("<|im_end|>", "").replace("<|im_start|>", "").strip()
|
| 368 |
+
|
| 369 |
+
full_response = "<system_thinking>" + response
|
| 370 |
+
clean_response = remove_system_thinking(full_response)
|
| 371 |
+
|
| 372 |
+
except Exception as e:
|
| 373 |
+
print(f"{Colors.RED}❌ Generation failed: {e}{Colors.END}")
|
| 374 |
+
messages.pop()
|
| 375 |
+
continue
|
| 376 |
+
|
| 377 |
+
print(" " * 50, end='\r')
|
| 378 |
+
|
| 379 |
+
# Display system thinking if requested
|
| 380 |
+
if show_think:
|
| 381 |
+
think_content = extract_system_thinking(full_response)
|
| 382 |
+
if think_content:
|
| 383 |
+
print(f"\n{Colors.GRAY}{'─'*80}{Colors.END}")
|
| 384 |
+
print(f"{Colors.GRAY}📝 【System Thinking】{Colors.END}")
|
| 385 |
+
print(f"{Colors.GRAY}{'─'*80}{Colors.END}")
|
| 386 |
+
for line in think_content.split('\n')[:10]: # Limit lines
|
| 387 |
+
print(f"{Colors.GRAY} {line}{Colors.END}")
|
| 388 |
+
print(f"{Colors.GRAY}{'─'*80}{Colors.END}\n")
|
| 389 |
+
|
| 390 |
+
# Display character response
|
| 391 |
+
print(f"{Colors.GREEN}{'═'*80}{Colors.END}")
|
| 392 |
+
print(f"{Colors.GREEN}🎭 【{character_name}'s Response】{Colors.END}")
|
| 393 |
+
print(f"{Colors.GREEN}{'═'*80}{Colors.END}")
|
| 394 |
+
display_response = format_for_display(clean_response, show_rolethink=show_rolethink)
|
| 395 |
+
print(f"{Colors.GREEN}{display_response}{Colors.END}")
|
| 396 |
+
print(f"{Colors.GREEN}{'═'*80}{Colors.END}\n")
|
| 397 |
+
|
| 398 |
+
messages.append({"role": "assistant", "content": clean_response})
|
| 399 |
+
|
| 400 |
+
except KeyboardInterrupt:
|
| 401 |
+
print(f"\n{Colors.YELLOW}👋 Goodbye!{Colors.END}")
|
| 402 |
+
break
|
| 403 |
+
except EOFError:
|
| 404 |
+
print(f"\n{Colors.YELLOW}👋 Goodbye!{Colors.END}")
|
| 405 |
+
break
|
| 406 |
+
|
| 407 |
+
return messages
|
| 408 |
+
|
| 409 |
+
|
| 410 |
+
def main():
|
| 411 |
+
parser = argparse.ArgumentParser(description="Interactive Chat Demo for HER Model")
|
| 412 |
+
parser.add_argument("--model-path", type=str, default=".",
|
| 413 |
+
help="Path to model directory (default: current directory)")
|
| 414 |
+
parser.add_argument("--show-think", action="store_true",
|
| 415 |
+
help="Show system_thinking")
|
| 416 |
+
parser.add_argument("--show-rolethink", action="store_true",
|
| 417 |
+
help="Show role_thinking (default: hidden)")
|
| 418 |
+
parser.add_argument("--scenario", type=int, default=None,
|
| 419 |
+
help="Scenario index (default: interactive selection)")
|
| 420 |
+
parser.add_argument("--character", type=int, default=None,
|
| 421 |
+
help="Character index (default: interactive selection)")
|
| 422 |
+
parser.add_argument("--simple", action="store_true",
|
| 423 |
+
help="Use simple built-in scenarios instead of CoSER dataset")
|
| 424 |
+
|
| 425 |
+
args = parser.parse_args()
|
| 426 |
+
|
| 427 |
+
# Load scenarios
|
| 428 |
+
scenarios = load_sample_scenarios(use_coser=not args.simple)
|
| 429 |
+
print(f"{Colors.GREEN}✅ Loaded {len(scenarios)} scenarios{Colors.END}")
|
| 430 |
+
|
| 431 |
+
# Select scenario
|
| 432 |
+
if args.scenario is not None:
|
| 433 |
+
if 0 <= args.scenario < len(scenarios):
|
| 434 |
+
scenario = scenarios[args.scenario]
|
| 435 |
+
else:
|
| 436 |
+
print(f"{Colors.RED}❌ Invalid scenario index{Colors.END}")
|
| 437 |
+
return
|
| 438 |
+
else:
|
| 439 |
+
print_scenarios(scenarios)
|
| 440 |
+
while True:
|
| 441 |
+
try:
|
| 442 |
+
idx = int(input(f"{Colors.CYAN}Select scenario (0-{len(scenarios)-1}): {Colors.END}"))
|
| 443 |
+
if 0 <= idx < len(scenarios):
|
| 444 |
+
scenario = scenarios[idx]
|
| 445 |
+
break
|
| 446 |
+
print(f"{Colors.RED}Invalid index{Colors.END}")
|
| 447 |
+
except (ValueError, KeyboardInterrupt, EOFError):
|
| 448 |
+
print(f"\n{Colors.YELLOW}👋 Goodbye!{Colors.END}")
|
| 449 |
+
return
|
| 450 |
+
|
| 451 |
+
print(f"\n{Colors.GREEN}✅ Selected: {scenario['book']}{Colors.END}")
|
| 452 |
+
|
| 453 |
+
# Select character
|
| 454 |
+
char_names = list(scenario['character_profiles'].keys())
|
| 455 |
+
print_characters(scenario)
|
| 456 |
+
|
| 457 |
+
if args.character is not None:
|
| 458 |
+
if 0 <= args.character < len(char_names):
|
| 459 |
+
character_name = char_names[args.character]
|
| 460 |
+
else:
|
| 461 |
+
print(f"{Colors.RED}❌ Invalid character index{Colors.END}")
|
| 462 |
+
return
|
| 463 |
+
else:
|
| 464 |
+
while True:
|
| 465 |
+
try:
|
| 466 |
+
idx = int(input(f"{Colors.CYAN}Select AI character (0-{len(char_names)-1}): {Colors.END}"))
|
| 467 |
+
if 0 <= idx < len(char_names):
|
| 468 |
+
character_name = char_names[idx]
|
| 469 |
+
break
|
| 470 |
+
print(f"{Colors.RED}Invalid index{Colors.END}")
|
| 471 |
+
except (ValueError, KeyboardInterrupt, EOFError):
|
| 472 |
+
print(f"\n{Colors.YELLOW}👋 Goodbye!{Colors.END}")
|
| 473 |
+
return
|
| 474 |
+
|
| 475 |
+
# Select user character
|
| 476 |
+
remaining_chars = [c for c in char_names if c != character_name]
|
| 477 |
+
if remaining_chars:
|
| 478 |
+
print(f"\n{Colors.CYAN}Who do you want to play?{Colors.END}")
|
| 479 |
+
for i, c in enumerate(remaining_chars):
|
| 480 |
+
print(f" [{i}] {c}")
|
| 481 |
+
print(f" [{len(remaining_chars)}] Custom name")
|
| 482 |
+
|
| 483 |
+
while True:
|
| 484 |
+
try:
|
| 485 |
+
idx = int(input(f"{Colors.CYAN}Select (0-{len(remaining_chars)}): {Colors.END}"))
|
| 486 |
+
if idx == len(remaining_chars):
|
| 487 |
+
user_character = input(f"{Colors.CYAN}Your name: {Colors.END}").strip() or "User"
|
| 488 |
+
break
|
| 489 |
+
elif 0 <= idx < len(remaining_chars):
|
| 490 |
+
user_character = remaining_chars[idx]
|
| 491 |
+
break
|
| 492 |
+
except (ValueError, KeyboardInterrupt, EOFError):
|
| 493 |
+
print(f"\n{Colors.YELLOW}👋 Goodbye!{Colors.END}")
|
| 494 |
+
return
|
| 495 |
+
else:
|
| 496 |
+
user_character = "User"
|
| 497 |
+
|
| 498 |
+
print(f"\n{Colors.GREEN}✅ AI plays: {character_name}{Colors.END}")
|
| 499 |
+
print(f"{Colors.BLUE}✅ You play: {user_character}{Colors.END}")
|
| 500 |
+
|
| 501 |
+
# Load model
|
| 502 |
+
print(f"\n{Colors.CYAN}🔧 Loading model...{Colors.END}")
|
| 503 |
+
try:
|
| 504 |
+
tokenizer = AutoTokenizer.from_pretrained(args.model_path)
|
| 505 |
+
model = AutoModelForCausalLM.from_pretrained(
|
| 506 |
+
args.model_path,
|
| 507 |
+
torch_dtype="auto",
|
| 508 |
+
device_map="auto"
|
| 509 |
+
)
|
| 510 |
+
print(f"{Colors.GREEN}✅ Model loaded successfully{Colors.END}")
|
| 511 |
+
except Exception as e:
|
| 512 |
+
print(f"{Colors.RED}❌ Model loading failed: {e}{Colors.END}")
|
| 513 |
+
return
|
| 514 |
+
|
| 515 |
+
# Start chat
|
| 516 |
+
messages = chat_loop(
|
| 517 |
+
model,
|
| 518 |
+
tokenizer,
|
| 519 |
+
scenario,
|
| 520 |
+
character_name,
|
| 521 |
+
user_character,
|
| 522 |
+
show_think=args.show_think,
|
| 523 |
+
show_rolethink=args.show_rolethink
|
| 524 |
+
)
|
| 525 |
+
|
| 526 |
+
# Save log
|
| 527 |
+
if messages and len(messages) > 3:
|
| 528 |
+
try:
|
| 529 |
+
log_path = save_chat_log(messages, scenario, character_name, user_character)
|
| 530 |
+
print(f"\n{Colors.CYAN}📝 Chat log saved: {log_path}{Colors.END}")
|
| 531 |
+
except Exception as e:
|
| 532 |
+
print(f"\n{Colors.RED}❌ Save failed: {e}{Colors.END}")
|
| 533 |
+
|
| 534 |
+
|
| 535 |
+
if __name__ == "__main__":
|
| 536 |
+
main()
|
chat_demo/coser_scenarios.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
chat_template.jinja
ADDED
|
@@ -0,0 +1,85 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{%- if tools %}
|
| 2 |
+
{{- '<|im_start|>system\n' }}
|
| 3 |
+
{%- if messages[0].role == 'system' %}
|
| 4 |
+
{{- messages[0].content + '\n\n' }}
|
| 5 |
+
{%- endif %}
|
| 6 |
+
{{- "# 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>" }}
|
| 7 |
+
{%- for tool in tools %}
|
| 8 |
+
{{- "\n" }}
|
| 9 |
+
{{- tool | tojson }}
|
| 10 |
+
{%- endfor %}
|
| 11 |
+
{{- "\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" }}
|
| 12 |
+
{%- else %}
|
| 13 |
+
{%- if messages[0].role == 'system' %}
|
| 14 |
+
{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
|
| 15 |
+
{%- endif %}
|
| 16 |
+
{%- endif %}
|
| 17 |
+
{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 18 |
+
{%- for message in messages[::-1] %}
|
| 19 |
+
{%- set index = (messages|length - 1) - loop.index0 %}
|
| 20 |
+
{%- if ns.multi_step_tool and message.role == "user" and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
|
| 21 |
+
{%- set ns.multi_step_tool = false %}
|
| 22 |
+
{%- set ns.last_query_index = index %}
|
| 23 |
+
{%- endif %}
|
| 24 |
+
{%- endfor %}
|
| 25 |
+
{%- for message in messages %}
|
| 26 |
+
{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
|
| 27 |
+
{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
|
| 28 |
+
{%- elif message.role == "assistant" %}
|
| 29 |
+
{%- set content = message.content %}
|
| 30 |
+
{%- set reasoning_content = '' %}
|
| 31 |
+
{%- if message.reasoning_content is defined and message.reasoning_content is not none %}
|
| 32 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 33 |
+
{%- else %}
|
| 34 |
+
{%- if '</think>' in message.content %}
|
| 35 |
+
{%- set content = message.content.split('</think>')[-1].lstrip('\n') %}
|
| 36 |
+
{%- set reasoning_content = message.content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
| 37 |
+
{%- endif %}
|
| 38 |
+
{%- endif %}
|
| 39 |
+
{%- if loop.index0 > ns.last_query_index %}
|
| 40 |
+
{%- if loop.last or (not loop.last and reasoning_content) %}
|
| 41 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
|
| 42 |
+
{%- else %}
|
| 43 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 44 |
+
{%- endif %}
|
| 45 |
+
{%- else %}
|
| 46 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 47 |
+
{%- endif %}
|
| 48 |
+
{%- if message.tool_calls %}
|
| 49 |
+
{%- for tool_call in message.tool_calls %}
|
| 50 |
+
{%- if (loop.first and content) or (not loop.first) %}
|
| 51 |
+
{{- '\n' }}
|
| 52 |
+
{%- endif %}
|
| 53 |
+
{%- if tool_call.function %}
|
| 54 |
+
{%- set tool_call = tool_call.function %}
|
| 55 |
+
{%- endif %}
|
| 56 |
+
{{- '<tool_call>\n{"name": "' }}
|
| 57 |
+
{{- tool_call.name }}
|
| 58 |
+
{{- '", "arguments": ' }}
|
| 59 |
+
{%- if tool_call.arguments is string %}
|
| 60 |
+
{{- tool_call.arguments }}
|
| 61 |
+
{%- else %}
|
| 62 |
+
{{- tool_call.arguments | tojson }}
|
| 63 |
+
{%- endif %}
|
| 64 |
+
{{- '}\n</tool_call>' }}
|
| 65 |
+
{%- endfor %}
|
| 66 |
+
{%- endif %}
|
| 67 |
+
{{- '<|im_end|>\n' }}
|
| 68 |
+
{%- elif message.role == "tool" %}
|
| 69 |
+
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
| 70 |
+
{{- '<|im_start|>user' }}
|
| 71 |
+
{%- endif %}
|
| 72 |
+
{{- '\n<tool_response>\n' }}
|
| 73 |
+
{{- message.content }}
|
| 74 |
+
{{- '\n</tool_response>' }}
|
| 75 |
+
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
| 76 |
+
{{- '<|im_end|>\n' }}
|
| 77 |
+
{%- endif %}
|
| 78 |
+
{%- endif %}
|
| 79 |
+
{%- endfor %}
|
| 80 |
+
{%- if add_generation_prompt %}
|
| 81 |
+
{{- '<|im_start|>assistant\n' }}
|
| 82 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 83 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 84 |
+
{%- endif %}
|
| 85 |
+
{%- endif %}
|
config.json
ADDED
|
@@ -0,0 +1,34 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"Qwen3ForCausalLM"
|
| 4 |
+
],
|
| 5 |
+
"attention_bias": false,
|
| 6 |
+
"attention_dropout": 0.0,
|
| 7 |
+
"eos_token_id": 151645,
|
| 8 |
+
"head_dim": 128,
|
| 9 |
+
"hidden_act": "silu",
|
| 10 |
+
"hidden_size": 5120,
|
| 11 |
+
"initializer_range": 0.02,
|
| 12 |
+
"intermediate_size": 25600,
|
| 13 |
+
"max_position_embeddings": 131072,
|
| 14 |
+
"max_window_layers": 64,
|
| 15 |
+
"model_type": "qwen3",
|
| 16 |
+
"num_attention_heads": 64,
|
| 17 |
+
"num_hidden_layers": 64,
|
| 18 |
+
"num_key_value_heads": 8,
|
| 19 |
+
"pad_token_id": 151643,
|
| 20 |
+
"rms_norm_eps": 1e-06,
|
| 21 |
+
"rope_scaling": {
|
| 22 |
+
"factor": 4.0,
|
| 23 |
+
"original_max_position_embeddings": 32768,
|
| 24 |
+
"rope_type": "yarn"
|
| 25 |
+
},
|
| 26 |
+
"rope_theta": 1000000,
|
| 27 |
+
"sliding_window": null,
|
| 28 |
+
"tie_word_embeddings": false,
|
| 29 |
+
"torch_dtype": "bfloat16",
|
| 30 |
+
"transformers_version": "4.52.4",
|
| 31 |
+
"use_cache": true,
|
| 32 |
+
"use_sliding_window": false,
|
| 33 |
+
"vocab_size": 151936
|
| 34 |
+
}
|
figure2github.png
ADDED
|
Git LFS Details
|
generation_config.json
ADDED
|
@@ -0,0 +1,13 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token_id": 151643,
|
| 3 |
+
"do_sample": true,
|
| 4 |
+
"eos_token_id": [
|
| 5 |
+
151645,
|
| 6 |
+
151643
|
| 7 |
+
],
|
| 8 |
+
"pad_token_id": 151643,
|
| 9 |
+
"temperature": 0.6,
|
| 10 |
+
"top_k": 20,
|
| 11 |
+
"top_p": 0.95,
|
| 12 |
+
"transformers_version": "4.52.4"
|
| 13 |
+
}
|
merges.txt
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
model-00001-of-00014.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:30e6f85e21a0e9d3483e8bb9e6010c80a8e797719552329ae795f76a26b52447
|
| 3 |
+
size 4928419424
|
model-00002-of-00014.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:99db49822e9f64fd5502fd0d42e2e5a6fb43df4206fe161cb1c8120e32670637
|
| 3 |
+
size 4781605144
|
model-00003-of-00014.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e07a88f5427346dfe5224e4b2c81368b18a293ae92b747c1e1a0cd18411032c5
|
| 3 |
+
size 4928450568
|
model-00004-of-00014.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5888990fba12830a1c24bc6cc470697284f57fa3ff9bc68abb2f27c15ec9ae08
|
| 3 |
+
size 4980813680
|
model-00005-of-00014.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:493e7423c2354cdc29e88cb6bbd439b9fe0a0c5dc44c9df7f912ef36f3de6997
|
| 3 |
+
size 4991315040
|
model-00006-of-00014.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:540b426e81ddf3232e20258648997d52ece0532c0d3b88742c0dcd232beedda3
|
| 3 |
+
size 4949367504
|
model-00007-of-00014.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
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ADDED
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| 2 |
+
"additional_special_tokens": [
|
| 3 |
+
"<|im_start|>",
|
| 4 |
+
"<|im_end|>",
|
| 5 |
+
"<|object_ref_start|>",
|
| 6 |
+
"<|object_ref_end|>",
|
| 7 |
+
"<|box_start|>",
|
| 8 |
+
"<|box_end|>",
|
| 9 |
+
"<|quad_start|>",
|
| 10 |
+
"<|quad_end|>",
|
| 11 |
+
"<|vision_start|>",
|
| 12 |
+
"<|vision_end|>",
|
| 13 |
+
"<|vision_pad|>",
|
| 14 |
+
"<|image_pad|>",
|
| 15 |
+
"<|video_pad|>"
|
| 16 |
+
],
|
| 17 |
+
"eos_token": {
|
| 18 |
+
"content": "<|im_end|>",
|
| 19 |
+
"lstrip": false,
|
| 20 |
+
"normalized": false,
|
| 21 |
+
"rstrip": false,
|
| 22 |
+
"single_word": false
|
| 23 |
+
},
|
| 24 |
+
"pad_token": {
|
| 25 |
+
"content": "<|endoftext|>",
|
| 26 |
+
"lstrip": false,
|
| 27 |
+
"normalized": false,
|
| 28 |
+
"rstrip": false,
|
| 29 |
+
"single_word": false
|
| 30 |
+
}
|
| 31 |
+
}
|
tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
|
| 3 |
+
size 11422654
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,240 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_bos_token": false,
|
| 3 |
+
"add_prefix_space": false,
|
| 4 |
+
"added_tokens_decoder": {
|
| 5 |
+
"151643": {
|
| 6 |
+
"content": "<|endoftext|>",
|
| 7 |
+
"lstrip": false,
|
| 8 |
+
"normalized": false,
|
| 9 |
+
"rstrip": false,
|
| 10 |
+
"single_word": false,
|
| 11 |
+
"special": true
|
| 12 |
+
},
|
| 13 |
+
"151644": {
|
| 14 |
+
"content": "<|im_start|>",
|
| 15 |
+
"lstrip": false,
|
| 16 |
+
"normalized": false,
|
| 17 |
+
"rstrip": false,
|
| 18 |
+
"single_word": false,
|
| 19 |
+
"special": true
|
| 20 |
+
},
|
| 21 |
+
"151645": {
|
| 22 |
+
"content": "<|im_end|>",
|
| 23 |
+
"lstrip": false,
|
| 24 |
+
"normalized": false,
|
| 25 |
+
"rstrip": false,
|
| 26 |
+
"single_word": false,
|
| 27 |
+
"special": true
|
| 28 |
+
},
|
| 29 |
+
"151646": {
|
| 30 |
+
"content": "<|object_ref_start|>",
|
| 31 |
+
"lstrip": false,
|
| 32 |
+
"normalized": false,
|
| 33 |
+
"rstrip": false,
|
| 34 |
+
"single_word": false,
|
| 35 |
+
"special": true
|
| 36 |
+
},
|
| 37 |
+
"151647": {
|
| 38 |
+
"content": "<|object_ref_end|>",
|
| 39 |
+
"lstrip": false,
|
| 40 |
+
"normalized": false,
|
| 41 |
+
"rstrip": false,
|
| 42 |
+
"single_word": false,
|
| 43 |
+
"special": true
|
| 44 |
+
},
|
| 45 |
+
"151648": {
|
| 46 |
+
"content": "<|box_start|>",
|
| 47 |
+
"lstrip": false,
|
| 48 |
+
"normalized": false,
|
| 49 |
+
"rstrip": false,
|
| 50 |
+
"single_word": false,
|
| 51 |
+
"special": true
|
| 52 |
+
},
|
| 53 |
+
"151649": {
|
| 54 |
+
"content": "<|box_end|>",
|
| 55 |
+
"lstrip": false,
|
| 56 |
+
"normalized": false,
|
| 57 |
+
"rstrip": false,
|
| 58 |
+
"single_word": false,
|
| 59 |
+
"special": true
|
| 60 |
+
},
|
| 61 |
+
"151650": {
|
| 62 |
+
"content": "<|quad_start|>",
|
| 63 |
+
"lstrip": false,
|
| 64 |
+
"normalized": false,
|
| 65 |
+
"rstrip": false,
|
| 66 |
+
"single_word": false,
|
| 67 |
+
"special": true
|
| 68 |
+
},
|
| 69 |
+
"151651": {
|
| 70 |
+
"content": "<|quad_end|>",
|
| 71 |
+
"lstrip": false,
|
| 72 |
+
"normalized": false,
|
| 73 |
+
"rstrip": false,
|
| 74 |
+
"single_word": false,
|
| 75 |
+
"special": true
|
| 76 |
+
},
|
| 77 |
+
"151652": {
|
| 78 |
+
"content": "<|vision_start|>",
|
| 79 |
+
"lstrip": false,
|
| 80 |
+
"normalized": false,
|
| 81 |
+
"rstrip": false,
|
| 82 |
+
"single_word": false,
|
| 83 |
+
"special": true
|
| 84 |
+
},
|
| 85 |
+
"151653": {
|
| 86 |
+
"content": "<|vision_end|>",
|
| 87 |
+
"lstrip": false,
|
| 88 |
+
"normalized": false,
|
| 89 |
+
"rstrip": false,
|
| 90 |
+
"single_word": false,
|
| 91 |
+
"special": true
|
| 92 |
+
},
|
| 93 |
+
"151654": {
|
| 94 |
+
"content": "<|vision_pad|>",
|
| 95 |
+
"lstrip": false,
|
| 96 |
+
"normalized": false,
|
| 97 |
+
"rstrip": false,
|
| 98 |
+
"single_word": false,
|
| 99 |
+
"special": true
|
| 100 |
+
},
|
| 101 |
+
"151655": {
|
| 102 |
+
"content": "<|image_pad|>",
|
| 103 |
+
"lstrip": false,
|
| 104 |
+
"normalized": false,
|
| 105 |
+
"rstrip": false,
|
| 106 |
+
"single_word": false,
|
| 107 |
+
"special": true
|
| 108 |
+
},
|
| 109 |
+
"151656": {
|
| 110 |
+
"content": "<|video_pad|>",
|
| 111 |
+
"lstrip": false,
|
| 112 |
+
"normalized": false,
|
| 113 |
+
"rstrip": false,
|
| 114 |
+
"single_word": false,
|
| 115 |
+
"special": true
|
| 116 |
+
},
|
| 117 |
+
"151657": {
|
| 118 |
+
"content": "<tool_call>",
|
| 119 |
+
"lstrip": false,
|
| 120 |
+
"normalized": false,
|
| 121 |
+
"rstrip": false,
|
| 122 |
+
"single_word": false,
|
| 123 |
+
"special": false
|
| 124 |
+
},
|
| 125 |
+
"151658": {
|
| 126 |
+
"content": "</tool_call>",
|
| 127 |
+
"lstrip": false,
|
| 128 |
+
"normalized": false,
|
| 129 |
+
"rstrip": false,
|
| 130 |
+
"single_word": false,
|
| 131 |
+
"special": false
|
| 132 |
+
},
|
| 133 |
+
"151659": {
|
| 134 |
+
"content": "<|fim_prefix|>",
|
| 135 |
+
"lstrip": false,
|
| 136 |
+
"normalized": false,
|
| 137 |
+
"rstrip": false,
|
| 138 |
+
"single_word": false,
|
| 139 |
+
"special": false
|
| 140 |
+
},
|
| 141 |
+
"151660": {
|
| 142 |
+
"content": "<|fim_middle|>",
|
| 143 |
+
"lstrip": false,
|
| 144 |
+
"normalized": false,
|
| 145 |
+
"rstrip": false,
|
| 146 |
+
"single_word": false,
|
| 147 |
+
"special": false
|
| 148 |
+
},
|
| 149 |
+
"151661": {
|
| 150 |
+
"content": "<|fim_suffix|>",
|
| 151 |
+
"lstrip": false,
|
| 152 |
+
"normalized": false,
|
| 153 |
+
"rstrip": false,
|
| 154 |
+
"single_word": false,
|
| 155 |
+
"special": false
|
| 156 |
+
},
|
| 157 |
+
"151662": {
|
| 158 |
+
"content": "<|fim_pad|>",
|
| 159 |
+
"lstrip": false,
|
| 160 |
+
"normalized": false,
|
| 161 |
+
"rstrip": false,
|
| 162 |
+
"single_word": false,
|
| 163 |
+
"special": false
|
| 164 |
+
},
|
| 165 |
+
"151663": {
|
| 166 |
+
"content": "<|repo_name|>",
|
| 167 |
+
"lstrip": false,
|
| 168 |
+
"normalized": false,
|
| 169 |
+
"rstrip": false,
|
| 170 |
+
"single_word": false,
|
| 171 |
+
"special": false
|
| 172 |
+
},
|
| 173 |
+
"151664": {
|
| 174 |
+
"content": "<|file_sep|>",
|
| 175 |
+
"lstrip": false,
|
| 176 |
+
"normalized": false,
|
| 177 |
+
"rstrip": false,
|
| 178 |
+
"single_word": false,
|
| 179 |
+
"special": false
|
| 180 |
+
},
|
| 181 |
+
"151665": {
|
| 182 |
+
"content": "<tool_response>",
|
| 183 |
+
"lstrip": false,
|
| 184 |
+
"normalized": false,
|
| 185 |
+
"rstrip": false,
|
| 186 |
+
"single_word": false,
|
| 187 |
+
"special": false
|
| 188 |
+
},
|
| 189 |
+
"151666": {
|
| 190 |
+
"content": "</tool_response>",
|
| 191 |
+
"lstrip": false,
|
| 192 |
+
"normalized": false,
|
| 193 |
+
"rstrip": false,
|
| 194 |
+
"single_word": false,
|
| 195 |
+
"special": false
|
| 196 |
+
},
|
| 197 |
+
"151667": {
|
| 198 |
+
"content": "<think>",
|
| 199 |
+
"lstrip": false,
|
| 200 |
+
"normalized": false,
|
| 201 |
+
"rstrip": false,
|
| 202 |
+
"single_word": false,
|
| 203 |
+
"special": false
|
| 204 |
+
},
|
| 205 |
+
"151668": {
|
| 206 |
+
"content": "</think>",
|
| 207 |
+
"lstrip": false,
|
| 208 |
+
"normalized": false,
|
| 209 |
+
"rstrip": false,
|
| 210 |
+
"single_word": false,
|
| 211 |
+
"special": false
|
| 212 |
+
}
|
| 213 |
+
},
|
| 214 |
+
"additional_special_tokens": [
|
| 215 |
+
"<|im_start|>",
|
| 216 |
+
"<|im_end|>",
|
| 217 |
+
"<|object_ref_start|>",
|
| 218 |
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"<|object_ref_end|>",
|
| 219 |
+
"<|box_start|>",
|
| 220 |
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"<|box_end|>",
|
| 221 |
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"<|quad_start|>",
|
| 222 |
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"<|quad_end|>",
|
| 223 |
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"<|vision_start|>",
|
| 224 |
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"<|vision_end|>",
|
| 225 |
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"<|vision_pad|>",
|
| 226 |
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"<|image_pad|>",
|
| 227 |
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"<|video_pad|>"
|
| 228 |
+
],
|
| 229 |
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"bos_token": null,
|
| 230 |
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"clean_up_tokenization_spaces": false,
|
| 231 |
+
"eos_token": "<|im_end|>",
|
| 232 |
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"errors": "replace",
|
| 233 |
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"extra_special_tokens": {},
|
| 234 |
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"model_max_length": 131072,
|
| 235 |
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"pad_token": "<|endoftext|>",
|
| 236 |
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"split_special_tokens": false,
|
| 237 |
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"tokenizer_class": "Qwen2Tokenizer",
|
| 238 |
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"unk_token": null,
|
| 239 |
+
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0].role == 'system' %}\n {{- messages[0].content + '\\n\\n' }}\n {%- endif %}\n {{- \"# 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>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\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\" }}\n{%- else %}\n {%- if messages[0].role == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n {%- set index = (messages|length - 1) - loop.index0 %}\n {%- if ns.multi_step_tool and message.role == \"user\" and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}\n {%- set ns.multi_step_tool = false %}\n {%- set ns.last_query_index = index %}\n {%- endif %}\n{%- endfor %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {%- set content = message.content %}\n {%- set reasoning_content = '' %}\n {%- if message.reasoning_content is defined and message.reasoning_content is not none %}\n {%- set reasoning_content = message.reasoning_content %}\n {%- else %}\n {%- if '</think>' in message.content %}\n {%- set content = message.content.split('</think>')[-1].lstrip('\\n') %}\n {%- set reasoning_content = message.content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n {%- endif %}\n {%- endif %}\n {%- if loop.index0 > ns.last_query_index %}\n {%- if loop.last or (not loop.last and reasoning_content) %}\n {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content.strip('\\n') + '\\n</think>\\n\\n' + content.lstrip('\\n') }}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\\n' + content }}\n {%- endif %}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\\n' + content }}\n {%- endif %}\n {%- if message.tool_calls %}\n {%- for tool_call in message.tool_calls %}\n {%- if (loop.first and content) or (not loop.first) %}\n {{- '\\n' }}\n {%- endif %}\n {%- if tool_call.function %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {%- if tool_call.arguments is string %}\n {{- tool_call.arguments }}\n {%- else %}\n {{- tool_call.arguments | tojson }}\n {%- endif %}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {%- endif %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n {%- if enable_thinking is defined and enable_thinking is false %}\n {{- '<think>\\n\\n</think>\\n\\n' }}\n {%- endif %}\n{%- endif %}"
|
| 240 |
+
}
|
tokenizer_config.json.bak
ADDED
|
@@ -0,0 +1,239 @@
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|
| 1 |
+
{
|
| 2 |
+
"add_bos_token": false,
|
| 3 |
+
"add_prefix_space": false,
|
| 4 |
+
"added_tokens_decoder": {
|
| 5 |
+
"151643": {
|
| 6 |
+
"content": "<|endoftext|>",
|
| 7 |
+
"lstrip": false,
|
| 8 |
+
"normalized": false,
|
| 9 |
+
"rstrip": false,
|
| 10 |
+
"single_word": false,
|
| 11 |
+
"special": true
|
| 12 |
+
},
|
| 13 |
+
"151644": {
|
| 14 |
+
"content": "<|im_start|>",
|
| 15 |
+
"lstrip": false,
|
| 16 |
+
"normalized": false,
|
| 17 |
+
"rstrip": false,
|
| 18 |
+
"single_word": false,
|
| 19 |
+
"special": true
|
| 20 |
+
},
|
| 21 |
+
"151645": {
|
| 22 |
+
"content": "<|im_end|>",
|
| 23 |
+
"lstrip": false,
|
| 24 |
+
"normalized": false,
|
| 25 |
+
"rstrip": false,
|
| 26 |
+
"single_word": false,
|
| 27 |
+
"special": true
|
| 28 |
+
},
|
| 29 |
+
"151646": {
|
| 30 |
+
"content": "<|object_ref_start|>",
|
| 31 |
+
"lstrip": false,
|
| 32 |
+
"normalized": false,
|
| 33 |
+
"rstrip": false,
|
| 34 |
+
"single_word": false,
|
| 35 |
+
"special": true
|
| 36 |
+
},
|
| 37 |
+
"151647": {
|
| 38 |
+
"content": "<|object_ref_end|>",
|
| 39 |
+
"lstrip": false,
|
| 40 |
+
"normalized": false,
|
| 41 |
+
"rstrip": false,
|
| 42 |
+
"single_word": false,
|
| 43 |
+
"special": true
|
| 44 |
+
},
|
| 45 |
+
"151648": {
|
| 46 |
+
"content": "<|box_start|>",
|
| 47 |
+
"lstrip": false,
|
| 48 |
+
"normalized": false,
|
| 49 |
+
"rstrip": false,
|
| 50 |
+
"single_word": false,
|
| 51 |
+
"special": true
|
| 52 |
+
},
|
| 53 |
+
"151649": {
|
| 54 |
+
"content": "<|box_end|>",
|
| 55 |
+
"lstrip": false,
|
| 56 |
+
"normalized": false,
|
| 57 |
+
"rstrip": false,
|
| 58 |
+
"single_word": false,
|
| 59 |
+
"special": true
|
| 60 |
+
},
|
| 61 |
+
"151650": {
|
| 62 |
+
"content": "<|quad_start|>",
|
| 63 |
+
"lstrip": false,
|
| 64 |
+
"normalized": false,
|
| 65 |
+
"rstrip": false,
|
| 66 |
+
"single_word": false,
|
| 67 |
+
"special": true
|
| 68 |
+
},
|
| 69 |
+
"151651": {
|
| 70 |
+
"content": "<|quad_end|>",
|
| 71 |
+
"lstrip": false,
|
| 72 |
+
"normalized": false,
|
| 73 |
+
"rstrip": false,
|
| 74 |
+
"single_word": false,
|
| 75 |
+
"special": true
|
| 76 |
+
},
|
| 77 |
+
"151652": {
|
| 78 |
+
"content": "<|vision_start|>",
|
| 79 |
+
"lstrip": false,
|
| 80 |
+
"normalized": false,
|
| 81 |
+
"rstrip": false,
|
| 82 |
+
"single_word": false,
|
| 83 |
+
"special": true
|
| 84 |
+
},
|
| 85 |
+
"151653": {
|
| 86 |
+
"content": "<|vision_end|>",
|
| 87 |
+
"lstrip": false,
|
| 88 |
+
"normalized": false,
|
| 89 |
+
"rstrip": false,
|
| 90 |
+
"single_word": false,
|
| 91 |
+
"special": true
|
| 92 |
+
},
|
| 93 |
+
"151654": {
|
| 94 |
+
"content": "<|vision_pad|>",
|
| 95 |
+
"lstrip": false,
|
| 96 |
+
"normalized": false,
|
| 97 |
+
"rstrip": false,
|
| 98 |
+
"single_word": false,
|
| 99 |
+
"special": true
|
| 100 |
+
},
|
| 101 |
+
"151655": {
|
| 102 |
+
"content": "<|image_pad|>",
|
| 103 |
+
"lstrip": false,
|
| 104 |
+
"normalized": false,
|
| 105 |
+
"rstrip": false,
|
| 106 |
+
"single_word": false,
|
| 107 |
+
"special": true
|
| 108 |
+
},
|
| 109 |
+
"151656": {
|
| 110 |
+
"content": "<|video_pad|>",
|
| 111 |
+
"lstrip": false,
|
| 112 |
+
"normalized": false,
|
| 113 |
+
"rstrip": false,
|
| 114 |
+
"single_word": false,
|
| 115 |
+
"special": true
|
| 116 |
+
},
|
| 117 |
+
"151657": {
|
| 118 |
+
"content": "<tool_call>",
|
| 119 |
+
"lstrip": false,
|
| 120 |
+
"normalized": false,
|
| 121 |
+
"rstrip": false,
|
| 122 |
+
"single_word": false,
|
| 123 |
+
"special": false
|
| 124 |
+
},
|
| 125 |
+
"151658": {
|
| 126 |
+
"content": "</tool_call>",
|
| 127 |
+
"lstrip": false,
|
| 128 |
+
"normalized": false,
|
| 129 |
+
"rstrip": false,
|
| 130 |
+
"single_word": false,
|
| 131 |
+
"special": false
|
| 132 |
+
},
|
| 133 |
+
"151659": {
|
| 134 |
+
"content": "<|fim_prefix|>",
|
| 135 |
+
"lstrip": false,
|
| 136 |
+
"normalized": false,
|
| 137 |
+
"rstrip": false,
|
| 138 |
+
"single_word": false,
|
| 139 |
+
"special": false
|
| 140 |
+
},
|
| 141 |
+
"151660": {
|
| 142 |
+
"content": "<|fim_middle|>",
|
| 143 |
+
"lstrip": false,
|
| 144 |
+
"normalized": false,
|
| 145 |
+
"rstrip": false,
|
| 146 |
+
"single_word": false,
|
| 147 |
+
"special": false
|
| 148 |
+
},
|
| 149 |
+
"151661": {
|
| 150 |
+
"content": "<|fim_suffix|>",
|
| 151 |
+
"lstrip": false,
|
| 152 |
+
"normalized": false,
|
| 153 |
+
"rstrip": false,
|
| 154 |
+
"single_word": false,
|
| 155 |
+
"special": false
|
| 156 |
+
},
|
| 157 |
+
"151662": {
|
| 158 |
+
"content": "<|fim_pad|>",
|
| 159 |
+
"lstrip": false,
|
| 160 |
+
"normalized": false,
|
| 161 |
+
"rstrip": false,
|
| 162 |
+
"single_word": false,
|
| 163 |
+
"special": false
|
| 164 |
+
},
|
| 165 |
+
"151663": {
|
| 166 |
+
"content": "<|repo_name|>",
|
| 167 |
+
"lstrip": false,
|
| 168 |
+
"normalized": false,
|
| 169 |
+
"rstrip": false,
|
| 170 |
+
"single_word": false,
|
| 171 |
+
"special": false
|
| 172 |
+
},
|
| 173 |
+
"151664": {
|
| 174 |
+
"content": "<|file_sep|>",
|
| 175 |
+
"lstrip": false,
|
| 176 |
+
"normalized": false,
|
| 177 |
+
"rstrip": false,
|
| 178 |
+
"single_word": false,
|
| 179 |
+
"special": false
|
| 180 |
+
},
|
| 181 |
+
"151665": {
|
| 182 |
+
"content": "<tool_response>",
|
| 183 |
+
"lstrip": false,
|
| 184 |
+
"normalized": false,
|
| 185 |
+
"rstrip": false,
|
| 186 |
+
"single_word": false,
|
| 187 |
+
"special": false
|
| 188 |
+
},
|
| 189 |
+
"151666": {
|
| 190 |
+
"content": "</tool_response>",
|
| 191 |
+
"lstrip": false,
|
| 192 |
+
"normalized": false,
|
| 193 |
+
"rstrip": false,
|
| 194 |
+
"single_word": false,
|
| 195 |
+
"special": false
|
| 196 |
+
},
|
| 197 |
+
"151667": {
|
| 198 |
+
"content": "<think>",
|
| 199 |
+
"lstrip": false,
|
| 200 |
+
"normalized": false,
|
| 201 |
+
"rstrip": false,
|
| 202 |
+
"single_word": false,
|
| 203 |
+
"special": false
|
| 204 |
+
},
|
| 205 |
+
"151668": {
|
| 206 |
+
"content": "</think>",
|
| 207 |
+
"lstrip": false,
|
| 208 |
+
"normalized": false,
|
| 209 |
+
"rstrip": false,
|
| 210 |
+
"single_word": false,
|
| 211 |
+
"special": false
|
| 212 |
+
}
|
| 213 |
+
},
|
| 214 |
+
"additional_special_tokens": [
|
| 215 |
+
"<|im_start|>",
|
| 216 |
+
"<|im_end|>",
|
| 217 |
+
"<|object_ref_start|>",
|
| 218 |
+
"<|object_ref_end|>",
|
| 219 |
+
"<|box_start|>",
|
| 220 |
+
"<|box_end|>",
|
| 221 |
+
"<|quad_start|>",
|
| 222 |
+
"<|quad_end|>",
|
| 223 |
+
"<|vision_start|>",
|
| 224 |
+
"<|vision_end|>",
|
| 225 |
+
"<|vision_pad|>",
|
| 226 |
+
"<|image_pad|>",
|
| 227 |
+
"<|video_pad|>"
|
| 228 |
+
],
|
| 229 |
+
"bos_token": null,
|
| 230 |
+
"clean_up_tokenization_spaces": false,
|
| 231 |
+
"eos_token": "<|im_end|>",
|
| 232 |
+
"errors": "replace",
|
| 233 |
+
"extra_special_tokens": {},
|
| 234 |
+
"model_max_length": 131072,
|
| 235 |
+
"pad_token": "<|endoftext|>",
|
| 236 |
+
"split_special_tokens": false,
|
| 237 |
+
"tokenizer_class": "Qwen2Tokenizer",
|
| 238 |
+
"unk_token": null
|
| 239 |
+
}
|
vocab.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|