Revert commit for build_prompt
Browse files
README.md
CHANGED
|
@@ -200,30 +200,13 @@ def build_conversation_history_prompt(conversation_history: str):
|
|
| 200 |
|
| 201 |
|
| 202 |
# Helper function to build the input prompt for our model
|
| 203 |
-
def build_prompt(task_instruction: str, format_instruction: str, tools: list, query: str
|
| 204 |
-
prompt = f"[BEGIN OF TASK INSTRUCTION]
|
| 205 |
-
{
|
| 206 |
-
[END OF
|
| 207 |
-
|
| 208 |
-
"
|
| 209 |
-
prompt += f"[BEGIN OF AVAILABLE TOOLS]
|
| 210 |
-
{json.dumps(xlam_format_tools)}
|
| 211 |
-
[END OF AVAILABLE TOOLS]
|
| 212 |
-
|
| 213 |
-
"
|
| 214 |
-
prompt += f"[BEGIN OF FORMAT INSTRUCTION]
|
| 215 |
-
{format_instruction}
|
| 216 |
-
[END OF FORMAT INSTRUCTION]
|
| 217 |
-
|
| 218 |
-
"
|
| 219 |
-
prompt += f"[BEGIN OF QUERY]
|
| 220 |
-
{query}
|
| 221 |
-
[END OF QUERY]
|
| 222 |
-
|
| 223 |
-
"
|
| 224 |
-
|
| 225 |
-
if len(conversation_history) > 0: prompt += build_conversation_history_prompt(conversation_history)
|
| 226 |
return prompt
|
|
|
|
| 227 |
|
| 228 |
# Build the input and start the inference
|
| 229 |
xlam_format_tools = convert_to_xlam_tool(openai_format_tools)
|
|
@@ -493,6 +476,15 @@ If you find this repo helpful, please consider to cite our papers:
|
|
| 493 |
}
|
| 494 |
```
|
| 495 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 496 |
```bibtex
|
| 497 |
@article{zhang2024agentohana,
|
| 498 |
title={AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning},
|
|
|
|
| 200 |
|
| 201 |
|
| 202 |
# Helper function to build the input prompt for our model
|
| 203 |
+
def build_prompt(task_instruction: str, format_instruction: str, tools: list, query: str):
|
| 204 |
+
prompt = f"[BEGIN OF TASK INSTRUCTION]\n{task_instruction}\n[END OF TASK INSTRUCTION]\n\n"
|
| 205 |
+
prompt += f"[BEGIN OF AVAILABLE TOOLS]\n{json.dumps(xlam_format_tools)}\n[END OF AVAILABLE TOOLS]\n\n"
|
| 206 |
+
prompt += f"[BEGIN OF FORMAT INSTRUCTION]\n{format_instruction}\n[END OF FORMAT INSTRUCTION]\n\n"
|
| 207 |
+
prompt += f"[BEGIN OF QUERY]\n{query}\n[END OF QUERY]\n\n"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 208 |
return prompt
|
| 209 |
+
|
| 210 |
|
| 211 |
# Build the input and start the inference
|
| 212 |
xlam_format_tools = convert_to_xlam_tool(openai_format_tools)
|
|
|
|
| 476 |
}
|
| 477 |
```
|
| 478 |
|
| 479 |
+
```bixtex
|
| 480 |
+
@article{zhang2025actionstudio,
|
| 481 |
+
title={ActionStudio: A Lightweight Framework for Data and Training of Action Models},
|
| 482 |
+
author={Zhang, Jianguo and Hoang, Thai and Zhu, Ming and Liu, Zuxin and Wang, Shiyu and Awalgaonkar, Tulika and Prabhakar, Akshara and Chen, Haolin and Yao, Weiran and Liu, Zhiwei and others},
|
| 483 |
+
journal={arXiv preprint arXiv:2503.22673},
|
| 484 |
+
year={2025}
|
| 485 |
+
}
|
| 486 |
+
```
|
| 487 |
+
|
| 488 |
```bibtex
|
| 489 |
@article{zhang2024agentohana,
|
| 490 |
title={AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning},
|