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update qwen model to latest

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Yuhang Zhou
2026-02-23 16:50:16 +08:00
parent d3e34caaa3
commit f41a6b2a19
1 changed files with 8 additions and 16 deletions
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24
examples/run_qwen.py
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@@ -18,10 +18,6 @@ Workforce example using Qwen models from Alibaba Cloud.
To run this file, you need to configure the Qwen API key. To run this file, you need to configure the Qwen API key.
You can obtain your API key from Bailian platform: bailian.console.aliyun.com You can obtain your API key from Bailian platform: bailian.console.aliyun.com
Set it as QWEN_API_KEY="your-api-key" in your .env file or add it to your environment variables. Set it as QWEN_API_KEY="your-api-key" in your .env file or add it to your environment variables.
Qwen models support:
- QWEN_MAX: For text-based tasks
- QWEN_VL_MAX: For vision-language tasks (multimodal)
""" """
import sys import sys
@@ -59,43 +55,39 @@ set_log_level(level="DEBUG")
def construct_agent_list() -> List[Dict[str, Any]]: def construct_agent_list() -> List[Dict[str, Any]]:
"""Construct a list of agents with their configurations.""" """Construct a list of agents with their configurations."""
# Use QWEN_MAX for text-based tasks
web_model = ModelFactory.create( web_model = ModelFactory.create(
model_platform=ModelPlatformType.QWEN, model_platform=ModelPlatformType.QWEN,
model_type=ModelType.QWEN_MAX, model_type="qwen3.5-plus",
model_config_dict={"temperature": 0}, model_config_dict={"temperature": 0},
) )
# Use QWEN_VL_MAX for document processing (supports multimodal)
document_processing_model = ModelFactory.create( document_processing_model = ModelFactory.create(
model_platform=ModelPlatformType.QWEN, model_platform=ModelPlatformType.QWEN,
model_type=ModelType.QWEN_VL_MAX, model_type="qwen3.5-plus",
model_config_dict={"temperature": 0}, model_config_dict={"temperature": 0},
) )
# Use QWEN_MAX for reasoning tasks
reasoning_model = ModelFactory.create( reasoning_model = ModelFactory.create(
model_platform=ModelPlatformType.QWEN, model_platform=ModelPlatformType.QWEN,
model_type=ModelType.QWEN_MAX, model_type="qwen3.5-plus",
model_config_dict={"temperature": 0}, model_config_dict={"temperature": 0},
) )
# Use QWEN_VL_MAX for image analysis
image_analysis_model = ModelFactory.create( image_analysis_model = ModelFactory.create(
model_platform=ModelPlatformType.QWEN, model_platform=ModelPlatformType.QWEN,
model_type=ModelType.QWEN_VL_MAX, model_type="qwen3.5-plus",
model_config_dict={"temperature": 0}, model_config_dict={"temperature": 0},
) )
browsing_model = ModelFactory.create( browsing_model = ModelFactory.create(
model_platform=ModelPlatformType.QWEN, model_platform=ModelPlatformType.QWEN,
model_type=ModelType.QWEN_MAX, model_type="qwen3.5-plus",
model_config_dict={"temperature": 0}, model_config_dict={"temperature": 0},
) )
planning_model = ModelFactory.create( planning_model = ModelFactory.create(
model_platform=ModelPlatformType.QWEN, model_platform=ModelPlatformType.QWEN,
model_type=ModelType.QWEN_MAX, model_type="qwen3.5-plus",
model_config_dict={"temperature": 0}, model_config_dict={"temperature": 0},
) )
@@ -193,7 +185,7 @@ def construct_workforce() -> Workforce:
coordinator_agent_kwargs = { coordinator_agent_kwargs = {
"model": ModelFactory.create( "model": ModelFactory.create(
model_platform=ModelPlatformType.QWEN, model_platform=ModelPlatformType.QWEN,
model_type=ModelType.QWEN_MAX, model_type="qwen3.5-plus",
model_config_dict={"temperature": 0}, model_config_dict={"temperature": 0},
) )
} }
@@ -201,7 +193,7 @@ def construct_workforce() -> Workforce:
task_agent_kwargs = { task_agent_kwargs = {
"model": ModelFactory.create( "model": ModelFactory.create(
model_platform=ModelPlatformType.QWEN, model_platform=ModelPlatformType.QWEN,
model_type=ModelType.QWEN_MAX, model_type="qwen3.5-plus",
model_config_dict={"temperature": 0}, model_config_dict={"temperature": 0},
) )
} }