d30c7e37a6
##前端美化和bug修复 #### 💄 美化 - **前端美化**:对于整个前端效果进行了重新设计,现在的前端看起来会更立体。 #### 🐛 修复 - **前端演示**:修复了前端展示workflow列表的bug,但是workflow的具体条目显示由于序列化导致仍然有问题。 - **密钥修复**:对于secret_key现在在使用默认情况时,会强制生成一个安全的密钥。
79 lines
3.8 KiB
Python
79 lines
3.8 KiB
Python
# Copyright 2026 zhaoxi826
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from pydantic_ai import Agent
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from pydantic_ai.models.openai import OpenAIChatModel
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from pydantic_ai.models.anthropic import AnthropicModel
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from pydantic_ai.providers.openai import OpenAIProvider
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from pydantic_ai.providers.anthropic import AnthropicProvider
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from pretor.adapter.model_adapter.deepseek_reasoner import DeepSeekReasonerAgent
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from pretor.core.global_state_machine.model_provider import Provider
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from pretor.utils.agent_model import ResponseModel, DepsModel
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from pretor.utils.error import ModelNotExistError
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class AgentFactory:
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"""AgentFactory 核心组件类。
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这是一个领域数据模型或功能封装类,承载了 AgentFactory 相关的内聚属性定义与状态维护。它的存在隔离了局部的业务复杂性,并对外提供了类型安全的访问接口。 """
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def __init__(self):
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self._models_mapping = {"openai": (OpenAIChatModel, OpenAIProvider),
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"claude": (AnthropicModel, AnthropicProvider),
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"deepseek": (OpenAIChatModel, OpenAIProvider),}
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def create_agent(self,
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provider: Provider,
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model_id: str,
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output_type: ResponseModel,
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system_prompt: str,
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deps_type: DepsModel,
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agent_name: str,
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tools: list = None) -> Agent:
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"""
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create_agent方法,将输入的provider对象实例化为一个pydantic-ai的agent对象
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Args:
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provider: Provider对象,从global_state_machine中获取
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model_id: 模型名
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output_type: 输出格式
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system_prompt: 系统提示词
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deps_type: 依赖类型,在agent运行时动态输入的格式化消息
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agent_name: agent的名字
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tools: 工具列表
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Returns:
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返回被实例化的pydantic-ai的Agent对象
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"""
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if model_id not in provider.provider_models:
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raise ModelNotExistError("模型不存在")
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if provider.provider_type not in self._models_mapping:
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raise ValueError(f"不支持的协议类型: {provider.provider_type}")
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model_class, provider_class = self._models_mapping[provider.provider_type]
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model = model_class(model_id, provider=provider_class(api_key=provider.provider_apikey, base_url=provider.provider_url))
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match provider.provider_type:
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case "deepseek":
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agent = DeepSeekReasonerAgent(model=model,
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name=agent_name,
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output_type=output_type,
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deps_type=deps_type,
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system_prompt=system_prompt,
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tools=tools,
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retries=3,
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)
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case _:
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agent = Agent(model=model,
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name=agent_name,
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system_prompt=system_prompt,
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output_type=output_type,
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deps_type=deps_type,
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tools=tools)
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return agent |