809b634420
- Add new fields in AssistantConfig for FastGPT connection details, including `fastgpt_api_url`, `fastgpt_api_key`, and `fastgpt_app_id`. - Update the pipeline to utilize the new FastGPT configuration, ensuring proper integration with external services. - Introduce type handling for different assistant types, including support for realtime modes and external brain management. - Refactor frontend components to include hints for FastGPT configuration inputs, improving user guidance during setup.
129 lines
4.0 KiB
Python
129 lines
4.0 KiB
Python
"""面向前端的请求/响应 DTO。与 DB 模型解耦,**响应里的 key 一律打码**。
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模型资源 DTO 字段对齐前端 ComponentsModelsPage 的 ModelResource:
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JSON 用 camelCase(modelId/interfaceType/apiUrl/apiKey),Python 内部用 snake_case,
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靠 Pydantic alias 自动互转。FastAPI 响应默认 by_alias=True,所以出参也是 camelCase。
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"""
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from __future__ import annotations
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from typing import Any, Literal
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from pydantic import BaseModel, ConfigDict, Field, model_validator
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from pydantic.alias_generators import to_camel
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RuntimeMode = Literal["pipeline", "realtime"]
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ModelType = Literal["LLM", "ASR", "TTS", "Realtime", "Embedding"]
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AssistantType = Literal["prompt", "workflow", "dify", "fastgpt", "opencode"]
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# 外部应用类型:其 config.apiKey 是该助手私有密钥,读时打码 / 写时哨兵
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EXTERNAL_TYPES = {"dify", "fastgpt", "opencode"}
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# 支持 realtime(语音到语音)的类型;外部托管大脑只能走 cascade。
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# 与 services.brains 各 BrainSpec.supported_runtime_modes 对齐(此处独立声明,
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# 避免 HTTP schema 层为做校验而引入 pipecat 重依赖)。
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REALTIME_CAPABLE_TYPES = {"prompt", "workflow"}
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class CamelModel(BaseModel):
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"""JSON camelCase ↔ Python snake_case。protected_namespaces 关掉以允许 model_id。"""
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model_config = ConfigDict(
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alias_generator=to_camel,
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populate_by_name=True,
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protected_namespaces=(),
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)
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# 各 type 允许的瘦字段(其余字段写入时清零,防止跨类型脏数据)
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ALLOWED_FIELDS: dict[str, set[str]] = {
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"prompt": {"prompt"},
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"workflow": {"graph"},
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"dify": {"api_url", "api_key"},
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"fastgpt": {"app_id", "api_url", "api_key"},
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"opencode": {"prompt", "api_url", "api_key"},
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}
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# ---------- 助手(单表 STI:瘦类型真列 + workflow 图 JSON 列) ----------
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class AssistantUpsert(CamelModel):
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name: str
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type: AssistantType = "prompt"
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runtime_mode: RuntimeMode = "pipeline"
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greeting: str = ""
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enable_interrupt: bool = True
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model_resource_ids: dict[ModelType, str] = Field(default_factory=dict)
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knowledge_base_id: str | None = None
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# 瘦类型专属(真列);按 type 取用,无关字段写入时清零
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prompt: str = ""
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api_url: str = ""
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api_key: str = "" # 写时:占位符/空 → 保留旧(哨兵)
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app_id: str = ""
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# workflow 专属:图
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graph: dict[str, Any] = Field(default_factory=dict)
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@model_validator(mode="after")
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def _strip_irrelevant_fields(self):
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allowed = ALLOWED_FIELDS[self.type]
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for field in ("prompt", "api_url", "api_key", "app_id"):
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if field not in allowed:
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setattr(self, field, "")
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if "graph" not in allowed:
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self.graph = {}
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# 外部托管大脑只能 cascade,拦住不兼容的 realtime
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if self.runtime_mode == "realtime" and self.type not in REALTIME_CAPABLE_TYPES:
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raise ValueError(f"类型 {self.type} 不支持 realtime 运行模式")
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return self
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class AssistantOut(AssistantUpsert):
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id: str
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updated_at: str | None = None
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# ---------- 知识库 ----------
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class KnowledgeBaseUpsert(CamelModel):
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name: str
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description: str = ""
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embedding_model_resource_id: str | None = None
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class KnowledgeBaseOut(KnowledgeBaseUpsert):
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id: str
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status: str = "active"
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updated_at: str | None = None
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# ---------- 接口定义驱动的统一模型资源 ----------
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class InterfaceDefinitionOut(CamelModel):
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interface_type: str
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name: str
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capability: ModelType
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field_schema: dict[str, Any]
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enabled: bool
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version: int
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class ModelResourceUpsert(CamelModel):
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name: str
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interface_type: str
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values: dict[str, Any] = Field(default_factory=dict)
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secrets: dict[str, Any] = Field(default_factory=dict)
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enabled: bool = True
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is_default: bool = False
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class ModelResourceOut(ModelResourceUpsert):
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id: str
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capability: ModelType
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updated_at: str | None = None
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class ModelResourceTestResult(CamelModel):
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ok: bool
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latency_ms: int | None = None
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message: str
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detail: str = ""
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