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.
47 lines
1.7 KiB
Python
47 lines
1.7 KiB
Python
"""「大脑」抽象:把不同助手类型(prompt/workflow/fastgpt/…)在运行时的差异收口。
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cascade 管线骨架对所有类型一致(STT → LLM 槽 → TTS),变化的只有:
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- 谁产出助手文本(LLM 槽里塞什么)——build_llm
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- 开场白来源(静态 / 外部异步拉取)——greeting
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- 对话上下文归谁维护——spec.owns_context
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- 是否支持 realtime——spec.supported_runtime_modes
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阶段 1 只抽到「够 fastgpt 用」的程度;workflow 编排仍内联在 pipeline.py,
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待阶段 2 再搬进 WorkflowBrain 收口。
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"""
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from __future__ import annotations
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from dataclasses import dataclass
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from typing import Protocol, runtime_checkable
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from models import AssistantConfig
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from pipecat.processors.aggregators.llm_context import LLMContext
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from pipecat.processors.frame_processor import FrameProcessor
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@dataclass(frozen=True)
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class BrainSpec:
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"""类型元数据。单一来源,供运行时门控与上下文归属决策复用。"""
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type: str
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supported_runtime_modes: frozenset[str]
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# True:由本服务维护 LLMContext(prompt/workflow);
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# False:上下文/知识库/工具由外部服务端接管(fastgpt/dify),本地不写 context。
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owns_context: bool
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@runtime_checkable
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class Brain(Protocol):
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"""每通电话 new 一个实例(可持有 chatId / 当前节点等会话状态)。"""
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spec: BrainSpec
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async def greeting(self, cfg: AssistantConfig) -> str:
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"""开场白。内部类型通常直接用 cfg.greeting;外部类型异步拉取后端配置。"""
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...
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def build_llm(self, cfg: AssistantConfig, context: LLMContext) -> FrameProcessor:
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"""返回丢进管线 LLM 槽位的帧处理器(标准 LLMService 或外部托管的伪 LLM)。"""
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...
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