mirror of
https://gitee.com/wanwujie/deer-flow
synced 2026-04-03 14:22:13 +08:00
462752b462
* feat: add rag provider and retriever * feat: retriever tool * feat: add retriever tool to the researcher node * feat: add rag http apis * feat: new message input supports resource mentions * feat: new message input component support resource mentions * refactor: need_web_search to need_search * chore: RAG integration docs * chore: change example api host * fix: user message color in dark mode * fix: mentions style * feat: add local_search_tool to researcher prompt * chore: research prompt * fix: ragflow page size and reporter with * docs: ragflow integration and add acknowledgment projects * chore: format
93 lines
3.4 KiB
Python
93 lines
3.4 KiB
Python
# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates
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# SPDX-License-Identifier: MIT
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from typing import List, Optional, Union
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from pydantic import BaseModel, Field
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from src.rag.retriever import Resource
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class ContentItem(BaseModel):
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type: str = Field(..., description="The type of content (text, image, etc.)")
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text: Optional[str] = Field(None, description="The text content if type is 'text'")
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image_url: Optional[str] = Field(
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None, description="The image URL if type is 'image'"
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)
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class ChatMessage(BaseModel):
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role: str = Field(
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..., description="The role of the message sender (user or assistant)"
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)
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content: Union[str, List[ContentItem]] = Field(
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...,
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description="The content of the message, either a string or a list of content items",
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)
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class ChatRequest(BaseModel):
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messages: Optional[List[ChatMessage]] = Field(
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[], description="History of messages between the user and the assistant"
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)
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resources: Optional[List[Resource]] = Field(
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[], description="Resources to be used for the research"
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)
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debug: Optional[bool] = Field(False, description="Whether to enable debug logging")
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thread_id: Optional[str] = Field(
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"__default__", description="A specific conversation identifier"
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)
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max_plan_iterations: Optional[int] = Field(
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1, description="The maximum number of plan iterations"
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)
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max_step_num: Optional[int] = Field(
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3, description="The maximum number of steps in a plan"
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)
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max_search_results: Optional[int] = Field(
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3, description="The maximum number of search results"
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)
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auto_accepted_plan: Optional[bool] = Field(
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False, description="Whether to automatically accept the plan"
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)
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interrupt_feedback: Optional[str] = Field(
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None, description="Interrupt feedback from the user on the plan"
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)
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mcp_settings: Optional[dict] = Field(
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None, description="MCP settings for the chat request"
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)
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enable_background_investigation: Optional[bool] = Field(
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True, description="Whether to get background investigation before plan"
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)
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class TTSRequest(BaseModel):
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text: str = Field(..., description="The text to convert to speech")
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voice_type: Optional[str] = Field(
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"BV700_V2_streaming", description="The voice type to use"
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)
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encoding: Optional[str] = Field("mp3", description="The audio encoding format")
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speed_ratio: Optional[float] = Field(1.0, description="Speech speed ratio")
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volume_ratio: Optional[float] = Field(1.0, description="Speech volume ratio")
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pitch_ratio: Optional[float] = Field(1.0, description="Speech pitch ratio")
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text_type: Optional[str] = Field("plain", description="Text type (plain or ssml)")
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with_frontend: Optional[int] = Field(
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1, description="Whether to use frontend processing"
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)
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frontend_type: Optional[str] = Field("unitTson", description="Frontend type")
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class GeneratePodcastRequest(BaseModel):
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content: str = Field(..., description="The content of the podcast")
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class GeneratePPTRequest(BaseModel):
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content: str = Field(..., description="The content of the ppt")
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class GenerateProseRequest(BaseModel):
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prompt: str = Field(..., description="The content of the prose")
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option: str = Field(..., description="The option of the prose writer")
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command: Optional[str] = Field(
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"", description="The user custom command of the prose writer"
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)
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