mirror of
https://gitee.com/wanwujie/deer-flow
synced 2026-04-03 22:32:12 +08:00
2510cc61de
* fix: support local models by making thought field optional in Plan model - Make thought field optional in Plan model to fix Pydantic validation errors with local models - Add Ollama configuration example to conf.yaml.example - Update documentation to include local model support - Improve planner prompt with better JSON format requirements Fixes local model integration issues where models like qwen3:14b would fail due to missing thought field in JSON output. * feat: Add intelligent clarification feature for research queries - Add multi-turn clarification process to refine vague research questions - Implement three-dimension clarification standard (Tech/App, Focus, Scope) - Add clarification state management in coordinator node - Update coordinator prompt with detailed clarification guidelines - Add UI settings to enable/disable clarification feature (disabled by default) - Update workflow to handle clarification rounds recursively - Add comprehensive test coverage for clarification functionality - Update documentation with clarification feature usage guide Key components: - src/graph/nodes.py: Core clarification logic and state management - src/prompts/coordinator.md: Detailed clarification guidelines - src/workflow.py: Recursive clarification handling - web/: UI settings integration - tests/: Comprehensive test coverage - docs/: Updated configuration guide * fix: Improve clarification conversation continuity - Add comprehensive conversation history to clarification context - Include previous exchanges summary in system messages - Add explicit guidelines for continuing rounds in coordinator prompt - Prevent LLM from starting new topics during clarification - Ensure topic continuity across clarification rounds Fixes issue where LLM would restart clarification instead of building upon previous exchanges. * fix: Add conversation history to clarification context * fix: resolve clarification feature message to planer, prompt, test issues - Optimize coordinator.md prompt template for better clarification flow - Simplify final message sent to planner after clarification - Fix API key assertion issues in test_search.py * fix: Add configurable max_clarification_rounds and comprehensive tests - Add max_clarification_rounds parameter for external configuration - Add comprehensive test cases for clarification feature in test_app.py - Fixes issues found during interactive mode testing where: - Recursive call failed due to missing initial_state parameter - Clarification exited prematurely at max rounds - Incorrect logging of max rounds reached * Move clarification tests to test_nodes.py and add max_clarification_rounds to zh.json
118 lines
4.4 KiB
Python
118 lines
4.4 KiB
Python
# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates
|
|
# SPDX-License-Identifier: MIT
|
|
|
|
from typing import List, Optional, Union
|
|
|
|
from pydantic import BaseModel, Field
|
|
|
|
from src.config.report_style import ReportStyle
|
|
from src.rag.retriever import Resource
|
|
|
|
|
|
class ContentItem(BaseModel):
|
|
type: str = Field(..., description="The type of content (text, image, etc.)")
|
|
text: Optional[str] = Field(None, description="The text content if type is 'text'")
|
|
image_url: Optional[str] = Field(
|
|
None, description="The image URL if type is 'image'"
|
|
)
|
|
|
|
|
|
class ChatMessage(BaseModel):
|
|
role: str = Field(
|
|
..., description="The role of the message sender (user or assistant)"
|
|
)
|
|
content: Union[str, List[ContentItem]] = Field(
|
|
...,
|
|
description="The content of the message, either a string or a list of content items",
|
|
)
|
|
|
|
|
|
class ChatRequest(BaseModel):
|
|
messages: Optional[List[ChatMessage]] = Field(
|
|
[], description="History of messages between the user and the assistant"
|
|
)
|
|
resources: Optional[List[Resource]] = Field(
|
|
[], description="Resources to be used for the research"
|
|
)
|
|
debug: Optional[bool] = Field(False, description="Whether to enable debug logging")
|
|
thread_id: Optional[str] = Field(
|
|
"__default__", description="A specific conversation identifier"
|
|
)
|
|
max_plan_iterations: Optional[int] = Field(
|
|
1, description="The maximum number of plan iterations"
|
|
)
|
|
max_step_num: Optional[int] = Field(
|
|
3, description="The maximum number of steps in a plan"
|
|
)
|
|
max_search_results: Optional[int] = Field(
|
|
3, description="The maximum number of search results"
|
|
)
|
|
auto_accepted_plan: Optional[bool] = Field(
|
|
False, description="Whether to automatically accept the plan"
|
|
)
|
|
interrupt_feedback: Optional[str] = Field(
|
|
None, description="Interrupt feedback from the user on the plan"
|
|
)
|
|
mcp_settings: Optional[dict] = Field(
|
|
None, description="MCP settings for the chat request"
|
|
)
|
|
enable_background_investigation: Optional[bool] = Field(
|
|
True, description="Whether to get background investigation before plan"
|
|
)
|
|
report_style: Optional[ReportStyle] = Field(
|
|
ReportStyle.ACADEMIC, description="The style of the report"
|
|
)
|
|
enable_deep_thinking: Optional[bool] = Field(
|
|
False, description="Whether to enable deep thinking"
|
|
)
|
|
enable_clarification: Optional[bool] = Field(
|
|
None,
|
|
description="Whether to enable multi-turn clarification (default: None, uses State default=False)",
|
|
)
|
|
max_clarification_rounds: Optional[int] = Field(
|
|
None,
|
|
description="Maximum number of clarification rounds (default: None, uses State default=3)",
|
|
)
|
|
|
|
|
|
class TTSRequest(BaseModel):
|
|
text: str = Field(..., description="The text to convert to speech")
|
|
voice_type: Optional[str] = Field(
|
|
"BV700_V2_streaming", description="The voice type to use"
|
|
)
|
|
encoding: Optional[str] = Field("mp3", description="The audio encoding format")
|
|
speed_ratio: Optional[float] = Field(1.0, description="Speech speed ratio")
|
|
volume_ratio: Optional[float] = Field(1.0, description="Speech volume ratio")
|
|
pitch_ratio: Optional[float] = Field(1.0, description="Speech pitch ratio")
|
|
text_type: Optional[str] = Field("plain", description="Text type (plain or ssml)")
|
|
with_frontend: Optional[int] = Field(
|
|
1, description="Whether to use frontend processing"
|
|
)
|
|
frontend_type: Optional[str] = Field("unitTson", description="Frontend type")
|
|
|
|
|
|
class GeneratePodcastRequest(BaseModel):
|
|
content: str = Field(..., description="The content of the podcast")
|
|
|
|
|
|
class GeneratePPTRequest(BaseModel):
|
|
content: str = Field(..., description="The content of the ppt")
|
|
|
|
|
|
class GenerateProseRequest(BaseModel):
|
|
prompt: str = Field(..., description="The content of the prose")
|
|
option: str = Field(..., description="The option of the prose writer")
|
|
command: Optional[str] = Field(
|
|
"", description="The user custom command of the prose writer"
|
|
)
|
|
|
|
|
|
class EnhancePromptRequest(BaseModel):
|
|
prompt: str = Field(..., description="The original prompt to enhance")
|
|
context: Optional[str] = Field(
|
|
"", description="Additional context about the intended use"
|
|
)
|
|
report_style: Optional[str] = Field(
|
|
"academic", description="The style of the report"
|
|
)
|