98 lines
4.2 KiB
Python
98 lines
4.2 KiB
Python
from enum import StrEnum
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from pydantic import BaseModel, ConfigDict, Field
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class WriteFileTransport(StrEnum):
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"""How a model supplies the body of a ``write_file`` call."""
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NATIVE = "native"
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BUFFERED_GATEWAY = "buffered_gateway"
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ARTIFACT_RENDERER = "artifact_renderer"
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# Kept for existing deployments that already opted into the first bridge
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# implementation. New buffered-gateway configurations should use
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# ``buffered_gateway``; unlike the legacy free-form body bridge it keeps
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# the original writer contract and enforces a typed transaction boundary.
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TEXT_BRIDGE = "text_bridge"
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class ToolCallTransport(StrEnum):
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"""How provider tool calls reach DeerFlow.
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``deepseek_dsml`` is an application-side compatibility fallback for
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OpenAI-compatible gateways that leave DeepSeek V4/V4.1 DSML in assistant
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``content`` instead of returning standard ``message.tool_calls``.
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"""
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NATIVE = "native"
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DEEPSEEK_DSML = "deepseek_dsml"
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class ModelConfig(BaseModel):
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"""Config section for a model"""
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name: str = Field(..., description="Unique name for the model")
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display_name: str | None = Field(..., default_factory=lambda: None, description="Display name for the model")
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description: str | None = Field(..., default_factory=lambda: None, description="Description for the model")
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use: str = Field(
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...,
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description="Class path of the model provider(e.g. langchain_openai.ChatOpenAI)",
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)
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model: str = Field(..., description="Model name")
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max_input_tokens: int | None = Field(
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default=None,
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ge=1,
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description="Maximum input context tokens DeerFlow may send to the model",
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)
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model_config = ConfigDict(extra="allow")
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use_responses_api: bool | None = Field(
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default=None,
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description="Whether to route OpenAI ChatOpenAI calls through the /v1/responses API",
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)
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output_version: str | None = Field(
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default=None,
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description="Structured output version for OpenAI responses content, e.g. responses/v1",
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)
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write_file_transport: WriteFileTransport = Field(
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default=WriteFileTransport.NATIVE,
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description=(
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"How DeerFlow receives write_file content. Use buffered_gateway to keep the "
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"original write_file contract while obtaining its body from a second ordinary-text "
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"stream when an OpenAI-compatible gateway buffers tool arguments. "
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"artifact_renderer is the earlier internal-handshake compatibility mode. "
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"text_bridge remains available only for backward compatibility."
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),
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)
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tool_call_transport: ToolCallTransport = Field(
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default=ToolCallTransport.NATIVE,
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description=(
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"How DeerFlow receives provider tool calls. Use deepseek_dsml only "
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"for a DeepSeek V4/V4.1 OpenAI-compatible endpoint that leaks raw "
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"DSML through assistant content instead of message.tool_calls."
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),
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)
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supports_thinking: bool = Field(default_factory=lambda: False, description="Whether the model supports thinking")
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supports_reasoning_effort: bool = Field(
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default_factory=lambda: False,
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description=(
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"Legacy parser compatibility only. Gateway reasoning-effort capability is stored in the "
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"model_capabilities database table."
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),
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)
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when_thinking_enabled: dict | None = Field(
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default_factory=lambda: None,
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description="Extra settings to be passed to the model when thinking is enabled",
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)
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when_thinking_disabled: dict | None = Field(
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default_factory=lambda: None,
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description="Extra settings to be passed to the model when thinking is disabled",
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)
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supports_vision: bool = Field(default_factory=lambda: False, description="Whether the model supports vision/image inputs")
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thinking: dict | None = Field(
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default_factory=lambda: None,
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description=(
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"Thinking settings for the model. If provided, these settings will be passed to the model when thinking is enabled. "
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"This is a shortcut for `when_thinking_enabled` and will be merged with `when_thinking_enabled` if both are provided."
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),
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)
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