65 lines
2.0 KiB
Python
65 lines
2.0 KiB
Python
from __future__ import annotations
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from typing import Literal
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from pydantic import BaseModel, Field
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class EmailData(BaseModel):
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subject: str
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body: str
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class ClassifyRequest(BaseModel):
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email_data: EmailData
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provider: Literal["openai", "anthropic"] | None = None
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model: str | None = None
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base_url: str | None = None
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api_key: str | None = Field(default=None, exclude=True)
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temperature: float | None = None
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id: str | None = None
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internetMessageId: str | None = None
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conversationId: str | None = None
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bodyPreview: str | None = None
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receivedDateTime: str | None = None
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sentDateTime: str | None = None
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hasAttachments: bool | None = None
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importance: str | None = None
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isRead: bool | None = None
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from_address: str | None = None
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class ClassificationDetails(BaseModel):
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summary: str | None = None
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suggested_title: str | None = None
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suggested_notes: str | None = None
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deadline: str | None = None
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people: list[str] = Field(default_factory=list)
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organizations: list[str] = Field(default_factory=list)
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attachments_referenced: list[str] = Field(default_factory=list)
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next_steps: list[str] = Field(default_factory=list)
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key_points: list[str] = Field(default_factory=list)
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source_signals: list[str] = Field(default_factory=list)
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dedupe_key: str | None = None
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class DedupeResult(BaseModel):
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status: Literal["new", "duplicate", "updated"]
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seen_count: int = 1
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matched_on: Literal["none", "id", "conversation", "fingerprint"] = "none"
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message_id: str | None = None
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conversation_id: str | None = None
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fingerprint: str
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class ClassificationResult(BaseModel):
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needs_action: bool
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category: Literal["action_required", "question", "fyi", "newsletter", "promotional", "automated", "alert", "uncategorized"]
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priority: Literal["high", "medium", "low"]
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task_description: str | None = None
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reasoning: str
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confidence: float
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details: ClassificationDetails | None = None
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dedupe: DedupeResult | None = None
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