1aa60dada2
Implements three-phase AI assistant feature: - Phase 0: RAG infrastructure with pgvector embeddings, Voyage AI integration, tree chunking service, and semantic search over team's flow library - Phase 1: In-session copilot panel during flow navigation with contextual AI help, current step awareness, and suggested related flows - Phase 2: Standalone AI chat page with persistent conversation history, pin/delete, and configurable retention policies (account-level) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
60 lines
1.4 KiB
Python
60 lines
1.4 KiB
Python
"""Pydantic schemas for standalone AI assistant chat."""
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from typing import Optional, Any
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from uuid import UUID
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from datetime import datetime
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from pydantic import BaseModel, Field
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from app.schemas.copilot import SuggestedFlow
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class ChatCreateRequest(BaseModel):
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"""Empty body — creates a new blank conversation."""
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pass
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class ChatMessageRequest(BaseModel):
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message: str = Field(..., min_length=1, max_length=8000)
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class ChatMessageResponse(BaseModel):
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content: str
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suggested_flows: list[SuggestedFlow] = []
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class ChatListResponse(BaseModel):
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id: UUID
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title: str
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message_count: int
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pinned: bool
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created_at: datetime
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updated_at: datetime
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model_config = {"from_attributes": True}
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class ChatDetailResponse(BaseModel):
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id: UUID
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title: str
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messages: list[dict[str, Any]]
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message_count: int
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pinned: bool
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created_at: datetime
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updated_at: datetime
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model_config = {"from_attributes": True}
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class ChatUpdateRequest(BaseModel):
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title: Optional[str] = Field(None, min_length=1, max_length=255)
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pinned: Optional[bool] = None
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class RetentionSettingsResponse(BaseModel):
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chat_retention_days: Optional[int]
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chat_retention_max_count: Optional[int]
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class RetentionSettingsUpdate(BaseModel):
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chat_retention_days: Optional[int] = Field(None, ge=1, le=365)
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chat_retention_max_count: Optional[int] = Field(None, ge=10, le=10000)
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