882f67f42e
AI Assistant - Conclude Session:
- 3-step modal: select outcome (resolved/escalated/paused), add notes, AI-generated summary
- AI generates structured ticket notes from conversation transcript (PSA-ready format)
- Copy to clipboard for pasting into ticketing systems
- "Resume in New Chat" for paused sessions (pre-loads context into new chat)
- Backend: POST /chats/{id}/conclude endpoint, conclusion_summary/outcome/concluded_at fields
- Migration 048: add conclusion fields to assistant_chats
Survey Completion Flow:
- Email-to-self option after submission (branded HTML email with formatted responses)
- Finish button navigates to /survey/thank-you page
- Thank you page with close-window message and feedback email callout
- Already-submitted state updated with same messaging
- Backend: POST /survey/email-copy public endpoint
Survey Admin Management:
- Read/unread indicators (cyan dot, bold name, auto-mark on expand)
- Unread count stat card
- Per-row context menu: mark read/unread, archive/unarchive, delete
- Bulk actions bar: select all, mark read/unread, archive, delete
- Show Archived toggle to filter archived responses
- Backend: 7 new admin endpoints (read, unread, archive, unarchive, delete, bulk)
- Migration 049: add is_read, archived_at to survey_responses
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
71 lines
1.7 KiB
Python
71 lines
1.7 KiB
Python
"""Pydantic schemas for standalone AI assistant chat."""
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from typing import Optional, Any, Literal
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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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class ConcludeChatRequest(BaseModel):
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outcome: Literal["resolved", "escalated", "paused"]
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notes: Optional[str] = Field(None, max_length=2000)
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class ConcludeChatResponse(BaseModel):
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summary: str
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outcome: str
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concluded_at: datetime
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