c52b360068
* perf(workflow): pass JSON data to HTTP node as a string * perf(prompt_opt): simplify log output * feat(memory): add perceptual memory page API and related database schema * perf(log): clean up API exception log output * perf(memory): simplify perceptual memory timeline response by removing metadata
134 lines
3.3 KiB
Python
134 lines
3.3 KiB
Python
import uuid
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from datetime import datetime
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from typing import Optional
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from pydantic import BaseModel, Field
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from app.models.memory_perceptual_model import PerceptualType, FileStorageType
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class PerceptualFilter(BaseModel):
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type: PerceptualType | None = Field(
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default=None,
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description="Perceptual type used for filtering the query; optional"
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)
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class PerceptualQuerySchema(BaseModel):
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filter: PerceptualFilter = Field(
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default_factory=lambda: PerceptualFilter(),
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description="Query filter containing perceptual type criteria"
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)
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page: int = Field(
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default=1,
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ge=1,
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description="Page number for pagination, starting from 1"
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)
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page_size: int = Field(
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default=10,
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ge=1,
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le=100,
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description="Number of records per page, range 1-100"
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)
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class PerceptualMemoryItem(BaseModel):
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"""感知记忆项"""
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id: uuid.UUID = Field(..., description="Unique memory ID")
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perceptual_type: PerceptualType = Field(..., description="Type of perception, e.g., text, audio, or video")
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file_path: str = Field(..., description="File path in the storage service")
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file_name: str = Field(..., description="File name")
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summary: Optional[str] = Field(None, description="摘要")
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storage_type: FileStorageType = Field(..., description="Storage type for file")
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created_time: Optional[datetime] = Field(None, description="创建时间")
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class Config:
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from_attributes = True
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class PerceptualTimelineResponse(BaseModel):
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"""感知记忆时间线响应"""
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total: int = Field(..., description="总数量")
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page: int = Field(..., description="当前页码")
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page_size: int = Field(..., description="每页大小")
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total_pages: int = Field(..., description="总页数")
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memories: list[PerceptualMemoryItem] = Field(..., description="记忆列表")
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class Config:
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from_attributes = True
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# --------------------------
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# TODO: FileMetaData
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# --------------------------
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class Identity(BaseModel):
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title: str
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filename: str
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source: str # upload | crawl | system
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author: Optional[str] = None
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class Semantic(BaseModel):
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topic: str
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domain: str
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difficulty: str # beginner | intermediate | advanced
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intent: str # informative | instructional | promotional
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sentiment: str # positive | neutral | negative
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class Content(BaseModel):
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summary: str
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keywords: list[str]
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topic: str
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domain: str
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class Usage(BaseModel):
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target_audience: list[str]
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use_cases: list[str]
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class Stats(BaseModel):
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duration_sec: Optional[int] = None
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char_count: int
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word_count: int
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class Processing(BaseModel):
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transcribed: bool
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ocr_applied: bool
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chunked: bool
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vectorized: bool
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embedding_model: Optional[str] = None
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class VideoModal(BaseModel):
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scene: list[str]
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class AudioModal(BaseModel):
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speaker_count: int
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class TextModal(BaseModel):
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section_count: int
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class Asset(BaseModel):
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type: str
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modality: str # text | audio | video
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format: str # docx | mp3 | mp4
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language: str
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encoding: str
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identity: Identity
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semantic: Semantic
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content: Content
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usage: Usage
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stats: Stats
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processing: Processing
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created_at: str
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modalities: AudioModal | TextModal | VideoModal
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