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| from abc import ABC | |
| from pydantic import UUID4, Field | |
| from llm_engineering.domain.types import DataCategory | |
| from .base import VectorBaseDocument | |
| class EmbeddedChunk(VectorBaseDocument, ABC): | |
| content: str | |
| embedding: list[float] | None | |
| platform: str | |
| document_id: UUID4 | |
| author_id: UUID4 | |
| author_full_name: str | |
| metadata: dict = Field(default_factory=dict) | |
| def to_context(cls, chunks: list["EmbeddedChunk"]) -> str: | |
| context = "" | |
| for i, chunk in enumerate(chunks): | |
| context += f""" | |
| Source: {chunk.name} | |
| Link: {chunk.link} | |
| Content: {chunk.content}\n | |
| """ | |
| print(chunk) | |
| return context | |
| class EmbeddedPostChunk(EmbeddedChunk): | |
| class Config: | |
| name = "embedded_posts" | |
| category = DataCategory.POSTS | |
| use_vector_index = True | |
| class EmbeddedArticleChunk(EmbeddedChunk): | |
| link: str | |
| class Config: | |
| name = "embedded_articles" | |
| category = DataCategory.ARTICLES | |
| use_vector_index = True | |
| class EmbeddedRepositoryChunk(EmbeddedChunk): | |
| name: str | |
| link: str | |
| class Config: | |
| name = "embedded_repositories" | |
| category = DataCategory.REPOSITORIES | |
| use_vector_index = True | |