lgcosta
b9c0c66d21
- Stack: GPT4All + Llama 3.2 3B, LangChain, Qdrant, FastAPI, Docker - 11 tarefas implementadas com 100% de conclusão - Funcionalidades: chat com IA, upload PDF, bot Telegram, agendamento - 6 livros PDF indexados (A Gênese, Livro dos Espíritos, etc.) - Documentação rica: README, BUILD, task reports, design specs - Deploy com Docker Compose - Production ready Tech stack: - AI: GPT4All 2.4.6, Llama 3.2 3B q4_0 - Backend: FastAPI 0.115.0, Celery 5.4.0, Redis 5.2.0 - RAG: LangChain 0.3.7, Qdrant 1.11.1 - Frontend: HTML5/CSS3/Vanilla JS - Deploy: Docker Compose Acceptance Criteria: ✅ CPU-only, <8GB RAM, ~5GB storage ✅ Suporta upload de PDFs ✅ Interface web rica e responsiva ✅ Bot Telegram funcional ✅ Agendamento de mensagens ✅ Código limpo e documentado ✅ Deploy via Docker Status: PRODUCTION READY Version: 1.0.0 Date: 2026-11-01
32 lines
595 B
Python
32 lines
595 B
Python
from pydantic import BaseModel
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from typing import Optional, List, Dict
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class ChatRequest(BaseModel):
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message: str
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top_k: int = 3
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class ChatResponse(BaseModel):
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query: str
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response: str
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sources: List[Dict]
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class BookInfo(BaseModel):
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title: str
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source: str
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class UploadResponse(BaseModel):
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message: str
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filename: str
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class ScheduleInfo(BaseModel):
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id: int
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time: str
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book: Optional[str]
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enabled: bool
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next_run: Optional[str] = None
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class ScheduleRequest(BaseModel):
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time: str
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book: Optional[str] = None
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enabled: bool = True
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