rpappalax

from __future__ import annotations

from vertexai.preview.generative_models import GenerativeModel, Part

from app.common.config import Settings
from app.llm.vertex_init import init_vertex


def generate(
    settings: Settings,

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__pycache__
*.pyc
*.pyo
*.pyd
.Python
.venv
venv
.git
.pytest_cache

rpappalax

FROM python:3.11-slim

ENV PYTHONDONTWRITEBYTECODE=1
ENV PYTHONUNBUFFERED=1

WORKDIR /app

COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

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fastapi==0.115.0
uvicorn[standard]==0.30.6

google-cloud-bigquery==3.25.0
google-cloud-core==2.4.1

google-cloud-aiplatform==1.67.1

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fastapi==0.115.0
uvicorn[standard]==0.30.6

google-cloud-bigquery==3.25.0
google-cloud-core==2.4.1

google-cloud-aiplatform==1.67.1

rpappalax

from __future__ import annotations

from vertexai.preview.generative_models import Part

from app.common.config import Settings
from app.llm.gemini_client import generate
from app.retrieval.retriever import Retriever


def build_augmented_prompt(prompt: str, *, top_notes: list[dict]) -> str:

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from __future__ import annotations

from typing import List
from google.cloud import bigquery

from app.common.config import Settings
from app.retrieval.types import Note


class BigQueryNotesRepository:

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from __future__ import annotations

import logging
from typing import List

from app.common.config import Settings
from app.llm.embeddings import embed_text
from app.retrieval.retriever import Retriever
from app.retrieval.types import Note
from app.retrieval.utils import cosine

rpappalax

from __future__ import annotations

from abc import ABC, abstractmethod
from typing import List

from app.retrieval.types import Note


class Retriever(ABC):
    @abstractmethod

rpappalax

from __future__ import annotations

from abc import ABC, abstractmethod
from typing import List

from app.retrieval.types import Note


class Retriever(ABC):
    @abstractmethod