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aa70d3d9f0
* Add simple Basic auth To enable the basic authentication, one must set `server.auth.enabled` to true. The static string defined in `server.auth.secret` must be set in the header `Authorization`. The health check endpoint will always be accessible, no matter the API auth configuration. * Fix linting and type check * Fighting with mypy being too restrictive Had to disable mypy in the `auth` as we are not using the same signature for the authenticated method. mypy was complaining that the signatures of `authenticated` must be identical, no matter in which logical branch we are. Given that fastapi is accomodating itself of method signatures (it will inject the dependencies in the method call), this warning of mypy is actually preventing us to do something legit. mypy doc: https://mypy.readthedocs.io/en/stable/common_issues.html * Write tests to verify that the simple auth is working
36 lines
1.1 KiB
Python
36 lines
1.1 KiB
Python
from typing import Literal
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from fastapi import APIRouter, Depends
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from pydantic import BaseModel
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from private_gpt.di import root_injector
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from private_gpt.server.embeddings.embeddings_service import (
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Embedding,
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EmbeddingsService,
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)
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from private_gpt.server.utils.auth import authenticated
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embeddings_router = APIRouter(prefix="/v1", dependencies=[Depends(authenticated)])
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class EmbeddingsBody(BaseModel):
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input: str | list[str]
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class EmbeddingsResponse(BaseModel):
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object: Literal["list"]
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model: Literal["private-gpt"]
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data: list[Embedding]
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@embeddings_router.post("/embeddings", tags=["Embeddings"])
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def embeddings_generation(body: EmbeddingsBody) -> EmbeddingsResponse:
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"""Get a vector representation of a given input.
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That vector representation can be easily consumed
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by machine learning models and algorithms.
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"""
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service = root_injector.get(EmbeddingsService)
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input_texts = body.input if isinstance(body.input, list) else [body.input]
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embeddings = service.texts_embeddings(input_texts)
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return EmbeddingsResponse(object="list", model="private-gpt", data=embeddings)
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