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feat: Add optional metadata param to ingest routes

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This commit is contained in:
Nathan Lenas 2024-07-23 08:50:54 +02:00
parent b62669784b
commit d559d54e1a
6 changed files with 76 additions and 32 deletions
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21
private_gpt/server/ingest/ingest_router.py
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@ -1,6 +1,6 @@
from typing import Literal
from typing import Literal, Dict
from fastapi import APIRouter, Depends, HTTPException, Request, UploadFile
from fastapi import APIRouter, Depends, HTTPException, Request, UploadFile, Form
from pydantic import BaseModel, Field
from private_gpt.server.ingest.ingest_service import IngestService
@ -20,6 +20,15 @@ class IngestTextBody(BaseModel):
"Chinese martial arts."
]
)
metadata: Dict = Field(None,
examples=[
{
"title": "Avatar: The Last Airbender",
"author": "Michael Dante DiMartino, Bryan Konietzko",
"year": "2005",
}
]
)
class IngestResponse(BaseModel):
@ -38,7 +47,7 @@ def ingest(request: Request, file: UploadFile) -> IngestResponse:
@ingest_router.post("/ingest/file", tags=["Ingestion"])
def ingest_file(request: Request, file: UploadFile) -> IngestResponse:
def ingest_file(request: Request, file: UploadFile, metadata: str = Form(None)) -> IngestResponse:
"""Ingests and processes a file, storing its chunks to be used as context.
The context obtained from files is later used in
@ -57,7 +66,9 @@ def ingest_file(request: Request, file: UploadFile) -> IngestResponse:
service = request.state.injector.get(IngestService)
if file.filename is None:
raise HTTPException(400, "No file name provided")
ingested_documents = service.ingest_bin_data(file.filename, file.file)
metadata_dict = None if metadata is None else eval(metadata)
ingested_documents = service.ingest_bin_data(file.filename, file.file, metadata_dict)
return IngestResponse(object="list", model="private-gpt", data=ingested_documents)
@ -77,7 +88,7 @@ def ingest_text(request: Request, body: IngestTextBody) -> IngestResponse:
service = request.state.injector.get(IngestService)
if len(body.file_name) == 0:
raise HTTPException(400, "No file name provided")
ingested_documents = service.ingest_text(body.file_name, body.text)
ingested_documents = service.ingest_text(body.file_name, body.text, body.metadata)
return IngestResponse(object="list", model="private-gpt", data=ingested_documents)