mirror of
https://github.com/open-webui/open-webui
synced 2024-12-28 23:02:25 +00:00
Add batching
This commit is contained in:
Gabriel Ecegi
parent
bfdbb2df69
commit
f2e2b59c18
@ -2,16 +2,14 @@
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import json
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import logging
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import mimetypes
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import os
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import shutil
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import uuid
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from datetime import datetime
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from pathlib import Path
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from typing import Iterator, Optional, Sequence, Union
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from typing import List, Optional
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from fastapi import Depends, FastAPI, File, Form, HTTPException, UploadFile, status
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from fastapi import Depends, FastAPI, HTTPException, status
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from fastapi.middleware.cors import CORSMiddleware
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from pydantic import BaseModel
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import tiktoken
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@ -52,7 +50,7 @@ from open_webui.apps.retrieval.utils import (
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query_doc_with_hybrid_search,
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)
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from open_webui.apps.webui.models.files import Files
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from open_webui.apps.webui.models.files import FileModel, Files
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from open_webui.config import (
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BRAVE_SEARCH_API_KEY,
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KAGI_SEARCH_API_KEY,
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@ -64,7 +62,6 @@ from open_webui.config import (
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CONTENT_EXTRACTION_ENGINE,
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CORS_ALLOW_ORIGIN,
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ENABLE_RAG_HYBRID_SEARCH,
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ENABLE_RAG_LOCAL_WEB_FETCH,
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ENABLE_RAG_WEB_LOADER_SSL_VERIFICATION,
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ENABLE_RAG_WEB_SEARCH,
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ENV,
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@ -86,7 +83,6 @@ from open_webui.config import (
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RAG_RERANKING_MODEL,
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RAG_RERANKING_MODEL_AUTO_UPDATE,
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RAG_RERANKING_MODEL_TRUST_REMOTE_CODE,
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DEFAULT_RAG_TEMPLATE,
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RAG_TEMPLATE,
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RAG_TOP_K,
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RAG_WEB_SEARCH_CONCURRENT_REQUESTS,
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@ -118,10 +114,7 @@ from open_webui.env import (
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DOCKER,
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)
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from open_webui.utils.misc import (
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calculate_sha256,
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calculate_sha256_string,
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extract_folders_after_data_docs,
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sanitize_filename,
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)
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from open_webui.utils.auth import get_admin_user, get_verified_user
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@ -1047,6 +1040,106 @@ def process_file(
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)
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class BatchProcessFilesForm(BaseModel):
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files: List[FileModel]
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collection_name: str
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class BatchProcessFilesResult(BaseModel):
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file_id: str
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status: str
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error: Optional[str] = None
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class BatchProcessFilesResponse(BaseModel):
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results: List[BatchProcessFilesResult]
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errors: List[BatchProcessFilesResult]
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@app.post("/process/files/batch")
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def process_files_batch(
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form_data: BatchProcessFilesForm,
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user=Depends(get_verified_user),
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) -> BatchProcessFilesResponse:
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"""
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Process a batch of files and save them to the vector database.
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"""
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results: List[BatchProcessFilesResult] = []
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errors: List[BatchProcessFilesResult] = []
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collection_name = form_data.collection_name
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# Prepare all documents first
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all_docs: List[Document] = []
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for file_request in form_data.files:
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try:
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file = Files.get_file_by_id(file_request.file_id)
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if not file:
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log.error(f"process_files_batch: File {file_request.file_id} not found")
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raise ValueError(f"File {file_request.file_id} not found")
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text_content = file_request.content
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docs: List[Document] = [
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Document(
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page_content=text_content.replace("<br/>", "\n"),
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metadata={
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**file.meta,
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"name": file_request.filename,
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"created_by": file.user_id,
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"file_id": file.id,
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"source": file_request.filename,
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},
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)
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]
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hash = calculate_sha256_string(text_content)
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Files.update_file_hash_by_id(file.id, hash)
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Files.update_file_data_by_id(file.id, {"content": text_content})
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all_docs.extend(docs)
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results.append(BatchProcessFilesResult(
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file_id=file.id,
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status="prepared"
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))
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except Exception as e:
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log.error(f"process_files_batch: Error processing file {file_request.file_id}: {str(e)}")
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errors.append(BatchProcessFilesResult(
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file_id=file_request.file_id,
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status="failed",
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error=str(e)
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))
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# Save all documents in one batch
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if all_docs:
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try:
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save_docs_to_vector_db(
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docs=all_docs,
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collection_name=collection_name,
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add=True
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)
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# Update all files with collection name
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for result in results:
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Files.update_file_metadata_by_id(
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result.file_id,
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{"collection_name": collection_name}
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)
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result.status = "completed"
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except Exception as e:
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log.error(f"process_files_batch: Error saving documents to vector DB: {str(e)}")
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for result in results:
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result.status = "failed"
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errors.append(BatchProcessFilesResult(
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file_id=result.file_id,
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error=str(e)
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))
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return BatchProcessFilesResponse(
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results=results,
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errors=errors
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)
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class ProcessTextForm(BaseModel):
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name: str
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content: str
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@ -1509,3 +1602,4 @@ if ENV == "dev":
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@app.get("/ef/{text}")
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async def get_embeddings_text(text: str):
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return {"result": app.state.EMBEDDING_FUNCTION(text)}
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@ -1,5 +1,4 @@
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import json
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from typing import Optional, Union
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from typing import List, Optional
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from pydantic import BaseModel
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from fastapi import APIRouter, Depends, HTTPException, status, Request
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import logging
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@ -12,11 +11,11 @@ from open_webui.apps.webui.models.knowledge import (
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)
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from open_webui.apps.webui.models.files import Files, FileModel
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from open_webui.apps.retrieval.vector.connector import VECTOR_DB_CLIENT
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from open_webui.apps.retrieval.main import process_file, ProcessFileForm
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from open_webui.apps.retrieval.main import BatchProcessFilesForm, process_file, ProcessFileForm, process_files_batch
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from open_webui.constants import ERROR_MESSAGES
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from open_webui.utils.auth import get_admin_user, get_verified_user
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from open_webui.utils.auth import get_verified_user
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from open_webui.utils.access_control import has_access, has_permission
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@ -508,3 +507,78 @@ async def reset_knowledge_by_id(id: str, user=Depends(get_verified_user)):
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knowledge = Knowledges.update_knowledge_data_by_id(id=id, data={"file_ids": []})
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return knowledge
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############################
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# AddFilesToKnowledge
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############################
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@router.post("/{id}/files/batch/add", response_model=Optional[KnowledgeFilesResponse])
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def add_files_to_knowledge_batch(
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id: str,
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form_data: list[KnowledgeFileIdForm],
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user=Depends(get_verified_user),
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):
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"""
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Add multiple files to a knowledge base
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"""
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knowledge = Knowledges.get_knowledge_by_id(id=id)
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if not knowledge:
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail=ERROR_MESSAGES.NOT_FOUND,
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)
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if knowledge.user_id != user.id and user.role != "admin":
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail=ERROR_MESSAGES.ACCESS_PROHIBITED,
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)
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# Get files content
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print(f"files/batch/add - {len(form_data)} files")
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files: List[FileModel] = []
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for form in form_data:
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file = Files.get_file_by_id(form.file_id)
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if not file:
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raise HTTPException(
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status_code=status.HTTP_400_BAD_REQUEST,
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detail=f"File {form.file_id} not found",
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)
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files.append(file)
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# Process files
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result = process_files_batch(BatchProcessFilesForm(
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files=files,
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collection_name=id
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))
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# Add successful files to knowledge base
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data = knowledge.data or {}
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existing_file_ids = data.get("file_ids", [])
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# Only add files that were successfully processed
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successful_file_ids = [r.file_id for r in result.results if r.status == "completed"]
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for file_id in successful_file_ids:
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if file_id not in existing_file_ids:
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existing_file_ids.append(file_id)
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data["file_ids"] = existing_file_ids
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knowledge = Knowledges.update_knowledge_data_by_id(id=id, data=data)
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# If there were any errors, include them in the response
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if result.errors:
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error_details = [f"{err.file_id}: {err.error}" for err in result.errors]
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return KnowledgeFilesResponse(
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**knowledge.model_dump(),
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files=Files.get_files_by_ids(existing_file_ids),
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warnings={
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"message": "Some files failed to process",
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"errors": error_details
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}
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)
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return KnowledgeFilesResponse(
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**knowledge.model_dump(),
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files=Files.get_files_by_ids(existing_file_ids)
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)
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