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POST
/
api
/
v1
/
upload
Upload
curl --request POST \
  --url https://api.example.com/api/v1/upload \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: multipart/form-data' \
  --form 'collection_id=<string>' \
  --form 'file=<string>' \
  --form 'files=<string>' \
  --form 'content=<string>' \
  --form 'urls=<string>' \
  --form content_type=file \
  --form 'metadata=<string>' \
  --form 'user_id=<string>' \
  --form 'label=<string>' \
  --form 'description=<string>' \
  --form crawl=false \
  --form ingest=true \
  --form 'reader=<string>' \
  --form file.0='@example-file' \
  --form files.0.items='@example-file'
{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>"
    }
  ]
}

Authorizations

​
Authorization
string
header
required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Headers

​
X-Workspace-Id
string | null

The workspace ID

Body

multipart/form-data
​
collection_id
string
required
​
file
file | null
​
files
file[] | null
​
content
string | null
​
urls
string[] | null
​
content_type
string | null
default:file
​
metadata
string | null
​
user_id
string | null
​
label
string | null
​
description
string | null
​
crawl
boolean | null
default:false
​
ingest
boolean | null
default:true
​
reader
string | null
Reader to use for processing files. Supported values:
    - 'native': Use native implementation (default)
    - 'langchain': Use LangChain readers for all files
    - 'markitdown': Use MarkItDown for universal conversion to markdown
    
    Provider + Type Format:
        - 'langchain_pdfplumber': LangChain with PDFPlumber (better OCR, tables)
        - 'langchain_pypdf': LangChain with PyPDF (faster for text-based PDFs)
    
    Specific Reader:
        - 'pdf', 'csv', 'docx', 'json', 'markdown', 'text'

Response

Successful Response