Document ingestion

Index plain text and PDF files into an agent's knowledge base via the ingestion endpoints.

Use the ingestion endpoints to embed content into an agent's vector store. After a successful call the chunks are immediately available for search and RAG.

POST /documents/embed/text

Indexes a plain-text document and returns the assigned document ID and chunk count.

Authentication: Bearer API key required (see Authentication).

Request body

Prop

Type

Example

curl -X POST https://api.mojar.ai/documents/embed/text \
  -H "Authorization: Bearer nest-YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "agentId": 42,
    "title": "Q2 Product Roadmap",
    "content": "This document outlines the product roadmap for Q2 2026..."
  }'

const response = await fetch("https://api.mojar.ai/documents/embed/text", {
  method: "POST",
  headers: {
    Authorization: "Bearer nest-YOUR_API_KEY",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    agentId: 42,
    title: "Q2 Product Roadmap",
    content: "This document outlines the product roadmap for Q2 2026...",
  }),
});

const data = await response.json();

Response — 201 Created

{
  "message": "Text content indexed successfully",
  "documentId": 1001,
  "chunkCount": 14
}

Prop

Type

POST /documents/embed/pdf

Uploads one or more PDF files and indexes their extracted text. Files are sent as multipart/form-data.

Authentication: Bearer API key required.

Limits:

Maximum 10 files per request.
Maximum 10 MB per file.
Only application/pdf MIME type is accepted.

Request — multipart/form-data

Field	Type	Required	Description
`files`	file (repeatable)	Yes	One or more PDF files. Field name must be `files`.
`agentId`	number	Yes	ID of the agent that will own the documents.

Example

curl -X POST https://api.mojar.ai/documents/embed/pdf \
  -H "Authorization: Bearer nest-YOUR_API_KEY" \
  -F "agentId=42" \
  -F "files=@report.pdf;type=application/pdf" \
  -F "files=@appendix.pdf;type=application/pdf"

const form = new FormData();
form.append("agentId", "42");
form.append("files", pdfBlob1, "report.pdf");
form.append("files", pdfBlob2, "appendix.pdf");

const response = await fetch("https://api.mojar.ai/documents/embed/pdf", {
  method: "POST",
  headers: {
    Authorization: "Bearer nest-YOUR_API_KEY",
  },
  body: form,
});

const data = await response.json();

Response — 201 Created

{
  "message": "PDF files processed successfully",
  "results": [
    {
      "filename": "report.pdf",
      "documentId": 1002,
      "chunkCount": 38
    },
    {
      "filename": "appendix.pdf",
      "documentId": 1003,
      "chunkCount": 12
    }
  ]
}

Prop

Type

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