curl --request POST \
--url https://pria.praxislxp.com/api/user/embeddings \
--header 'Content-Type: application/json' \
--header 'x-access-token: <api-key>' \
--data '
{
"upload": "665a1b2c3d4e5f6789012300"
}
'{
"success": true,
"data": [
{
"_id": "665a1b2c3d4e5f6789012345",
"chunkText": "This is a paragraph from the uploaded document...",
"chunkLen": 512,
"chunkIndex": 0,
"upload": "665a1b2c3d4e5f6789012300",
"chunkUrl": "#page=2",
"created": "2023-11-07T05:31:56Z",
"usage": 128
}
],
"embeddingModel": {
"name": "text-embedding-3-small",
"provider": "openai_cli",
"maxInputTokens": 8191
},
"currentEmbeddingModel": {
"name": "text-embedding-3-small",
"provider": "openai_cli"
},
"chunkMaxChars": 8000
}Get embedding chunks for an upload
Retrieves all embedding chunks for a specific IP Vault upload, sorted by chunk index. Each uploaded file is split into text chunks and converted into vector embeddings for retrieval-augmented generation (RAG). This endpoint returns the chunk metadata and text content (up to 1000 chunks per request).
curl --request POST \
--url https://pria.praxislxp.com/api/user/embeddings \
--header 'Content-Type: application/json' \
--header 'x-access-token: <api-key>' \
--data '
{
"upload": "665a1b2c3d4e5f6789012300"
}
'{
"success": true,
"data": [
{
"_id": "665a1b2c3d4e5f6789012345",
"chunkText": "This is a paragraph from the uploaded document...",
"chunkLen": 512,
"chunkIndex": 0,
"upload": "665a1b2c3d4e5f6789012300",
"chunkUrl": "#page=2",
"created": "2023-11-07T05:31:56Z",
"usage": 128
}
],
"embeddingModel": {
"name": "text-embedding-3-small",
"provider": "openai_cli",
"maxInputTokens": 8191
},
"currentEmbeddingModel": {
"name": "text-embedding-3-small",
"provider": "openai_cli"
},
"chunkMaxChars": 8000
}Documentation Index
Fetch the complete documentation index at: https://docs.praxis-ai.com/llms.txt
Use this file to discover all available pages before exploring further.
Authorizations
JWT token passed in x-access-token header
Body
The ID of the upload whose embedding chunks to retrieve
"665a1b2c3d4e5f6789012300"
Response
Embedding chunks retrieved successfully
true
Embedding chunks sorted by chunkIndex (max 1000)
Show child attributes
Show child attributes
Model actually used to generate these chunks' vectors. Null when the upload has no recorded embedding model.
Show child attributes
Show child attributes
The institution's currently-configured embedding model (what a re-ingestion would use). Compare against embeddingModel to detect drift.
Show child attributes
Show child attributes
Soft cap (characters) for segment edit/create UI. Matches the server-side RAG chunk-size constant so admin edits stay in lockstep with new ingestion output.
8000
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