Developer Portal

Integrate our high-performance HTTP and RPC endpoints directly into your pipelines. Access chunked legal documents and dense vector embeddings with minimal latency.

REST API

Standard JSON/BSON over HTTP. Best for metadata queries and dataset exploration.

api.dataflare.com/v1

RPC Services

High-throughput binary streaming. Best for consuming massive vector datasets directly.

rpc.dataflare.com:443

Authentication

All REST API and RPC requests must be authenticated using your securely generated API key.

API Header Auth

Generate your exclusive API key from the Partner Dashboard. You must pass it in the x-api-key header for every HTTP request or gRPC invocation.

HTTP Request

POST /v1/datasets HTTP/1.1

Host: api.dataflare.com

x-api-key: dfk_live_your_api_key_here

Content-Type: application/json

Datasets

Search and retrieve paginated chunks of curated legal & technical Arabic text.

POST/v1/datasets

JSON Body Parameters

datasetstring
Required. E.g., "legal", "medical"
limitint32
Optional. Number of records to return.
cursorstring
Optional. Pagination token from previous request.
search_termstring
Optional. Semantic search query (if vector store enabled).
filtersmap<string, string>
Optional. Filter by specific metadata.

Response (200 OK)

{
  "dataset": "legal",
  "data": [
    {
      "id": "69b5d123c...",
      "content": "بموجب أحكام المادة (٤) من القانون...",
      "metadata": {
        "title": "اللائحة التنفيذية لقانون الشركات...",
        "summary": "قرار إداري بشأن تنظيم اللوائح..."
      }
    }
  ],
  "count": 1,
  "nextCursor": "69b5d122b2fef71e909ce883",
  "latency": "1.737513ms",
  "fields": [
    "category",
    "content",
    "decision",
    "title"
  ]
}

RPC Integration

For LLM training pipelines, REST overhead is unacceptable. Use our compiled RPC services to stream dense embeddings straight into RAPIDS or PyTorch.

Service Reflection

Our RPC endpoints support server reflection. You can use grpcurl to inspect services such as DatasetService and EnrichService directly from your terminal.

grpcurl -H "x-api-key: $DF_API_KEY" rpc.dataflare.com:443 list

dfapi.v1.DatasetService
dfapi.v1.EnrichService

Executing a Query

Once you have inspected the services, you can make direct RPC calls. Here is an example of querying DatasetService.Query using the same JSON payload structure as the REST API.

grpcurl -d '{"dataset": "legal", "limit": 10}' \
-H "x-api-key: $DF_API_KEY" \
rpc.dataflare.com:443 dfapi.v1.DatasetService.Query

Native Streaming

For large-scale vector embeddings or multi-gigabyte dataset extractions, we highly recommend utilizing the DatasetService.Stream method via Python's grpcio library to maintain memory efficiency in your PyTorch or RAPIDS training loops.

Roadmap

Features currently in development for the Dataflare API ecosystem.

Coming Soon

Official SDKs

Native Python and Node.js clients wrapping our gRPC streaming protocols and REST API for seamless pipeline integration.

Coming Soon

Enrichment Service

Direct access to dfapi.v1.EnrichService for programmatic PII redaction, entity extraction, and semantic tagging.

Private Beta

Vector Embeddings API

Generate dense, native-Arabic vector embeddings on-the-fly without needing to load massive models into your own VRAM.

Private Beta

Inference Endpoints

OpenAI-compatible endpoints mapped directly to our proprietary sovereign alignment language models.