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name: sdk-webrtc description: "Route Roboflow Inference SDK users through InferenceHTTPClient, HTTP configuration and error mapping, workflow and pipeline APIs, and WebRTC streaming sources and session lifecycle." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

SDK and WebRTC

Use this sub-skill when the user wants to call the Python SDK, configure HTTP requests, choose workflow versus model_id streaming, or stream webcam, video file, RTSP, MJPEG, local RTSP/RTMP, or manual frames through WebRTC.

Route here when

• The user asks how to create or reuse InferenceHTTPClient.
• They need infer, infer_async, infer_from_workflow, run_workflow, or pipeline lifecycle calls.
• They want to configure InferenceConfiguration, inspect HTTPClientMode, or interpret SDK errors.
• They want to use client.webrtc.stream(...) with WebcamSource, VideoFileSource, RTSPSource, MJPEGSource, LocalStreamSource, or ManualSource.
• They need to understand session lifecycle, on_frame, on_data, on_error, video(), wait(), or cleanup behavior.
• They need the bundled webcam or video-file example flows.

Do not route here when

• The request is about CLI commands such as inference workflows .... Use workflow-processing.
• The request is about starting or deploying the inference server, Docker, or CLI server lifecycle. Use cli-operations.
• The request is about backend/package negotiation, AutoModel, or model runtime selection. Use model-runtime.

Read these bundled references

1. API reference for verified signatures, config fields, and error classes.
2. Workflow and WebRTC patterns for workflow versus model_id choice, source selection, and session usage.
3. Troubleshooting for auth, wrong URL/mode, missing WebRTC deps, invalid parameter combinations, and cleanup failures.
4. Surface probe when you need a safe import/signature check.
5. Webcam example for an interactive webcam flow.
6. Video file example for an interactive video-file flow.

Operating rules

• Start with InferenceHTTPClient.init(api_url, api_key) or InferenceHTTPClient(api_url, api_key) and check client.client_mode before assuming an endpoint family.
• Use client.webrtc.stream(...) for WebRTC sessions. Pass exactly one of workflow or model_id.
• Use workflow= for multi-step workflows, inline workflow specs, or VLM-style flows. Use model_id= for a single supported model when you want the raw predictions dict per frame.
• If workflow is a string ID, also provide workspace=. If workflow is a dict, workspace= is optional.
• Do not pass task_type without model_id.
• In model_id mode, treat data as the raw serialized predictions dict and check for None.
• Prefer with client.webrtc.stream(...) as session: or call session.close() explicitly.
• Use session.on_error for server-reported per-frame failures; connection or initialization failures surface as exceptions.
• Use session.video() for iterator-style consumption and session.run() for callback-style consumption.
• VideoFileSource and WebcamSource are the two bundled examples; adapt them rather than reopening the source repo.
• Route anything about workflow CLI commands to workflow-processing, and route backend negotiation or AutoModel questions to model-runtime.

What this sub-skill should answer

• How do I create the SDK client and pick the right HTTP mode?
• How do I run a hosted workflow, an inline workflow spec, or a pipeline request?
• How do I stream webcam or video frames and handle cleanup?
• When should I use workflow= versus model_id=?
• Which source class should I use for webcam, RTSP, MJPEG, video files, local streams, or manual frames?