feat(livekit-plugins-dataspike): add real-time deepfake detection plugin

.github/workflows/ci.yml

@@ -73,6 +73,7 @@ jobs:
               -p livekit.plugins.bithuman
               -p livekit.plugins.cartesia
               -p livekit.plugins.clova
+              -p livekit.plugins.dataspike
               -p livekit.plugins.deepgram
               -p livekit.plugins.elevenlabs
               -p livekit.plugins.fal

CONTRIBUTING.md

@@ -69,6 +69,7 @@ uv pip install pip && uv run mypy --install-types --non-interactive \
     -p livekit.plugins.bithuman \
     -p livekit.plugins.cartesia \
     -p livekit.plugins.clova \
+    -p livekit.plugins.dataspike \
     -p livekit.plugins.deepgram \
     -p livekit.plugins.elevenlabs \
     -p livekit.plugins.fal \

examples/deepfake-detection/dataspike/README.md

@@ -0,0 +1,26 @@
+# LiveKit Dataspike Deepfake Detection Example
+
+This example demonstrates how to use the [Dataspike](https://dataspike.io/) deepfake detection plugin with a LiveKit Agent.
+
+## Usage
+
+* Update the environment:
+
+```bash
+# Dataspike Config
+export DATASPIKE_API_KEY="..."
+
+# OpenAI config (or other models, tts, stt)
+export OPENAI_API_KEY="..."
+
+# LiveKit config
+export LIVEKIT_API_KEY="..."
+export LIVEKIT_API_SECRET="..."
+export LIVEKIT_URL="..."
+```
+
+* Start the agent worker:
+
+```bash
+python examples/avatar_agents/dataspike/agent_worker.py dev
+```

examples/deepfake-detection/dataspike/agent_worker.py

@@ -0,0 +1,61 @@
+import logging
+
+from dotenv import load_dotenv
+
+from livekit.agents import (
+    Agent,
+    AgentSession,
+    JobContext,
+    JobRequest,
+    WorkerOptions,
+    WorkerType,
+    cli,
+)
+from livekit.plugins import dataspike, openai
+
+logger = logging.getLogger("dataspike-deepfake-example")
+logger.setLevel(logging.DEBUG)
+
+load_dotenv()
+
+
+async def entrypoint(ctx: JobContext):
+    session = AgentSession(
+        llm=openai.realtime.RealtimeModel(voice="alloy"),
+        resume_false_interruption=False,
+    )
+
+    # Configure the Dataspike detector.
+    # - api_key: optional; if omitted, uses DATASPIKE_API_KEY from environment
+    # - notification_cb: optional; callback for handling notifications
+    #   (defaults to publishing results in the room data channel)
+    # - other config: see plugin docs for available parameters
+    detector = dataspike.DataspikeDetector(
+        # api_key="YOUR_API_KEY",
+        # notification_cb=on_notification,
+    )
+
+    # Start the Dataspike detector and attach it to the current session and room.
+    await detector.start(session, room=ctx.room)
+
+    # Launch the main agent, which will automatically join the same room.
+    await session.start(
+        agent=Agent(instructions="Talk to me!"),
+        room=ctx.room,
+    )
+
+
+async def on_request(req: JobRequest):
+    logger.info(f"[worker] job request for room={req.room.name} id={req.id}")
+    # you can set the agent's participant name/identity here:
+    await req.accept(name="dataspike-agent")
+
+
+if __name__ == "__main__":
+    cli.run_app(
+        WorkerOptions(
+            entrypoint_fnc=entrypoint,
+            request_fnc=on_request,
+            worker_type=WorkerType.ROOM,
+        )
+    )

livekit-plugins/livekit-plugins-dataspike/README.md

@@ -0,0 +1,37 @@
+# Dataspike Deepfake Detection Plugin for LiveKit Agents
+
+This plugin integrates [Dataspike](https://dataspike.io/) with LiveKit Agents to provide **real-time deepfake detection**.  
+It enables detection of synthetic or manipulated media during live or recorded video streams.
+
+## Installation
+
+```bash
+pip install livekit-plugins-dataspike
+```
+
+## Prerequisites
+
+You’ll need a **Dataspike API key**. Set it as an environment variable before running your agent:
+
+```bash
+export DATASPIKE_API_KEY="your_api_key_here"
+```
+
+## Usage Example
+
+```python
+from livekit.plugins import dataspike
+from livekit.agents import AgentSession, Agent
+
+async def entrypoint(ctx):
+    await ctx.connect()
+    session = AgentSession(...)
+    detector = dataspike.DataspikeDetector()
+    await detector.start(session, room=ctx.room)
+    await session.start(agent=Agent(instructions="Talk to me!"), room=ctx.room)
+```
+
+## Links
+
+- [Dataspike API](https://docs.dataspike.io/api)
+- [LiveKit Agents SDK](https://github.com/livekit/agents)

livekit-plugins/livekit-plugins-dataspike/livekit/plugins/dataspike/__init__.py

@@ -0,0 +1,57 @@
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Dataspike deepfake detection plugin for LiveKit Agents."
+
+This module provides a realtime deepfake detector that attaches to a LiveKit room,
+samples frames from subscribed remote video tracks, and streams them to the
+Dataspike WebSocket API for analysis. Results can be published back into the room
+or handled via a custom callback.
+
+Typical usage:
+    >>> detector = DataspikeDetector()
+    >>> await detector.start(agent_session, room)
+
+Public API:
+- `InputTrack`: Internal helper representing a sampled video track.
+- `DataspikeDetector`: The main detector that manages sampling and the WS pipeline.
+"""
+
+from .detector import DataspikeDetector
+from .log import logger
+from .version import __version__
+
+__all__ = [
+    "DataspikeDetector",
+    "InputTrack",
+    "logger",
+    "__version__",
+]
+
+from livekit.agents import Plugin
+
+
+class DataspikePlugin(Plugin):
+    def __init__(self) -> None:
+        super().__init__(__name__, __version__, __package__, logger)
+
+
+Plugin.register_plugin(DataspikePlugin())
+
+# Cleanup docs of unexported modules
+_module = dir()
+NOT_IN_ALL = [m for m in _module if m not in __all__]
+
+__pdoc__ = {}
+
+for n in NOT_IN_ALL:
+    __pdoc__[n] = False