GetStream
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diff --git a/‎plugins/moondream/README.md‎
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diff --git a/‎plugins/moondream/py.typed‎ b/‎plugins/moondream/py.typed‎
diff --git a/‎plugins/moondream/pyproject.toml‎
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@@ -23,7 +23,7 @@ requires-python = ">=3.10"
 dependencies = [
     "getstream[webrtc,telemetry]>=2.5.7",
     "python-dotenv>=1.1.1",
-    "pillow>=11.3.0",
+    "pillow>=10.4.0",  # Compatible with moondream SDK (<11.0.0)
     "numpy>=1.24.0",
     "mcp>=1.16.0",
     "colorlog>=6.10.1",
 
@@ -0,0 +1,172 @@
+# Moondream Plugin
+
+This plugin provides Moondream 3 detection capabilities for vision-agents, enabling real-time zero-shot object detection on video streams. Choose between cloud-hosted or local processing depending on your needs.
+
+## Installation
+
+```bash
+uv add vision-agents-plugins-moondream
+```
+
+## Choosing the Right Processor
+
+### CloudDetectionProcessor (Recommended for Most Users)
+- **Use when:** You want a simple setup with no infrastructure management
+- **Pros:** No model download, no GPU required, automatic updates
+- **Cons:** Requires API key, 2 RPS rate limit by default (can be increased)
+- **Best for:** Development, testing, low-to-medium volume applications
+
+### LocalDetectionProcessor (For Advanced Users)
+- **Use when:** You need higher throughput, have your own GPU infrastructure, or want to avoid rate limits
+- **Pros:** No rate limits, no API costs, full control over hardware
+- **Cons:** Requires GPU for best performance, model download on first use, infrastructure management
+- **Best for:** Production deployments, high-volume applications, Digital Ocean Gradient AI GPUs, or custom infrastructure
+
+## Quick Start
+
+### Using CloudDetectionProcessor (Hosted)
+
+The `CloudDetectionProcessor` uses Moondream's hosted API. By default it has a 2 RPS (requests per second) rate limit and requires an API key. The rate limit can be adjusted by contacting the Moondream team to request a higher limit.
+
+```python
+from vision_agents.plugins import moondream
+from vision_agents.core import Agent
+
+# Create a cloud processor with detection
+processor = moondream.CloudDetectionProcessor(
+    api_key="your-api-key",  # or set MOONDREAM_API_KEY env var
+    detect_objects="person",  # or ["person", "car", "dog"] for multiple
+    fps=30
+)
+
+# Use in an agent
+agent = Agent(
+    processors=[processor],
+    llm=your_llm,
+    # ... other components
+)
+```
+
+### Using LocalDetectionProcessor (On-Device)
+
+If you are running on your own infrastructure or using a service like Digital Ocean's Gradient AI GPUs, you can use the `LocalDetectionProcessor` which downloads the model from HuggingFace and runs on device. By default it will use CUDA for best performance. Performance will vary depending on your specific hardware configuration.
+
+**Note:** The moondream3-preview model is gated and requires HuggingFace authentication:
+- Request access at https://huggingface.co/moondream/moondream3-preview
+- Set `HF_TOKEN` environment variable: `export HF_TOKEN=your_token_here`
+- Or run: `huggingface-cli login`
+
+```python
+from vision_agents.plugins import moondream
+from vision_agents.core import Agent
+
+# Create a local processor (no API key needed)
+processor = moondream.LocalDetectionProcessor(
+    detect_objects=["person", "car", "dog"],
+    conf_threshold=0.3,
+    device="cuda",  # Auto-detects CUDA, MPS, or CPU
+    fps=30
+)
+
+# Use in an agent
+agent = Agent(
+    processors=[processor],
+    llm=your_llm,
+    # ... other components
+)
+```
+
+### Detect Multiple Objects
+
+```python
+# Detect multiple object types with zero-shot detection
+processor = moondream.CloudDetectionProcessor(
+    api_key="your-api-key",
+    detect_objects=["person", "car", "dog", "basketball"],
+    conf_threshold=0.3
+)
+
+# Access results for LLM
+state = processor.state()
+print(state["detections_summary"])  # "Detected: 2 persons, 1 car"
+print(state["detections_count"])  # Total number of detections
+print(state["last_image"])  # PIL Image for vision models
+```
+
+## Configuration
+
+### CloudDetectionProcessor Parameters
+
+- `api_key`: str - API key for Moondream Cloud API. If not provided, will attempt to read from `MOONDREAM_API_KEY` environment variable.
+- `detect_objects`: str | List[str] - Object(s) to detect using zero-shot detection. Can be any object name like "person", "car", "basketball". Default: `"person"`
+- `conf_threshold`: float - Confidence threshold for detections (default: 0.3)
+- `fps`: int - Frame processing rate (default: 30)
+- `interval`: int - Processing interval in seconds (default: 0)
+- `max_workers`: int - Thread pool size for CPU-intensive operations (default: 10)
+
+**Rate Limits:** By default, the Moondream Cloud API has a 2rps (requests per second) rate limit. Contact the Moondream team to request a higher limit.
+
+### LocalDetectionProcessor Parameters
+
+- `detect_objects`: str | List[str] - Object(s) to detect using zero-shot detection. Can be any object name like "person", "car", "basketball". Default: `"person"`
+- `conf_threshold`: float - Confidence threshold for detections (default: 0.3)
+- `fps`: int - Frame processing rate (default: 30)
+- `interval`: int - Processing interval in seconds (default: 0)
+- `max_workers`: int - Thread pool size for CPU-intensive operations (default: 10)
+- `device`: str - Device to run inference on ('cuda', 'mps', or 'cpu'). Auto-detects CUDA, then MPS (Apple Silicon), then defaults to CPU. Default: `None` (auto-detect)
+- `model_name`: str - Hugging Face model identifier (default: "moondream/moondream3-preview")
+- `options`: AgentOptions - Model directory configuration. If not provided, uses default which defaults to tempfile.gettempdir()
+
+**Performance:** Performance will vary depending on your hardware configuration. CUDA is recommended for best performance on NVIDIA GPUs. The model will be downloaded from HuggingFace on first use.
+
+## Video Publishing
+
+The processor publishes annotated video frames with bounding boxes drawn on detected objects:
+
+```python
+processor = moondream.CloudDetectionProcessor(
+    api_key="your-api-key",
+    detect_objects=["person", "car"]
+)
+
+# The track will show:
+# - Green bounding boxes around detected objects
+# - Labels with confidence scores
+# - Real-time annotation overlay
+```
+
+## Testing
+
+The plugin includes comprehensive tests:
+
+```bash
+# Run all tests
+pytest plugins/moondream/tests/ -v
+
+# Run specific test categories
+pytest plugins/moondream/tests/ -k "inference" -v
+pytest plugins/moondream/tests/ -k "annotation" -v
+pytest plugins/moondream/tests/ -k "state" -v
+```
+
+## Dependencies
+
+### Required
+- `vision-agents` - Core framework
+- `moondream` - Moondream SDK for cloud API (CloudDetectionProcessor only)
+- `numpy>=2.0.0` - Array operations
+- `pillow>=10.0.0` - Image processing
+- `opencv-python>=4.8.0` - Video annotation
+- `aiortc` - WebRTC support
+
+### LocalDetectionProcessor Additional Dependencies
+- `torch` - PyTorch for model inference
+- `transformers` - HuggingFace transformers library for model loading
+
+## Links
+
+- [Moondream Documentation](https://docs.moondream.ai/)
+- [Vision Agents Documentation](https://visionagents.ai/)
+- [GitHub Repository](https://github.com/GetStream/Vision-Agents)
+
+
@@ -0,0 +1,43 @@
+[build-system]
+requires = ["hatchling", "hatch-vcs"]
+build-backend = "hatchling.build"
+
+[project]
+name = "vision-agents-plugins-moondream"
+dynamic = ["version"]
+description = "Moondream 3 vision processor plugin for Vision Agents"
+readme = "README.md"
+requires-python = ">=3.10"
+license = "MIT"
+dependencies = [
+    "vision-agents",
+    "numpy>=2.0.0",
+    "pillow>=10.4.0",
+    "opencv-python>=4.8.0",
+    "moondream>=0.1.1",  # Now compatible with vision-agents pillow>=10.4.0
+    "transformers>=4.40.0",  # For local model loading
+    "torch>=2.0.0",  # PyTorch for model inference
+    "accelerate>=0.20.0",  # Required for device_map and device management
+]
+
+[project.urls]
+Documentation = "https://visionagents.ai/"
+Website = "https://visionagents.ai/"
+Source = "https://github.com/GetStream/Vision-Agents"
+
+[tool.hatch.version]
+source = "vcs"
+raw-options = { root = "..", search_parent_directories = true, fallback_version = "0.0.0" }
+
+[tool.hatch.build.targets.wheel]
+packages = [".", "vision_agents"]
+
+[tool.uv.sources]
+vision-agents = { workspace = true }
+
+[dependency-groups]
+dev = [
+    "pytest>=8.4.1",
+    "pytest-asyncio>=1.0.0",
+]
+