semvec/pypi-packages huggingface dataset:
dockrion-runtime 0.0.1
Dockrion Runtime - FastAPI server for deployed agents
License: Apache-2.0
Requires Python: >=3.11
Keywords: dockrion, runtime, agents, fastapi

# Dockrion Runtime

FastAPI-based runtime server for deployed Dockrion agents.

## Overview

This package provides the runtime infrastructure for Dockrion agents:

- **App Factory**: `create_app()` builds a configured FastAPI application
- **Authentication**: API key validation middleware
- **Metrics**: Prometheus metrics for requests, latency, errors
- **Policy Engine**: Input validation, output redaction, safety checks
- **Endpoints**: Health, invoke, schema, metrics endpoints

## Usage

The runtime is typically used via generated code, but can be used directly:

```python
from dockrion_runtime import create_app
from dockrion_schema import DockSpec

# Load your spec
spec_data = {...}  # From Dockfile.yaml
spec = DockSpec.model_validate(spec_data)

# Create the app
app = create_app(
    spec=spec,
    agent_entrypoint="myagent.graph:build_graph"
)

# Run with uvicorn
if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=8080)
```

## Endpoints

| Endpoint | Method | Description |
|----------|--------|-------------|
| `/health` | GET | Health check |
| `/ready` | GET | Readiness check |
| `/invoke` | POST | Invoke the agent |
| `/invoke/stream` | POST | Streaming invocation (SSE) |
| `/schema` | GET | Input/output schema |
| `/info` | GET | Agent metadata |
| `/metrics` | GET | Prometheus metrics |

## Configuration

The runtime is configured via the `DockSpec` object which contains:

- Agent configuration (name, entrypoint, framework)
- Model configuration (provider, name, temperature)
- Auth configuration (mode, API keys)
- Policy configuration (redaction, tool allowlists)
- Expose configuration (host, port, CORS)
dockrion-policy 0.0.1
Policy engine for Dockrion - redaction, tool gating, and safety controls
License: Apache-2.0
Requires Python: >=3.11
Keywords: dockrion, policy, security, redaction

# dockrion-policy

Policy engine for Dockrion - redaction, tool gating, and safety controls for AI agents.

## Installation

```bash
pip install dockrion-policy
```

## Features

- **Policy Engine**: Define and enforce policies for AI agent behavior
- **Redaction**: Automatically redact sensitive information from agent outputs
- **Tool Guard**: Gate and control access to tools based on policies

## Usage

```python
from dockrion_policy.policy_engine import PolicyEngine
from dockrion_policy.redactor import Redactor
from dockrion_policy.tool_guard import ToolGuard

# Initialize the policy engine
engine = PolicyEngine()

# Set up redaction for sensitive data
redactor = Redactor()
safe_output = redactor.redact(agent_output)

# Control tool access
guard = ToolGuard(allowed_tools=["search", "calculate"])
if guard.is_allowed("search"):
    # Execute tool
    pass
```

## License

Apache-2.0
dockrion-telemetry 0.0.1
Telemetry and observability helpers for Dockrion
License: Apache-2.0
Requires Python: >=3.11
Keywords: dockrion, telemetry, observability, metrics

# dockrion-telemetry

Telemetry and observability helpers for Dockrion - metrics, logging, and monitoring utilities.

## Installation

```bash
pip install dockrion-telemetry
```

## Features

- **Prometheus Metrics**: Built-in Prometheus client integration for exposing metrics
- **Structured Logging**: Consistent logging utilities across Dockrion services
- **Observability Helpers**: Common patterns for monitoring AI agent deployments

## Usage

```python
from dockrion_telemetry.prometheus_utils import setup_metrics
from dockrion_telemetry.logger import get_logger

# Set up Prometheus metrics
setup_metrics()

# Get a configured logger
logger = get_logger(__name__)
logger.info("Agent started successfully")
```

## License

Apache-2.0