FastAPI Agents provides a robust service layer for developing LLM-based agents using the FastAPI web framework. It allows you to define agent behaviors with LangChain chains, tools, and memory systems. Each agent can be exposed as a standard REST endpoint, supporting asynchronous requests, streaming responses, and customizable payloads. Integration with vector stores enables retrieval-augmented generation for knowledge-driven applications. The framework includes built-in logging, monitoring hooks, and Docker support for containerized deployment. You can easily extend agents with new tools, middleware, and authentication. FastAPI Agents accelerates the production readiness of AI solutions, ensuring security, scalability, and maintainability of agent-based applications in enterprise and research settings.

SPEAR (Scalable Platform for Edge AI Real-Time) is designed to manage the full lifecycle of AI inference at the edge. Developers can define streaming pipelines that ingest sensor data, videos, or logs via connectors to Kafka, MQTT, or HTTP sources. SPEAR dynamically deploys containerized models to worker nodes, balancing loads across clusters while ensuring low-latency responses. It includes built-in model versioning, health checks, and telemetry, exposing metrics to Prometheus and Grafana. Users can apply custom transformations or alerts through a modular plugin architecture. With automated scaling and fault recovery, SPEAR delivers reliable real-time analytics for IoT, industrial automation, smart cities, and autonomous systems in heterogeneous environments.