Results for “lodgify”

Deploy Meta's LlamaGuard moderation model to filter LLM inputs and outputs across 6 safety categories using HuggingFace, vLLM, or FastAPI.

Designs incremental migration strategies, identifies service boundaries, produces dependency maps and migration roadmaps, and generates API facade designs for aging codebases.

Automate recruiting workflows in Lever ATS -- manage opportunities, job postings, requisitions, pipeline stages, and candidate tags through the Composio Lever integration.

Provides expertise in Langfuse for LLM observability, including tracing, prompt management, evaluation, and integration with LangChain, LlamaIndex, and OpenAI.

Meta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons, substances, self-harm, criminal planning. 94-95% accuracy. Deploy with vLLM, HuggingFace, Sagemaker. Integrates with NeMo Guardrails.

Streams change data capture from Oracle Database into Redpanda or Kafka using the oracledb_cdc input in Redpanda Connect, which reads redo logs via LogMiner. Covers configuration, Oracle setup, checkpointing, and enterprise features.

Guides building LLM applications on the Dify platform, covering visual workflows, knowledge bases, agents, and API deployment.

Meta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons, substances, self-harm, criminal planning. 94-95% accuracy. Deploy with vLLM, HuggingFace, Sagemaker. Integrates with NeMo Guardrails.

Streams change data capture from PostgreSQL into Redpanda or Kafka using Redpanda Connect's postgres_cdc input, covering setup, snapshotting, and troubleshooting.