ReddRadar
Topic: agent-orchestration
2,114 skills in this topic.
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llamaindex-agent
LlamaIndex agent and query engine setup for RAG-powered agents
a5c-ai/babysitter 514
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llm-classifier
LLM-based zero-shot and few-shot classification for flexible intent detection
a5c-ai/babysitter 514
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mem0-integration
Mem0 memory layer integration for AI agents. Implement persistent, semantic memory for long-term context retention and personalization.
a5c-ai/babysitter 514
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memory-summarization
Conversation summarization for memory compression and context management
a5c-ai/babysitter 514
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milvus-integration
Milvus distributed vector database configuration for large-scale RAG applications
a5c-ai/babysitter 514
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nemo-guardrails
NVIDIA NeMo Guardrails configuration for conversational safety and control
a5c-ai/babysitter 514
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opentelemetry-llm
OpenTelemetry instrumentation for LLM applications with distributed tracing
a5c-ai/babysitter 514
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phoenix-arize-setup
Arize Phoenix observability platform setup for LLM debugging and evaluation
a5c-ai/babysitter 514
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pii-redaction
PII detection and redaction utilities for privacy-compliant conversational AI
a5c-ai/babysitter 514
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pinecone-integration
Pinecone vector database setup, configuration, and operations for RAG applications
a5c-ai/babysitter 514
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prompt-compression
Token-efficient prompt compression techniques for cost optimization
a5c-ai/babysitter 514
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prompt-injection-detector
Prompt injection detection and prevention for secure LLM applications
a5c-ai/babysitter 514
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prompt-template-design
Structured prompt template creation with variables, formatting, and version control
a5c-ai/babysitter 514
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qdrant-integration
Qdrant vector database with filtering, payloads, and quantization support
a5c-ai/babysitter 514
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rag-chunking-strategy
Document chunking with multiple strategies including semantic, recursive, and fixed-size chunking
a5c-ai/babysitter 514
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rag-embedding-generation
Batch embedding generation with caching, rate limiting, and multiple provider support
a5c-ai/babysitter 514
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rag-hybrid-search
Hybrid search combining semantic and keyword retrieval for RAG pipelines. Implement BM25 + dense vector search with fusion strategies.
a5c-ai/babysitter 514
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rag-query-transformation
Query expansion, HyDE, and multi-query generation for improved retrieval
a5c-ai/babysitter 514
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rag-reranking
Cross-encoder reranking and MMR diversity filtering for improved retrieval quality
a5c-ai/babysitter 514
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rasa-nlu-integration
Rasa NLU pipeline configuration and training for intent and entity extraction
a5c-ai/babysitter 514
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redis-memory-backend
Redis backend for conversation state persistence and caching
a5c-ai/babysitter 514
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semantic-kernel-setup
Microsoft Semantic Kernel planner and plugin setup for orchestrated AI
a5c-ai/babysitter 514
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setfit-few-shot
SetFit few-shot learning for efficient intent classification with minimal data
a5c-ai/babysitter 514
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spacy-ner
spaCy NER model training and entity extraction for conversational AI
a5c-ai/babysitter 514