sectum-ai-adapters

The adapter SDK for Sectum AI — the connectors that point the marker substrate and the attack catalog at real systems.

Every adapter family ships a deterministic in-memory fake (used by the unit suite and offline runs) plus live backends, each behind a capability-reporting interface so probes can declare what they require:

  • Vector stores — pgvector, Chroma, Weaviate, Qdrant, Pinecone, Milvus, OpenSearch, Azure AI Search
  • RAG pipelines — generic HTTP, LangChain
  • Observability — Langfuse, LangSmith, Phoenix, Helicone, Datadog APM, generic OpenTelemetry
  • Agents — LangGraph, AutoGen, CrewAI, OpenAI Assistants, Anthropic tool-use, generic HTTP
  • MCP — stdio + streamable-HTTP Model Context Protocol clients
  • Cache — Redis
  • Model — HuggingFace + PEFT LoRA, vLLM and TGI (serving-only)
pip install sectum-ai-adapters
# live backends are opt-in extras, e.g.:
pip install "sectum-ai-adapters[pgvector]"   # or [redis], [langgraph], [anthropic-tooluse], ...

Most users install the umbrella package sectum-ai instead, which pulls this in automatically.

Apache-2.0.

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Credits

Author: Sectum AI

GitHub Statistics

Data verified by PyPI on Aug 17, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

Apache-2.0
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Requires

Python >=3.12

Provides Extra

anthropic-tooluse autogen azure-search boto3 chroma crewai gcs huggingface langfuse langgraph langsmith mcp mem0 milvus openai-assistants opensearch pgvector phoenix pinecone qdrant rag-langchain redis tgi vllm weaviate

Tags

adapters ai-security multi-tenant verification

Classifiers

Report project as malware

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