name: models-resources-vector
description: "Guides SuperAGI model providers, resource ingestion, knowledge
flows, vector stores, embeddings, and storage configuration troubleshooting."
disable-model-invocation: true
metadata:
disco-role: operating
license: MIT
SuperAGI Models, Resources, and Vector Stores
Use this sub-skill when the task is about provider selection, model API keys,
resource summarization, knowledge installation, vector DB configuration, or
embedding/vector-store behavior.
Read First
Main Topics
- Model provider enums and factories: OpenAI, Google Palm, Replicate, Hugging
Face, and Local LLM.
- Resource storage: FILE vs S3, plus resource summarization into vector stores.
- Knowledge records and vector DB indices.
- Vector store selection and factory paths for Redis, Pinecone, Weaviate,
Qdrant, and related enums.
- Image LLM wrappers when a task names DALL·E or Stable Diffusion.
Safe Workflow
- Decide whether the user is asking about providers, resources, knowledge, or
vector stores; use the specific reference rather than general troubleshooting.
- Check the config and credential requirements before assuming a backend is
available.
- Treat provider-key validation and vector-store connection checks as live
operations that may touch external services.
- Use the config checker for structural validation before running a live
request.
Boundary Notes
- API route prefixes, controllers, and CRUD endpoints belong to
api-service.
- Tool wrappers that call model/vector providers belong to
toolkits-integrations.
- Deployment/runtime setup and config file creation belong to
deployment-configuration.
- Agent execution logic that consumes the selected provider or vector store
belongs to
agents-workflows.