L’interface est localisée ; les présentations et documents des Skills sont traduits automatiquement par IA dans votre langue. Le code, les commandes, chemins et termes techniques restent en version originale, et le document de l’auteur fait foi.
Explorer les Skills
Productivité · SKILL.md

models-resources-vector

models-resources-vector

Guides SuperAGI model providers, resource ingestion, knowledge flows, vector stores, embeddings, and storage configuration troubleshooting.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

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

  1. Decide whether the user is asking about providers, resources, knowledge, or vector stores; use the specific reference rather than general troubleshooting.
  2. Check the config and credential requirements before assuming a backend is available.
  3. Treat provider-key validation and vector-store connection checks as live operations that may touch external services.
  4. 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.
Skills enregistrées