OSS-first docs
These docs teach the open system first: contracts, generated surfaces, runtimes, governance, and incremental adoption. Studio shows up as the operating layer on top, not as the source of truth.
Qdrant
Qdrant is a high-performance vector database for semantic search, recommendations, and RAG (Retrieval-Augmented Generation) applications.
Setup
# .env QDRANT_URL=https://... QDRANT_API_KEY=... QDRANT_COLLECTION=documents
Storing vectors
capabilityId: qdrant-upsert provider: type: qdrant operation: upsert inputs: collection: type: string points: type: array items: type: object properties: id: string vector: array payload: object outputs: status: type: string
Semantic search
capabilityId: qdrant-search provider: type: qdrant operation: search inputs: collection: type: string vector: type: array items: type: number limit: type: number default: 10 outputs: results: type: array items: type: object properties: id: string score: number payload: object
RAG workflow example
workflowId: rag-query version: '1.0.0'.0.0 steps: - id: generate-embedding capability: openai-embeddings inputs: text: ${input.query} - id: search-documents capability: qdrant-search inputs: collection: "documents" vector: ${steps.generate-embedding.output.embedding} limit: 5 - id: generate-answer capability: openai-chat inputs: messages: - role: "system" content: "Answer based on the context provided" - role: "user" content: | Context: ${steps.search-documents.output.results} Question: ${input.query}
Mistral integration
Use Mistral through the same provider contract model and runtime guardrails.
Gmail integration
Ingest email threads through delta-aware provider contracts and governed outbound-send mutations.
Why ContractSpec
Keep educational and comparison content reachable without letting it define the primary OSS learning path.