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: stringSemantic 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: objectRAG 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}OSS docsintegrationsStart with OSS. Adopt Studio when you want the operating layer.
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Stripe integration
Bind payments and billing behavior without smearing provider logic across the codebase.
Why ContractSpec
Keep educational and comparison content reachable without letting it define the primary OSS learning path.