2026-01-15 11:04:37 +00:00
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post:
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tags:
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- Flow Services
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summary: Document RAG - retrieve and generate from documents
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description: |
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Retrieval-Augmented Generation over document embeddings.
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## Document RAG Overview
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Document RAG combines:
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1. **Retrieval**: Search document embeddings using semantic similarity
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2. **Generation**: Use LLM to synthesize answer from retrieved documents
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This provides grounded answers based on your document corpus.
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## Query Process
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1. Convert query to embedding
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2. Search document embeddings for most similar chunks
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3. Retrieve top N document chunks (configurable via doc-limit)
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4. Pass query + retrieved context to LLM
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5. Generate answer grounded in documents
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## Streaming
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Enable `streaming: true` to receive the answer as it's generated:
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2026-04-07 22:24:59 +01:00
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- Multiple `chunk` messages with `response` content
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- `explain` messages with inline provenance triples (`explain_triples`)
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2026-01-15 11:04:37 +00:00
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- Final message with `end-of-stream: true`
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2026-04-07 22:24:59 +01:00
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- Session ends with `end_of_session: true`
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Explain events carry `explain_id`, `explain_graph`, and `explain_triples`
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inline in the stream, so no follow-up knowledge graph query is needed.
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2026-01-15 11:04:37 +00:00
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Without streaming, returns complete answer in single response.
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## Parameters
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- **doc-limit**: Controls retrieval depth (1-100, default 20)
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- Higher = more context but slower
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- Lower = faster but may miss relevant info
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- **collection**: Target specific document collection
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- **user**: Multi-tenant isolation
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operationId: documentRagService
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security:
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- bearerAuth: []
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parameters:
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- name: flow
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in: path
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required: true
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schema:
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type: string
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description: Flow instance ID
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example: my-flow
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requestBody:
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required: true
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content:
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application/json:
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schema:
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$ref: '../../components/schemas/rag/DocumentRagRequest.yaml'
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examples:
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basicQuery:
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summary: Basic document query
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value:
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query: What are the key findings in the research papers?
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user: alice
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collection: research
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streamingQuery:
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summary: Streaming query
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value:
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query: Summarize the main conclusions
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user: alice
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collection: research
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doc-limit: 15
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streaming: true
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limitedRetrieval:
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summary: Query with limited retrieval
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value:
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query: What is quantum entanglement?
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doc-limit: 5
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responses:
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'200':
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description: Successful response
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content:
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application/json:
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schema:
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$ref: '../../components/schemas/rag/DocumentRagResponse.yaml'
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examples:
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completeResponse:
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summary: Complete non-streaming response
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value:
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response: |
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The research papers present three key findings:
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1. Quantum entanglement exhibits non-local correlations
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2. Bell's inequality is violated in experimental tests
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3. Applications in quantum cryptography are promising
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end-of-stream: false
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streamingChunk:
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summary: Streaming response chunk
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value:
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response: "The research papers present three"
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end-of-stream: false
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explainEvent:
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summary: Explain event with inline provenance triples
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value:
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message_type: explain
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explain_id: urn:trustgraph:question:abc123
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explain_graph: urn:graph:retrieval
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explain_triples:
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- s: {t: i, i: "urn:trustgraph:question:abc123"}
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p: {t: i, i: "http://www.w3.org/1999/02/22-rdf-syntax-ns#type"}
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o: {t: i, i: "https://trustgraph.ai/ns/DocumentRagQuestion"}
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- s: {t: i, i: "urn:trustgraph:question:abc123"}
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p: {t: i, i: "https://trustgraph.ai/ns/query"}
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o: {t: l, v: "What are the key findings in the research papers?"}
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end-of-stream: false
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end_of_session: false
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streamingComplete:
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summary: Streaming complete marker
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value:
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response: ""
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end-of-stream: true
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'401':
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$ref: '../../components/responses/Unauthorized.yaml'
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'500':
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$ref: '../../components/responses/Error.yaml'
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