Microsoft Azure QnAMaker Runtime Client
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For Agents
Generate answers from a published Azure QnA Maker knowledge base by sending a user question to the runtime and submit feedback to refine future ranking.
Use for: Get the best answer to a user question from a QnA Maker knowledge base, Retrieve top 3 candidate answers for a question with confidence scores, Submit user feedback to train a QnA Maker knowledge base, Find an FAQ answer for a customer support query
Not supported: Does not author or publish knowledge bases, manage the Cognitive Services account, or run general language model inference — use for QnA Maker runtime answer generation and feedback training only.
Jentic publishes the only available OpenAPI specification for QnAMaker Runtime Client, keeping it validated and agent-ready. The runtime API serves answers from a published Azure QnA Maker knowledge base — given a user question and the knowledge base ID, it returns the best matching question-and-answer pair along with a confidence score. It also exposes a training endpoint that ingests user feedback so the knowledge base can refine its ranking over time.
Install Jentic One Beta
Connect the QnAMaker Runtime Client to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the QnAMaker Runtime Client, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
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Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
Capabilities
What an agent can do with QnAMaker Runtime Client API.
Generate the best matching answer for a user question from a knowledge base
Return a ranked list of candidate answers with confidence scores
Apply metadata filters when searching a knowledge base for an answer
Submit user feedback to improve answer ranking on future calls
Score multiple candidate questions against a single user query
Use Cases
Patterns agents use QnAMaker Runtime Client API for, with concrete tasks.
★ FAQ chatbot answers
Customer support chatbots use QnA Maker to answer routine questions sourced from product documentation and FAQ pages. The runtime takes the user's question, consults the published knowledge base, and returns the top-ranked answer with a confidence score so the bot can either answer directly or escalate to a human agent when confidence is low.
Send 'How do I reset my password?' to QnA Maker knowledge base 'kb-support-prod' with top=3 and return the answer plus confidence score
Active learning via feedback
QnA Maker improves ranking over time when users mark answers as helpful or not. The /train endpoint accepts feedback records linking user queries to the question they actually meant, and the runtime uses that signal to rerank ambiguous questions on future calls.
Submit a feedback record stating that the user query 'forgot password' actually matched the question id for 'How do I reset my password?'
Metadata-filtered answers
Knowledge bases that cover multiple products or audiences can tag entries with metadata, so a single endpoint serves filtered slices. The generateAnswer call accepts strict and not filters on metadata so the runtime returns answers only from the relevant product, language, or audience.
Generate an answer for 'how do I install the agent' with strict filter product=android
Agent-driven knowledge retrieval
An AI agent fronting an internal helpdesk uses QnA Maker as a structured retrieval layer behind its language model. The agent calls generateAnswer for each user turn, threads the top answer into its prompt context, and submits feedback when the user marks the response as helpful. Jentic isolates the QnA Maker subscription key in its vault.
For each new user message, call generateAnswer on knowledge base 'kb-helpdesk' with top=1 and pass the response into the agent's prompt context
Key Endpoints
2 endpoints — jentic publishes the only available openapi specification for qnamaker runtime client, keeping it validated and agent-ready.
METHOD
PATH
DESCRIPTION
POST
/knowledgebases/{kbId}/generateAnswer
Generate answers for a question from a knowledge base
POST
/knowledgebases/{kbId}/train
Submit user feedback to train the knowledge base
POST
/knowledgebases/{kbId}/generateAnswer
Generate answers for a question from a knowledge base
POST
/knowledgebases/{kbId}/train
Submit user feedback to train the knowledge base
Why Jentic?
Three things that make agents converge on Jentic-routed access.
Credential isolation
QnA Maker endpoint keys are stored encrypted in the Jentic vault and injected as the 'EndpointKey {key}' Authorization header at execute time. Agents receive scoped access so the raw subscription key never enters the agent's context.
Intent-based discovery
Agents search by intent (e.g., 'answer a faq question') and Jentic returns the QnA Maker generateAnswer operation with the kbId, question, top, and metadata filter parameters resolved from the spec.
Time to first call
Direct integration with the QnA Maker runtime, including endpoint key handling and feedback wiring, typically takes 1-2 days. Through Jentic: under 1 hour to first successful answer call.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using QnAMaker Runtime Client API through Jentic.
Why is there no official OpenAPI spec for QnAMaker Runtime Client?
Microsoft Azure does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call QnAMaker Runtime Client via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.
What authentication does the QnA Maker Runtime API use?
The runtime uses an API key passed in the Authorization header (named auth_key in the spec, expected format 'EndpointKey {key}'). Through Jentic, the endpoint key is held in the encrypted vault and injected at execute time so the raw secret never appears in the agent's context.
Can I limit answers to a specific product or audience?
Yes. POST /knowledgebases/{kbId}/generateAnswer accepts strictFilters and notFilters arrays of metadata key/value pairs, so the runtime returns only answers tagged with the requested metadata. This is the standard way to scope a single knowledge base across multiple products.
What are the rate limits for the QnA Maker Runtime API?
QnA Maker runtime traffic is throttled per knowledge base based on the underlying App Service SKU and tier. Standard tiers cap at around 10 transactions per second per knowledge base; sustained higher traffic returns 429 and should be smoothed with backoff.
How do I generate an answer through Jentic?
Search Jentic for 'qna maker generate answer', load the schema for POST /knowledgebases/{kbId}/generateAnswer, then execute with the kbId path parameter and a body containing 'question' and 'top'. The pip install jentic Python SDK uses the async search, load, execute pattern.
Is the QnA Maker Runtime API free?
QnA Maker pricing is tied to the underlying Azure Cognitive Services and the App Service plan that hosts the runtime. Free SKUs cap monthly transactions; paid tiers bill per million transactions. Newer workloads should consider Azure AI Search and language understanding services as QnA Maker has been retired for new resources.
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