kmail.at
← learning

langchain · difficulty ◆◆◆

Citation Metadata in langchain-mistralai: Trace RAG Answers

Grounded answers you can inspect and trust

Your Mistral RAG answers were untraceable, hiding bad retrieval and hallucinations.

2026-07-08 · 7 min read

$ export MISTRAL_API_KEY=your-key-here

What it does

The MistralAI integration surfaces citation metadata from chat responses. When the model returns document citations, LangChain exposes them on the AIMessage via additional_kwargs["citations"] as structured, inspectable metadata.

Why it matters

Knowing which source chunks generated an answer is critical for traceability, hallucination detection, and debugging retrieval quality. Before this change the citation data was opaque inside LangChain; now it is first-class and filterable.

Example

$ Invoke a Mistral model and read citation metadata off the AIMessage.
<class 'langchain_core.messages.ai.AIMessage'>
Citations returned: 2
  [0] {"text": "The EU AI Act classifies AI systems...", "source_id": "doc_001"}
  [1] {"text": "High-risk AI systems must undergo...", "source_id": "doc_042"}
Finish reason: stop

The exact schema is an array of objects with at minimum a source_id and cited text span.

Common flags

ChatMistralAI.invoke()
Returns an AIMessage with citation metadata
AIMessage.additional_kwargs
Dict holding non-standard LLM response fields
MistralAIEmbeddings.embed_query()
Embed text for retrieval, pair with citations
langchain-core 1.4.7
Added package version tracking to tracing metadata

History

Origin

Mistral returned citation spans in its raw API response, but LangChain kept them opaque before 1.1.6.

The fix

PR #37008 promoted citations to first-class metadata, enabling inspection and filtering like any message attribute.

Fun facts

Pros & cons

pros

  • + Traceability in production RAG
  • + First-class, filterable metadata
  • + Enables hallucination detection

cons

  • − Citation structure is provider-specific
  • − Requires retrieved context to trigger

Takeaways

  1. 1Inspect additional_kwargs for citations
  2. 2Flag claims without citations
  3. 3Use source_id to fetch original text

Related commands

← all learning