Question Answering
POST/v1/stores/question-answering
Authorization
Authorizationstringrequired
Bearer token for API authentication. Format: `Bearer YOUR_API_KEY`
Request Body
querystring
Question to answer. If not provided, the question will be extracted from the passed messages.
Constraints
•Minimum length: 1
store_identifiersarray | null
IDs or names of stores to search
top_kintegerdefault:
10Number of results to return
Constraints
•Minimum: 1
file_idsarray | array
Optional list of file IDs to filter chunks by (inclusion filter)
Constraints
•Minimum items: 2•Maximum items: 2
streambooleandefault:
falseWhether to stream the answer
Response Body
answerstringrequired
The answer generated by the LLM
Request
POST/v1/stores/question-answering
from mixedbread import Mixedbread
mxbai = Mixedbread(api_key="YOUR_API_KEY")
response = mxbai.stores.question_answering(
store_identifiers=["my-knowledge-base"],
query="What are the main features of the product?",
top_k=5,
qa_options={"cite": True, "multimodal": True},
)
print(response)Response
JSON
{
"answer": "Based on the documentation, the main features of the product include:\n\n1. **Real-time data processing** - The system can process up to 10,000 requests per second with sub-millisecond latency.\n\n2. **Advanced analytics dashboard** - Provides comprehensive insights with customizable charts and reports for tracking key metrics.\n\n3. **API integration** - RESTful API with support for webhooks and batch operations, making it easy to integrate with existing systems.\n\n4. **Security features** - Enterprise-grade security with end-to-end encryption, SSO support, and compliance with SOC 2 and GDPR standards.\n\n5. **Scalability** - Auto-scaling infrastructure that grows with your needs, supporting from small teams to enterprise deployments.",
"sources": [
{
"chunk_index": 3,
"mime_type": "text/plain",
"model": "mxbai-omni",
"score": 0.9234,
"file_id": "f47ac10b-58cc-4372-a567-0e02b2c3d479",
"filename": "product_overview.pdf",
"store_id": "c3d4e5f6-a7b8-9012-cdef-345678901234",
"metadata": {
"page": 2,
"section": "features"
},
"type": "text",
"text": "Our product offers real-time data processing capabilities, handling up to 10,000 requests per second..."
},
{
"chunk_index": 7,
"mime_type": "text/plain",
"model": "mxbai-omni",
"score": 0.8956,
"file_id": "b2c3d4e5-f6a7-8901-bcde-f23456789012",
"filename": "technical_specs.pdf",
"store_id": "c3d4e5f6-a7b8-9012-cdef-345678901234",
"metadata": {
"page": 5,
"section": "architecture"
},
"type": "text",
"text": "The platform includes an advanced analytics dashboard with customizable charts and reporting tools..."
}
]
}Last updated: January 7, 2026
Search Chunks
Perform semantic search across store chunks. This endpoint searches through store chunks using semantic similarity matching. It supports complex search queries with filters and returns relevance-scored results.
Create Embeddings
Create embeddings for text or images using the specified model, encoding format, and normalization.