Documentation Index
Fetch the complete documentation index at: https://mintlify.com/drona-gyawali/Quark/llms.txt
Use this file to discover all available pages before exploring further.
Quark retrieves the closest matching chunks from Qdrant, hydrates the prompt with short-term session memory and long-term user memory, and sends the grounded prompt to the LLM. Every answer is constrained to your ingested content.
When no chunk scores above the similarity threshold, Quark responds with:
I could not find any relevant notes for your question.
Querying from the CLI
Type any text that does not start with : and press Enter.What are the main findings in section 3?
Submit your question
Type the question at the prompt. The active session label is visible in the prompt box.
Wait for the answer
A spinner labelled Thinking is shown while Quark searches the vector store and calls the LLM.
Read the answer
The answer is printed as rendered Markdown, followed by source citations. The exchange is saved to the session’s local chat log automatically.
Use :ingest with a specific institution tag before querying to scope retrieval to that document set. The institution filter persists for the duration of your session.
Querying via the API
POST /api/v1/chat/completions
Request body
The question to send to the RAG pipeline.
The session ID that scopes the short-term memory context for this query.
Optional institution filter. When provided, retrieval is scoped to chunks tagged with this institution. Omit to search across all ingested documents.
Response
true when the query completed without an error.
The LLM-generated answer grounded in your ingested documents. When no relevant chunks are found, this is "I could not find any relevant notes for your question.".
Example
curl --request POST \
--url https://your-quark-host/api/v1/chat/completions \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{
"message": "What are the key takeaways from the biology lecture?",
"sessionId": "alice_01_m8x3k2",
"institution": "MIT"
}'
{
"success": true,
"data": "The key takeaways from the biology lecture are..."
}