Core Endpoints
Deep Research API
Multi-iteration autonomous research with hypothesis evolution and discovery tracking
POST
Deep Research API
Documentation Index
Fetch the complete documentation index at: https://mintlify.com/bio-xyz/BioAgents/llms.txt
Use this file to discover all available pages before exploring further.
Overview
The Deep Research API enables iterative, hypothesis-driven scientific research. Unlike the basic chat API, deep research runs multiple autonomous cycles of planning, execution, hypothesis generation, and reflection.Key Capabilities
- Autonomous Iteration: Runs multiple research cycles until objectives are met
- Hypothesis Evolution: Updates hypotheses based on new evidence
- Discovery Tracking: Identifies and links novel findings to supporting evidence
- Clarification Context: Accepts pre-approved research plans from clarification sessions
- Research Modes: Semi-autonomous, fully-autonomous, or steering modes
Authentication
All deep research endpoints require authentication.Bearer token for JWT authentication
Alternative API key authentication
POST /api/deep-research/start
Initiate a new deep research investigation.Request Body
The research question or objective
Optional conversation ID. Auto-generated if not provided.
Research execution mode:
semi-autonomous(default): Runs up to MAX_AUTO_ITERATIONS (default 5)fully-autonomous: Continues until complete or 20 iterationssteering: Single iteration only, always asks for user feedback
Optional clarification session ID containing pre-approved plan and answers
Optional files to upload for analysis
Response (In-Process Mode)
Returns202 Accepted immediately. Research runs in background.
Message ID for status polling
Conversation ID for tracking
User ID for ownership verification
Initial status:
processingURL to check research progress
Response (Queue Mode)
Returns202 Accepted with job information.
BullMQ job ID for the first iteration
Root message ID for tracking
Conversation ID
User ID
Job status:
queuedURL to check job status
Example: Start Research
Example Response
Example: With Clarification Context
Example: With File Upload
Research Workflow
Each iteration follows this sequence:- Planning: Determines tasks to execute based on current state
- Execution: Runs literature search and data analysis tasks in parallel
- Hypothesis: Generates or updates scientific hypothesis
- Reflection: Extracts insights and evolves research objectives
- Discovery: Identifies novel findings with evidence links
- Continuation: Decides whether to continue or ask user for guidance
World State
The conversation state accumulates knowledge across iterations:currentObjective: Current research focusevolvingObjective: Long-term research directioncurrentHypothesis: Latest scientific hypothesiskeyInsights: Extracted insights from all tasksdiscoveries: Novel findings with evidence attributionmethodology: Research methodology descriptionplan: All executed and planned taskssuggestedNextSteps: Agent’s suggestions for next iteration
Deduplication
The API prevents duplicate research runs for the same conversation:- If an active run exists, returns the existing
messageIdandpollUrl - Uses mutex locks to prevent race conditions
- Response includes
deduplicated: trueflag
Example: Deduplicated Response
Research Modes
Semi-Autonomous (Default)
Runs up toMAX_AUTO_ITERATIONS (default 5) before asking for user feedback.
Fully Autonomous
Continues iterating until research objectives are met or 20 iterations reached.Steering Mode
Executes only a single iteration and always returns control to user.Clarification Integration
When starting research with a clarification session:- User completes pre-research clarification flow
- Clarification session contains approved plan with initial tasks
- Pass
clarificationSessionIdto skip planning on first iteration - Initial tasks are executed with resolved dataset references
Clarification Context Structure
Error Codes
- Missing required field: message
- Clarification session not approved
- Invalid research mode
Missing or invalid authentication
Clarification session not found or access denied
- Setup failed
- Data setup failed
- Failed to initialize deep research run
Task Types
LITERATURE Tasks
Searches scientific literature from multiple sources:- OpenScholar: General scientific papers
- Edison/BioLit: Bioscience-specific literature
- Knowledge Base: Internal/custom knowledge
objective: Search queryoutput: Formatted literature results with DOI citationsjobId: External service job ID for traceabilityreasoning: Intermediate reasoning traces (for Edison/BioLit)
ANALYSIS Tasks
Executes data analysis on uploaded datasets:- Supports CSV, Excel, and other tabular formats
- Runs statistical analysis and visualization
- Generates plots and figures
objective: Analysis goaldatasets: Array of dataset referencesoutput: Analysis results with interpretationsartifacts: Generated plots and filesjobId: Analysis job ID
Related Endpoints
- Status API - Check research progress
- Chat API - Simple conversational queries
- Health API - Service health check
Deep Research API