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API Reference
Agent

Research

agent.research(AgentResearchParams**kwargs) -> ResearchEvent
POST/research

Execute AI-powered research queries that search the web, analyze sources, and synthesize comprehensive answers. This endpoint always streams responses using Server-Sent Events (SSE).

Streaming Response:

  • All responses are streamed using Server-Sent Events (text/event-stream)
  • Real-time progress updates as research progresses through phases

Research Modes:

  • fast - Quick answers with minimal web searches
  • balanced - Standard research with multiple iterations (default)

Use Cases:

  • Answering complex questions with cited sources
  • Synthesizing information from multiple web sources
  • Research reports on specific topics
  • Fact-checking and verification tasks
ParametersExpand Collapse
query: str

The research query or question to answer

fetch_timeout: Optional[int]

Timeout in seconds for fetching web pages

mode: Optional[Literal["fast", "balanced"]]

Research mode: fast (quick answers), balanced (standard research, default)

Accepts one of the following:
"fast"
"balanced"
nocache: Optional[bool]

Skip cache and force fresh research

ReturnsExpand Collapse
class ResearchEvent: …
data: Optional[object]

Event payload data

event: Optional[Literal["phase", "progress", "complete", "error"]]

The event type: phase, progress, complete, or error

Accepts one of the following:
"phase"
"progress"
"complete"
"error"
class ResearchEvent: …
data: Optional[object]

Event payload data

event: Optional[Literal["phase", "progress", "complete", "error"]]

The event type: phase, progress, complete, or error

Accepts one of the following:
"phase"
"progress"
"complete"
"error"

Research

import os
from tabstack import Tabstack

client = Tabstack(
    api_key=os.environ.get("TABSTACK_API_KEY"),  # This is the default and can be omitted
)
research_event = client.agent.research(
    query="What are the latest developments in quantum computing?",
)
print(research_event.data)
Returns Examples