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CrewAI integration for BrowseAI Dev — research infrastructure with Grounded Intelligence for AI agents

Project description

crewai-browseaidev

CrewAI integration for BrowseAI Dev — verified web search with citations and confidence scores for AI agents.

Installation

pip install crewai-browseaidev

Quick Start

from crewai import Agent, Task, Crew
from crewai_browseaidev import BrowseAIDevAnswerTool, BrowseAIDevSearchTool

# Create tools
answer_tool = BrowseAIDevAnswerTool(api_key="bai_xxx")
search_tool = BrowseAIDevSearchTool(api_key="bai_xxx")

# Create a research agent
researcher = Agent(
    role="Research Analyst",
    goal="Provide accurate, evidence-backed research",
    backstory="You are a meticulous researcher who verifies every claim.",
    tools=[answer_tool, search_tool],
)

# Create a task
task = Task(
    description="Research the current state of quantum computing",
    expected_output="A verified summary with citations and confidence scores",
    agent=researcher,
)

# Run
crew = Crew(agents=[researcher], tasks=[task])
result = crew.kickoff()

Available Tools

  • BrowseAIDevAnswerTool — Verified research with citations, confidence scores, contradiction detection
  • BrowseAIDevSearchTool — Web search returning ranked results
  • BrowseAIDevExtractTool — Extract structured claims from a URL
  • BrowseAIDevCompareTool — Compare raw LLM vs verified answer

Why BrowseAI Dev?

Unlike raw search APIs, BrowseAI Dev fact-checks results. Every answer includes per-claim verification, cross-source consensus, contradiction detection, and evidence-based confidence scores. Open source (Apache 2.0).

Links

License

Apache 2.0

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