LlamaIndex integration for BrowseAI Dev — research infrastructure with Grounded Intelligence for AI agents
Project description
llamaindex-browseaidev
LlamaIndex integration for BrowseAI Dev — verified web search with citations and confidence scores for AI agents.
Installation
pip install llamaindex-browseaidev
Quick Start
from llama_index.core.agent import ReActAgent
from llama_index.llms.openai import OpenAI
from llamaindex_browseaidev import BrowseAIDevAnswerTool, BrowseAIDevSearchTool
# Create tools
answer_tool = BrowseAIDevAnswerTool(api_key="bai_xxx")
search_tool = BrowseAIDevSearchTool(api_key="bai_xxx")
# Create agent
llm = OpenAI(model="gpt-4o")
agent = ReActAgent.from_tools([answer_tool, search_tool], llm=llm, verbose=True)
# Research with verified answers
response = agent.chat("What are the latest findings on mRNA vaccine efficacy?")
print(response)
Available Tools
BrowseAIDevAnswerTool— Verified research with citations, confidence scores, contradiction detectionBrowseAIDevSearchTool— Web search returning ranked resultsBrowseAIDevExtractTool— Extract structured claims from a URLBrowseAIDevCompareTool— Compare raw LLM vs verified answer
All tools are returned as FunctionTool instances, compatible with any LlamaIndex agent.
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
- Website · GitHub · Discord
- Python SDK · LangChain · CrewAI · MCP Server
License
Apache 2.0
Project details
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