langchain-browseaidev 0.1.2

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

langchain-browseaidev

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

Unlike raw search APIs, BrowseAI Dev fact-checks results before returning them. Every answer includes per-claim verification, cross-source consensus, contradiction detection, and evidence-based confidence scores.

Installation

pip install langchain-browseaidev

Quick Start

from langchain_browseaidev import BrowseAIDevAnswerTool

# Verified search with citations and confidence
tool = BrowseAIDevAnswerTool(api_key="bai_xxx")
result = tool.invoke({"query": "What is quantum computing?"})
print(result)

Available Tools

BrowseAIDevAnswerTool — Verified Research (recommended)

The primary tool. Searches the web, extracts claims, verifies them using multi-signal evidence matching, detects contradictions, and returns an answer with confidence scores.

from langchain_browseaidev import BrowseAIDevAnswerTool

tool = BrowseAIDevAnswerTool(api_key="bai_xxx")

# Fast mode (default)
result = tool.invoke({"query": "Is nuclear energy safe?"})

# Thorough mode (retries if confidence < 60%)
result = tool.invoke({"query": "Health effects of intermittent fasting", "depth": "thorough"})

# Deep mode (multi-step agentic research with gap analysis)
result = tool.invoke({"query": "Compare CRISPR vs base editing approaches", "depth": "deep"})

BrowseAIDevSearchTool — Web Search

Basic web search returning ranked results with URLs, titles, and snippets.

from langchain_browseaidev import BrowseAIDevSearchTool

tool = BrowseAIDevSearchTool(api_key="bai_xxx")
result = tool.invoke({"query": "AI safety regulations 2024", "limit": 5})

BrowseAIDevExtractTool — Page Extraction

Extract structured claims and knowledge from a specific URL.

from langchain_browseaidev import BrowseAIDevExtractTool

tool = BrowseAIDevExtractTool(api_key="bai_xxx")
result = tool.invoke({"url": "https://arxiv.org/abs/2303.08774", "query": "What are GPT-4's capabilities?"})

BrowseAIDevCompareTool — Raw vs Verified

Compare a raw LLM answer against an evidence-backed verified answer. Shows where LLMs hallucinate.

from langchain_browseaidev import BrowseAIDevCompareTool

tool = BrowseAIDevCompareTool(api_key="bai_xxx")
result = tool.invoke({"query": "Is remote work more productive?"})

Use with LangChain Agents

from langchain_browseaidev import BrowseAIDevAnswerTool, BrowseAIDevSearchTool
from langchain_openai import ChatOpenAI
from langchain.agents import create_tool_calling_agent, AgentExecutor
from langchain_core.prompts import ChatPromptTemplate

llm = ChatOpenAI(model="gpt-4o")
tools = [
    BrowseAIDevAnswerTool(api_key="bai_xxx"),
    BrowseAIDevSearchTool(api_key="bai_xxx"),
]

prompt = ChatPromptTemplate.from_messages([
    ("system", "You are a research assistant. Use browseaidev_answer for fact-checked answers with citations."),
    ("human", "{input}"),
    ("placeholder", "{agent_scratchpad}"),
])

agent = create_tool_calling_agent(llm, tools, prompt)
executor = AgentExecutor(agent=agent, tools=tools)

result = executor.invoke({"input": "What are the latest findings on mRNA vaccine efficacy?"})
print(result["output"])

Why BrowseAI Dev over Tavily/Exa?

Feature	BrowseAI Dev	Tavily	Exa
Claim verification	Yes	No	No
Evidence-based confidence scores	Yes	No	No
Cross-source consensus	Yes	No	No
Contradiction detection	Yes	No	No
Deep research mode	Yes	No	Yes
Open source (Apache 2.0)	Yes	No	No
Free tier	100 verified/day	1K search/mo	Limited

Get an API Key

1. Go to browseai.dev
2. Sign in with GitHub
3. Your bai_xxx key is on the dashboard

Your bai_xxx key is on the dashboard.

Links

• Website
• Documentation
• GitHub
• Discord
• Python SDK
• MCP Server

License

Apache 2.0