BoChaWanXiang
AI-native multimodal search engine with millisecond web comprehension
AI APIAI Developer ToolsAI Search EngineMultimodal SearchReal Time Information RetrievalSearch Engine API
- Pricing:
- Free plan
Overview
Bocha AI (Bocha Wanxiang) is a next-generation multimodal search engine open platform built for AI application scenarios. It focuses on providing high-quality, real-time, and rich web-wide information retrieval capabilities for large language models, intelligent agents, and various generative AI products. Unlike traditional search engines, Bocha AI outputs multimodal content such as web pages, images, videos, and news through a structured API, helping AI "see" the full picture of the world.
On the technical front, Bocha AI integrates cutting-edge retrieval algorithms such as semantic understanding, keyword recall, and multimodal feature matching. It supports context summary returns of up to millions of tokens and can precisely identify page content, image subjects, and timestamp information. The platform also offers fine-grained retrieval capabilities like highlighted snippets, source domain filtering, and time range filtering, enabling AI to cite accurate, credible, and traceable source materials when answering complex questions.
Through simple API calls, developers can seamlessly integrate Bocha AI into chatbots, knowledge assistants, vertical-industry agents, and other products, equipping them with core capabilities such as web search, real-time Q&A, trend tracking, and content summarization. Whether it's an enterprise-grade RAG system or a developer's personal AI tool, Bocha AI serves as an efficient bridge to real-world information.
Core capabilities
- Multimodal retrieval
- Covers web pages, images, videos, news and more content types via a unified API response
- Real-time web search
- Fetches the latest information across the web in milliseconds, with millisecond-level time filters and sorting
- Long-context summarization
- Returns content with million-token summaries, letting large models digest full information directly
- Precise semantic matching
- Combines semantic vectors with keyword search to automatically identify true user intent
- Structured output
- Returns structured fields like title, summary, URL, and publish time via a JSON API
- Highlight & snippet extraction
- Intelligently extracts the most relevant web snippets for accurate LLM citations
- Source filtering
- Supports filtering results by site domain, content type, publish date, and other dimensions
- Easy integration
- Compatible with OpenAI tool-calling conventions, adding web access to AI apps in a few lines of code
Use cases
- Equip AI chatbots with real-time web search to answer the latest news and current affairs questions
- Build enterprise RAG knowledge bases by crawling industry news from the web and generating structured summaries
- Develop vertical AI agents such as finance analysis assistants and medical information aggregation tools
- Enable material retrieval on content platforms, quickly filtering image, text, and video resources by topic
- Provide backend search services for AI search products, with unified multimodal result responses
- Quickly configure web-connected bot apps on low-code platforms like Coze and Dify
- Offer academic research tools a retrieval API for the latest papers, reports, and data sources
- Build public opinion monitoring systems to track brand and industry news across the web in real time
Who it's for
AI application developers, LLM app entrepreneurs, Agent developers, Enterprise R&D teams, Data engineers, Product managers
Getting started
- 1Register an account — Visit open.bochaai.com to complete developer registration and real-name verification.
- 2Get API key — Create an app in the console and obtain the API key for interface authentication.
- 3Call the API — Send query parameters to the /v1/search endpoint via HTTP, including query and result count.
- 4Integrate into AI apps — Configure the Bocha search plugin in frameworks like LangChain, Coze, and Dify to enable agent web access.
- 5Parse results — Parse the returned JSON data to extract page titles, summaries, and links for model citation.
- 6Optimize experience — Tune retrieval quality using advanced parameters like source filtering and highlighted snippets.
Pricing
default plan
free
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