WebGLM

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WebGLM is an AI Agents & Automation tool that provides an efficient web-enhanced question-answering system. It integrates web search and retrieval capabilities into a pre-trained language model to improve real-world application deployment.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is WebGLM?

WebGLM is an efficient web-enhanced question-answering system developed by THUDM, presented at KDD 2023. It leverages a 10-billion-parameter General Language Model (GLM) to integrate web search and retrieval capabilities, significantly improving the accuracy and relevance of answers. The system features an LLM-augmented Retriever for enhanced web content retrieval, a Bootstrapped Generator for human-like response generation, and a Human Preference-aware Scorer to ensure useful and engaging content. WebGLM supports both 2B and 10B parameter models and offers options for searching via SerpAPI or Bing. It is designed for researchers and developers looking to implement advanced, web-aware QA systems.

Best used for

Ideal for developers and data scientists who need to build advanced question-answering systems, integrate real-time web search, and generate human-like responses. Especially valuable for research and development of efficient, web-enhanced AI agents.

Common actions

answer questions

retrieve information

generate responses

enhance search

open-sourcelow-code/no-codecollaborationdeepfakeautomated workflowworkflows"AI Agents"github copilotface swapping

Capabilities

Key features

Web-enhanced QA system
LLM-augmented Retriever
Bootstrapped Generator
Human Preference Scorer
SerpAPI/Bing search
2B and 10B models

Target Audience

developerdata scientiststartup founder

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What are the core components of WebGLM's question-answering system?

WebGLM integrates an LLM-augmented Retriever to fetch relevant web content, a Bootstrapped Generator that uses the GLM to create human-like answers, and a Human Preference-aware Scorer to evaluate and refine the quality of the generated responses, ensuring they are useful and engaging.

How can I use WebGLM for web search and retrieval?

WebGLM supports web search through either SerpAPI or Bing. Users need to obtain a SerpAPI key or configure Bing search with a local browser environment (playwright). This allows the system to retrieve up-to-date information from the web to answer questions.

What model sizes are available for WebGLM?

WebGLM is available in two main parameter versions: WebGLM-2B and WebGLM-10B. These models can be used for different scales of question-answering tasks, with the 10B version offering more comprehensive capabilities for complex queries.

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AI Frameworks & Infra Chatbots & Conversational AI General-Purpose Agents Workflow Agents Personal Assistants Voice Agents

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Research & Education › AI Search Engines

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