lastsearch
★ 20
vs
wet
★ 19
lastsearch vs wet
lastsearch: LastSearch provides a robust research infrastructure for AI agents, offering real-time web search, evidence extraction, and multi-step verification to ensure every claim is backed by a URL and has an evidence-based confidence score. It features iterative deep research modes, persistent memory sessions for collaborative knowledge accumulation, and integrates with various platforms like Python SDK and LangChain.; wet: WET is an open-source MCP server designed to empower AI agents with advanced web capabilities. It provides web search, content extraction, and library documentation indexing, offering comprehensive data retrieval for agent-driven tasks.
01
TL;DR
lastsearchRAG / Knowledge Base · ★ 20
AI Agent Grounding: Provide reliable, cited information to AI agents, preventing hallucinations and ensuring factual accuracy.
wetRAG / Knowledge Base · ★ 19
AI Agent Web Exploration: Empower AI agents to conduct comprehensive web searches and retrieve relevant content for diverse tasks, facilitating informed decision-making.
02
Side-by-Side Comparison
Field
lastsearchwetCategory
RAG / Knowledge Base
RAG / Knowledge Base
Stars
★ 20
★ 19
License
Apache-2.0
Apache-2.0
Install Command
pip install lastsearch
pip install wet
Updated
5d ago
1d ago
Open Source
Yes
Yes
Tags
AI Agents, Web Search, Fact-Checking
AI Agents, Web Search, Content Extraction
03
Features
lastsearch01Evidence-Based Verification & Confidence Scoring: Multi-step pipeline including atomic claim decomposition, hybrid retrieval, semantic reranking, and cross-source consensus to ensure accuracy.
02Multiple Research Depth Modes: From `fast` lookups to `thorough` iterative verification and `deep` multi-step agentic reasoning with gap analysis.
03Research Memory (Sessions): Persistent sessions that accumulate verified knowledge across multiple queries, allowing for collaborative and forkable research workflows.
04Self-Improving Accuracy via Feedback Loop: The verification pipeline automatically improves with user feedback, adjusting domain authority, thresholds, and confidence weights.
05Enterprise Search Providers: Integrate with internal data sources like Elasticsearch and Confluence, including zero data retention options for compliance.
wet01Web Search: Embedded SearXNG metasearch (Google, Bing, DuckDuckGo, Brave) with query expansion, TTL cache, standardized citation format, and 200-token snippet cap. Optional cloud search backends as a fallback chain.
02Academic Research: Search across major academic databases including Google Scholar, Semantic Scholar, arXiv, PubMed, CrossRef, and BASE.
03Library Docs: Automatically discover and index library documentation using FTS5 hybrid search, HyDE-enhanced retrieval, and support for version-specific queries.
04Content Extraction: Utilizes a 5-strategy escalation chain for robust URL content extraction, producing smart chunks with structured output (text, markdown, JSON-LD, code blocks, metadata), supports batch processing, deep crawling, local file conversion, and includes anti-bot strategies.
05Zero Config Fallbacks: Offers out-of-the-box functionality with built-in local reference embedding and reranking via fastretrieval, requiring no API keys, while also supporting optional cloud providers for enhanced quality.
04
Use Cases
lastsearch↳AI Agent Grounding: Provide reliable, cited information to AI agents, preventing hallucinations and ensuring factual accuracy.
↳Fact-Checking and Content Verification: Verify claims, surface contradictions, and assess the trustworthiness of information for critical research or content creation.
↳Collaborative Research: Share and fork research sessions to enable multi-agent or human-agent teams to build deeper knowledge over time.
↳Building Knowledge Bases from Internal Data: Use enterprise search providers to ground LLMs on company-specific knowledge for internal tools or customer support bots.
↳Automated Research for Complex Questions: Leverage deep mode for iterative, multi-step agentic research to comprehensively answer complex inquiries.
wet↳AI Agent Web Exploration: Empower AI agents to conduct comprehensive web searches and retrieve relevant content for diverse tasks, facilitating informed decision-making.
↳Automated Research & Knowledge Gathering: Automate academic and library documentation research, efficiently gathering and providing structured information to AI agents for analysis and synthesis.
↳Content Analysis & Summarization: Facilitate advanced content extraction from URLs and local files, preparing data for in-depth analysis, summarization, or integration into Retrieval-Augmented Generation (RAG) systems.
↳Developer Documentation Lookup: Grant AI agents version-aware access to comprehensive library and project documentation, aiding in coding assistance, debugging, and issue resolution.
FAQ
FAQ
What is the difference between lastsearch and wet?
Both lastsearch and wet are in the RAG / Knowledge Base category. lastsearch has 20 stars, while wet has 19 stars.
Which is better, lastsearch or wet?
The best choice depends on your use case. Choose lastsearch if AI Agent Grounding: Provide reliable, cited information to AI agents, preventing hallucinations and ensuring factual accuracy., and wet if AI Agent Web Exploration: Empower AI agents to conduct comprehensive web searches and retrieve relevant content for diverse tasks, facilitating informed decision-making..
Is lastsearch free or open source?
Yes, lastsearch is open source on GitHub (Apache-2.0).
Is wet free or open source?
Yes, wet is open source on GitHub (Apache-2.0).
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