Repository History

8 repositories tagged with LangChain

Topic: LangChain
AgentEvals: Robust Evaluation Tools for LLM Agent Trajectories

AgentEvals: Robust Evaluation Tools for LLM Agent Trajectories

AgentEvals is a powerful open-source package from LangChain designed to simplify the evaluation of agentic applications. It provides a collection of ready-made evaluators and utilities, with a particular focus on analyzing agent trajectories, the intermediate steps an agent takes to solve problems. This helps developers understand and improve the reliability and performance of their LLM agents.

Analyzed Jun 30, 2026
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Phoenix: AI Observability and Evaluation Platform for LLMs

Phoenix: AI Observability and Evaluation Platform for LLMs

Phoenix is an open-source AI observability platform from Arize AI, designed for comprehensive experimentation, evaluation, and troubleshooting of LLM applications. It provides robust features including OpenTelemetry-based tracing, LLM evaluation, and systematic prompt management. This platform helps developers optimize and debug their AI models effectively across various environments.

Analyzed Jun 28, 2026
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Open Deep Research: A Configurable Open-Source Deep Research Agent

Open Deep Research: A Configurable Open-Source Deep Research Agent

Open Deep Research is a fully open-source, configurable agent designed for deep research applications. It supports various model providers, search tools, and Model Context Protocol (MCP) servers, offering performance comparable to other popular deep research agents. Developed by LangChain, it leverages LangGraph for robust agent orchestration and provides extensive customization options.

Analyzed May 15, 2026
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rag-from-scratch: Building Retrieval Augmented Generation Systems

rag-from-scratch: Building Retrieval Augmented Generation Systems

This repository by LangChain AI offers a comprehensive guide to understanding and implementing Retrieval Augmented Generation (RAG) from scratch. It includes a series of Jupyter notebooks and an accompanying video playlist, making complex RAG concepts accessible for practical application. The resource highlights RAG's advantages over fine-tuning for factual recall in Large Language Models (LLMs).

Analyzed Apr 30, 2026
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Article-Assistant--RAG-Telegram-Bot: AI-Powered Knowledge Base via Telegram

Article-Assistant--RAG-Telegram-Bot: AI-Powered Knowledge Base via Telegram

The Article Assistant is a sophisticated RAG (Retrieval-Augmented Generation) Telegram bot designed to create interactive knowledge bases from various documents. Users can upload PDFs or provide URLs, and the bot will provide AI-powered answers with source citations. This tool efficiently transforms static content into a dynamic, queryable resource.

Analyzed Apr 24, 2026
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Langsmith-sdk: Client SDK for LLM Debugging, Evaluation, and Monitoring

Langsmith-sdk: Client SDK for LLM Debugging, Evaluation, and Monitoring

The Langsmith-sdk provides client SDKs for interacting with the LangSmith platform, enabling robust debugging, evaluation, and monitoring of language models and intelligent agents. It offers native integrations with both LangChain Python and LangChain JS, making it an essential tool for LLM application development.

Analyzed Mar 18, 2026
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Helicone: Open Source LLM Observability Platform and AI Gateway

Helicone: Open Source LLM Observability Platform and AI Gateway

Helicone is an open-source LLM observability platform and AI Gateway for AI engineers. It provides one-line code integration to monitor, evaluate, and experiment with large language models, offering features like cost tracking, prompt management, and intelligent routing. The platform supports a wide range of inference providers and frameworks, simplifying LLM development and deployment.

Analyzed Mar 1, 2026
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Opik: Open-Source LLM Observability, Evaluation, and Optimization

Opik: Open-Source LLM Observability, Evaluation, and Optimization

Opik is an open-source platform by Comet designed to streamline the lifecycle of LLM applications. It provides comprehensive tools for debugging, evaluating, and monitoring RAG systems and agentic workflows. Developers can leverage its tracing, automated evaluations, and production-ready dashboards to build and optimize generative AI applications.

Analyzed Dec 13, 2025
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