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title: Building LLM Agents Using LangChain &amp; OpenAI API | daily.dev
description: This post provides a guide on building LLM Agents using LangChain and OpenAI API. It explains how the agents work and the various tasks they can perform.
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# Building LLM Agents Using LangChain & OpenAI API

**[Towards AI](https://daily.dev/sources/tai)** · 2 min read · 13 upvotes · 1 comments

## Summary

This post provides a guide on building LLM Agents using LangChain and OpenAI API. It explains how the agents work and the various tasks they can perform.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://towardsai.net/p/machine-learning/building-llm-agents-using-langchain-openai-api>

## Community discussion

Top comments from developers on daily.dev.

**@kartiknvj** · 0 upvotes

> LangGraph is solid but the eval story is weak. I wrap every node with a traceAI span and run trajectory evals on the full graph, not per-node. Catches the "node A correct, node B correct, but A→B handoff broken" failures.

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---

Tags: [#ai](https://daily.dev/tags/ai), [#openai](https://daily.dev/tags/openai), [#langchain](https://daily.dev/tags/langchain)

[View this post on daily.dev](https://daily.dev/posts/building-llm-agents-using-langchain-openai-api-ccyptzmmb)

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