From b62f2d5ccdd032d4501d6e590e589a91ca66a3f7 Mon Sep 17 00:00:00 2001
From: Jeff Tang <jeff.x.tang@gmail.com>
Date: Wed, 4 Dec 2024 14:54:04 -0800
Subject: [PATCH] README update
---
recipes/use_cases/gmail_agent/README.md | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/recipes/use_cases/gmail_agent/README.md b/recipes/use_cases/gmail_agent/README.md
index 33cd0efa..b606000e 100644
--- a/recipes/use_cases/gmail_agent/README.md
+++ b/recipes/use_cases/gmail_agent/README.md
@@ -44,7 +44,7 @@ In a November 2024 blog by Letta [The AI agents stack](https://www.letta.com/blo
In addition, Harrison Chase defines agent in the blog [What is an AI agent](https://blog.langchain.dev/what-is-an-agent/) as "a system that uses an LLM to decide the control flow of an application."
-Yet another simple [summary](https://www.felicis.com/insight/the-agentic-web) by Felicis of what an agent does is that an agent expands LLMs to go from chat to act: an agent can pair with LLMs with external data, multi-step reasoning and planning, and act on user's behalf.
+Yet another simple [summary](https://www.felicis.com/insight/the-agentic-web) by Felicis of what an agent does is that an agent expands LLMs to go from chat to act: an agent can pair LLMs with external data, multi-step reasoning and planning, and act on the user's behalf.
All in all (see [Resources](#resources) for even more info), agents are systems that take a high-level task, use an LLM as a reasoning and planning engine, with the help of contextual info and long-term memory if needed, to decide what actions to take, reflect and improve on the actions, and eventually execute those actions to accomplish the task.
@@ -324,4 +324,4 @@ Tool calling returned: [{'message_id': '1936ef72ad3f30e8', 'sender': 'gmagent_te
7. Amazon's [Multi-Agent Orchestrator framework](https://awslabs.github.io/multi-agent-orchestrator/)
8. Deeplearning.ai's [agent related courses](https://www.deeplearning.ai/courses/?courses_date_desc%5Bquery%5D=agents) (Meta, AWS, Microsoft, LangChain, LlamaIndex, crewAI, AutoGen) and some [lessons ported to using Llama](https://github.com/meta-llama/llama-recipes/tree/main/recipes/quickstart/agents/DeepLearningai_Course_Notebooks).
9. Felicis's [The Agentic Web](https://www.felicis.com/insight/the-agentic-web)
-10. A pretty complete [list of AI agents](https://github.com/e2b-dev/awesome-ai-agents), not including [/dev/agents](https://sdsa.ai/), a very new startup building the next-gen OS for AI agents, though.
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+10. A pretty complete [list of AI agents](https://github.com/e2b-dev/awesome-ai-agents), not including [/dev/agents](https://sdsa.ai/), a very new startup building the next-gen OS for AI agents, though.
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