From 42207f5befaace80de4420adf2533305115b5f8c Mon Sep 17 00:00:00 2001 From: Surya Pratap Singh Shekhawat Date: Sat, 25 May 2024 03:44:41 +0530 Subject: [PATCH] Update agent_executor.ipynb (#22104) fixed typos in the doc. --------- Co-authored-by: ccurme --- docs/docs/how_to/agent_executor.ipynb | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/docs/docs/how_to/agent_executor.ipynb b/docs/docs/how_to/agent_executor.ipynb index a1fcc4f7ab0..fb1d8709cf4 100644 --- a/docs/docs/how_to/agent_executor.ipynb +++ b/docs/docs/how_to/agent_executor.ipynb @@ -19,13 +19,13 @@ "\n", "By themselves, language models can't take actions - they just output text.\n", "A big use case for LangChain is creating **agents**.\n", - "Agents are systems that use an LLM as a reasoning enginer to determine which actions to take and what the inputs to those actions should be.\n", - "The results of those actions can then be fed back into the agent and it determine whether more actions are needed, or whether it is okay to finish.\n", + "Agents are systems that use an LLM as a reasoning engine to determine which actions to take and what the inputs to those actions should be.\n", + "The results of those actions can then be fed back into the agent and it determines whether more actions are needed, or whether it is okay to finish.\n", "\n", - "In this tutorial we will build an agent that can interact with multiple different tools: one being a local database, the other being a search engine. You will be able to ask this agent questions, watch it call tools, and have conversations with it.\n", + "In this tutorial, we will build an agent that can interact with multiple different tools: one being a local database, the other being a search engine. You will be able to ask this agent questions, watch it call tools, and have conversations with it.\n", "\n", ":::{.callout-important}\n", - "This section will cover building with LangChain Agents. LangChain Agents are fine for getting started, but past a certain point you will likely want flexibility and control that they do not offer. For working with more advanced agents, we'd reccommend checking out [LangGraph](/docs/concepts/#langgraph)\n", + "This section will cover building with LangChain Agents. LangChain Agents are fine for getting started, but past a certain point, you will likely want flexibility and control that they do not offer. For working with more advanced agents, we'd reccommend checking out [LangGraph](/docs/concepts/#langgraph)\n", ":::\n", "\n", "## Concepts\n", @@ -34,7 +34,7 @@ "- Using [language models](/docs/concepts/#chat-models), in particular their tool calling ability\n", "- Creating a [Retriever](/docs/concepts/#retrievers) to expose specific information to our agent\n", "- Using a Search [Tool](/docs/concepts/#tools) to look up things online\n", - "- [`Chat History`](/docs/concepts/#chat-history), which allows a chatbot to \"remember\" past interactions and take them into account when responding to followup questions. \n", + "- [`Chat History`](/docs/concepts/#chat-history), which allows a chatbot to \"remember\" past interactions and take them into account when responding to follow-up questions. \n", "- Debugging and tracing your application using [LangSmith](/docs/concepts/#langsmith)\n", "\n", "## Setup\n",