diff --git a/docs/docs/modules/agents/agent_types/index.mdx b/docs/docs/modules/agents/agent_types/index.mdx index 75dae52ff..c97947e78 100644 --- a/docs/docs/modules/agents/agent_types/index.mdx +++ b/docs/docs/modules/agents/agent_types/index.mdx @@ -38,7 +38,7 @@ It uses the ReAct framework to decide which tool to use, and uses memory to reme ## [Self-ask with search](/docs/modules/agents/agent_types/self_ask_with_search) This agent utilizes a single tool that should be named `Intermediate Answer`. -This tool should be able to lookup factual answers to questions. This agent +This tool should be able to look up factual answers to questions. This agent is equivalent to the original [self-ask with search paper](https://ofir.io/self-ask.pdf), where a Google search API was provided as the tool. @@ -46,7 +46,7 @@ where a Google search API was provided as the tool. This agent uses the ReAct framework to interact with a docstore. Two tools must be provided: a `Search` tool and a `Lookup` tool (they must be named exactly as so). -The `Search` tool should search for a document, while the `Lookup` tool should lookup +The `Search` tool should search for a document, while the `Lookup` tool should look up a term in the most recently found document. This agent is equivalent to the original [ReAct paper](https://arxiv.org/pdf/2210.03629.pdf), specifically the Wikipedia example. diff --git a/docs/docs/modules/agents/how_to/custom_llm_agent.mdx b/docs/docs/modules/agents/how_to/custom_llm_agent.mdx index 7d10cf50b..6e92c5471 100644 --- a/docs/docs/modules/agents/how_to/custom_llm_agent.mdx +++ b/docs/docs/modules/agents/how_to/custom_llm_agent.mdx @@ -1,4 +1,4 @@ -# Custom LLM agent +# Custom LLM Agent This notebook goes through how to create your own custom LLM agent. diff --git a/docs/docs/modules/agents/how_to/custom_llm_chat_agent.mdx b/docs/docs/modules/agents/how_to/custom_llm_chat_agent.mdx index a00f59d11..f9d8045dc 100644 --- a/docs/docs/modules/agents/how_to/custom_llm_chat_agent.mdx +++ b/docs/docs/modules/agents/how_to/custom_llm_chat_agent.mdx @@ -1,13 +1,13 @@ -# Custom LLM Agent (with a ChatModel) +# Custom LLM Chat Agent -This notebook goes through how to create your own custom agent based on a chat model. +This notebook explains how to create your own custom agent based on a chat model. -An LLM chat agent consists of three parts: +An LLM chat agent consists of four key components: -- `PromptTemplate`: This is the prompt template that can be used to instruct the language model on what to do -- `ChatModel`: This is the language model that powers the agent -- `stop` sequence: Instructs the LLM to stop generating as soon as this string is found -- `OutputParser`: This determines how to parse the LLM output into an `AgentAction` or `AgentFinish` object +- `PromptTemplate`: This is the prompt template that instructs the language model on what to do. +- `ChatModel`: This is the language model that powers the agent. +- `stop` sequence: Instructs the LLM to stop generating as soon as this string is found. +- `OutputParser`: This determines how to parse the LLM output into an `AgentAction` or `AgentFinish` object. The LLM Agent is used in an `AgentExecutor`. This `AgentExecutor` can largely be thought of as a loop that: 1. Passes user input and any previous steps to the Agent (in this case, the LLM Agent) diff --git a/docs/docs/modules/agents/how_to/mrkl.mdx b/docs/docs/modules/agents/how_to/mrkl.mdx index 6657fedc9..2269766ee 100644 --- a/docs/docs/modules/agents/how_to/mrkl.mdx +++ b/docs/docs/modules/agents/how_to/mrkl.mdx @@ -3,7 +3,7 @@ This walkthrough demonstrates how to replicate the [MRKL](https://arxiv.org/pdf/2205.00445.pdf) system using agents. This uses the example Chinook database. -To set it up follow the instructions on https://database.guide/2-sample-databases-sqlite/, placing the `.db` file in a notebooks folder at the root of this repository. +To set it up, follow the instructions on https://database.guide/2-sample-databases-sqlite/ and place the `.db` file in a "notebooks" folder at the root of this repository. ```python from langchain.chains import LLMMathChain @@ -127,7 +127,7 @@ mrkl.run("What is the full name of the artist who recently released an album cal -## With a chat model +## Using a Chat Model ```python from langchain.chat_models import ChatOpenAI diff --git a/docs/docs/modules/agents/tools/index.mdx b/docs/docs/modules/agents/tools/index.mdx index bf04ed6c4..31e0fca7d 100644 --- a/docs/docs/modules/agents/tools/index.mdx +++ b/docs/docs/modules/agents/tools/index.mdx @@ -4,17 +4,17 @@ sidebar_position: 2 # Tools :::info -Head to [Integrations](/docs/integrations/tools/) for documentation on built-in tool integrations. +For documentation on built-in tool integrations, visit [Integrations](/docs/integrations/tools/). ::: Tools are interfaces that an agent can use to interact with the world. -## Get started +## Getting Started Tools are functions that agents can use to interact with the world. These tools can be generic utilities (e.g. search), other chains, or even other agents. -Currently, tools can be loaded with the following snippet: +Currently, tools can be loaded using the following snippet: ```python from langchain.agents import load_tools diff --git a/docs/docs/modules/agents/tools/toolkits.mdx b/docs/docs/modules/agents/tools/toolkits.mdx index a09facee7..b8d199702 100644 --- a/docs/docs/modules/agents/tools/toolkits.mdx +++ b/docs/docs/modules/agents/tools/toolkits.mdx @@ -4,7 +4,7 @@ sidebar_position: 3 # Toolkits :::info -Head to [Integrations](/docs/integrations/toolkits/) for documentation on built-in toolkit integrations. +For documentation on built-in toolkit integrations, visit [Integrations](/docs/integrations/toolkits/). ::: -Toolkits are collections of tools that are designed to be used together for specific tasks and have convenience loading methods. +Toolkits are collections of tools that are designed to be used together for specific tasks and have convenient loading methods.