diff --git a/docs/modules/agents.rst b/docs/modules/agents.rst index d356a0d7..fea87524 100644 --- a/docs/modules/agents.rst +++ b/docs/modules/agents.rst @@ -2,7 +2,7 @@ Agents ========================== Some applications will require not just a predetermined chain of calls to LLMs/other tools, -but potentially an unknown chain that depends on the user input. +but potentially an unknown chain that depends on the user's input. In these types of chains, there is a “agent” which has access to a suite of tools. Depending on the user input, the agent can then decide which, if any, of these tools to call. @@ -12,7 +12,7 @@ The following sections of documentation are provided: - `Key Concepts <./agents/key_concepts.html>`_: A conceptual guide going over the various concepts related to agents. -- `How-To Guides <./agents/how_to_guides.html>`_: A collection of how-to guides. These highlight how to integrate various types of tools, how to work with different types of agent, and how to customize agents. +- `How-To Guides <./agents/how_to_guides.html>`_: A collection of how-to guides. These highlight how to integrate various types of tools, how to work with different types of agents, and how to customize agents. - `Reference <../reference/modules/agents.html>`_: API reference documentation for all Agent classes. @@ -27,4 +27,4 @@ The following sections of documentation are provided: ./agents/getting_started.ipynb ./agents/key_concepts.md ./agents/how_to_guides.rst - Reference<../reference/modules/agents.rst> \ No newline at end of file + Reference<../reference/modules/agents.rst> diff --git a/docs/modules/agents/agents.md b/docs/modules/agents/agents.md index 641fb243..a1e8aa94 100644 --- a/docs/modules/agents/agents.md +++ b/docs/modules/agents/agents.md @@ -1,7 +1,7 @@ # Agents Agents use an LLM to determine which actions to take and in what order. -An action can either be using a tool and observing its output, or returning to the user. +An action can either be using a tool and observing its output, or returning a response to the user. For a list of easily loadable tools, see [here](tools.md). Here are the agents available in LangChain. diff --git a/docs/modules/chains.rst b/docs/modules/chains.rst index 5d71a8c1..a23fead3 100644 --- a/docs/modules/chains.rst +++ b/docs/modules/chains.rst @@ -2,8 +2,8 @@ Chains ========================== Using an LLM in isolation is fine for some simple applications, -but many more complex ones require chaining LLMs - either with eachother or with other experts. -LangChain provides a standard interface for Chains, as well as some common implementations of chains for easy use. +but many more complex ones require chaining LLMs - either with each other or with other experts. +LangChain provides a standard interface for Chains, as well as some common implementations of chains for ease of use. The following sections of documentation are provided: @@ -26,4 +26,4 @@ The following sections of documentation are provided: ./chains/getting_started.ipynb ./chains/how_to_guides.rst ./chains/key_concepts.rst - Reference<../reference/modules/chains.rst> \ No newline at end of file + Reference<../reference/modules/chains.rst> diff --git a/docs/modules/chains/getting_started.ipynb b/docs/modules/chains/getting_started.ipynb index f3570abf..aab88c17 100644 --- a/docs/modules/chains/getting_started.ipynb +++ b/docs/modules/chains/getting_started.ipynb @@ -9,13 +9,13 @@ "In this tutorial, we will learn about creating simple chains in LangChain. We will learn how to create a chain, add components to it, and run it.\n", "\n", "In this tutorial, we will cover:\n", - "- Using the simple LLM chain\n", + "- Using a simple LLM chain\n", "- Creating sequential chains\n", "- Creating a custom chain\n", "\n", "## Why do we need chains?\n", "\n", - "Chains allow us to combine multiple components together to create a single, coherent application. For example, we can create a chain that takes user input, format it with a PromptTemplate, and then passes the formatted response to an LLM. We can build more complex chains by combining multiple chains together, or by combining chains with other components.\n" + "Chains allow us to combine multiple components together to create a single, coherent application. For example, we can create a chain that takes user input, formats it with a PromptTemplate, and then passes the formatted response to an LLM. We can build more complex chains by combining multiple chains together, or by combining chains with other components.\n" ] }, { @@ -88,7 +88,7 @@ "source": [ "## Combine chains with the `SequentialChain`\n", "\n", - "The next step after calling a language model is make a series of calls to a language model. We can do this using sequential chains, which are chains that execute their links in a predefined order. Specifically, we will use the `SimpleSequentialChain`. This is the simplest form of sequential chains, where each step has a singular input/output, and the output of one step is the input to the next.\n", + "The next step after calling a language model is to make a series of calls to a language model. We can do this using sequential chains, which are chains that execute their links in a predefined order. Specifically, we will use the `SimpleSequentialChain`. This is the simplest type of a sequential chain, where each step has a single input/output, and the output of one step is the input to the next.\n", "\n", "In this tutorial, our sequential chain will:\n", "1. First, create a company name for a product. We will reuse the `LLMChain` we'd previously initialized to create this company name.\n", @@ -156,7 +156,7 @@ "source": [ "## Create a custom chain with the `Chain` class\n", "\n", - "LangChain provides many chains out of the box, but sometimes you may want to create a custom chains for your specific use case. For this example, we will create a custom chain that concatenates the outputs of 2 `LLMChain`s.\n", + "LangChain provides many chains out of the box, but sometimes you may want to create a custom chain for your specific use case. For this example, we will create a custom chain that concatenates the outputs of 2 `LLMChain`s.\n", "\n", "In order to create a custom chain:\n", "1. Start by subclassing the `Chain` class,\n",