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# docs: modules pages simplified Fixied #5627 issue Merged several repetitive sections in the `modules` pages. Some texts, that were hard to understand, were also simplified. ## Who can review? @hwchase17 @dev2049
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4.7 KiB
ReStructuredText
106 lines
4.7 KiB
ReStructuredText
Agents
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==========================
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.. note::
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`Conceptual Guide <https://docs.langchain.com/docs/components/agents>`_
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Some applications require not just a predetermined chain of calls to LLMs/other tools,
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but potentially an unknown chain that depends on the user's input.
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In these types of chains, there is an **agent** which has access to a suite of **tools**.
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Depending on the user input, the agent can then decide which, if any, of these tools to call.
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At the moment, there are two main types of agents:
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1. **Action Agents**: these agents decide the actions to take and execute that actions one action at a time.
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2. **Plan-and-Execute Agents**: these agents first decide a plan of actions to take, and then execute those actions one at a time.
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When should you use each one? Action Agents are more conventional, and good for small tasks.
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For more complex or long running tasks, the initial planning step helps to maintain long term objectives and focus.
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However, that comes at the expense of generally more calls and higher latency.
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These two agents are also not mutually exclusive - in fact, it is often best to have an Action Agent be in charge
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of the execution for the Plan and Execute agent.
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Action Agents
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-------------
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High level pseudocode of the Action Agents:
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- The **user input** is received
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- The **agent** decides which **tool** - if any - to use, and what the **tool input** should be
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- That **tool** is then called with the **tool input**, and an **observation** is recorded (the output of this calling)
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- That history of **tool**, **tool input**, and **observation** is passed back into the **agent**, and it decides the next step
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- This is repeated until the **agent** decides it no longer needs to use a **tool**, and then it responds directly to the user.
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The different abstractions involved in agents are:
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- **Agent**: this is where the logic of the application lives. Agents expose an interface that takes in user input
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along with a list of previous steps the agent has taken, and returns either an **AgentAction** or **AgentFinish**
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- **AgentAction** corresponds to the tool to use and the input to that tool
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- **AgentFinish** means the agent is done, and has information around what to return to the user
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- **Tools**: these are the actions an agent can take. What tools you give an agent highly depend on what you want the agent to do
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- **Toolkits**: these are groups of tools designed for a specific use case. For example, in order for an agent to
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interact with a SQL database in the best way it may need access to one tool to execute queries and another tool to inspect tables.
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- **Agent Executor**: this wraps an agent and a list of tools. This is responsible for the loop of running the agent
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iteratively until the stopping criteria is met.
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- `Getting Started <./agents/getting_started.html>`_: An overview of agents. It covers how to use all things related to agents in an end-to-end manner.
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**Agent Construction:**
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Although an agent can be constructed in many way, the typical way to construct an agent is with:
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- **PromptTemplate**: this is responsible for taking the user input and previous steps and constructing a prompt
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to send to the language model
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- **Language Model**: this takes the prompt constructed by the PromptTemplate and returns some output
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- **Output Parser**: this takes the output of the Language Model and parses it into an **AgentAction** or **AgentFinish** object.
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**Additional Documentation:**
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- `Tools <./agents/tools.html>`_: Different types of **tools** LangChain supports natively. We also cover how to add your own tools.
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- `Agents <./agents/agents.html>`_: Different types of **agents** LangChain supports natively. We also cover how to
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modify and create your own agents.
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- `Toolkits <./agents/toolkits.html>`_: Various **toolkits** that LangChain supports out of the box, and how to
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create an agent from them.
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- `Agent Executor <./agents/agent_executors.html>`_: The **Agent Executor** class, which is responsible for calling
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the agent and tools in a loop. We go over different ways to customize this, and options you can use for more control.
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Plan-and-Execute Agents
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-----------------------
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High level pseudocode of the **Plan-and-Execute Agents**:
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- The **user input** is received
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- The **planner** lists out the steps to take
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- The **executor** goes through the list of steps, executing them
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The most typical implementation is to have the planner be a language model, and the executor be an action agent.
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- `Plan-and-Execute Agents <./agents/plan_and_execute.html>`_
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.. toctree::
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:maxdepth: 1
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:hidden:
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./agents/getting_started.ipynb
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./agents/tools.rst
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./agents/agents.rst
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./agents/toolkits.rst
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./agents/agent_executors.rst
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./agents/plan_and_execute.ipynb
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