(WIP) agents (#171)

docs/explanation/agents.md

@@ -0,0 +1,28 @@
+# Agents
+
+Agents use an LLM to determine which tools to call and in what order.
+Here are the supported types of agents available in LangChain.
+
+For a tutorial on how to load agents, see [here](/getting_started/agents.ipynb).
+
+### `zero-shot-react-description`
+
+This agent uses the ReAct framework to determine which tool to use
+based solely on the tool's description. Any number of tools can be provided.
+This agent requires that a description is provided for each tool.
+
+### `react-docstore`
+
+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
+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.
+
+### `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
+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.

docs/explanation/core_concepts.md

@@ -25,3 +25,7 @@ These are datastores that store documents. They expose a method for passing in a
 ## Chains
 These are pipelines that combine multiple of the above ideas. 
 They vary greatly in complexity and are combination of generic, highly configurable pipelines and more narrow (but usually more complex) pipelines.
+
+## Agents
+As opposed to a chain, whether the steps to be taken are known ahead of time, agents
+use an LLM to determine which tools to call and in what order.

docs/explanation/glossary.md

@@ -29,7 +29,7 @@ This induces the to model to think about what action to take, then take it.
 
 Resources:
 - [Paper](https://arxiv.org/pdf/2210.03629.pdf)
-- [LangChain Example](https://github.com/hwchase17/langchain/blob/master/examples/react.ipynb)
+- [LangChain Example](https://github.com/hwchase17/langchain/blob/master/docs/examples/agents/react.ipynb)
 
 ### Self-ask
 
@@ -38,7 +38,7 @@ In this method, the model explicitly asks itself follow-up questions, which are
 
 Resources:
 - [Paper](https://ofir.io/self-ask.pdf)
-- [LangChain Example](https://github.com/hwchase17/langchain/blob/master/examples/self_ask_with_search.ipynb)
+- [LangChain Example](https://github.com/hwchase17/langchain/blob/master/docs/examples/agents/self_ask_with_search.ipynb)
 
 ### Prompt Chaining