[AUTO-GENERATED] Add JSDoc examples to classes. (langchain-ai#3330)

* [AUTO-GENERATED] Add JSDoc examples to classes.

* cr

langchain/src/agents/toolkits/json/json.ts

@@ -14,6 +14,14 @@ import { AgentExecutor } from "../../executor.js";
 /**
  * Represents a toolkit for working with JSON data. It initializes the
  * JSON tools based on the provided JSON specification.
+ * @example
+ * ```typescript
+ * const toolkit = new JsonToolkit(new JsonSpec());
+ * const executor = createJsonAgent(model, toolkit);
+ * const result = await executor.invoke({
+ *   input: 'What are the required parameters in the request body to the /completions endpoint?'
+ * });
+ * ```
  */
 export class JsonToolkit extends Toolkit {
   tools: Tool[];

langchain/src/agents/toolkits/openapi/openapi.ts

@@ -36,6 +36,24 @@ export class RequestsToolkit extends Toolkit {
  * exploring JSON data. It creates a JSON agent using the `JsonToolkit`
  * and the provided language model, and adds the JSON explorer tool to the
  * toolkit.
+ * @example
+ * ```typescript
+ * const toolkit = new OpenApiToolkit(
+ *   new JsonSpec({
+ *   }),
+ *   new ChatOpenAI({ temperature: 0 }),
+ *   {
+ *     "Content-Type": "application/json",
+ *     Authorization: `Bearer ${process.env.OPENAI_API_KEY}`,
+ *   },
+ * );
+ *
+ * const result = await toolkit.invoke({
+ *   input:
+ *     "Make a POST request to openai /completions. The prompt should be 'tell me a joke.'",
+ * });
+ * console.log(`Got output ${result.output}`);
+ * ```
  */
 export class OpenApiToolkit extends RequestsToolkit {
   constructor(jsonSpec: JsonSpec, llm: BaseLanguageModel, headers?: Headers) {

langchain/src/agents/toolkits/sql/sql.ts

@@ -26,6 +26,14 @@ export interface SqlCreatePromptArgs extends ZeroShotCreatePromptArgs {
 /**
  * Class that represents a toolkit for working with SQL databases. It
  * initializes SQL tools based on the provided SQL database.
+ * @example
+ * ```typescript
+ * const model = new ChatOpenAI({});
+ * const toolkit = new SqlToolkit(sqlDb, model);
+ * const executor = createSqlAgent(model, toolkit);
+ * const result = await executor.invoke({ input: 'List the total sales per country. Which country's customers spent the most?' });
+ * console.log(`Got output ${result.output}`);
+ * ```
  */
 export class SqlToolkit extends Toolkit {
   tools: Tool[];

langchain/src/agents/toolkits/vectorstore/vectorstore.ts

@@ -23,6 +23,22 @@ export interface VectorStoreInfo {
  * Class representing a toolkit for working with a single vector store. It
  * initializes the vector store QA tool based on the provided vector store
  * information and language model.
+ * @example
+ * ```typescript
+ * const toolkit = new VectorStoreToolkit(
+ *   {
+ *     name: "state_of_union_address",
+ *     description: "the most recent state of the Union address",
+ *     vectorStore: new HNSWLib(),
+ *   },
+ *   new ChatOpenAI({ temperature: 0 }),
+ * );
+ * const result = await toolkit.invoke({
+ *   input:
+ *     "What did biden say about Ketanji Brown Jackson in the state of the union address?",
+ * });
+ * console.log(`Got output ${result.output}`);
+ * ```
  */
 export class VectorStoreToolkit extends Toolkit {
   tools: Tool[];

langchain/src/agents/toolkits/zapier/zapier.ts

@@ -5,6 +5,16 @@ import { ZapierNLARunAction, ZapierNLAWrapper } from "../../../tools/zapier.js";
 /**
  * Represents a toolkit for working with Zapier actions. It extends the
  * Toolkit class and provides functionality for managing Zapier tools.
+ * @example
+ * ```typescript
+ * const toolkit = await ZapierToolKit.fromZapierNLAWrapper(
+ *   new ZapierNLAWrapper(),
+ * );
+ * const result = await toolkit.invoke({
+ *   input:
+ *     "Summarize the last email I received regarding Silicon Valley Bank. Send the summary to the #test-zapier Slack channel.",
+ * });
+ * ```
  */
 export class ZapierToolKit extends Toolkit {
   tools: Tool[] = [];

langchain/src/retrievers/self_query/pinecone.ts

@@ -8,6 +8,20 @@ import { BasicTranslator } from "./base.js";
  * LangChain. The class is initialized with a set of allowed operators and
  * comparators, which are used in the translation process to construct
  * queries and compare results.
+ * @example
+ * ```typescript
+ * const selfQueryRetriever = await SelfQueryRetriever.fromLLM({
+ *   llm: new ChatOpenAI(),
+ *   vectorStore: new PineconeStore(),
+ *   documentContents: "Brief summary of a movie",
+ *   attributeInfo: [],
+ *   structuredQueryTranslator: new PineconeTranslator(),
+ * });
+ *
+ * const queryResult = await selfQueryRetriever.getRelevantDocuments(
+ *   "Which movies are directed by Greta Gerwig?",
+ * );
+ * ```
  */
 export class PineconeTranslator<
   T extends PineconeStore

langchain/src/retrievers/self_query/supabase.ts

@@ -36,6 +36,20 @@ type ValueType = {
  * A specialized translator designed to work with Supabase, extending the
  * BaseTranslator class. It translates structured queries into a format
  * that can be understood by the Supabase database.
+ * @example
+ * ```typescript
+ * const selfQueryRetriever = new SelfQueryRetriever({
+ *   llm: new ChatOpenAI(),
+ *   vectorStore: new SupabaseVectorStore(),
+ *   documentContents: "Brief summary of a movie",
+ *   attributeInfo: [],
+ *   structuredQueryTranslator: new SupabaseTranslator(),
+ * });
+ *
+ * const queryResult = await selfQueryRetriever.getRelevantDocuments(
+ *   "Which movies are directed by Greta Gerwig?",
+ * );
+ * ```
  */
 export class SupabaseTranslator<
   T extends SupabaseVectorStore

langchain/src/retrievers/self_query/weaviate.ts

@@ -54,6 +54,20 @@ export type WeaviateStructuredQueryResult = {
  * A class that translates or converts data into a format that can be used
  * with Weaviate, a vector search engine. It extends the `BaseTranslator`
  * class and provides specific implementation for Weaviate.
+ * @example
+ * ```typescript
+ * const selfQueryRetriever = new SelfQueryRetriever({
+ *   llm: new ChatOpenAI(),
+ *   vectorStore: new WeaviateStore(),
+ *   documentContents: "Brief summary of a movie",
+ *   attributeInfo: [],
+ *   structuredQueryTranslator: new WeaviateTranslator(),
+ * });
+ *
+ * const relevantDocuments = await selfQueryRetriever.getRelevantDocuments(
+ *   "Which movies are rated higher than 8.5?",
+ * );
+ * ```
  */
 export class WeaviateTranslator<
   T extends WeaviateStore

langchain/src/schema/runnable/base.ts

@@ -966,6 +966,14 @@ export class RunnableRetry<
 
 /**
  * A sequence of runnables, where the output of each is the input of the next.
+ * @example
+ * ```typescript
+ * const promptTemplate = PromptTemplate.fromTemplate(
+ *   "Tell me a joke about {topic}",
+ * );
+ * const chain = RunnableSequence.from([promptTemplate, new ChatOpenAI({})]);
+ * const result = await chain.invoke({ topic: "bears" });
+ * ```
  */
 export class RunnableSequence<
   // eslint-disable-next-line @typescript-eslint/no-explicit-any
@@ -1260,6 +1268,18 @@ export class RunnableSequence<
 /**
  * A runnable that runs a mapping of runnables in parallel,
  * and returns a mapping of their outputs.
+ * @example
+ * ```typescript
+ * const mapChain = RunnableMap.from({
+ *   joke: PromptTemplate.fromTemplate("Tell me a joke about {topic}").pipe(
+ *     new ChatAnthropic({}),
+ *   ),
+ *   poem: PromptTemplate.fromTemplate("write a 2-line poem about {topic}").pipe(
+ *     new ChatAnthropic({}),
+ *   ),
+ * });
+ * const result = await mapChain.invoke({ topic: "bear" });
+ * ```
  */
 export class RunnableMap<RunInput> extends Runnable<
   RunInput,

langchain/src/schema/runnable/branch.ts

@@ -24,6 +24,34 @@ export type BranchLike<RunInput, RunOutput> = [
  * it evaluates the condition of each branch in order and executes the
  * corresponding branch if the condition is true. If none of the conditions
  * are true, it executes the default branch.
+ * @example
+ * ```typescript
+ * const branch = RunnableBranch.from([
+ *   [
+ *     (x: { topic: string; question: string }) =>
+ *       x.topic.toLowerCase().includes("anthropic"),
+ *     anthropicChain,
+ *   ],
+ *   [
+ *     (x: { topic: string; question: string }) =>
+ *       x.topic.toLowerCase().includes("langchain"),
+ *     langChainChain,
+ *   ],
+ *   generalChain,
+ * ]);
+ *
+ * const fullChain = RunnableSequence.from([
+ *   {
+ *     topic: classificationChain,
+ *     question: (input: { question: string }) => input.question,
+ *   },
+ *   branch,
+ * ]);
+ *
+ * const result = await fullChain.invoke({
+ *   question: "how do I use LangChain?",
+ * });
+ * ```
  */
 // eslint-disable-next-line @typescript-eslint/no-explicit-any
 export class RunnableBranch<RunInput = any, RunOutput = any> extends Runnable<

langchain/src/stores/message/cassandra.ts

@@ -19,6 +19,31 @@ export interface CassandraChatMessageHistoryOptions extends DseClientOptions {
  * Class for storing chat message history within Cassandra. It extends the
  * BaseListChatMessageHistory class and provides methods to get, add, and
  * clear messages.
+ * @example
+ * ```typescript
+ * const chatHistory = new CassandraChatMessageHistory({
+ *   cloud: {
+ *     secureConnectBundle: "<path to your secure bundle>",
+ *   },
+ *   credentials: {
+ *     username: "token",
+ *     password: "<your Cassandra access token>",
+ *   },
+ *   keyspace: "langchain",
+ *   table: "message_history",
+ *   sessionId: "<some unique session identifier>",
+ * });
+ *
+ * const chain = new ConversationChain({
+ *   llm: new ChatOpenAI(),
+ *   memory: chatHistory,
+ * });
+ *
+ * const response = await chain.invoke({
+ *   input: "What did I just say my name was?",
+ * });
+ * console.log({ response });
+ * ```
  */
 export class CassandraChatMessageHistory extends BaseListChatMessageHistory {
   lc_namespace = ["langchain", "stores", "message", "cassandra"];

langchain/src/stores/message/cloudflare_d1.ts

@@ -39,6 +39,24 @@ interface selectStoredMessagesDTO {
 /**
  * Class for storing and retrieving chat message history from a
  * Cloudflare D1 database. Extends the BaseListChatMessageHistory class.
+ * @example
+ * ```typescript
+ * const memory = new BufferMemory({
+ *   returnMessages: true,
+ *   chatHistory: new CloudflareD1MessageHistory({
+ *     tableName: "stored_message",
+ *     sessionId: "example",
+ *     database: env.DB,
+ *   }),
+ * });
+ *
+ * const chainInput = { input };
+ *
+ * const res = await memory.chatHistory.invoke(chainInput);
+ * await memory.saveContext(chainInput, {
+ *   output: res,
+ * });
+ * ```
  */
 export class CloudflareD1MessageHistory extends BaseListChatMessageHistory {
   lc_namespace = ["langchain", "stores", "message", "cloudflare_d1"];

langchain/src/stores/message/firestore.ts

@@ -33,6 +33,25 @@ export interface FirestoreDBChatMessageHistory {
 /**
  * Class for managing chat message history using Google's Firestore as a
  * storage backend. Extends the BaseListChatMessageHistory class.
+ * @example
+ * ```typescript
+ * const chatHistory = new FirestoreChatMessageHistory({
+ *   collectionName: "langchain",
+ *   sessionId: "lc-example",
+ *   userId: "a@example.com",
+ *   config: { projectId: "your-project-id" },
+ * });
+ *
+ * const chain = new ConversationChain({
+ *   llm: new ChatOpenAI(),
+ *   memory: new BufferMemory({ chatHistory }),
+ * });
+ *
+ * const response = await chain.invoke({
+ *   input: "What did I just say my name was?",
+ * });
+ * console.log({ response });
+ * ```
  */
 export class FirestoreChatMessageHistory extends BaseListChatMessageHistory {
   lc_namespace = ["langchain", "stores", "message", "firestore"];

langchain/src/stores/message/ioredis.ts

@@ -21,6 +21,24 @@ export type RedisChatMessageHistoryInput = {
 /**
  * Class used to store chat message history in Redis. It provides methods
  * to add, retrieve, and clear messages from the chat history.
+ * @example
+ * ```typescript
+ * const chatHistory = new RedisChatMessageHistory({
+ *   sessionId: new Date().toISOString(),
+ *   sessionTTL: 300,
+ *   url: "redis:
+ * });
+ *
+ * const chain = new ConversationChain({
+ *   llm: new ChatOpenAI({ temperature: 0 }),
+ *   memory: { chatHistory },
+ * });
+ *
+ * const response = await chain.invoke({
+ *   input: "What did I just say my name was?",
+ * });
+ * console.log({ response });
+ * ```
  */
 export class RedisChatMessageHistory extends BaseListChatMessageHistory {
   lc_namespace = ["langchain", "stores", "message", "ioredis"];

langchain/src/stores/message/momento.ts

@@ -51,6 +51,24 @@ export interface MomentoChatMessageHistoryProps {
  * A class that stores chat message history using Momento Cache. It
  * interacts with a Momento cache client to perform operations like
  * fetching, adding, and deleting messages.
+ * @example
+ * ```typescript
+ * const chatHistory = await MomentoChatMessageHistory.fromProps({
+ *   client: new CacheClient({
+ *     configuration: Configurations.Laptop.v1(),
+ *     credentialProvider: CredentialProvider.fromEnvironmentVariable({
+ *       environmentVariableName: "MOMENTO_API_KEY",
+ *     }),
+ *     defaultTtlSeconds: 60 * 60 * 24,
+ *   }),
+ *   cacheName: "langchain",
+ *   sessionId: new Date().toISOString(),
+ *   sessionTtl: 300,
+ * });
+ *
+ * const messages = await chatHistory.getMessages();
+ * console.log({ messages });
+ * ```
  */
 export class MomentoChatMessageHistory extends BaseListChatMessageHistory {
   lc_namespace = ["langchain", "stores", "message", "momento"];

langchain/src/stores/message/mongodb.ts

@@ -10,6 +10,17 @@ export interface MongoDBChatMessageHistoryInput {
   sessionId: string;
 }
 
+/**
+ * @example
+ * ```typescript
+ * const chatHistory = new MongoDBChatMessageHistory({
+ *   collection: myCollection,
+ *   sessionId: 'unique-session-id',
+ * });
+ * const messages = await chatHistory.getMessages();
+ * await chatHistory.clear();
+ * ```
+ */
 export class MongoDBChatMessageHistory extends BaseListChatMessageHistory {
   lc_namespace = ["langchain", "stores", "message", "mongodb"];