community[patch]: Update JSDoc on Chroma vectorstore (#6509)

* partners[minor]: Update JSDocs on vectorstores

* update examples

Author: bracesproul

libs/langchain-community/src/vectorstores/chroma.ts

@@ -46,9 +46,137 @@ export interface ChromaDeleteParams<T> {
 }
 
 /**
- * The main class that extends the `VectorStore` class. It provides
- * methods for interacting with the Chroma database, such as adding
- * documents, deleting documents, and searching for similar vectors.
+ * Chroma vector store integration.
+ *
+ * Setup:
+ * Install `@langchain/community` and `chromadb`, then clone the official `ChromaDB` repository.
+ *
+ * ```bash
+ * npm install @langchain/community chromadb
+ * ```
+ *
+ * ```bash
+ * git clone https://github.com/chroma-core/chroma.git
+ * ```
+ *
+ * Next, navigate into the `chroma` directory and start the docker container:
+ *
+ * ```bash
+ * cd ./chroma
+ *
+ * docker compose up
+ * ```
+ *
+ * ## [Constructor args](https://api.js.langchain.com/classes/langchain_community_vectorstores_chroma.Chroma.html#constructor)
+ *
+ * <details open>
+ * <summary><strong>Instantiate</strong></summary>
+ *
+ * ```typescript
+ * import { Chroma } from '@langchain/community/vectorstores/chroma';
+ * import { OpenAIEmbeddings } from '@langchain/openai';
+ *
+ * const vectorStore = new Chroma(
+ *   new OpenAIEmbeddings(),
+ *   {
+ *     collectionName: "foo",
+ *     url: "http://localhost:8000", // URL of the Chroma server
+ *   }
+ * );
+ * ```
+ * </details>
+ *
+ * <br />
+ *
+ * <details>
+ * <summary><strong>Add documents</strong></summary>
+ *
+ * ```typescript
+ * import { Document } from '@langchain/core/documents';
+ *
+ * const document1 = new Document({ pageContent: "foo", metadata: { baz: "bar" } });
+ * const document2 = new Document({ pageContent: "thud", metadata: { bar: "baz" } });
+ * const document3 = new Document({ pageContent: "i will be deleted :(" });
+ *
+ * const documents = [document1, document2, document3];
+ * const ids = ["1", "2", "3"];
+ * await vectorStore.addDocuments(documents, { ids });
+ * ```
+ * </details>
+ *
+ * <br />
+ *
+ * <details>
+ * <summary><strong>Delete documents</strong></summary>
+ *
+ * ```typescript
+ * await vectorStore.delete({ ids: ["3"] });
+ * ```
+ * </details>
+ *
+ * <br />
+ *
+ * <details>
+ * <summary><strong>Similarity search</strong></summary>
+ *
+ * ```typescript
+ * const results = await vectorStore.similaritySearch("thud", 1);
+ * for (const doc of results) {
+ *   console.log(`* ${doc.pageContent} [${JSON.stringify(doc.metadata, null)}]`);
+ * }
+ * // Output: * thud [{"baz":"bar"}]
+ * ```
+ * </details>
+ *
+ * <br />
+ *
+ *
+ * <details>
+ * <summary><strong>Similarity search with filter</strong></summary>
+ *
+ * ```typescript
+ * const resultsWithFilter = await vectorStore.similaritySearch("thud", 1, { baz: "bar" });
+ *
+ * for (const doc of resultsWithFilter) {
+ *   console.log(`* ${doc.pageContent} [${JSON.stringify(doc.metadata, null)}]`);
+ * }
+ * // Output: * foo [{"baz":"bar"}]
+ * ```
+ * </details>
+ *
+ * <br />
+ *
+ *
+ * <details>
+ * <summary><strong>Similarity search with score</strong></summary>
+ *
+ * ```typescript
+ * const resultsWithScore = await vectorStore.similaritySearchWithScore("qux", 1);
+ * for (const [doc, score] of resultsWithScore) {
+ *   console.log(`* [SIM=${score.toFixed(6)}] ${doc.pageContent} [${JSON.stringify(doc.metadata, null)}]`);
+ * }
+ * // Output: * [SIM=0.000000] qux [{"bar":"baz","baz":"bar"}]
+ * ```
+ * </details>
+ *
+ * <br />
+ *
+ * <details>
+ * <summary><strong>As a retriever</strong></summary>
+ *
+ * ```typescript
+ * const retriever = vectorStore.asRetriever({
+ *   searchType: "mmr",
+ *   k: 1,
+ * });
+ * const resultAsRetriever = await retriever.invoke("thud");
+ * console.log(resultAsRetriever);
+ *
+ * // Output: [Document({ metadata: { "baz":"bar" }, pageContent: "thud" })]
+ * ```
+ * </details>
+ *
+ * <br />
  */
 export class Chroma extends VectorStore {
   declare FilterType: Where;