add docs for chroma persistance (langchain-ai#1202)

Author: hwchase17

docs/modules/indexes/vectorstore_examples/chroma.ipynb

@@ -12,7 +12,7 @@
  },
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+ "execution_count": 1,
  "id": "aac9563e",
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@@ -25,7 +25,7 @@
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@@ -41,7 +41,7 @@
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@@ -63,7 +63,7 @@
  },
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@@ -89,10 +89,115 @@
  "print(docs[0].page_content)"
  ]
  },
+ {
+ "cell_type": "markdown",
+ "id": "8061454b",
+ "metadata": {},
+ "source": [
+ "## Persistance\n",
+ "\n",
+ "The below steps cover how to persist a ChromaDB instance"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "2b76db26",
+ "metadata": {},
+ "source": [
+ "### Initialize PeristedChromaDB\n",
+ "Create embeddings for each chunk and insert into the Chroma vector database. The persist_directory argument tells ChromaDB where to store the database when it's persisted.\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "cdb86e0d",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Running Chroma using direct local API.\n",
+ "No existing DB found in db, skipping load\n",
+ "No existing DB found in db, skipping load\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Embed and store the texts\n",
+ "# Supplying a persist_directory will store the embeddings on disk\n",
+ "persist_directory = 'db'\n",
+ "\n",
+ "embedding = OpenAIEmbeddings()\n",
+ "vectordb = Chroma.from_documents(documents=docs, embedding=embedding, persist_directory=persist_directory)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "f568a322",
+ "metadata": {},
+ "source": [
+ "### Persist the Database\n",
+ "In a notebook, we should call persist() to ensure the embeddings are written to disk. This isn't necessary in a script - the database will be automatically persisted when the client object is destroyed."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "id": "74b08cb4",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Persisting DB to disk, putting it in the save folder db\n",
+ "PersistentDuckDB del, about to run persist\n",
+ "Persisting DB to disk, putting it in the save folder db\n"
+ ]
+ }
+ ],
+ "source": [
+ "vectordb.persist()\n",
+ "vectordb = None"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "cc9ed900",
+ "metadata": {},
+ "source": [
+ "### Load the Database from disk, and create the chain\n",
+ "Be sure to pass the same persist_directory and embedding_function as you did when you instantiated the database. Initialize the chain we will use for question answering."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "id": "31fecfe9",
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Running Chroma using direct local API.\n",
+ "loaded in 4 embeddings\n",
+ "loaded in 1 collections\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Now we can load the persisted database from disk, and use it as normal. \n",
+ "vectordb = Chroma(persist_directory=persist_directory, embedding_function=embedding)\n"
+ ]
+ },
  {
  "cell_type": "code",
  "execution_count": null,
- "id": "a359ed74",
+ "id": "4dde7a0d",
  "metadata": {},
  "outputs": [],
  "source": []