doc_fix_chroma_integration (#26565)

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- [x] **PR title**: "package: description"
docs:integrations:vectorstores:chroma:fix_typo


- [x] **PR message**: ***Delete this entire checklist*** and replace
with


- **Description:** fix_typo in docs:integrations:vectorstores:chroma
https://python.langchain.com/docs/integrations/vectorstores/chroma/
    - **Issue:** https://github.com/langchain-ai/langchain/issues/26561

- [ ] **Add tests and docs**: If you're adding a new integration, please
include
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in
`docs/docs/integrations` directory.


- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/

Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.

If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.
This commit is contained in:
venkatram-dev 2024-09-17 05:17:54 -07:00 committed by GitHub
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commit 6ba3c715b7
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@ -99,7 +99,7 @@
"vector_store = Chroma(\n", "vector_store = Chroma(\n",
" collection_name=\"example_collection\",\n", " collection_name=\"example_collection\",\n",
" embedding_function=embeddings,\n", " embedding_function=embeddings,\n",
" persist_directory=\"./chroma_langchain_db\", # Where to save data locally, remove if not neccesary\n", " persist_directory=\"./chroma_langchain_db\", # Where to save data locally, remove if not necessary\n",
")" ")"
] ]
}, },
@ -179,7 +179,7 @@
"from langchain_core.documents import Document\n", "from langchain_core.documents import Document\n",
"\n", "\n",
"document_1 = Document(\n", "document_1 = Document(\n",
" page_content=\"I had chocalate chip pancakes and scrambled eggs for breakfast this morning.\",\n", " page_content=\"I had chocolate chip pancakes and scrambled eggs for breakfast this morning.\",\n",
" metadata={\"source\": \"tweet\"},\n", " metadata={\"source\": \"tweet\"},\n",
" id=1,\n", " id=1,\n",
")\n", ")\n",
@ -273,7 +273,7 @@
"outputs": [], "outputs": [],
"source": [ "source": [
"updated_document_1 = Document(\n", "updated_document_1 = Document(\n",
" page_content=\"I had chocalate chip pancakes and fried eggs for breakfast this morning.\",\n", " page_content=\"I had chocolate chip pancakes and fried eggs for breakfast this morning.\",\n",
" metadata={\"source\": \"tweet\"},\n", " metadata={\"source\": \"tweet\"},\n",
" id=1,\n", " id=1,\n",
")\n", ")\n",
@ -287,7 +287,7 @@
"vector_store.update_document(document_id=uuids[0], document=updated_document_1)\n", "vector_store.update_document(document_id=uuids[0], document=updated_document_1)\n",
"# You can also update multiple documents at once\n", "# You can also update multiple documents at once\n",
"vector_store.update_documents(\n", "vector_store.update_documents(\n",
" ids=uuids[:2], documents=[updated_document_1, updated_document_1]\n", " ids=uuids[:2], documents=[updated_document_1, updated_document_2]\n",
")" ")"
] ]
}, },