Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Don't need to install milvus if running on cloud; Don't need schema i… #1225

Merged
merged 1 commit into from
Dec 18, 2023
Merged

Don't need to install milvus if running on cloud; Don't need schema i… #1225

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion bootcamp/RAG/readthedocs_zilliz_langchain.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -206,7 +206,7 @@
"## Create a Milvus collection\n",
"\n",
"You can think of a collection in Milvus like a \"table\" in SQL databases. The **collection** will contain the \n",
"- **Schema** (or no-schema Milvus Client). \n",
"- **Schema** (or [no-schema Milvus client](https://milvus.io/docs/using_milvusclient.md)). \n",
"💡 You'll need the vector `EMBEDDING_LENGTH` parameter from your embedding model.\n",
"Typical values are:\n",
" - 768 for sbert embedding models\n",
Expand Down
8 changes: 2 additions & 6 deletions bootcamp/Retrieval/imdb_milvus_client.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -24,7 +24,7 @@
"outputs": [],
"source": [
"# For colab install these libraries in this order:\n",
"# !pip install milvus, pymilvus, langchain, torch, transformers, python-dotenv\n",
"# !pip install pymilvus, langchain, torch, transformers, python-dotenv\n",
"\n",
"# Import common libraries.\n",
"import time\n",
Expand Down Expand Up @@ -175,11 +175,7 @@
"- **Vector index** for efficient vector search\n",
"- **Vector distance metric** for measuring nearest neighbor vectors\n",
"- **Consistency level**\n",
"In Milvus, transactional consistency is possible; however, according to the [CAP theorem](https://en.wikipedia.org/wiki/CAP_theorem), some latency must be sacrificed. 💡 Searching movie reviews is not mission-critical, so [`eventually`](https://milvus.io/docs/consistency.md) consistent is fine here.\n",
"\n",
"Some supported [data types](https://milvus.io/docs/schema.md) for Milvus schemas are:\n",
"- INT64 - primary key\n",
"- FLOAT_VECTOR - embedings = list of `numpy.ndarray` of `numpy.float32` numbers\n"
"In Milvus, transactional consistency is possible; however, according to the [CAP theorem](https://en.wikipedia.org/wiki/CAP_theorem), some latency must be sacrificed. 💡 Searching movie reviews is not mission-critical, so [`eventually`](https://milvus.io/docs/consistency.md) consistent is fine here.\n"
]
},
{
Expand Down