Astra DB: minor improvements to docstrings and demo notebook (#13449)

This PR brings a few minor improvements to the docs, namely class/method
docstrings and the demo notebook.

- A note on how to control concurrency levels to tune performance in
bulk inserts, both in the class docstring and the demo notebook;
- Slightly increased concurrency defaults after careful experimentation
(still on the conservative side even for clients running on
less-than-typical network/hardware specs)
- renamed the DB token variable to the standardized
`ASTRA_DB_APPLICATION_TOKEN` name (used elsewhere, e.g. in the Astra DB
docs)
- added a note and a reference (add_text docstring, demo notebook) on
allowed metadata field names.

Thank you!
pull/13480/head
Stefano Lottini 9 months ago committed by GitHub
parent 1e43fd6afe
commit b029d9f4e6
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@ -44,7 +44,7 @@
"metadata": {},
"source": [
"_Note: depending on your LangChain setup, you may need to install/upgrade other dependencies needed for this demo_\n",
"_(specifically, recent versions of `datasets` `openai` `pypdf` and `tiktoken` are required)._"
"_(specifically, recent versions of `datasets`, `openai`, `pypdf` and `tiktoken` are required)._"
]
},
{
@ -65,7 +65,6 @@
"from langchain.embeddings import OpenAIEmbeddings\n",
"from langchain.prompts import ChatPromptTemplate\n",
"\n",
"# if not present yet, run: pip install \"datasets==2.14.6\"\n",
"from langchain.schema import Document\n",
"from langchain.schema.output_parser import StrOutputParser\n",
"from langchain.schema.runnable import RunnablePassthrough\n",
@ -145,7 +144,7 @@
"outputs": [],
"source": [
"ASTRA_DB_API_ENDPOINT = input(\"ASTRA_DB_API_ENDPOINT = \")\n",
"ASTRA_DB_TOKEN = getpass(\"ASTRA_DB_TOKEN = \")"
"ASTRA_DB_APPLICATION_TOKEN = getpass(\"ASTRA_DB_APPLICATION_TOKEN = \")"
]
},
{
@ -159,7 +158,7 @@
" embedding=embe,\n",
" collection_name=\"astra_vector_demo\",\n",
" api_endpoint=ASTRA_DB_API_ENDPOINT,\n",
" token=ASTRA_DB_TOKEN,\n",
" token=ASTRA_DB_APPLICATION_TOKEN,\n",
")"
]
},
@ -171,6 +170,14 @@
"### Load a dataset"
]
},
{
"cell_type": "markdown",
"id": "552e56b0-301a-4b06-99c7-57ba6faa966f",
"metadata": {},
"source": [
"Convert each entry in the source dataset into a `Document`, then write them into the vector store:"
]
},
{
"cell_type": "code",
"execution_count": null,
@ -190,6 +197,16 @@
"print(f\"\\nInserted {len(inserted_ids)} documents.\")"
]
},
{
"cell_type": "markdown",
"id": "79d4f436-ef04-4288-8f79-97c9abb983ed",
"metadata": {},
"source": [
"In the above, `metadata` dictionaries are created from the source data and are part of the `Document`.\n",
"\n",
"_Note: check the [Astra DB API Docs](https://docs.datastax.com/en/astra-serverless/docs/develop/dev-with-json.html#_json_api_limits) for the valid metadata field names: some characters are reserved and cannot be used._"
]
},
{
"cell_type": "markdown",
"id": "084d8802-ab39-4262-9a87-42eafb746f92",
@ -213,6 +230,16 @@
"print(f\"\\nInserted {len(inserted_ids_2)} documents.\")"
]
},
{
"cell_type": "markdown",
"id": "63840eb3-8b29-4017-bc2f-301bf5001f28",
"metadata": {},
"source": [
"_Note: you may want to speed up the execution of `add_texts` and `add_documents` by increasing the concurrency level for_\n",
"_these bulk operations - check out the `*_concurrency` parameters in the class constructor and the `add_texts` docstrings_\n",
"_for more details. Depending on the network and the client machine specifications, your best-performing choice of parameters may vary._"
]
},
{
"cell_type": "markdown",
"id": "c031760a-1fc5-4855-adf2-02ed52fe2181",
@ -625,7 +652,7 @@
"outputs": [],
"source": [
"ASTRA_DB_ID = input(\"ASTRA_DB_ID = \")\n",
"ASTRA_DB_TOKEN = getpass(\"ASTRA_DB_TOKEN = \")\n",
"ASTRA_DB_APPLICATION_TOKEN = getpass(\"ASTRA_DB_APPLICATION_TOKEN = \")\n",
"\n",
"desired_keyspace = input(\"ASTRA_DB_KEYSPACE (optional, can be left empty) = \")\n",
"if desired_keyspace:\n",
@ -645,7 +672,7 @@
"\n",
"cassio.init(\n",
" database_id=ASTRA_DB_ID,\n",
" token=ASTRA_DB_TOKEN,\n",
" token=ASTRA_DB_APPLICATION_TOKEN,\n",
" keyspace=ASTRA_DB_KEYSPACE,\n",
")"
]

@ -34,7 +34,7 @@ DocDict = Dict[str, Any] # dicts expressing entries to insert
# (20 is the max batch size for the HTTP API at the time of writing)
DEFAULT_BATCH_SIZE = 20
# Number of threads to insert batches concurrently:
DEFAULT_BULK_INSERT_BATCH_CONCURRENCY = 5
DEFAULT_BULK_INSERT_BATCH_CONCURRENCY = 16
# Number of threads in a batch to insert pre-existing entries:
DEFAULT_BULK_INSERT_OVERWRITE_CONCURRENCY = 10
# Number of threads (for deleting multiple rows concurrently):
@ -139,6 +139,20 @@ class AstraDB(VectorStore):
threads in a batch to insert pre-existing entries.
bulk_delete_concurrency (Optional[int]): Number of threads
(for deleting multiple rows concurrently).
A note on concurrency: as a rule of thumb, on a typical client machine
it is suggested to keep the quantity
bulk_insert_batch_concurrency * bulk_insert_overwrite_concurrency
much below 1000 to avoid exhausting the client multithreading/networking
resources. The hardcoded defaults are somewhat conservative to meet
most machines' specs, but a sensible choice to test may be:
bulk_insert_batch_concurrency = 80
bulk_insert_overwrite_concurrency = 10
A bit of experimentation is required to nail the best results here,
depending on both the machine/network specs and the expected workload
(specifically, how often a write is an update of an existing id).
Remember you can pass concurrency settings to individual calls to
add_texts and add_documents as well.
"""
# Conflicting-arg checks:
@ -330,6 +344,12 @@ class AstraDB(VectorStore):
pre-existing documents in each batch (which require individual
API calls). Defaults to instance-level setting if not provided.
A note on metadata: there are constraints on the allowed field names
in this dictionary, coming from the underlying Astra DB API.
For instance, the `$` (dollar sign) cannot be used in the dict keys.
See this document for details:
docs.datastax.com/en/astra-serverless/docs/develop/dev-with-json.html
Returns:
List[str]: List of ids of the added texts.
"""

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