Getting Started With Zilliz And OpenAI
chatgptopenaigpt-4zillizexamplesvector_databasesopenai-apiopenai-cookbook
Export
Getting Started with Zilliz and OpenAI
Finding your next book
In this notebook we will be going over generating embeddings of book descriptions with OpenAI and using those embeddings within Zilliz to find relevant books. The dataset in this example is sourced from HuggingFace datasets, and contains a little over 1 million title-description pairs.
Lets begin by first downloading the required libraries for this notebook:
openaiis used for communicating with the OpenAI embedding servicepymilvusis used for communicating with the Zilliz instancedatasetsis used for downloading the datasettqdmis used for the progress bars
[1]
Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com Requirement already satisfied: openai in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (0.27.2) Requirement already satisfied: pymilvus in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (2.2.2) Requirement already satisfied: datasets in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (2.10.1) Requirement already satisfied: tqdm in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (4.64.1) Requirement already satisfied: requests>=2.20 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from openai) (2.28.2) Requirement already satisfied: aiohttp in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from openai) (3.8.4) Requirement already satisfied: ujson<=5.4.0,>=2.0.0 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from pymilvus) (5.1.0) Requirement already satisfied: grpcio-tools<=1.48.0,>=1.47.0 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from pymilvus) (1.47.2) Requirement already satisfied: grpcio<=1.48.0,>=1.47.0 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from pymilvus) (1.47.2) Requirement already satisfied: mmh3<=3.0.0,>=2.0 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from pymilvus) (3.0.0) Requirement already satisfied: pandas>=1.2.4 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from pymilvus) (1.5.3) Requirement already satisfied: numpy>=1.17 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from datasets) (1.23.5) Requirement already satisfied: xxhash in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from datasets) (3.2.0) Requirement already satisfied: responses<0.19 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from datasets) (0.18.0) Requirement already satisfied: dill<0.3.7,>=0.3.0 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from datasets) (0.3.6) Requirement already satisfied: huggingface-hub<1.0.0,>=0.2.0 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from datasets) (0.12.1) Requirement already satisfied: pyarrow>=6.0.0 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from datasets) (10.0.1) Requirement already satisfied: multiprocess in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from datasets) (0.70.14) Requirement already satisfied: pyyaml>=5.1 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from datasets) (5.4.1) Requirement already satisfied: fsspec[http]>=2021.11.1 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from datasets) (2023.1.0) Requirement already satisfied: packaging in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from datasets) (23.0) Requirement already satisfied: frozenlist>=1.1.1 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from aiohttp->openai) (1.3.3) Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from aiohttp->openai) (4.0.2) Requirement already satisfied: aiosignal>=1.1.2 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from aiohttp->openai) (1.3.1) Requirement already satisfied: attrs>=17.3.0 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from aiohttp->openai) (22.2.0) Requirement already satisfied: charset-normalizer<4.0,>=2.0 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from aiohttp->openai) (3.0.1) Requirement already satisfied: yarl<2.0,>=1.0 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from aiohttp->openai) (1.8.2) Requirement already satisfied: multidict<7.0,>=4.5 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from aiohttp->openai) (6.0.4) Requirement already satisfied: six>=1.5.2 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from grpcio<=1.48.0,>=1.47.0->pymilvus) (1.16.0) Requirement already satisfied: protobuf<4.0dev,>=3.12.0 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from grpcio-tools<=1.48.0,>=1.47.0->pymilvus) (3.20.1) Requirement already satisfied: setuptools in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from grpcio-tools<=1.48.0,>=1.47.0->pymilvus) (65.6.3) Requirement already satisfied: typing-extensions>=3.7.4.3 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from huggingface-hub<1.0.0,>=0.2.0->datasets) (4.5.0) Requirement already satisfied: filelock in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from huggingface-hub<1.0.0,>=0.2.0->datasets) (3.9.0) Requirement already satisfied: python-dateutil>=2.8.1 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from pandas>=1.2.4->pymilvus) (2.8.2) Requirement already satisfied: pytz>=2020.1 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from pandas>=1.2.4->pymilvus) (2022.7.1) Requirement already satisfied: urllib3<1.27,>=1.21.1 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from requests>=2.20->openai) (1.26.14) Requirement already satisfied: idna<4,>=2.5 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from requests>=2.20->openai) (3.4) Requirement already satisfied: certifi>=2017.4.17 in /Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages (from requests>=2.20->openai) (2022.12.7)
To get Zilliz up and running take a look here. With your account and database set up, proceed to set the following values:
- URI: The URI your database is running on
- USER: Your database username
- PASSWORD: Your database password
- COLLECTION_NAME: What to name the collection within Zilliz
- DIMENSION: The dimension of the embeddings
- OPENAI_ENGINE: Which embedding model to use
- openai.api_key: Your OpenAI account key
- INDEX_PARAM: The index settings to use for the collection
- QUERY_PARAM: The search parameters to use
- BATCH_SIZE: How many texts to embed and insert at once
[1]
Zilliz
This segment deals with Zilliz and setting up the database for this use case. Within Zilliz we need to setup a collection and index it.
[3]
[4]
[5]
[6]
Dataset
With Zilliz up and running we can begin grabbing our data. Hugging Face Datasets is a hub that holds many different user datasets, and for this example we are using Skelebor's book dataset. This dataset contains title-description pairs for over 1 million books. We are going to embed each description and store it within Zilliz along with its title.
[7]
/Users/filiphaltmayer/miniconda3/envs/haystack/lib/python3.9/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html from .autonotebook import tqdm as notebook_tqdm Found cached dataset parquet (/Users/filiphaltmayer/.cache/huggingface/datasets/Skelebor___parquet/Skelebor--book_titles_and_descriptions_en_clean-3596935b1d8a7747/0.0.0/2a3b91fbd88a2c90d1dbbb32b460cf621d31bd5b05b934492fdef7d8d6f236ec)
Insert the Data
Now that we have our data on our machine we can begin embedding it and inserting it into Zilliz. The embedding function takes in text and returns the embeddings in a list format.
[8]
This next step does the actual inserting. Due to having so many datapoints, if you want to immediately test it out you can stop the inserting cell block early and move along. Doing this will probably decrease the accuracy of the results due to less datapoints, but it should still be good enough.
[10]
0%| | 2999/1032335 [00:19<1:49:30, 156.66it/s]
--------------------------------------------------------------------------- KeyboardInterrupt Traceback (most recent call last) Cell In[10], line 14 12 if len(data[0]) % BATCH_SIZE == 0: 13 data.append(embed(data[1])) ---> 14 collection.insert(data) 15 data = [[],[]] 17 # Embed and insert the remainder File ~/miniconda3/envs/haystack/lib/python3.9/site-packages/pymilvus/orm/collection.py:430, in Collection.insert(self, data, partition_name, timeout, **kwargs) 427 entities = Prepare.prepare_insert_data(data, self._schema) 429 conn = self._get_connection() --> 430 res = conn.batch_insert(self._name, entities, partition_name, 431 timeout=timeout, schema=self._schema_dict, **kwargs) 433 if kwargs.get("_async", False): 434 return MutationFuture(res) File ~/miniconda3/envs/haystack/lib/python3.9/site-packages/pymilvus/decorators.py:105, in error_handler.<locals>.wrapper.<locals>.handler(*args, **kwargs) 103 try: 104 record_dict["RPC start"] = str(datetime.datetime.now()) --> 105 return func(*args, **kwargs) 106 except MilvusException as e: 107 record_dict["RPC error"] = str(datetime.datetime.now()) File ~/miniconda3/envs/haystack/lib/python3.9/site-packages/pymilvus/decorators.py:136, in tracing_request.<locals>.wrapper.<locals>.handler(self, *args, **kwargs) 134 if req_id: 135 self.set_onetime_request_id(req_id) --> 136 ret = func(self, *args, **kwargs) 137 return ret File ~/miniconda3/envs/haystack/lib/python3.9/site-packages/pymilvus/decorators.py:50, in retry_on_rpc_failure.<locals>.wrapper.<locals>.handler(self, *args, **kwargs) 48 while True: 49 try: ---> 50 return func(self, *args, **kwargs) 51 except grpc.RpcError as e: 52 # DEADLINE_EXCEEDED means that the task wat not completed 53 # UNAVAILABLE means that the service is not reachable currently 54 # Reference: https://grpc.github.io/grpc/python/grpc.html#grpc-status-code 55 if e.code() != grpc.StatusCode.DEADLINE_EXCEEDED and e.code() != grpc.StatusCode.UNAVAILABLE: File ~/miniconda3/envs/haystack/lib/python3.9/site-packages/pymilvus/client/grpc_handler.py:378, in GrpcHandler.batch_insert(self, collection_name, entities, partition_name, timeout, **kwargs) 375 f.add_callback(ts_utils.update_ts_on_mutation(collection_name)) 376 return f --> 378 response = rf.result() 379 if response.status.error_code == 0: 380 m = MutationResult(response) File ~/miniconda3/envs/haystack/lib/python3.9/site-packages/grpc/_channel.py:733, in _MultiThreadedRendezvous.result(self, timeout) 728 """Returns the result of the computation or raises its exception. 729 730 See grpc.Future.result for the full API contract. 731 """ 732 with self._state.condition: --> 733 timed_out = _common.wait(self._state.condition.wait, 734 self._is_complete, 735 timeout=timeout) 736 if timed_out: 737 raise grpc.FutureTimeoutError() File ~/miniconda3/envs/haystack/lib/python3.9/site-packages/grpc/_common.py:141, in wait(wait_fn, wait_complete_fn, timeout, spin_cb) 139 if timeout is None: 140 while not wait_complete_fn(): --> 141 _wait_once(wait_fn, MAXIMUM_WAIT_TIMEOUT, spin_cb) 142 else: 143 end = time.time() + timeout File ~/miniconda3/envs/haystack/lib/python3.9/site-packages/grpc/_common.py:106, in _wait_once(wait_fn, timeout, spin_cb) 105 def _wait_once(wait_fn, timeout, spin_cb): --> 106 wait_fn(timeout=timeout) 107 if spin_cb is not None: 108 spin_cb() File ~/miniconda3/envs/haystack/lib/python3.9/threading.py:316, in Condition.wait(self, timeout) 314 else: 315 if timeout > 0: --> 316 gotit = waiter.acquire(True, timeout) 317 else: 318 gotit = waiter.acquire(False) KeyboardInterrupt:
Query the Database
With our data safely inserted in Zilliz, we can now perform a query. The query takes in a string or a list of strings and searches them. The results print out your provided description and the results that include the result score, the result title, and the result book description.
[11]
[12]
Description: Book about a k-9 from europe Results: Rank: 1 Score: 0.3047754764556885 Title: Bark M For Murder Who let the dogs out? Evildoers beware! Four of mystery fiction's top storytellers are setting the hounds on your trail -- in an incomparable quartet of crime stories with a canine edge. Man's (and woman's) best friends take the lead in this phenomenal collection of tales tense and surprising, humorous and thrilling: New York Timesbestselling author J.A. Jance's spellbinding saga of a scam-busting septuagenarian and her two golden retrievers; Anthony Award winner Virginia Lanier's pureblood thriller featuring bloodhounds and bloody murder; Chassie West's suspenseful stunner about a life-saving German shepherd and a ghastly forgotten crime; rising star Lee Charles Kelley's edge-of-your-seat yarn that pits an ex-cop/kennel owner and a yappy toy poodle against a craven killer. Rank: 2 Score: 0.3283390402793884 Title: Texas K-9 Unit Christmas: Holiday Hero\Rescuing Christmas CHRISTMAS COMES WRAPPED IN DANGER Holiday Hero by Shirlee McCoy Emma Fairchild never expected to find trouble in sleepy Sagebrush, Texas. But when she's attacked and left for dead in her own diner, her childhood friend turned K-9 cop Lucas Harwood offers a chance at justice--and love. Rescuing Christmas by Terri Reed She escaped a kidnapper, but now a killer has set his sights on K-9 dog trainer Lily Anderson. When fellow officer Jarrod Evans appoints himself her bodyguard, Lily knows more than her life is at risk--so is her heart. Texas K-9 Unit: These lawmen solve the toughest cases with the help of their brave canine partners Rank: 3 Score: 0.33899369835853577 Title: Dogs on Duty: Soldiers' Best Friends on the Battlefield and Beyond When the news of the raid on Osama Bin Laden's compound broke, the SEAL team member that stole the show was a highly trained canine companion. Throughout history, dogs have been key contributors to military units. Dorothy Hinshaw Patent follows man's best friend onto the battlefield, showing readers why dogs are uniquely qualified for the job at hand, how they are trained, how they contribute to missions, and what happens when they retire. With full-color photographs throughout and sidebars featuring heroic canines throughout history, Dogs on Duty provides a fascinating look at these exceptional soldiers and companions. Rank: 4 Score: 0.34207457304000854 Title: Toute Allure: Falling in Love in Rural France After saying goodbye to life as a successful fashion editor in London, Karen Wheeler is now happy in her small village house in rural France. Her idyll is complete when she meets the love of her life - he has shaggy hair, four paws and a wet nose! Rank: 5 Score: 0.343595951795578 Title: Otherwise Alone (Evan Arden, #1) Librarian's note: This is an alternate cover edition for ASIN: B00AP5NNWC. Lieutenant Evan Arden sits in a shack in the middle of nowhere, waiting for orders that will send him back home - if he ever gets them. Other than his loyal Great Pyrenees, there's no one around to break up the monotony. The tedium is excruciating, but it is suddenly interrupted when a young woman stumbles up his path. "It's only 50-something pages, but in that short amount of time, the author's awesome writing packs in a whole lotta character detail. And sets the stage for the series, perfectly." -Maryse.net, 4.5 Stars He has two choices - pick her off from a distance with his trusty sniper-rifle, or dare let her approach his cabin and enter his life. Why not? It's been ages, and he is otherwise alone...