code stringlengths 193 97.3k | apis listlengths 1 8 | extract_api stringlengths 113 214k |
|---|---|---|
# Ultralytics YOLO 🚀, AGPL-3.0 license
import getpass
from typing import List
import cv2
import numpy as np
import pandas as pd
from ultralytics.data.augment import LetterBox
from ultralytics.utils import LOGGER as logger
from ultralytics.utils import SETTINGS
from ultralytics.utils.checks import check_requirements... | [
"lancedb.pydantic.Vector"
] | [((3694, 3716), 'numpy.stack', 'np.stack', (['imgs'], {'axis': '(0)'}), '(imgs, axis=0)\n', (3702, 3716), True, 'import numpy as np\n'), ((4027, 4060), 'numpy.concatenate', 'np.concatenate', (['batch_idx'], {'axis': '(0)'}), '(batch_idx, axis=0)\n', (4041, 4060), True, 'import numpy as np\n'), ((4394, 4429), 'ultralyti... |
# type: ignore
import lancedb
import uuid
from datetime import datetime
from tqdm import tqdm
from typing import Optional, List, Iterator, Dict
from memgpt.config import MemGPTConfig
from memgpt.agent_store.storage import StorageConnector, TableType
from memgpt.config import AgentConfig, MemGPTConfig
from memgpt.cons... | [
"lancedb.pydantic.Vector"
] | [((639, 658), 'memgpt.config.MemGPTConfig.load', 'MemGPTConfig.load', ([], {}), '()\n', (656, 658), False, 'from memgpt.config import AgentConfig, MemGPTConfig\n'), ((1094, 1147), 'lancedb.pydantic.Vector', 'Vector', (['config.default_embedding_config.embedding_dim'], {}), '(config.default_embedding_config.embedding_di... |
# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | [
"lancedb.utils.CONFIG.copy",
"lancedb.utils.CONFIG.update"
] | [((641, 654), 'click.group', 'click.group', ([], {}), '()\n', (652, 654), False, 'import click\n'), ((656, 727), 'click.version_option', 'click.version_option', ([], {'help': '"""LanceDB command line interface entry point"""'}), "(help='LanceDB command line interface entry point')\n", (676, 727), False, 'import click\n... |
# Copyright (c) Hegel AI, Inc.
# All rights reserved.
#
# This source code's license can be found in the
# LICENSE file in the root directory of this source tree.
import itertools
import warnings
import pandas as pd
from typing import Callable, Optional
try:
import lancedb
from lancedb.embeddings import with_... | [
"lancedb.connect",
"lancedb.embeddings.with_embeddings"
] | [((797, 961), 'warnings.warn', 'warnings.warn', (['"""`nprobes` and `refine_factor` are not used by the default `query_builder`. Feel free to open an issue to request adding support for them."""'], {}), "(\n '`nprobes` and `refine_factor` are not used by the default `query_builder`. Feel free to open an issue to req... |
import os
from pathlib import Path
from tqdm import tqdm
from lancedb import connect
from pydantic import BaseModel
from lancedb.pydantic import LanceModel, Vector
from lancedb.embeddings import get_registry
from typing import Iterable
DB_PATH = Path(os.getcwd(), "db")
DATA_PATH = Path(os.getcwd(), "data")
DB_TABLE =... | [
"lancedb.connect",
"lancedb.embeddings.get_registry"
] | [((253, 264), 'os.getcwd', 'os.getcwd', ([], {}), '()\n', (262, 264), False, 'import os\n'), ((289, 300), 'os.getcwd', 'os.getcwd', ([], {}), '()\n', (298, 300), False, 'import os\n'), ((2068, 2084), 'lancedb.connect', 'connect', (['DB_PATH'], {}), '(DB_PATH)\n', (2075, 2084), False, 'from lancedb import connect\n'), (... |
import lancedb
import lancedb.embeddings.imagebind
from lancedb.embeddings import get_registry
from lancedb.pydantic import LanceModel, Vector
import gradio as gr
from downloader import dowload_and_save_audio, dowload_and_save_image, base_path
model = get_registry().get("imagebind").create()
class TextModel(LanceMod... | [
"lancedb.connect",
"lancedb.embeddings.get_registry"
] | [((550, 574), 'downloader.dowload_and_save_image', 'dowload_and_save_image', ([], {}), '()\n', (572, 574), False, 'from downloader import dowload_and_save_audio, dowload_and_save_image, base_path\n'), ((589, 613), 'downloader.dowload_and_save_audio', 'dowload_and_save_audio', ([], {}), '()\n', (611, 613), False, 'from ... |
"""LanceDB vector store with cloud storage support."""
import os
from typing import Any, Optional
from dotenv import load_dotenv
from llama_index.schema import NodeRelationship, RelatedNodeInfo, TextNode
from llama_index.vector_stores import LanceDBVectorStore as LanceDBVectorStoreBase
from llama_index.vector_stores.l... | [
"lancedb.connect"
] | [((490, 503), 'dotenv.load_dotenv', 'load_dotenv', ([], {}), '()\n', (501, 503), False, 'from dotenv import load_dotenv\n'), ((1464, 1492), 'os.getenv', 'os.getenv', (['"""LANCEDB_API_KEY"""'], {}), "('LANCEDB_API_KEY')\n", (1473, 1492), False, 'import os\n'), ((1520, 1547), 'os.getenv', 'os.getenv', (['"""LANCEDB_REGI... |
from pathlib import Path
from typing import Any, Callable
from lancedb import DBConnection as LanceDBConnection
from lancedb import connect as lancedb_connect
from lancedb.table import Table as LanceDBTable
from openai import Client as OpenAIClient
from pydantic import Field, PrivateAttr
from crewai_tools.tools.rag.r... | [
"lancedb.connect"
] | [((393, 407), 'openai.Client', 'OpenAIClient', ([], {}), '()\n', (405, 407), True, 'from openai import Client as OpenAIClient\n'), ((724, 774), 'pydantic.Field', 'Field', ([], {'default_factory': '_default_embedding_function'}), '(default_factory=_default_embedding_function)\n', (729, 774), False, 'from pydantic import... |
import logging
from typing import Any, Dict, Generator, List, Optional, Sequence, Tuple, Type
import lancedb
import pandas as pd
from dotenv import load_dotenv
from lancedb.pydantic import LanceModel, Vector
from lancedb.query import LanceVectorQueryBuilder
from pydantic import BaseModel, ValidationError, create_model... | [
"lancedb.connect",
"lancedb.pydantic.Vector"
] | [((911, 938), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (928, 938), False, 'import logging\n'), ((1125, 1149), 'langroid.embedding_models.models.OpenAIEmbeddingsConfig', 'OpenAIEmbeddingsConfig', ([], {}), '()\n', (1147, 1149), False, 'from langroid.embedding_models.models import Ope... |
import json
import lancedb
from lancedb.pydantic import Vector, LanceModel
from datetime import datetime
# import pyarrow as pa
TABLE_NAME = "documents"
uri = "data/sample-lancedb"
db = lancedb.connect(uri)
# vector: list of vectors
# file_name: name of file
# file_path: path of file
# id
# updated_at
# created_at... | [
"lancedb.connect",
"lancedb.pydantic.Vector"
] | [((189, 209), 'lancedb.connect', 'lancedb.connect', (['uri'], {}), '(uri)\n', (204, 209), False, 'import lancedb\n'), ((461, 472), 'lancedb.pydantic.Vector', 'Vector', (['(768)'], {}), '(768)\n', (467, 472), False, 'from lancedb.pydantic import Vector, LanceModel\n'), ((786, 800), 'datetime.datetime.now', 'datetime.now... |
import json
from sentence_transformers import SentenceTransformer
from pydantic.main import ModelMetaclass
from pathlib import Path
import pandas as pd
import sqlite3
from uuid import uuid4
import lancedb
encoder = SentenceTransformer('all-MiniLM-L6-v2')
data_folder = Path('data/collections')
config_file = Path('data... | [
"lancedb.connect",
"lancedb.pydantic.Vector"
] | [((216, 255), 'sentence_transformers.SentenceTransformer', 'SentenceTransformer', (['"""all-MiniLM-L6-v2"""'], {}), "('all-MiniLM-L6-v2')\n", (235, 255), False, 'from sentence_transformers import SentenceTransformer\n'), ((271, 295), 'pathlib.Path', 'Path', (['"""data/collections"""'], {}), "('data/collections')\n", (2... |
import os
import urllib.request
import html2text
import predictionguard as pg
from langchain import PromptTemplate, FewShotPromptTemplate
from langchain.text_splitter import CharacterTextSplitter
from sentence_transformers import SentenceTransformer
import numpy as np
import lancedb
from lancedb.embeddings i... | [
"lancedb.connect",
"lancedb.embeddings.with_embeddings"
] | [((670, 691), 'html2text.HTML2Text', 'html2text.HTML2Text', ([], {}), '()\n', (689, 691), False, 'import html2text\n'), ((1001, 1056), 'langchain.text_splitter.CharacterTextSplitter', 'CharacterTextSplitter', ([], {'chunk_size': '(700)', 'chunk_overlap': '(50)'}), '(chunk_size=700, chunk_overlap=50)\n', (1022, 1056), F... |
from lancedb.pydantic import LanceModel, Vector
from lancedb.embeddings import EmbeddingFunctionRegistry
registry = EmbeddingFunctionRegistry.get_instance()
func = registry.get("openai").create()
class Questions(LanceModel):
question: str = func.SourceField()
vector: Vector(func.ndims()) = func.VectorField()... | [
"lancedb.embeddings.EmbeddingFunctionRegistry.get_instance"
] | [((117, 157), 'lancedb.embeddings.EmbeddingFunctionRegistry.get_instance', 'EmbeddingFunctionRegistry.get_instance', ([], {}), '()\n', (155, 157), False, 'from lancedb.embeddings import EmbeddingFunctionRegistry\n')] |
"""
---------Parameters to be changed between different devices----------
1. Models and directory
2. Input and output directory
3. Device selection (CPU/GPU) - LINE 46 AND 300
Reference:
1. similarity_search_by_vector(): https://python.langchain.com/docs/modules/data_connection/vectorstores/
2. LanceDB Code do... | [
"lancedb.connect",
"lancedb.embeddings.EmbeddingFunctionRegistry.get_instance"
] | [((1778, 1818), 'lancedb.embeddings.EmbeddingFunctionRegistry.get_instance', 'EmbeddingFunctionRegistry.get_instance', ([], {}), '()\n', (1816, 1818), False, 'from lancedb.embeddings import EmbeddingFunctionRegistry\n'), ((15779, 15819), 'logging.basicConfig', 'logging.basicConfig', ([], {'level': 'logging.ERROR'}), '(... |
import logging
import os
import time
from functools import wraps
from pathlib import Path
from random import random, seed
import lancedb
import pyarrow as pa
import pyarrow.parquet as pq
import typer
from lancedb.db import LanceTable
log_level = os.environ.get("LOG_LEVEL", "info")
logging.basicConfig(
level=getat... | [
"lancedb.connect"
] | [((248, 283), 'os.environ.get', 'os.environ.get', (['"""LOG_LEVEL"""', '"""info"""'], {}), "('LOG_LEVEL', 'info')\n", (262, 283), False, 'import os\n'), ((446, 473), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (463, 473), False, 'import logging\n'), ((480, 493), 'typer.Typer', 'typer.T... |
import argparse
import os
import shutil
from functools import lru_cache
from pathlib import Path
from typing import Any, Iterator
import srsly
from codetiming import Timer
from config import Settings
from dotenv import load_dotenv
from rich import progress
from schemas.wine import LanceModelWine, Wine
from sentence_tr... | [
"lancedb.connect",
"lancedb.pydantic.pydantic_to_schema"
] | [((455, 468), 'dotenv.load_dotenv', 'load_dotenv', ([], {}), '()\n', (466, 468), False, 'from dotenv import load_dotenv\n'), ((560, 571), 'functools.lru_cache', 'lru_cache', ([], {}), '()\n', (569, 571), False, 'from functools import lru_cache\n'), ((668, 678), 'config.Settings', 'Settings', ([], {}), '()\n', (676, 678... |
from datasets import load_dataset
data = load_dataset('jamescalam/youtube-transcriptions', split='train')
from lancedb.context import contextualize
df = (contextualize(data.to_pandas())
.groupby("title").text_col("text")
.window(20).stride(4)
.to_df())
df.head(1)
import openai
import os
# Configur... | [
"lancedb.connect"
] | [((42, 106), 'datasets.load_dataset', 'load_dataset', (['"""jamescalam/youtube-transcriptions"""'], {'split': '"""train"""'}), "('jamescalam/youtube-transcriptions', split='train')\n", (54, 106), False, 'from datasets import load_dataset\n'), ((831, 862), 'lancedb.connect', 'lancedb.connect', (['"""/tmp/lancedb"""'], {... |
import hashlib
import io
import logging
from typing import List
import numpy as np
from lancedb.pydantic import LanceModel, vector
from PIL import Image
from pydantic import BaseModel, Field, computed_field
from homematch.config import IMAGES_DIR
logger = logging.getLogger(__name__)
class PropertyListingBase(BaseM... | [
"lancedb.pydantic.vector"
] | [((259, 286), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (276, 286), False, 'import logging\n'), ((2511, 2522), 'lancedb.pydantic.vector', 'vector', (['(768)'], {}), '(768)\n', (2517, 2522), False, 'from lancedb.pydantic import LanceModel, vector\n'), ((2146, 2158), 'io.BytesIO', 'io.... |
# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | [
"lancedb.remote.VectorQueryResult",
"lancedb.remote.connection_timeout.LanceDBClientHTTPAdapterFactory",
"lancedb.remote.errors.LanceDBClientError"
] | [((1587, 1612), 'attrs.define', 'attrs.define', ([], {'slots': '(False)'}), '(slots=False)\n', (1599, 1612), False, 'import attrs\n'), ((1207, 1225), 'functools.wraps', 'functools.wraps', (['f'], {}), '(f)\n', (1222, 1225), False, 'import functools\n'), ((1733, 1758), 'attrs.field', 'attrs.field', ([], {'default': 'Non... |
from langchain.text_splitter import (
RecursiveCharacterTextSplitter,
Language,
LatexTextSplitter,
)
from langchain.document_loaders import TextLoader
from langchain.embeddings import OpenAIEmbeddings
import argparse, os, arxiv
os.environ["OPENAI_API_KEY"] = "sk-ORoaAljc5ylMsRwnXpLTT3BlbkFJQJz0esJOFYg8Z6... | [
"lancedb.connect",
"lancedb.pydantic.Vector"
] | [((342, 360), 'langchain.embeddings.OpenAIEmbeddings', 'OpenAIEmbeddings', ([], {}), '()\n', (358, 360), False, 'from langchain.embeddings import OpenAIEmbeddings\n'), ((2116, 2133), 'lancedb.connect', 'lancedb.connect', ([], {}), '()\n', (2131, 2133), False, 'import lancedb\n'), ((2820, 2867), 'langchain.vectorstores.... |
# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | [
"lancedb.utils.general.TryExcept"
] | [((5469, 5493), 'lancedb.utils.general.TryExcept', 'TryExcept', ([], {'verbose': '(False)'}), '(verbose=False)\n', (5478, 5493), False, 'from lancedb.utils.general import TryExcept\n'), ((4631, 4642), 'time.time', 'time.time', ([], {}), '()\n', (4640, 4642), False, 'import time\n'), ((2582, 2613), 'platform.python_vers... |
import time
import os
import pandas as pd
import streamlit as st
import lancedb
from lancedb.embeddings import with_embeddings
from langchain import PromptTemplate
import predictionguard as pg
import streamlit as st
import duckdb
import re
import numpy as np
from sentence_transformers import SentenceTransformer
#---... | [
"lancedb.connect"
] | [((413, 433), 'lancedb.connect', 'lancedb.connect', (['uri'], {}), '(uri)\n', (428, 433), False, 'import lancedb\n'), ((890, 947), 'streamlit.markdown', 'st.markdown', (['hide_streamlit_style'], {'unsafe_allow_html': '(True)'}), '(hide_streamlit_style, unsafe_allow_html=True)\n', (901, 947), True, 'import streamlit as ... |
from FlagEmbedding import LLMEmbedder, FlagReranker
import os
import lancedb
import re
import pandas as pd
import random
from datasets import load_dataset
import torch
import gc
import lance
from lancedb.embeddings import with_embeddings
task = "qa" # Encode for a specific task (qa, icl, chat, lrl... | [
"lancedb.connect",
"lancedb.embeddings.with_embeddings"
] | [((356, 404), 'FlagEmbedding.LLMEmbedder', 'LLMEmbedder', (['"""BAAI/llm-embedder"""'], {'use_fp16': '(False)'}), "('BAAI/llm-embedder', use_fp16=False)\n", (367, 404), False, 'from FlagEmbedding import LLMEmbedder, FlagReranker\n'), ((463, 516), 'FlagEmbedding.FlagReranker', 'FlagReranker', (['"""BAAI/bge-reranker-bas... |
# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | [
"lancedb.utils.events.register_event",
"lancedb.embeddings.registry.EmbeddingFunctionRegistry.get_instance",
"lancedb.common.data_to_reader",
"lancedb.common.validate_schema"
] | [((24504, 24527), 'lancedb.common.validate_schema', 'validate_schema', (['schema'], {}), '(schema)\n', (24519, 24527), False, 'from lancedb.common import data_to_reader, validate_schema\n'), ((25026, 25056), 'lancedb.utils.events.register_event', 'register_event', (['"""create_table"""'], {}), "('create_table')\n", (25... |
import time
import re
import shutil
import os
import urllib
import html2text
import predictionguard as pg
from langchain import PromptTemplate, FewShotPromptTemplate
from langchain.text_splitter import CharacterTextSplitter
from langchain.agents import load_tools
from langchain.agents import initialize_agent
from lang... | [
"lancedb.connect",
"lancedb.embeddings.with_embeddings"
] | [((728, 820), 'langchain.PromptTemplate', 'PromptTemplate', ([], {'input_variables': "['user', 'assistant']", 'template': 'demo_formatter_template'}), "(input_variables=['user', 'assistant'], template=\n demo_formatter_template)\n", (742, 820), False, 'from langchain import PromptTemplate, FewShotPromptTemplate\n'),... |
import logging
from pathlib import Path
from typing import Dict, Iterable, List, Optional, Union
logger = logging.getLogger(__name__)
from hamilton import contrib
with contrib.catch_import_errors(__name__, __file__, logger):
import pyarrow as pa
import lancedb
import numpy as np
import pandas as pd
... | [
"lancedb.connect"
] | [((107, 134), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (124, 134), False, 'import logging\n'), ((1219, 1242), 'hamilton.function_modifiers.tag', 'tag', ([], {'side_effect': '"""True"""'}), "(side_effect='True')\n", (1222, 1242), False, 'from hamilton.function_modifiers import tag\n'... |
# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | [
"lancedb.utils.general.TryExcept"
] | [((5422, 5446), 'lancedb.utils.general.TryExcept', 'TryExcept', ([], {'verbose': '(False)'}), '(verbose=False)\n', (5431, 5446), False, 'from lancedb.utils.general import TryExcept\n'), ((4584, 4595), 'time.time', 'time.time', ([], {}), '()\n', (4593, 4595), False, 'import time\n'), ((2567, 2598), 'platform.python_vers... |
import argparse
import os
import sys
from concurrent.futures import ProcessPoolExecutor, as_completed
from functools import lru_cache
from pathlib import Path
from typing import Any, Iterator
import lancedb
import pandas as pd
import srsly
from codetiming import Timer
from dotenv import load_dotenv
from lancedb.pydant... | [
"lancedb.connect",
"lancedb.pydantic.pydantic_to_schema"
] | [((580, 593), 'dotenv.load_dotenv', 'load_dotenv', ([], {}), '()\n', (591, 593), False, 'from dotenv import load_dotenv\n'), ((685, 696), 'functools.lru_cache', 'lru_cache', ([], {}), '()\n', (694, 696), False, 'from functools import lru_cache\n'), ((793, 803), 'api.config.Settings', 'Settings', ([], {}), '()\n', (801,... |
# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | [
"lancedb.remote.VectorQueryResult"
] | [((1402, 1427), 'attrs.define', 'attrs.define', ([], {'slots': '(False)'}), '(slots=False)\n', (1414, 1427), False, 'import attrs\n'), ((1006, 1024), 'functools.wraps', 'functools.wraps', (['f'], {}), '(f)\n', (1021, 1024), False, 'import functools\n'), ((1548, 1573), 'attrs.field', 'attrs.field', ([], {'default': 'Non... |
import os
from typing import List, Dict, Optional, Any
from dataclasses import dataclass, field
from .preprocessor import call_pdf_preprocess, call_image_preprocess, call_audio_preprocess
from .utils.semantic_chuncker import SemanticChunker
from .utils.txt_preprocessor import NERExtractor
from langchain_openai.em... | [
"lancedb.connect",
"lancedb.embeddings.EmbeddingFunctionRegistry"
] | [((801, 855), 'dataclasses.field', 'field', ([], {'default_factory': "(lambda : ['txt', 'csv', 'json'])"}), "(default_factory=lambda : ['txt', 'csv', 'json'])\n", (806, 855), False, 'from dataclasses import dataclass, field\n'), ((877, 916), 'dataclasses.field', 'field', ([], {'default_factory': "(lambda : ['pdf'])"}),... |
import os
import time
import shutil
import pandas as pd
import lancedb
from lancedb.embeddings import with_embeddings
from langchain import PromptTemplate
import predictionguard as pg
import numpy as np
from sentence_transformers import SentenceTransformer
#---------------------#
# Lance DB Setup #
#-------------... | [
"lancedb.connect",
"lancedb.embeddings.with_embeddings"
] | [((359, 391), 'pandas.read_csv', 'pd.read_csv', (['"""datasets/jobs.csv"""'], {}), "('datasets/jobs.csv')\n", (370, 391), True, 'import pandas as pd\n'), ((429, 463), 'pandas.read_csv', 'pd.read_csv', (['"""datasets/social.csv"""'], {}), "('datasets/social.csv')\n", (440, 463), True, 'import pandas as pd\n'), ((503, 53... |
import typer
import openai
from rag_app.models import TextChunk
from lancedb import connect
from typing import List
from pathlib import Path
from rich.console import Console
from rich.table import Table
from rich import box
import duckdb
app = typer.Typer()
@app.command(help="Query LanceDB for some results")
def db(... | [
"lancedb.connect"
] | [((245, 258), 'typer.Typer', 'typer.Typer', ([], {}), '()\n', (256, 258), False, 'import typer\n'), ((340, 378), 'typer.Option', 'typer.Option', ([], {'help': '"""Your LanceDB path"""'}), "(help='Your LanceDB path')\n", (352, 378), False, 'import typer\n'), ((402, 448), 'typer.Option', 'typer.Option', ([], {'help': '""... |
import typer
from lancedb import connect
from rag_app.models import TextChunk, Document
from pathlib import Path
from typing import Iterable
from tqdm import tqdm
from rich import print
import frontmatter
import hashlib
from datetime import datetime
from unstructured.partition.text import partition_text
app = typer.Ty... | [
"lancedb.connect"
] | [((312, 325), 'typer.Typer', 'typer.Typer', ([], {}), '()\n', (323, 325), False, 'import typer\n'), ((1598, 1636), 'typer.Option', 'typer.Option', ([], {'help': '"""Your LanceDB path"""'}), "(help='Your LanceDB path')\n", (1610, 1636), False, 'import typer\n'), ((1660, 1706), 'typer.Option', 'typer.Option', ([], {'help... |
# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | [
"lancedb.utils.CONFIG.copy",
"lancedb.utils.CONFIG.update"
] | [((641, 654), 'click.group', 'click.group', ([], {}), '()\n', (652, 654), False, 'import click\n'), ((656, 727), 'click.version_option', 'click.version_option', ([], {'help': '"""LanceDB command line interface entry point"""'}), "(help='LanceDB command line interface entry point')\n", (676, 727), False, 'import click\n... |
import json
from sentence_transformers import SentenceTransformer
from pydantic.main import ModelMetaclass
from pathlib import Path
import pandas as pd
import sqlite3
from uuid import uuid4
import lancedb
encoder = SentenceTransformer('all-MiniLM-L6-v2')
data_folder = Path('data/collections')
config_file = Path('data... | [
"lancedb.connect",
"lancedb.pydantic.Vector"
] | [((216, 255), 'sentence_transformers.SentenceTransformer', 'SentenceTransformer', (['"""all-MiniLM-L6-v2"""'], {}), "('all-MiniLM-L6-v2')\n", (235, 255), False, 'from sentence_transformers import SentenceTransformer\n'), ((271, 295), 'pathlib.Path', 'Path', (['"""data/collections"""'], {}), "('data/collections')\n", (2... |
import argparse
import pandas as pd
from unstructured.partition.pdf import partition_pdf
import lancedb.embeddings.gte
from lancedb.embeddings import get_registry
from lancedb.pydantic import LanceModel, Vector
def split_text_into_chunks(text, chunk_size, overlap):
"""
Split text into chunks with a specifie... | [
"lancedb.embeddings.get_registry"
] | [((1242, 1265), 'unstructured.partition.pdf.partition_pdf', 'partition_pdf', (['pdf_file'], {}), '(pdf_file)\n', (1255, 1265), False, 'from unstructured.partition.pdf import partition_pdf\n'), ((1658, 1688), 'pandas.DataFrame', 'pd.DataFrame', (["{'text': chunks}"], {}), "({'text': chunks})\n", (1670, 1688), True, 'imp... |
from datetime import datetime
from typing import List, Union
from pydantic import field_validator
from lancedb.embeddings import get_registry
from lancedb.pydantic import LanceModel, Vector
from pydantic import BaseModel
openai = get_registry().get("openai").create(name="text-embedding-3-large", dim=256)
class TextC... | [
"lancedb.embeddings.get_registry"
] | [((671, 698), 'pydantic.field_validator', 'field_validator', (['"""metadata"""'], {}), "('metadata')\n", (686, 698), False, 'from pydantic import field_validator\n'), ((1082, 1109), 'pydantic.field_validator', 'field_validator', (['"""metadata"""'], {}), "('metadata')\n", (1097, 1109), False, 'from pydantic import fiel... |
import os
import shutil
from pathlib import Path
import lancedb
from lancedb.pydantic import LanceModel, Vector, pydantic_to_schema
from langchain.document_loaders import TextLoader
from langchain.embeddings import HuggingFaceEmbeddings
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.... | [
"lancedb.connect",
"lancedb.pydantic.Vector",
"lancedb.pydantic.pydantic_to_schema"
] | [((429, 440), 'lancedb.pydantic.Vector', 'Vector', (['(384)'], {}), '(384)\n', (435, 440), False, 'from lancedb.pydantic import LanceModel, Vector, pydantic_to_schema\n'), ((538, 553), 'pathlib.Path', 'Path', (['"""../data"""'], {}), "('../data')\n", (542, 553), False, 'from pathlib import Path\n'), ((1650, 1714), 'lan... |
import zipfile
import numpy as np
import pandas as pd
import scipy.sparse
import torch
import implicit
from implicit import evaluation
import lancedb
import pydantic
from lancedb.pydantic import pydantic_to_schema, vector
import argparse
def products_bought_by_user_in_the_past(user_id: int, top: int = 10):
select... | [
"lancedb.connect",
"lancedb.pydantic.vector",
"lancedb.pydantic.pydantic_to_schema"
] | [((774, 832), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""Product Recommender"""'}), "(description='Product Recommender')\n", (797, 832), False, 'import argparse\n'), ((2049, 2076), 'pandas.read_csv', 'pd.read_csv', (['"""products.csv"""'], {}), "('products.csv')\n", (2060, 2076), Tru... |
import lancedb
import uuid
from datetime import datetime
from tqdm import tqdm
from typing import Optional, List, Iterator, Dict
from memgpt.config import MemGPTConfig
from memgpt.agent_store.storage import StorageConnector, TableType
from memgpt.config import AgentConfig, MemGPTConfig
from memgpt.constants import MEM... | [
"lancedb.pydantic.Vector"
] | [((623, 642), 'memgpt.config.MemGPTConfig.load', 'MemGPTConfig.load', ([], {}), '()\n', (640, 642), False, 'from memgpt.config import AgentConfig, MemGPTConfig\n'), ((1078, 1106), 'lancedb.pydantic.Vector', 'Vector', (['config.embedding_dim'], {}), '(config.embedding_dim)\n', (1084, 1106), False, 'from lancedb.pydantic... |
import os
import argparse
import lancedb
from lancedb.context import contextualize
from lancedb.embeddings import with_embeddings
from datasets import load_dataset
import openai
import pytest
OPENAI_MODEL = None
def embed_func(c):
rs = openai.Embedding.create(input=c, engine=OPENAI_MODEL)
return [record["emb... | [
"lancedb.connect",
"lancedb.embeddings.with_embeddings"
] | [((243, 296), 'openai.Embedding.create', 'openai.Embedding.create', ([], {'input': 'c', 'engine': 'OPENAI_MODEL'}), '(input=c, engine=OPENAI_MODEL)\n', (266, 296), False, 'import openai\n'), ((1031, 1192), 'openai.Completion.create', 'openai.Completion.create', ([], {'engine': 'OPENAI_MODEL', 'prompt': 'prompt', 'tempe... |
import os, time
import pandas as pd
import numpy as np
from collections import Counter
from .utils import abbreviate_book_name_in_full_reference, get_train_test_split_from_verse_list, embed_batch
from .types import TranslationTriplet, ChatResponse, VerseMap, AIResponse
from pydantic import BaseModel, Field
from typing ... | [
"lancedb.connect",
"lancedb.embeddings.with_embeddings"
] | [((559, 587), 'logging.getLogger', 'logging.getLogger', (['"""uvicorn"""'], {}), "('uvicorn')\n", (576, 587), False, 'import logging\n'), ((801, 880), 'pandas.read_csv', 'pd.read_csv', (['"""data/bsb-utf8.txt"""'], {'sep': '"""\t"""', 'names': "['vref', 'content']", 'header': '(0)'}), "('data/bsb-utf8.txt', sep='\\t', ... |
import logging
import pyarrow as pa
import pyarrow.compute as pc
from tabulate import tabulate
from llama_cpp import Llama
from dryg.settings import DEFAULT_MODEL
from dryg.db import open_table, create_table
from lancedb.embeddings import with_embeddings
MODEL = None
def get_code_blocks(body: pa.ChunkedArray):
... | [
"lancedb.embeddings.with_embeddings"
] | [((1527, 1575), 'lancedb.embeddings.with_embeddings', 'with_embeddings', (['embedding_func', 'issues', '"""title"""'], {}), "(embedding_func, issues, 'title')\n", (1542, 1575), False, 'from lancedb.embeddings import with_embeddings\n'), ((1611, 1662), 'dryg.db.create_table', 'create_table', (['issue_table', 'issues'], ... |
from pathlib import Path
from collections import defaultdict
import math
import json
import pandas as pd
import cv2
import duckdb
import matplotlib.pyplot as plt
import numpy as np
import yaml
from tqdm import tqdm
from ultralytics.utils import LOGGER, colorstr
from ultralytics.utils.plotting import Annotator, colors
... | [
"lancedb.connect",
"lancedb.embeddings.with_embeddings"
] | [((1044, 1064), 'cv2.imread', 'cv2.imread', (['img_path'], {}), '(img_path)\n', (1054, 1064), False, 'import cv2\n'), ((1214, 1249), 'numpy.frombuffer', 'np.frombuffer', (['img_encoded', 'np.byte'], {}), '(img_encoded, np.byte)\n', (1227, 1249), True, 'import numpy as np\n'), ((1260, 1300), 'cv2.imdecode', 'cv2.imdecod... |
"""
Run this script to benchmark the serial search performance of FTS and vector search
"""
import argparse
import random
from functools import lru_cache
from pathlib import Path
from typing import Any
from codetiming import Timer
from config import Settings
from rich import progress
from schemas.wine import SearchRes... | [
"lancedb.connect"
] | [((471, 482), 'functools.lru_cache', 'lru_cache', ([], {}), '()\n', (480, 482), False, 'from functools import lru_cache\n'), ((579, 589), 'config.Settings', 'Settings', ([], {}), '()\n', (587, 589), False, 'from config import Settings\n'), ((2943, 2968), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {}), '... |
from neumai.Shared.NeumSinkInfo import NeumSinkInfo
from neumai.Shared.NeumVector import NeumVector
from neumai.Shared.NeumSearch import NeumSearchResult
from neumai.Shared.Exceptions import(
LanceDBInsertionException,
LanceDBIndexInfoException,
LanceDBIndexCreationException,
LanceDBQueryException
)
fr... | [
"lancedb.connect"
] | [((2397, 2447), 'pydantic.Field', 'Field', (['...'], {'description': '"""URI for LanceDB database"""'}), "(..., description='URI for LanceDB database')\n", (2402, 2447), False, 'from pydantic import Field\n'), ((2477, 2537), 'pydantic.Field', 'Field', ([], {'default': 'None', 'description': '"""API key for LanceDB clou... |
from FlagEmbedding import LLMEmbedder, FlagReranker
import lancedb
import re
import pandas as pd
import random
from datasets import load_dataset
import torch
import gc
from lancedb.embeddings import with_embeddings
embed_model = LLMEmbedder(
"BAAI/llm-embedder", use_fp16=False
) # Load model (automatically use... | [
"lancedb.connect",
"lancedb.embeddings.with_embeddings"
] | [((233, 281), 'FlagEmbedding.LLMEmbedder', 'LLMEmbedder', (['"""BAAI/llm-embedder"""'], {'use_fp16': '(False)'}), "('BAAI/llm-embedder', use_fp16=False)\n", (244, 281), False, 'from FlagEmbedding import LLMEmbedder, FlagReranker\n'), ((344, 397), 'FlagEmbedding.FlagReranker', 'FlagReranker', (['"""BAAI/bge-reranker-bas... |
import os
import urllib.request
import shutil
import html2text
import predictionguard as pg
from langchain import PromptTemplate, FewShotPromptTemplate
from langchain.text_splitter import CharacterTextSplitter
from sentence_transformers import SentenceTransformer
import numpy as np
import lancedb
from lancedb.embedding... | [
"lancedb.connect",
"lancedb.embeddings.with_embeddings"
] | [((657, 678), 'html2text.HTML2Text', 'html2text.HTML2Text', ([], {}), '()\n', (676, 678), False, 'import html2text\n'), ((847, 902), 'langchain.text_splitter.CharacterTextSplitter', 'CharacterTextSplitter', ([], {'chunk_size': '(700)', 'chunk_overlap': '(50)'}), '(chunk_size=700, chunk_overlap=50)\n', (868, 902), False... |
import json
import logging
from typing import Any, Dict, Generator, List, Optional, Sequence, Set, Tuple, Type
import lancedb
import pandas as pd
from dotenv import load_dotenv
from lancedb.pydantic import LanceModel, Vector
from lancedb.query import LanceVectorQueryBuilder
from pydantic import BaseModel, ValidationEr... | [
"lancedb.connect",
"lancedb.pydantic.Vector"
] | [((877, 904), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (894, 904), False, 'import logging\n'), ((1067, 1091), 'src.embedding_models.models.OpenAIEmbeddingsConfig', 'OpenAIEmbeddingsConfig', ([], {}), '()\n', (1089, 1091), False, 'from src.embedding_models.models import OpenAIEmbeddi... |
from datasets import load_dataset
import os
import lancedb
import getpass
import time
import argparse
from tqdm.auto import tqdm
from lancedb.embeddings import EmbeddingFunctionRegistry
from lancedb.pydantic import LanceModel, Vector
def main(query=None):
if "COHERE_API_KEY" not in os.environ:
os.environ[... | [
"lancedb.connect",
"lancedb.embeddings.EmbeddingFunctionRegistry"
] | [((407, 463), 'datasets.load_dataset', 'load_dataset', (['"""wikipedia"""', '"""20220301.en"""'], {'streaming': '(True)'}), "('wikipedia', '20220301.en', streaming=True)\n", (419, 463), False, 'from datasets import load_dataset\n'), ((504, 560), 'datasets.load_dataset', 'load_dataset', (['"""wikipedia"""', '"""20220301... |
from typing import Optional
from pydantic import BaseModel, ConfigDict, Field, model_validator
from lancedb.pydantic import LanceModel, Vector
class Wine(BaseModel):
model_config = ConfigDict(
populate_by_name=True,
validate_assignment=True,
extra="allow",
str_strip_whitespace=Tr... | [
"lancedb.pydantic.Vector"
] | [((189, 894), 'pydantic.ConfigDict', 'ConfigDict', ([], {'populate_by_name': '(True)', 'validate_assignment': '(True)', 'extra': '"""allow"""', 'str_strip_whitespace': '(True)', 'json_schema_extra': "{'example': {'id': 45100, 'points': 85, 'title':\n 'Balduzzi 2012 Reserva Merlot (Maule Valley)', 'description':\n ... |
from typing import Any
from lancedb.embeddings import EmbeddingFunctionRegistry
def register_model(model_name: str) -> Any:
"""
Register a model with the given name using LanceDB's EmbeddingFunctionRegistry.
Args:
model_name (str): The name of the model to register.
Returns:
model: ... | [
"lancedb.embeddings.EmbeddingFunctionRegistry.get_instance"
] | [((430, 470), 'lancedb.embeddings.EmbeddingFunctionRegistry.get_instance', 'EmbeddingFunctionRegistry.get_instance', ([], {}), '()\n', (468, 470), False, 'from lancedb.embeddings import EmbeddingFunctionRegistry\n')] |
#!/usr/bin/env python
import os
import lancedb
from lancedb.embeddings import with_embeddings
import openai
import pandas as pd
from pydantic import BaseModel, Field
import requests
from aifunctools.openai_funcs import complete_with_functions
openai.api_key = os.getenv("OPENAI_API_KEY")
MODEL = "gpt-3.5-turbo-16k-0... | [
"lancedb.connect",
"lancedb.embeddings.with_embeddings"
] | [((263, 290), 'os.getenv', 'os.getenv', (['"""OPENAI_API_KEY"""'], {}), "('OPENAI_API_KEY')\n", (272, 290), False, 'import os\n'), ((331, 358), 'lancedb.connect', 'lancedb.connect', (['""".lancedb"""'], {}), "('.lancedb')\n", (346, 358), False, 'import lancedb\n'), ((389, 454), 'openai.Embedding.create', 'openai.Embedd... |
import lancedb
import uuid
from datetime import datetime
from tqdm import tqdm
from typing import Optional, List, Iterator, Dict
from memgpt.config import MemGPTConfig
from memgpt.connectors.storage import StorageConnector, TableType
from memgpt.config import AgentConfig, MemGPTConfig
from memgpt.constants import MEMG... | [
"lancedb.pydantic.Vector"
] | [((622, 641), 'memgpt.config.MemGPTConfig.load', 'MemGPTConfig.load', ([], {}), '()\n', (639, 641), False, 'from memgpt.config import AgentConfig, MemGPTConfig\n'), ((1077, 1105), 'lancedb.pydantic.Vector', 'Vector', (['config.embedding_dim'], {}), '(config.embedding_dim)\n', (1083, 1105), False, 'from lancedb.pydantic... |
""" Install lancedb with instructor embedding support
copy this and paste it in the terminal, and install additional dependencies via requirements.txt file
pip install git+https://github.com/lancedb/lancedb.git@main#subdirectory=python
"""
import lancedb
from lancedb.pydantic import LanceModel, Vecto... | [
"lancedb.connect",
"lancedb.embeddings.get_registry"
] | [((818, 847), 'lancedb.connect', 'lancedb.connect', (['"""~/.lancedb"""'], {}), "('~/.lancedb')\n", (833, 847), False, 'import lancedb\n'), ((445, 459), 'lancedb.embeddings.get_registry', 'get_registry', ([], {}), '()\n', (457, 459), False, 'from lancedb.embeddings import get_registry\n')] |
from pathlib import Path
from uuid import uuid4
from langchain.document_loaders import TextLoader
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.text_splitter import CharacterTextSplitter
from langchain.vectorstores import LanceDB
import lancedb
from knowledge_graph.configuration.config import... | [
"lancedb.connect"
] | [((410, 438), 'lancedb.connect', 'lancedb.connect', (['cfg.db_path'], {}), '(cfg.db_path)\n', (425, 438), False, 'import lancedb\n'), ((715, 743), 'lancedb.connect', 'lancedb.connect', (['cfg.db_path'], {}), '(cfg.db_path)\n', (730, 743), False, 'import lancedb\n'), ((1060, 1125), 'langchain.text_splitter.CharacterText... |
from glob import glob
from os.path import basename
from pathlib import Path
import chromadb
import lancedb
import pandas as pd
import torch
from chromadb.utils import embedding_functions
from lancedb.embeddings import EmbeddingFunctionRegistry
from lancedb.pydantic import LanceModel, Vector
from loguru import logger
f... | [
"lancedb.connect",
"lancedb.embeddings.EmbeddingFunctionRegistry.get_instance"
] | [((489, 529), 'lancedb.embeddings.EmbeddingFunctionRegistry.get_instance', 'EmbeddingFunctionRegistry.get_instance', ([], {}), '()\n', (527, 529), False, 'from lancedb.embeddings import EmbeddingFunctionRegistry\n'), ((881, 915), 'chromadb.PersistentClient', 'chromadb.PersistentClient', (['DB_PATH'], {}), '(DB_PATH)\n'... |
import getpass
from typing import List
import cv2
import numpy as np
import pandas as pd
from ultralytics.data.augment import LetterBox
from ultralytics.utils import LOGGER as logger
from ultralytics.utils import SETTINGS
from ultralytics.utils.checks import check_requirements
from ultralytics.utils.ops import xyxy2x... | [
"lancedb.pydantic.Vector"
] | [((3411, 3433), 'numpy.stack', 'np.stack', (['imgs'], {'axis': '(0)'}), '(imgs, axis=0)\n', (3419, 3433), True, 'import numpy as np\n'), ((3771, 3804), 'numpy.concatenate', 'np.concatenate', (['batch_idx'], {'axis': '(0)'}), '(batch_idx, axis=0)\n', (3785, 3804), True, 'import numpy as np\n'), ((4239, 4274), 'ultralyti... |
# Ultralytics YOLO 🚀, AGPL-3.0 license
import getpass
from typing import List
import cv2
import numpy as np
import pandas as pd
from ultralytics.data.augment import LetterBox
from ultralytics.utils import LOGGER as logger
from ultralytics.utils import SETTINGS
from ultralytics.utils.checks import check_requirements... | [
"lancedb.pydantic.Vector"
] | [((3694, 3716), 'numpy.stack', 'np.stack', (['imgs'], {'axis': '(0)'}), '(imgs, axis=0)\n', (3702, 3716), True, 'import numpy as np\n'), ((4054, 4087), 'numpy.concatenate', 'np.concatenate', (['batch_idx'], {'axis': '(0)'}), '(batch_idx, axis=0)\n', (4068, 4087), True, 'import numpy as np\n'), ((4421, 4456), 'ultralyti... |
from typing import Optional
from lancedb.pydantic import Vector
from pydantic import BaseModel, ConfigDict, Field, model_validator
class Wine(BaseModel):
model_config = ConfigDict(
populate_by_name=True,
validate_assignment=True,
extra="allow",
str_strip_whitespace=True,
j... | [
"lancedb.pydantic.Vector"
] | [((176, 881), 'pydantic.ConfigDict', 'ConfigDict', ([], {'populate_by_name': '(True)', 'validate_assignment': '(True)', 'extra': '"""allow"""', 'str_strip_whitespace': '(True)', 'json_schema_extra': "{'example': {'id': 45100, 'points': 85, 'title':\n 'Balduzzi 2012 Reserva Merlot (Maule Valley)', 'description':\n ... |
# Ultralytics YOLO 🚀, AGPL-3.0 license
import getpass
from typing import List
import cv2
import numpy as np
import pandas as pd
from engine.data.augment import LetterBox
from engine.utils import LOGGER as logger
from engine.utils import SETTINGS
from engine.utils.checks import check_requirements
from engine.utils.o... | [
"lancedb.pydantic.Vector"
] | [((3664, 3686), 'numpy.stack', 'np.stack', (['imgs'], {'axis': '(0)'}), '(imgs, axis=0)\n', (3672, 3686), True, 'import numpy as np\n'), ((3997, 4030), 'numpy.concatenate', 'np.concatenate', (['batch_idx'], {'axis': '(0)'}), '(batch_idx, axis=0)\n', (4011, 4030), True, 'import numpy as np\n'), ((4364, 4399), 'engine.ut... |
import json
import lancedb
import pytest
from lancedb.utils.events import _Events
@pytest.fixture(autouse=True)
def request_log_path(tmp_path):
return tmp_path / "request.json"
def mock_register_event(name: str, **kwargs):
if _Events._instance is None:
_Events._instance = _Events()
_Events._in... | [
"lancedb.connect",
"lancedb.utils.events._Events",
"lancedb.utils.events._Events._instance"
] | [((86, 114), 'pytest.fixture', 'pytest.fixture', ([], {'autouse': '(True)'}), '(autouse=True)\n', (100, 114), False, 'import pytest\n'), ((383, 416), 'lancedb.utils.events._Events._instance', '_Events._instance', (['name'], {}), '(name, **kwargs)\n', (400, 416), False, 'from lancedb.utils.events import _Events\n'), ((8... |
import os
import lancedb
import numpy as np
import pytest
from lancedb.conftest import MockTextEmbeddingFunction # noqa
from lancedb.embeddings import EmbeddingFunctionRegistry
from lancedb.pydantic import LanceModel, Vector
from lancedb.rerankers import (
CohereReranker,
ColbertReranker,
CrossEncoderRera... | [
"lancedb.rerankers.ColbertReranker",
"lancedb.connect",
"lancedb.rerankers.CohereReranker",
"lancedb.rerankers.CrossEncoderReranker",
"lancedb.table.LanceTable.create",
"lancedb.rerankers.OpenaiReranker",
"lancedb.embeddings.EmbeddingFunctionRegistry.get_instance"
] | [((412, 446), 'pytest.importorskip', 'pytest.importorskip', (['"""lancedb.fts"""'], {}), "('lancedb.fts')\n", (431, 446), False, 'import pytest\n'), ((488, 513), 'lancedb.connect', 'lancedb.connect', (['tmp_path'], {}), '(tmp_path)\n', (503, 513), False, 'import lancedb\n'), ((830, 879), 'lancedb.table.LanceTable.creat... |
# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | [
"lancedb.LanceDBConnection"
] | [((707, 763), 'pytest.mark.skip', 'pytest.mark.skip', ([], {'reason': '"""Need to set up a local server"""'}), "(reason='Need to set up a local server')\n", (723, 763), False, 'import pytest\n'), ((808, 859), 'lancedb.LanceDBConnection', 'LanceDBConnection', (['"""lancedb+http://localhost:10024"""'], {}), "('lancedb+ht... |
# Ultralytics YOLO 🚀, AGPL-3.0 license
import getpass
from typing import List
import cv2
import numpy as np
import pandas as pd
from ultralytics.data.augment import LetterBox
from ultralytics.utils import LOGGER as logger
from ultralytics.utils import SETTINGS
from ultralytics.utils.checks import check_requirements... | [
"lancedb.pydantic.Vector"
] | [((3694, 3716), 'numpy.stack', 'np.stack', (['imgs'], {'axis': '(0)'}), '(imgs, axis=0)\n', (3702, 3716), True, 'import numpy as np\n'), ((4027, 4060), 'numpy.concatenate', 'np.concatenate', (['batch_idx'], {'axis': '(0)'}), '(batch_idx, axis=0)\n', (4041, 4060), True, 'import numpy as np\n'), ((4394, 4429), 'ultralyti... |
# Ultralytics YOLO 🚀, AGPL-3.0 license
import getpass
from typing import List
import cv2
import numpy as np
import pandas as pd
from ultralytics.data.augment import LetterBox
from ultralytics.utils import LOGGER as logger
from ultralytics.utils import SETTINGS
from ultralytics.utils.checks import check_requirements... | [
"lancedb.pydantic.Vector"
] | [((3694, 3716), 'numpy.stack', 'np.stack', (['imgs'], {'axis': '(0)'}), '(imgs, axis=0)\n', (3702, 3716), True, 'import numpy as np\n'), ((4027, 4060), 'numpy.concatenate', 'np.concatenate', (['batch_idx'], {'axis': '(0)'}), '(batch_idx, axis=0)\n', (4041, 4060), True, 'import numpy as np\n'), ((4394, 4429), 'ultralyti... |
# Ultralytics YOLO 🚀, AGPL-3.0 license
import getpass
from typing import List
import cv2
import numpy as np
import pandas as pd
from ultralytics.data.augment import LetterBox
from ultralytics.utils import LOGGER as logger
from ultralytics.utils import SETTINGS
from ultralytics.utils.checks import check_requirements... | [
"lancedb.pydantic.Vector"
] | [((3694, 3716), 'numpy.stack', 'np.stack', (['imgs'], {'axis': '(0)'}), '(imgs, axis=0)\n', (3702, 3716), True, 'import numpy as np\n'), ((4027, 4060), 'numpy.concatenate', 'np.concatenate', (['batch_idx'], {'axis': '(0)'}), '(batch_idx, axis=0)\n', (4041, 4060), True, 'import numpy as np\n'), ((4394, 4429), 'ultralyti... |
# Ultralytics YOLO 🚀, AGPL-3.0 license
import getpass
from typing import List
import cv2
import numpy as np
import pandas as pd
from ultralytics.data.augment import LetterBox
from ultralytics.utils import LOGGER as logger
from ultralytics.utils import SETTINGS
from ultralytics.utils.checks import check_requirements... | [
"lancedb.pydantic.Vector"
] | [((3694, 3716), 'numpy.stack', 'np.stack', (['imgs'], {'axis': '(0)'}), '(imgs, axis=0)\n', (3702, 3716), True, 'import numpy as np\n'), ((4027, 4060), 'numpy.concatenate', 'np.concatenate', (['batch_idx'], {'axis': '(0)'}), '(batch_idx, axis=0)\n', (4041, 4060), True, 'import numpy as np\n'), ((4394, 4429), 'ultralyti... |
# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | [
"lancedb.utils.CONFIG.copy",
"lancedb.utils.CONFIG.update"
] | [((641, 654), 'click.group', 'click.group', ([], {}), '()\n', (652, 654), False, 'import click\n'), ((656, 727), 'click.version_option', 'click.version_option', ([], {'help': '"""LanceDB command line interface entry point"""'}), "(help='LanceDB command line interface entry point')\n", (676, 727), False, 'import click\n... |
# Copyright (c) Hegel AI, Inc.
# All rights reserved.
#
# This source code's license can be found in the
# LICENSE file in the root directory of this source tree.
import itertools
import warnings
import pandas as pd
from typing import Callable, Optional
try:
import lancedb
from lancedb.embeddings import with_... | [
"lancedb.connect",
"lancedb.embeddings.with_embeddings"
] | [((797, 961), 'warnings.warn', 'warnings.warn', (['"""`nprobes` and `refine_factor` are not used by the default `query_builder`. Feel free to open an issue to request adding support for them."""'], {}), "(\n '`nprobes` and `refine_factor` are not used by the default `query_builder`. Feel free to open an issue to req... |
"""LanceDB vector store with cloud storage support."""
import os
from typing import Any, Optional
from dotenv import load_dotenv
from llama_index.schema import NodeRelationship, RelatedNodeInfo, TextNode
from llama_index.vector_stores import LanceDBVectorStore as LanceDBVectorStoreBase
from llama_index.vector_stores.l... | [
"lancedb.connect"
] | [((490, 503), 'dotenv.load_dotenv', 'load_dotenv', ([], {}), '()\n', (501, 503), False, 'from dotenv import load_dotenv\n'), ((1464, 1492), 'os.getenv', 'os.getenv', (['"""LANCEDB_API_KEY"""'], {}), "('LANCEDB_API_KEY')\n", (1473, 1492), False, 'import os\n'), ((1520, 1547), 'os.getenv', 'os.getenv', (['"""LANCEDB_REGI... |
from pathlib import Path
from typing import Any, Callable
from lancedb import DBConnection as LanceDBConnection
from lancedb import connect as lancedb_connect
from lancedb.table import Table as LanceDBTable
from openai import Client as OpenAIClient
from pydantic import Field, PrivateAttr
from crewai_tools.tools.rag.r... | [
"lancedb.connect"
] | [((393, 407), 'openai.Client', 'OpenAIClient', ([], {}), '()\n', (405, 407), True, 'from openai import Client as OpenAIClient\n'), ((724, 774), 'pydantic.Field', 'Field', ([], {'default_factory': '_default_embedding_function'}), '(default_factory=_default_embedding_function)\n', (729, 774), False, 'from pydantic import... |
from langchain.text_splitter import (
RecursiveCharacterTextSplitter,
Language,
LatexTextSplitter,
)
from langchain.document_loaders import TextLoader
from langchain.embeddings import OpenAIEmbeddings
import argparse, os, arxiv
os.environ["OPENAI_API_KEY"] = "sk-ORoaAljc5ylMsRwnXpLTT3BlbkFJQJz0esJOFYg8Z6... | [
"lancedb.connect",
"lancedb.pydantic.Vector"
] | [((342, 360), 'langchain.embeddings.OpenAIEmbeddings', 'OpenAIEmbeddings', ([], {}), '()\n', (358, 360), False, 'from langchain.embeddings import OpenAIEmbeddings\n'), ((2116, 2133), 'lancedb.connect', 'lancedb.connect', ([], {}), '()\n', (2131, 2133), False, 'import lancedb\n'), ((2820, 2867), 'langchain.vectorstores.... |
# Ultralytics YOLO 🚀, AGPL-3.0 license
import getpass
from typing import List
import cv2
import numpy as np
import pandas as pd
from ultralytics.data.augment import LetterBox
from ultralytics.utils import LOGGER as logger
from ultralytics.utils import SETTINGS
from ultralytics.utils.checks import check_requirements... | [
"lancedb.pydantic.Vector"
] | [((3694, 3716), 'numpy.stack', 'np.stack', (['imgs'], {'axis': '(0)'}), '(imgs, axis=0)\n', (3702, 3716), True, 'import numpy as np\n'), ((4054, 4087), 'numpy.concatenate', 'np.concatenate', (['batch_idx'], {'axis': '(0)'}), '(batch_idx, axis=0)\n', (4068, 4087), True, 'import numpy as np\n'), ((4421, 4456), 'ultralyti... |
# Ultralytics YOLO 🚀, AGPL-3.0 license
import getpass
from typing import List
import cv2
import numpy as np
import pandas as pd
from ultralytics.data.augment import LetterBox
from ultralytics.utils import LOGGER as logger
from ultralytics.utils import SETTINGS
from ultralytics.utils.checks import check_requirements... | [
"lancedb.pydantic.Vector"
] | [((3694, 3716), 'numpy.stack', 'np.stack', (['imgs'], {'axis': '(0)'}), '(imgs, axis=0)\n', (3702, 3716), True, 'import numpy as np\n'), ((4054, 4087), 'numpy.concatenate', 'np.concatenate', (['batch_idx'], {'axis': '(0)'}), '(batch_idx, axis=0)\n', (4068, 4087), True, 'import numpy as np\n'), ((4421, 4456), 'ultralyti... |
from click.testing import CliRunner
from lancedb.cli.cli import cli
from lancedb.utils import CONFIG
def test_entry():
runner = CliRunner()
result = runner.invoke(cli)
assert result.exit_code == 0 # Main check
assert "lancedb" in result.output.lower() # lazy check
def test_diagnostics():
runne... | [
"lancedb.utils.CONFIG.copy"
] | [((134, 145), 'click.testing.CliRunner', 'CliRunner', ([], {}), '()\n', (143, 145), False, 'from click.testing import CliRunner\n'), ((324, 335), 'click.testing.CliRunner', 'CliRunner', ([], {}), '()\n', (333, 335), False, 'from click.testing import CliRunner\n'), ((660, 671), 'click.testing.CliRunner', 'CliRunner', ([... |
import os
import argparse
import lancedb
from lancedb.context import contextualize
from lancedb.embeddings import with_embeddings
from datasets import load_dataset
import openai
import pytest
import subprocess
from main import embed_func, create_prompt, complete
# DOWNLOAD =============================================... | [
"lancedb.connect",
"lancedb.embeddings.with_embeddings"
] | [((1071, 1184), 'argparse.Namespace', 'argparse.Namespace', ([], {'query': '"""test"""', 'context_length': '(3)', 'window_size': '(20)', 'stride': '(4)', 'openai_key': '"""test"""', 'model': '"""test"""'}), "(query='test', context_length=3, window_size=20, stride=4,\n openai_key='test', model='test')\n", (1089, 1184... |
from datetime import timedelta
import pyarrow as pa
import pytest
import pytest_asyncio
from lancedb import AsyncConnection, AsyncTable, connect_async
from lancedb.index import BTree, IvfPq
@pytest_asyncio.fixture
async def db_async(tmp_path) -> AsyncConnection:
return await connect_async(tmp_path, read_consiste... | [
"lancedb.index.IvfPq",
"lancedb.index.BTree"
] | [((495, 546), 'pyarrow.FixedSizeListArray.from_arrays', 'pa.FixedSizeListArray.from_arrays', (['vector_data', 'dim'], {}), '(vector_data, dim)\n', (528, 546), True, 'import pyarrow as pa\n'), ((470, 482), 'pyarrow.float32', 'pa.float32', ([], {}), '()\n', (480, 482), True, 'import pyarrow as pa\n'), ((1303, 1354), 'pyt... |
# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | [
"lancedb.pydantic.Vector",
"lancedb.conftest.MockTextEmbeddingFunction",
"lancedb.table.LanceTable",
"lancedb.connect",
"lancedb.table.LanceTable.create",
"lancedb.db.LanceDBConnection",
"lancedb.embeddings.EmbeddingFunctionConfig",
"lancedb.embeddings.EmbeddingFunctionRegistry.get_instance"
] | [((1992, 2014), 'lancedb.table.LanceTable', 'LanceTable', (['db', '"""test"""'], {}), "(db, 'test')\n", (2002, 2014), False, 'from lancedb.table import LanceTable\n'), ((3907, 3928), 'pandas.DataFrame', 'pd.DataFrame', (['data[0]'], {}), '(data[0])\n', (3919, 3928), True, 'import pandas as pd\n'), ((4450, 4494), 'lance... |
# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | [
"lancedb.remote.VectorQueryResult",
"lancedb.remote.connection_timeout.LanceDBClientHTTPAdapterFactory",
"lancedb.remote.errors.LanceDBClientError"
] | [((1587, 1612), 'attrs.define', 'attrs.define', ([], {'slots': '(False)'}), '(slots=False)\n', (1599, 1612), False, 'import attrs\n'), ((1207, 1225), 'functools.wraps', 'functools.wraps', (['f'], {}), '(f)\n', (1222, 1225), False, 'import functools\n'), ((1733, 1758), 'attrs.field', 'attrs.field', ([], {'default': 'Non... |
# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | [
"lancedb.pydantic.Vector",
"lancedb.pydantic.pydantic_to_schema"
] | [((860, 973), 'pytest.mark.skipif', 'pytest.mark.skipif', (['(sys.version_info < (3, 9))'], {'reason': '"""using native type alias requires python3.9 or higher"""'}), "(sys.version_info < (3, 9), reason=\n 'using native type alias requires python3.9 or higher')\n", (878, 973), False, 'import pytest\n'), ((2877, 2988... |
# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | [
"lancedb.pydantic.Vector",
"lancedb.query.Query",
"lancedb.query.LanceVectorQueryBuilder",
"lancedb.db.LanceDBConnection"
] | [((2041, 2074), 'lance.write_dataset', 'lance.write_dataset', (['df', 'tmp_path'], {}), '(df, tmp_path)\n', (2060, 2074), False, 'import lance\n'), ((4585, 4625), 'pandas.testing.assert_frame_equal', 'tm.assert_frame_equal', (['df_default', 'df_l2'], {}), '(df_default, df_l2)\n', (4606, 4625), True, 'import pandas.test... |
# Copyright (c) 2023. LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed... | [
"lancedb.connect",
"lancedb.embeddings.get_registry"
] | [((1288, 1357), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""alias"""', "['sentence-transformers', 'openai']"], {}), "('alias', ['sentence-transformers', 'openai'])\n", (1311, 1357), False, 'import pytest\n'), ((5687, 5773), 'pytest.mark.skipif', 'pytest.mark.skipif', (['(_imagebind is None)'], {'reason'... |
# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | [
"lancedb.connect",
"lancedb.remote.client.VectorQueryResult"
] | [((1101, 1164), 'lancedb.connect', 'lancedb.connect', (['"""db://client-will-be-injected"""'], {'api_key': '"""fake"""'}), "('db://client-will-be-injected', api_key='fake')\n", (1116, 1164), False, 'import lancedb\n'), ((924, 944), 'lancedb.remote.client.VectorQueryResult', 'VectorQueryResult', (['t'], {}), '(t)\n', (9... |
# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | [
"lancedb.context.contextualize"
] | [((726, 911), 'pandas.DataFrame', 'pd.DataFrame', (["{'token': ['The', 'quick', 'brown', 'fox', 'jumped', 'over', 'the', 'lazy',\n 'dog', 'I', 'love', 'sandwiches'], 'document_id': [1, 1, 1, 1, 1, 1, 1,\n 1, 1, 2, 2, 2]}"], {}), "({'token': ['The', 'quick', 'brown', 'fox', 'jumped', 'over',\n 'the', 'lazy', 'd... |
# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | [
"lancedb.embeddings.registry.register",
"lancedb.conftest.MockTextEmbeddingFunction",
"lancedb.connect",
"lancedb.embeddings.with_embeddings",
"lancedb.embeddings.registry.get_registry",
"lancedb.embeddings.EmbeddingFunctionRegistry.get_instance"
] | [((1948, 1988), 'lancedb.embeddings.EmbeddingFunctionRegistry.get_instance', 'EmbeddingFunctionRegistry.get_instance', ([], {}), '()\n', (1986, 1988), False, 'from lancedb.embeddings import EmbeddingFunctionConfig, EmbeddingFunctionRegistry, with_embeddings\n'), ((2476, 2527), 'lance.write_dataset', 'lance.write_datase... |
# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | [
"lancedb.util.join_uri",
"lancedb.util.get_uri_scheme"
] | [((1561, 1634), 'pytest.mark.skipif', 'pytest.mark.skipif', (["(os.name == 'nt')"], {'reason': '"""Windows paths are not POSIX"""'}), "(os.name == 'nt', reason='Windows paths are not POSIX')\n", (1579, 1634), False, 'import pytest\n'), ((2201, 2274), 'pytest.mark.skipif', 'pytest.mark.skipif', (["(os.name != 'nt')"], {... |
# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | [
"lancedb.utils.general.TryExcept"
] | [((5466, 5490), 'lancedb.utils.general.TryExcept', 'TryExcept', ([], {'verbose': '(False)'}), '(verbose=False)\n', (5475, 5490), False, 'from lancedb.utils.general import TryExcept\n'), ((4628, 4639), 'time.time', 'time.time', ([], {}), '()\n', (4637, 4639), False, 'import time\n'), ((2579, 2610), 'platform.python_vers... |
# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | [
"lancedb.remote.client.RestfulLanceDBClient"
] | [((2188, 2239), 'pytest.mark.skip', 'pytest.mark.skip', ([], {'reason': '"""flaky somehow, fix later"""'}), "(reason='flaky somehow, fix later')\n", (2204, 2239), False, 'import pytest\n'), ((839, 862), 'attrs.field', 'attrs.field', ([], {'init': '(False)'}), '(init=False)\n', (850, 862), False, 'import attrs\n'), ((88... |
# Copyright 2023 LanceDB Developers
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to i... | [
"lancedb.connect",
"lancedb.pydantic.Vector",
"lancedb.connect_async"
] | [((807, 832), 'lancedb.connect', 'lancedb.connect', (['tmp_path'], {}), '(tmp_path)\n', (822, 832), False, 'import lancedb\n'), ((1559, 1584), 'lancedb.connect', 'lancedb.connect', (['tmp_path'], {}), '(tmp_path)\n', (1574, 1584), False, 'import lancedb\n'), ((1667, 1769), 'pandas.DataFrame', 'pd.DataFrame', (["{'vecto... |
# Ultralytics YOLO 🚀, AGPL-3.0 license
from io import BytesIO
from pathlib import Path
from typing import Any, List, Tuple, Union
import cv2
import numpy as np
import torch
from PIL import Image
from matplotlib import pyplot as plt
from pandas import DataFrame
from tqdm import tqdm
from ultralytics.data.augment imp... | [
"lancedb.connect"
] | [((1697, 1890), 'ultralytics.data.augment.Format', 'Format', ([], {'bbox_format': '"""xyxy"""', 'normalize': '(False)', 'return_mask': 'self.use_segments', 'return_keypoint': 'self.use_keypoints', 'batch_idx': '(True)', 'mask_ratio': 'hyp.mask_ratio', 'mask_overlap': 'hyp.overlap_mask'}), "(bbox_format='xyxy', normaliz... |
import logging
import lancedb
from langchain.chains import RetrievalQA
from langchain.document_loaders import TextLoader
from langchain.embeddings import HuggingFaceEmbeddings
from langchain.llms import CTransformers
from langchain.prompts import PromptTemplate
from langchain.text_splitter import RecursiveCharacterTex... | [
"lancedb.connect"
] | [((400, 496), 'logging.basicConfig', 'logging.basicConfig', ([], {'level': 'logging.INFO', 'format': '"""%(asctime)s - %(levelname)s - %(message)s"""'}), "(level=logging.INFO, format=\n '%(asctime)s - %(levelname)s - %(message)s')\n", (419, 496), False, 'import logging\n'), ((501, 528), 'logging.getLogger', 'logging... |
from collections import OrderedDict
from typing import List, Optional
import lancedb
import pandas as pd
import pyarrow as pa
from lance.vector import vec_to_table
import duckdb
import json
from mindsdb.integrations.libs.const import HANDLER_CONNECTION_ARG_TYPE as ARG_TYPE
from mindsdb.integrations.libs.response impo... | [
"lancedb.connect"
] | [((752, 775), 'mindsdb.utilities.log.getLogger', 'log.getLogger', (['__name__'], {}), '(__name__)\n', (765, 775), False, 'from mindsdb.utilities import log\n'), ((13628, 14162), 'collections.OrderedDict', 'OrderedDict', ([], {'persist_directory': "{'type': ARG_TYPE.STR, 'description': 'The uri of the database.',\n '... |
"""Vector store."""
from langchain.vectorstores import LanceDB
import lancedb
class VectorStoreLanceDB:
"""Vector store lance DB."""
def __init__(self, db_path, table_name, mode, embedding_model):
self.db = lancedb.connect(db_path)
self.embedding_model = embedding_model
print(db_path... | [
"lancedb.connect"
] | [((226, 250), 'lancedb.connect', 'lancedb.connect', (['db_path'], {}), '(db_path)\n', (241, 250), False, 'import lancedb\n'), ((1608, 1681), 'langchain.vectorstores.LanceDB', 'LanceDB', ([], {'connection': 'table', 'embedding': 'self.embedding_model.embedding_model'}), '(connection=table, embedding=self.embedding_model... |
import os
from dotenv import load_dotenv
import streamlit as st
from langchain.llms import OpenAI
from langchain.chat_models import ChatOpenAI
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.chains import ConversationalRetrievalC... | [
"lancedb.connect"
] | [((924, 983), 'streamlit.set_page_config', 'st.set_page_config', ([], {'page_title': '"""GlobeBotter"""', 'page_icon': '"""🎬"""'}), "(page_title='GlobeBotter', page_icon='🎬')\n", (942, 983), True, 'import streamlit as st\n'), ((984, 1055), 'streamlit.header', 'st.header', (['"""🎬 Welcome to MovieHarbor, your favouri... |
from pathlib import Path
import geopandas as gpd
import lancedb
import matplotlib.pyplot as plt
from skimage import io
# Set working directory
wd = "/home/usr/Desktop/"
# To download the existing embeddings run aws s3 sync
# aws s3 sync s3://clay-worldcover-embeddings /my/dir/clay-worldcover-embeddings
vector_dir =... | [
"lancedb.connect"
] | [((321, 371), 'pathlib.Path', 'Path', (["(wd + 'clay-worldcover-embeddings/v002/2021/')"], {}), "(wd + 'clay-worldcover-embeddings/v002/2021/')\n", (325, 371), False, 'from pathlib import Path\n'), ((421, 468), 'lancedb.connect', 'lancedb.connect', (["(wd + 'worldcoverembeddings_db')"], {}), "(wd + 'worldcoverembedding... |
# Copyright 2023 llmware
# Licensed under the Apache License, Version 2.0 (the "License"); you
# may not use this file except in compliance with the License. You
# may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
#... | [
"lancedb.connect"
] | [((12701, 12771), 'llmware.resources.CollectionRetrieval', 'CollectionRetrieval', (['self.library_name'], {'account_name': 'self.account_name'}), '(self.library_name, account_name=self.account_name)\n', (12720, 12771), False, 'from llmware.resources import CollectionRetrieval, CollectionWriter\n'), ((13147, 13217), 'll... |
"""LanceDB vector store."""
import logging
from typing import Any, List, Optional
import numpy as np
from llama_index.core.bridge.pydantic import PrivateAttr
from llama_index.core.schema import (
BaseNode,
MetadataMode,
NodeRelationship,
RelatedNodeInfo,
TextNode,
)
from llama_index.core.vector_st... | [
"lancedb.connect"
] | [((685, 712), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (702, 712), False, 'import logging\n'), ((2814, 2827), 'llama_index.core.bridge.pydantic.PrivateAttr', 'PrivateAttr', ([], {}), '()\n', (2825, 2827), False, 'from llama_index.core.bridge.pydantic import PrivateAttr\n'), ((3431, ... |
# Copyright [2024] [Holosun ApS]
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed... | [
"lancedb.connect"
] | [((1190, 1215), 'os.getenv', 'os.getenv', (['"""SUPABASE_URL"""'], {}), "('SUPABASE_URL')\n", (1199, 1215), False, 'import os\n'), ((1239, 1264), 'os.getenv', 'os.getenv', (['"""SUPABASE_KEY"""'], {}), "('SUPABASE_KEY')\n", (1248, 1264), False, 'import os\n'), ((1376, 1417), 'supabase.create_client', 'create_client', (... |
import uuid
from ragna.core import Config, Document, PackageRequirement, Requirement, Source
from ._vector_database import VectorDatabaseSourceStorage
class LanceDB(VectorDatabaseSourceStorage):
"""[LanceDB vector database](https://lancedb.com/)
!!! info "Required packages"
- `chromadb>=0.4.13`
... | [
"lancedb.connect"
] | [((892, 944), 'lancedb.connect', 'lancedb.connect', (["(config.local_cache_root / 'lancedb')"], {}), "(config.local_cache_root / 'lancedb')\n", (907, 944), False, 'import lancedb\n'), ((503, 537), 'ragna.core.PackageRequirement', 'PackageRequirement', (['"""lancedb>=0.2"""'], {}), "('lancedb>=0.2')\n", (521, 537), Fals... |
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