Rename embedchain to mem0 and open sourcing code for long term memory (#1474)
Co-authored-by: Deshraj Yadav <deshrajdry@gmail.com>
This commit is contained in:
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embedchain/embedchain/models/__init__.py
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embedchain/embedchain/models/__init__.py
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from .embedding_functions import EmbeddingFunctions # noqa: F401
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from .providers import Providers # noqa: F401
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from .vector_dimensions import VectorDimensions # noqa: F401
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embedchain/embedchain/models/data_type.py
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embedchain/embedchain/models/data_type.py
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from enum import Enum
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class DirectDataType(Enum):
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"""
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DirectDataType enum contains data types that contain raw data directly.
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"""
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TEXT = "text"
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class IndirectDataType(Enum):
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"""
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IndirectDataType enum contains data types that contain references to data stored elsewhere.
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"""
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YOUTUBE_VIDEO = "youtube_video"
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PDF_FILE = "pdf_file"
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WEB_PAGE = "web_page"
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SITEMAP = "sitemap"
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XML = "xml"
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DOCX = "docx"
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DOCS_SITE = "docs_site"
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NOTION = "notion"
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CSV = "csv"
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MDX = "mdx"
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IMAGE = "image"
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UNSTRUCTURED = "unstructured"
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JSON = "json"
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OPENAPI = "openapi"
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GMAIL = "gmail"
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SUBSTACK = "substack"
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YOUTUBE_CHANNEL = "youtube_channel"
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DISCORD = "discord"
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CUSTOM = "custom"
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RSSFEED = "rss_feed"
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BEEHIIV = "beehiiv"
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GOOGLE_DRIVE = "google_drive"
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DIRECTORY = "directory"
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SLACK = "slack"
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DROPBOX = "dropbox"
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TEXT_FILE = "text_file"
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EXCEL_FILE = "excel_file"
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AUDIO = "audio"
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class SpecialDataType(Enum):
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"""
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SpecialDataType enum contains data types that are neither direct nor indirect, or simply require special attention.
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"""
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QNA_PAIR = "qna_pair"
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class DataType(Enum):
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TEXT = DirectDataType.TEXT.value
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YOUTUBE_VIDEO = IndirectDataType.YOUTUBE_VIDEO.value
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PDF_FILE = IndirectDataType.PDF_FILE.value
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WEB_PAGE = IndirectDataType.WEB_PAGE.value
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SITEMAP = IndirectDataType.SITEMAP.value
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XML = IndirectDataType.XML.value
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DOCX = IndirectDataType.DOCX.value
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DOCS_SITE = IndirectDataType.DOCS_SITE.value
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NOTION = IndirectDataType.NOTION.value
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CSV = IndirectDataType.CSV.value
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MDX = IndirectDataType.MDX.value
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QNA_PAIR = SpecialDataType.QNA_PAIR.value
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IMAGE = IndirectDataType.IMAGE.value
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UNSTRUCTURED = IndirectDataType.UNSTRUCTURED.value
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JSON = IndirectDataType.JSON.value
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OPENAPI = IndirectDataType.OPENAPI.value
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GMAIL = IndirectDataType.GMAIL.value
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SUBSTACK = IndirectDataType.SUBSTACK.value
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YOUTUBE_CHANNEL = IndirectDataType.YOUTUBE_CHANNEL.value
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DISCORD = IndirectDataType.DISCORD.value
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CUSTOM = IndirectDataType.CUSTOM.value
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RSSFEED = IndirectDataType.RSSFEED.value
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BEEHIIV = IndirectDataType.BEEHIIV.value
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GOOGLE_DRIVE = IndirectDataType.GOOGLE_DRIVE.value
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DIRECTORY = IndirectDataType.DIRECTORY.value
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SLACK = IndirectDataType.SLACK.value
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DROPBOX = IndirectDataType.DROPBOX.value
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TEXT_FILE = IndirectDataType.TEXT_FILE.value
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EXCEL_FILE = IndirectDataType.EXCEL_FILE.value
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AUDIO = IndirectDataType.AUDIO.value
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embedchain/embedchain/models/embedding_functions.py
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embedchain/embedchain/models/embedding_functions.py
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from enum import Enum
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class EmbeddingFunctions(Enum):
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OPENAI = "OPENAI"
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HUGGING_FACE = "HUGGING_FACE"
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VERTEX_AI = "VERTEX_AI"
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GPT4ALL = "GPT4ALL"
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OLLAMA = "OLLAMA"
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embedchain/embedchain/models/providers.py
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embedchain/embedchain/models/providers.py
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from enum import Enum
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class Providers(Enum):
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OPENAI = "OPENAI"
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ANTHROPHIC = "ANTHPROPIC"
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VERTEX_AI = "VERTEX_AI"
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GPT4ALL = "GPT4ALL"
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OLLAMA = "OLLAMA"
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AZURE_OPENAI = "AZURE_OPENAI"
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embedchain/embedchain/models/vector_dimensions.py
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embedchain/embedchain/models/vector_dimensions.py
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from enum import Enum
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# vector length created by embedding fn
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class VectorDimensions(Enum):
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GPT4ALL = 384
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OPENAI = 1536
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VERTEX_AI = 768
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HUGGING_FACE = 384
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GOOGLE_AI = 768
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MISTRAL_AI = 1024
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NVIDIA_AI = 1024
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COHERE = 384
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OLLAMA = 384
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