diff --git a/docs/docs/components/embeddings.mdx b/docs/docs/components/embeddings.mdx index 5b134f08d..1b7ca1dbe 100644 --- a/docs/docs/components/embeddings.mdx +++ b/docs/docs/components/embeddings.mdx @@ -12,6 +12,22 @@ Embeddings are vector representations of text that capture the semantic meaning --- +### BedrockEmbeddings + +Used to load [Amazon Bedrocks’s](https://aws.amazon.com/bedrock/) embedding models. + +**Params** + +- **credentials_profile_name:** The name of the profile in the ~/.aws/credentials or ~/.aws/config files, which has either access keys or role information specified. If not specified, the default credential profile or, if on an EC2 instance, credentials from IMDS will be used. See [the AWS documentation](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html) for more details. + +- **model_id:** Id of the model to call, e.g., amazon.titan-embed-text-v1, this is equivalent to the modelId property in the list-foundation-models api. + +- **endpoint_url:** Needed if you don’t want to default to us-east-1 endpoint. + +- **region_name:** The aws region e.g., us-west-2. Fallsback to AWS_DEFAULT_REGION env variable or region specified in ~/.aws/config in case it is not provided here. + +--- + ### CohereEmbeddings Used to load [Cohere’s](https://cohere.com/) embedding models. diff --git a/poetry.lock b/poetry.lock index ca30f2d11..d90908427 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand. 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"traitlets-5.13.0-py3-none-any.whl", hash = "sha256:baf991e61542da48fe8aef8b779a9ea0aa38d8a54166ee250d5af5ecf4486619"}, - {file = "traitlets-5.13.0.tar.gz", hash = "sha256:9b232b9430c8f57288c1024b34a8f0251ddcc47268927367a0dd3eeaca40deb5"}, + {file = "traitlets-5.11.2-py3-none-any.whl", hash = "sha256:98277f247f18b2c5cabaf4af369187754f4fb0e85911d473f72329db8a7f4fae"}, + {file = "traitlets-5.11.2.tar.gz", hash = "sha256:7564b5bf8d38c40fa45498072bf4dc5e8346eb087bbf1e2ae2d8774f6a0f078e"}, ] [package.extras] @@ -7944,13 +7951,13 @@ files = [ [[package]] name = "unstructured" -version = "0.10.28" +version = "0.10.24" description = "A library that prepares raw documents for downstream ML tasks." optional = false python-versions = ">=3.7.0" files = [ - {file = "unstructured-0.10.28-py3-none-any.whl", hash = "sha256:0965567c2477c5a926517a295fd0318c2823a603d79c6f47f2bbe58f5aacb89e"}, - {file = "unstructured-0.10.28.tar.gz", hash = "sha256:c995015c5d51d4732f2aa49663eebac4aacf51d7e905c8f240d14ff2269d392f"}, + {file = "unstructured-0.10.24-py3-none-any.whl", hash = "sha256:19bcc5392f2df517a8d2807e338a363025de5e52a9e0b8289ccbe4bc7f08c117"}, + {file = "unstructured-0.10.24.tar.gz", hash = "sha256:c991daf72cce18bcd09535e2e29cd3ff463bb7ab66206e181b1a9f5ced5cf82f"}, ] [package.dependencies] @@ -7973,7 +7980,7 @@ typing-extensions = "*" [package.extras] airtable = ["pyairtable"] -all-docs = ["markdown", "msg-parser", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pypandoc", "python-docx (>=1.0.1)", "python-pptx (<=0.6.21)", "unstructured-inference (==0.7.10)", "unstructured.pytesseract (>=0.3.12)", "xlrd"] +all-docs = ["ebooklib", "markdown", "msg-parser", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pypandoc", "python-docx (>=1.0.1)", "python-pptx (<=0.6.21)", "unstructured-inference (==0.7.7)", "unstructured.pytesseract (>=0.3.12)", "xlrd"] azure = ["adlfs", "fsspec (==2023.9.1)"] azure-cognitive-search = ["azure-search-documents"] bedrock = ["boto3", "langchain"] @@ -7987,8 +7994,7 @@ doc = ["python-docx (>=1.0.1)"] docx = ["python-docx (>=1.0.1)"] dropbox = ["dropboxdrivefs", "fsspec (==2023.9.1)"] elasticsearch = ["elasticsearch", "jq"] -embed-huggingface = ["huggingface", "langchain", "sentence-transformers"] -epub = ["pypandoc"] +epub = ["ebooklib"] gcs = ["bs4", "fsspec (==2023.9.1)", "gcsfs"] github = ["pygithub (>1.58.0)"] gitlab = ["python-gitlab"] @@ -7996,7 +8002,7 @@ google-drive = ["google-api-python-client"] huggingface = ["langdetect", "sacremoses", "sentencepiece", "torch", "transformers"] image = ["onnx", "pdf2image", "pdfminer.six", "unstructured-inference (==0.7.10)", "unstructured.pytesseract (>=0.3.12)"] jira = ["atlassian-python-api"] -local-inference = ["markdown", "msg-parser", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pypandoc", "python-docx (>=1.0.1)", "python-pptx (<=0.6.21)", "unstructured-inference (==0.7.10)", "unstructured.pytesseract (>=0.3.12)", "xlrd"] +local-inference = ["ebooklib", "markdown", "msg-parser", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pypandoc", "python-docx (>=1.0.1)", "python-pptx (<=0.6.21)", "unstructured-inference (==0.7.7)", "unstructured.pytesseract (>=0.3.12)", "xlrd"] md = ["markdown"] msg = ["msg-parser"] notion = ["htmlBuilder", "notion-client"] diff --git a/src/backend/langflow/components/embeddings/AmazonBedrockEmbeddings.py b/src/backend/langflow/components/embeddings/AmazonBedrockEmbeddings.py new file mode 100644 index 000000000..6efa22961 --- /dev/null +++ b/src/backend/langflow/components/embeddings/AmazonBedrockEmbeddings.py @@ -0,0 +1,46 @@ +from typing import Optional +from langflow import CustomComponent + +from langchain.embeddings import BedrockEmbeddings +from langchain.embeddings.base import Embeddings + + +class AmazonBedrockEmeddingsComponent(CustomComponent): + """ + A custom component for implementing an Embeddings Model using Amazon Bedrock. + """ + + display_name: str = "Amazon Bedrock Embeddings" + description: str = "Embeddings model from Amazon Bedrock." + documentation = "https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/bedrock" + beta = True + + def build_config(self): + return { + "model_id": { + "display_name": "Model Id", + "options": ["amazon.titan-embed-text-v1"], + }, + "credentials_profile_name": {"display_name": "Credentials Profile Name"}, + "endpoint_url": {"display_name": "Bedrock Endpoint URL"}, + "region_name": {"display_name": "AWS Region"}, + "code": {"show": False}, + } + + def build( + self, + model_id: str = "amazon.titan-embed-text-v1", + credentials_profile_name: Optional[str] = None, + endpoint_url: Optional[str] = None, + region_name: Optional[str] = None, + ) -> Embeddings: + try: + output = BedrockEmbeddings( + credentials_profile_name=credentials_profile_name, + model_id=model_id, + endpoint_url=endpoint_url, + region_name=region_name, + ) # type: ignore + except Exception as e: + raise ValueError("Could not connect to AmazonBedrock API.") from e + return output diff --git a/src/backend/langflow/components/embeddings/__init__.py b/src/backend/langflow/components/embeddings/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/src/backend/langflow/config.yaml b/src/backend/langflow/config.yaml index 421144a3a..31bab1ca8 100644 --- a/src/backend/langflow/config.yaml +++ b/src/backend/langflow/config.yaml @@ -106,6 +106,9 @@ embeddings: documentation: "https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/cohere" VertexAIEmbeddings: documentation: "https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/google_vertex_ai_palm" + AmazonBedrockEmbeddings: + documentation: "https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/bedrock" + llms: OpenAI: documentation: "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/openai" diff --git a/src/frontend/src/icons/AWS/AWS.jsx b/src/frontend/src/icons/AWS/AWS.jsx new file mode 100644 index 000000000..f79821431 --- /dev/null +++ b/src/frontend/src/icons/AWS/AWS.jsx @@ -0,0 +1,31 @@ +const SvgAWS = (props) => ( + + + + + + +); +export default SvgAWS; diff --git a/src/frontend/src/icons/AWS/AWS.svg b/src/frontend/src/icons/AWS/AWS.svg new file mode 100644 index 000000000..4715937ff --- /dev/null +++ b/src/frontend/src/icons/AWS/AWS.svg @@ -0,0 +1,38 @@ + + + + + + + + + + + + diff --git a/src/frontend/src/icons/AWS/index.tsx b/src/frontend/src/icons/AWS/index.tsx new file mode 100644 index 000000000..caedd54aa --- /dev/null +++ b/src/frontend/src/icons/AWS/index.tsx @@ -0,0 +1,8 @@ +import React, { forwardRef } from "react"; +import SvgAWS from "./AWS"; + +export const AWSIcon = forwardRef>( + (props, ref) => { + return ; + } +); diff --git a/src/frontend/src/utils/styleUtils.ts b/src/frontend/src/utils/styleUtils.ts index 873d4c9e2..86011f6e0 100644 --- a/src/frontend/src/utils/styleUtils.ts +++ b/src/frontend/src/utils/styleUtils.ts @@ -87,6 +87,7 @@ import { Zap, } from "lucide-react"; import { FaApple, FaGithub } from "react-icons/fa"; +import { AWSIcon } from "../icons/AWS"; import { AirbyteIcon } from "../icons/Airbyte"; import { AnthropicIcon } from "../icons/Anthropic"; import { BingIcon } from "../icons/Bing"; @@ -199,6 +200,7 @@ export const nodeIconsLucide: iconsType = { ArrowUpToLine: ArrowUpToLine, Chroma: ChromaIcon, AirbyteJSONLoader: AirbyteIcon, + AmazonBedrockEmbeddings: AWSIcon, Anthropic: AnthropicIcon, ChatAnthropic: AnthropicIcon, BingSearchAPIWrapper: BingIcon,