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langflow/docs/docs/components/embeddings.mdx
Lucas Oliveira 9b88eab828 Added warning of outdated information to all components
2024-06-24 04:37:06 -07:00

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import Admonition from "@theme/Admonition";
# Embeddings
<Admonition type="warning" title="warning">
This page may contain outdated information. It will be updated as soon as possible.
</Admonition>
## Amazon Bedrock Embeddings
Used to load embedding models from [Amazon Bedrock](https://aws.amazon.com/bedrock/).
| **Parameter** | **Type** | **Description** | **Default** |
| -------------------------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------------- | ----------- |
| `credentials_profile_name` | `str` | Name of the AWS credentials profile in ~/.aws/credentials or ~/.aws/config, which has access keys or role information. | |
| `model_id` | `str` | 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` | `str` | URL to set a specific service endpoint other than the default AWS endpoint. | |
| `region_name` | `str` | AWS region to use, e.g., `us-west-2`. Falls back to `AWS_DEFAULT_REGION` environment variable or region specified in ~/.aws/config if not provided. | |
## Astra vectorize
Used to generate server-side embeddings using [DataStax Astra](https://docs.datastax.com/en/astra-db-serverless/databases/embedding-generation.html).
| **Parameter** | **Type** | **Description** | **Default** |
|--------------------|----------|-----------------------------------------------------------------------------------------------------------------------|-------------|
| `provider` | `str` | The embedding provider to use. | |
| `model_name` | `str` | The embedding model to use. | |
| `authentication` | `dict` | Authentication parameters. Use the Astra Portal to add the embedding provider integration to your Astra organization. | |
| `provider_api_key` | `str` | An alternative to the Astra Authentication that let you use directly the API key of the provider. | |
| `model_parameters` | `dict` | Additional model parameters. | |
## Cohere Embeddings
Used to load embedding models from [Cohere](https://cohere.com/).
| **Parameter** | **Type** | **Description** | **Default** |
| ---------------- | -------- | ------------------------------------------------------------------------- | -------------------- |
| `cohere_api_key` | `str` | API key required to authenticate with the Cohere service. | |
| `model` | `str` | Language model used for embedding text documents and performing queries. | `embed-english-v2.0` |
| `truncate` | `bool` | Whether to truncate the input text to fit within the model's constraints. | `False` |
## Azure OpenAI Embeddings
Generate embeddings using Azure OpenAI models.
| **Parameter** | **Type** | **Description** | **Default** |
| ----------------- | -------- | -------------------------------------------------------------------------------------------------- | ----------- |
| `Azure Endpoint` | `str` | Your Azure endpoint, including the resource. Example: `https://example-resource.azure.openai.com/` | |
| `Deployment Name` | `str` | The name of the deployment. | |
| `API Version` | `str` | The API version to use, options include various dates. | |
| `API Key` | `str` | The API key to access the Azure OpenAI service. | |
## Hugging Face API Embeddings
Generate embeddings using Hugging Face Inference API models.
| **Parameter** | **Type** | **Description** | **Default** |
| --------------- | -------- | ----------------------------------------------------- | ------------------------ |
| `API Key` | `str` | API key for accessing the Hugging Face Inference API. | |
| `API URL` | `str` | URL of the Hugging Face Inference API. | `http://localhost:8080` |
| `Model Name` | `str` | Name of the model to use for embeddings. | `BAAI/bge-large-en-v1.5` |
| `Cache Folder` | `str` | Folder path to cache Hugging Face models. | |
| `Encode Kwargs` | `dict` | Additional arguments for the encoding process. | |
| `Model Kwargs` | `dict` | Additional arguments for the model. | |
| `Multi Process` | `bool` | Whether to use multiple processes. | `False` |
## Hugging Face Embeddings
Used to load embedding models from [HuggingFace](https://huggingface.co).
| **Parameter** | **Type** | **Description** | **Default** |
| --------------- | -------- | ---------------------------------------------- | ----------------------------------------- |
| `Cache Folder` | `str` | Folder path to cache HuggingFace models. | |
| `Encode Kwargs` | `dict` | Additional arguments for the encoding process. | |
| `Model Kwargs` | `dict` | Additional arguments for the model. | |
| `Model Name` | `str` | Name of the HuggingFace model to use. | `sentence-transformers/all-mpnet-base-v2` |
| `Multi Process` | `bool` | Whether to use multiple processes. | `False` |
## OpenAI Embeddings
Used to load embedding models from [OpenAI](https://openai.com/).
| **Parameter** | **Type** | **Description** | **Default** |
| -------------------------- | ---------------- | ------------------------------------------------ | ------------------------ |
| `OpenAI API Key` | `str` | The API key to use for accessing the OpenAI API. | |
| `Default Headers` | `Dict[str, str]` | Default headers for the HTTP requests. | |
| `Default Query` | `NestedDict` | Default query parameters for the HTTP requests. | |
| `Allowed Special` | `List[str]` | Special tokens allowed for processing. | `[]` |
| `Disallowed Special` | `List[str]` | Special tokens disallowed for processing. | `["all"]` |
| `Chunk Size` | `int` | Chunk size for processing. | `1000` |
| `Client` | `Any` | HTTP client for making requests. | |
| `Deployment` | `str` | Deployment name for the model. | `text-embedding-3-small` |
| `Embedding Context Length` | `int` | Length of embedding context. | `8191` |
| `Max Retries` | `int` | Maximum number of retries for failed requests. | `6` |
| `Model` | `str` | Name of the model to use. | `text-embedding-3-small` |
| `Model Kwargs` | `NestedDict` | Additional keyword arguments for the model. | |
| `OpenAI API Base` | `str` | Base URL of the OpenAI API. | |
| `OpenAI API Type` | `str` | Type of the OpenAI API. | |
| `OpenAI API Version` | `str` | Version of the OpenAI API. | |
| `OpenAI Organization` | `str` | Organization associated with the API key. | |
| `OpenAI Proxy` | `str` | Proxy server for the requests. | |
| `Request Timeout` | `float` | Timeout for the HTTP requests. | |
| `Show Progress Bar` | `bool` | Whether to show a progress bar for processing. | `False` |
| `Skip Empty` | `bool` | Whether to skip empty inputs. | `False` |
| `TikToken Enable` | `bool` | Whether to enable TikToken. | `True` |
| `TikToken Model Name` | `str` | Name of the TikToken model. | |
## Ollama Embeddings
Generate embeddings using Ollama models.
| **Parameter** | **Type** | **Description** | **Default** |
| ------------------- | -------- | ---------------------------------------------------------------------------------------- | ------------------------ |
| `Ollama Model` | `str` | Name of the Ollama model to use. | `llama2` |
| `Ollama Base URL` | `str` | Base URL of the Ollama API. | `http://localhost:11434` |
| `Model Temperature` | `float` | Temperature parameter for the model. Adjusts the randomness in the generated embeddings. | |
## VertexAI Embeddings
Wrapper around [Google Vertex AI](https://cloud.google.com/vertex-ai) [Embeddings API](https://cloud.google.com/vertex-ai/docs/generative-ai/embeddings/get-text-embeddings).
| **Parameter** | **Type** | **Description** | **Default** |
| --------------------- | ------------- | ------------------------------------------------------------------------------------------------------------------------------------ | ------------- |
| `credentials` | `Credentials` | The default custom credentials to use. | |
| `location` | `str` | The default location to use when making API calls. | `us-central1` |
| `max_output_tokens` | `int` | Token limit determines the maximum amount of text output from one prompt. | `128` |
| `model_name` | `str` | The name of the Vertex AI large language model. | `text-bison` |
| `project` | `str` | The default GCP project to use when making Vertex API calls. | |
| `request_parallelism` | `int` | The amount of parallelism allowed for requests issued to VertexAI models. | `5` |
| `temperature` | `float` | Tunes the degree of randomness in text generations. Should be a non-negative value. | `0` |
| `top_k` | `int` | How the model selects tokens for output, the next token is selected from the top `k` tokens. | `40` |
| `top_p` | `float` | Tokens are selected from the most probable to least until the sum of their probabilities exceeds the top `p` value. | `0.95` |
| `tuned_model_name` | `str` | The name of a tuned model. If provided, `model_name` is ignored. | |
| `verbose` | `bool` | This parameter controls the level of detail in the output. When set to `True`, it prints internal states of the chain to help debug. | `False` |
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