Package index • EndpointR

Getting Started

Essential functions for setting up and managing API keys

set_api_key(): Set your API keys so they can be accessed by EndpointR
get_api_key(): Retrieve an API key which has been stored as an Environment Variable.

Functions for generating text embeddings using Hugging Face endpoints

hf_embed_text(): Generate embeddings for a single text
hf_embed_batch(): Generate batches of embeddings for a list of texts
hf_embed_chunks(): Embed text chunks through Hugging Face Inference Embedding Endpoints
hf_embed_df(): Generate embeddings for texts in a data frame
tidy_embedding_response(): Process embedding API response into a tidy format

Functions for classifying text using Hugging Face endpoints

hf_classify_text(): Classify text using a Hugging Face Inference API endpoint
hf_classify_batch(): Classify multiple texts using Hugging Face Inference Endpoints
hf_classify_chunks(): Efficiently classify vectors of text in chunks
hf_classify_df(): Classify a data frame of texts using Hugging Face Inference Endpoints
tidy_classification_response(): Convert Hugging Face classification response to tidy format

Low-level functions for building and performing Hugging Face requests

hf_build_request(): Prepare a single text embedding request
hf_build_request_batch(): Prepare a batch request for multiple texts
hf_build_request_df(): Prepare embedding requests for texts in a data frame
hf_perform_request(): Execute a single embedding request and process the response

Functions for checking Hugging Face API endpoints

hf_get_endpoint_info(): Retrieve information about an endpoint
hf_get_model_max_length(): Check the max number of tokens allowed for your inputs

Functions for working with Anthropic’s Messages API

ant_build_messages_request(): Build an Anthropic Messages API request
ant_complete_text(): Generate a completion for a single text using Anthropic's Messages API
ant_complete_chunks(): Process text chunks through Anthropic's Messages API with batch file output
ant_complete_df(): Process a data frame through Anthropic's Messages API

Functions for working with OpenAI’s APIs including structured outputs

oai_build_completions_request(): Build an OpenAI API Chat Completions request
oai_build_completions_request_list(): Build OpenAI requests for batch processing
oai_complete_text(): Generate a completion for a single text using OpenAI's Chat Completions API
oai_complete_chunks(): Process text chunks through OpenAI's Chat Completions API with batch file output
oai_complete_df(): Process a data frame through OpenAI's Chat Completions API with chunked processing

Functions for extracting embeddings with OpenAI’s text embedding models

oai_build_embedding_request(): Build OpenAI embedding API request
oai_embed_text(): Generate embeddings for a single text using OpenAI
oai_embed_batch(): Generate embeddings for multiple texts using OpenAI
oai_embed_chunks(): Embed text chunks through OpenAI's Embeddings API
oai_embed_df(): Generate embeddings for texts in a data frame using OpenAI
tidy_oai_embedding(): Process OpenAI embedding API response into a tidy format

Type-safe schema creation and validation for structured LLM outputs

Helper functions for creating different types of JSON schema properties

Internal utility functions and data processing helpers

safely_perform_request(): Safely perform an embedding request with error handling
chunk_dataframe(): Split a data frame into chunks for batch processing
perform_requests_with_strategy(): Perform multiple requests with configurable concurrency strategy
process_response(): Process API response with error handling
hf_perform_request(): Execute a single embedding request and process the response
validate_hf_endpoint(): Validate that a Hugging Face Inference Endpoint is available
base_request(): Create a base HTTP POST request for API endpoints
safely_from_json(): Safely extract JSON

Datasets included with the package for examples and testing

batch_concurrent_benchmark: Batch concurrent benchmark results
sentiment_classification_example: Single sentiment classification result example
df_sentiment_classification_example: Example sentiment classification results from Hugging Face API
single_embedding_hf: Single embedding result example from Hugging Face API
df_embeddings_hf: Example embedding results from Hugging Face API