_pkgdown.yml

url: https://farach.github.io/huggingfaceR/

template:
  bootstrap: 5
  light-switch: true
  bslib:
    primary: "#FFD21E"
    bg: "#FFFFFF"
    fg: "#1A1A2E"
    border-color: "#E5E5E5"
    code-bg: "#F8F9FA"
    base_font:
      google: "Inter"
    heading_font:
      google: "Inter"
    code_font:
      google: "JetBrains Mono"
  includes:
    in_header: |
      <link rel="icon" type="image/svg+xml" href="favicon/favicon.svg">
      <meta property="og:image" content="https://farach.github.io/huggingfaceR/logo.svg">
      <meta name="twitter:card" content="summary">
  opengraph:
    twitter:
      site: "@huggingface"

navbar:
  bg: dark
  structure:
    left:  [intro, reference, articles, news]
    right: [search, github, lightswitch]
  components:
    articles:
      text: Articles
      icon: fa-book-open
      menu:
        - text: "Getting Started"
        - text: Getting Started with huggingfaceR
          href: articles/getting-started.html
        - text: "---"
        - text: "Core Capabilities"
        - text: Text Classification
          href: articles/text-classification.html
        - text: Embeddings and Similarity
          href: articles/embeddings-and-similarity.html
        - text: Chat and Generation
          href: articles/llm-chat-and-generation.html
        - text: "---"
        - text: "Advanced Workflows"
        - text: Hub, Datasets, and Modeling
          href: articles/hub-datasets-and-modeling.html
        - text: "---"
        - text: "Case Studies"
        - text: Anthropic Economic Index
          href: articles/anthropic-economic-index.html
        - text: OpenAI GDPval Benchmark
          href: articles/openai-gdpval-benchmark.html

footer:
  structure:
    left: [developed_by]
    right: [built_with]
  components:
    built_with: "Built with [pkgdown](https://pkgdown.r-lib.org/) | [View on GitHub](https://github.com/farach/huggingfaceR)"

home:
  title: "huggingfaceR - API-first ML for R"
  description: >
    Access machine learning models, embeddings, and datasets on the Hugging Face
    Hub from R via the Inference API. No Python required.
  sidebar:
    structure: [links, license, community, dev]
  links:
  - text: Report an issue
    href: https://github.com/farach/huggingfaceR/issues
  - text: Hugging Face Hub
    href: https://huggingface.co

reference:
  - title: "Authentication"
    desc: "Set up and verify your Hugging Face API token."
    contents:
      - hf_set_token
      - hf_whoami

  - title: "Text Classification"
    desc: "Classify text using pre-trained models or custom label sets."
    contents:
      - hf_classify
      - hf_classify_zero_shot

  - title: "Embeddings and Similarity"
    desc: "Generate vector representations and measure semantic relatedness."
    contents:
      - hf_embed
      - hf_similarity
      - hf_embed_umap

  - title: "Tidytext Integration"
    desc: "Embed, search, cluster, and extract topics from data frames."
    contents:
      - hf_embed_text
      - hf_nearest_neighbors
      - hf_cluster_texts
      - hf_extract_topics

  - title: "Batch Processing"
    desc: "Process large datasets with parallel requests and disk checkpointing."
    contents:
      - hf_embed_batch
      - hf_embed_chunks
      - hf_classify_batch
      - hf_classify_chunks
      - hf_classify_zero_shot_batch
      - hf_read_chunks

  - title: "Chat and Conversations"
    desc: "Interact with open-source language models."
    contents:
      - hf_chat
      - hf_conversation
      - chat

  - title: "Text Generation"
    desc: "Generate and complete text with language models."
    contents:
      - hf_generate
      - hf_fill_mask

  - title: "Hub Discovery"
    desc: "Search models, check inference availability, and explore datasets."
    contents:
      - hf_search_models
      - hf_model_info
      - hf_check_inference
      - hf_list_tasks
      - hf_search_datasets
      - hf_dataset_info

  - title: "Datasets"
    desc: "Load dataset rows from the Hub into tibbles."
    contents:
      - hf_load_dataset

  - title: "Tidymodels"
    desc: "Use embeddings as features in tidymodels recipes."
    contents:
      - step_hf_embed

  - title: "Legacy Functions"
    desc: "Functions from earlier versions. These may require Python/reticulate."
    contents:
      - starts_with("hf_ez_")
      - hf_load_tokenizer
      - hf_load_model
      - hf_load_AutoModel_for_task
      - hf_load_pipeline
      - hf_load_sentence_model
      - hf_list_authors
      - hf_list_datasets
      - hf_list_languages
      - hf_list_libraries
      - hf_list_licenses
      - hf_list_models
      - hf_inference
      - hf_sentence_encode
      - hf_set_device
      - hf_python_depends
      - ends_with("_payload")
      - models_with_downloads
      - "%>%"

articles:
  - title: "Getting Started"
    contents:
      - getting-started
  - title: "Core Capabilities"
    contents:
      - text-classification
      - embeddings-and-similarity
      - llm-chat-and-generation
  - title: "Advanced Workflows"
    contents:
      - hub-datasets-and-modeling
  - title: "Case Studies"
    contents:
      - anthropic-economic-index
      - openai-gdpval-benchmark

repo:
  url:
    home: https://github.com/farach/huggingfaceR/
    source: https://github.com/farach/huggingfaceR/blob/main/