--- title: HF Buckets description: Mount Hugging Face Buckets as a Mirage filesystem with async reads and S3-compatible writes for Python agents. icon: /images/huggingface-logo.svg --- The HF Buckets resource mounts a [Hugging Face Bucket](https://huggingface.co/docs/buckets) at some prefix such as `/hf/`. Speaks HF's HTTP API natively (async, streaming, no Python SDK dependency). For credential setup, see [HF Buckets Setup](/home/setup/hf_buckets). ## Install ```bash uv add "mirage-ai[hf]" ``` ## Config ```python import os from mirage import MountMode, Workspace from mirage.resource.hf_buckets import HfBucketsConfig, HfBucketsResource config = HfBucketsConfig( bucket=os.environ["HF_BUCKET_NAME"], # "namespace/bucket-name" token=os.environ["HF_TOKEN"], # Optional: # endpoint="https://huggingface.co", # timeout=30, # key_prefix="data/", ) resource = HfBucketsResource(config) ws = Workspace({"/hf": resource}, mode=MountMode.READ) ``` `HfBucketsResource(config)` takes an `HfBucketsConfig` object with the bucket in `namespace/bucket-name` form plus an optional access token. Both `READ` and `WRITE` modes are supported out of the box. ## Filesystem Layout The HF Buckets resource maps bucket object keys to virtual paths under the mount prefix. For example, if bucket `your-user/my-data` contains: ```text data/file.txt data/config.json reports/q1.csv reports/q2.csv ``` Then mounting at `/hf/` exposes: ```text /hf/ data/ file.txt config.json reports/ q1.csv q2.csv ``` Path mapping: virtual `/hf/data/file.txt` maps to bucket key `data/file.txt`. ## Cache The HF Buckets resource uses `IndexCacheStore` with `index_ttl = 600` (10 minutes). Directory listings are cached and populate file-size/type entries that `stat` reads via a fast path, so a `readdir` followed by per-entry `stat` calls (which is what `ls`, FUSE `getattr`, and most shell commands trigger) costs one HTTP request instead of N. ## Example ```python import asyncio import os from dotenv import load_dotenv from mirage import MountMode, Workspace from mirage.resource.hf_buckets import HfBucketsConfig, HfBucketsResource load_dotenv(".env.development") config = HfBucketsConfig( bucket=os.environ["HF_BUCKET_NAME"], token=os.environ["HF_TOKEN"], ) resource = HfBucketsResource(config) async def main() -> None: ws = Workspace({"/hf/": resource}, mode=MountMode.READ) r = await ws.execute("ls /hf/") print(await r.stdout_str()) r = await ws.execute("cat /hf/data/file.txt") print(await r.stdout_str()) r = await ws.execute("tree /hf/") print(await r.stdout_str()) r = await ws.execute("find /hf/ -name '*.json'") print(await r.stdout_str()) r = await ws.execute("grep example /hf/data/config.json") print(await r.stdout_str()) r = await ws.execute("stat /hf/data/file.txt") print(await r.stdout_str()) if __name__ == "__main__": asyncio.run(main()) ``` ## Shell Commands The HF Buckets resource supports the full set of shell commands since it operates on real file content (text, binary, JSON, CSV, etc.). Large files benefit from range reads to avoid downloading entire objects. ### Read Commands | Command | Notes | | --------------- | ------------------------------------------ | | `cat` | Read file content | | `head` / `tail` | First/last N lines | | `grep` / `rg` | Pattern search (file or directory level) | | `jq` | Query JSON fields | | `wc` | Line/word/byte counts | | `stat` | File metadata (name, size, type, modified) | | `find` | Recursive search with `-name`, `-maxdepth` | | `tree` | Directory tree view | | `nl` | Number lines | | `du` | Disk usage summary | | `file` | Detect file type | | `strings` | Extract printable strings from binary | | `xxd` | Hex dump | | `md5` | MD5 checksum | | `sha256sum` | SHA-256 checksum | ### Text Processing | Command | Notes | | ---------- | ------------------------------------------- | | `awk` | Pattern scanning and processing | | `sed` | Stream editor | | `tr` | Translate or delete characters | | `sort` | Sort lines | | `uniq` | Remove duplicate lines | | `cut` | Extract fields/columns | | `join` | Join lines on a common field | | `paste` | Merge lines side by side | | `column` | Columnate output | | `fold` | Wrap lines to a specified width | | `expand` | Convert tabs to spaces | | `unexpand` | Convert spaces to tabs | | `fmt` | Simple text formatter | | `rev` | Reverse lines | | `tac` | Concatenate and print in reverse | | `look` | Display lines beginning with a given string | | `shuf` | Shuffle lines | | `tsort` | Topological sort | | `comm` | Compare two sorted files | | `cmp` | Compare two files byte by byte | | `diff` | Compare files line by line | | `iconv` | Character encoding conversion | ### File Operations | Command | Notes | | -------- | ------------------------------------- | | `rm` | Remove files | | `touch` | Create empty file or update timestamp | | `mktemp` | Create temporary file | | `split` | Split file into pieces | | `csplit` | Split file by context | ### Path Utilities | Command | Notes | | ---------- | -------------------------- | | `basename` | Strip directory from path | | `dirname` | Strip filename from path | | `realpath` | Resolve path | | `readlink` | Print symbolic link target | | `ls` | List directory contents | ### Compression | Command | Notes | | -------- | --------------------- | | `gzip` | Compress files | | `gunzip` | Decompress gzip files | | `zip` | Create zip archives | | `unzip` | Extract zip archives | | `tar` | Archive files | | `zcat` | Cat compressed files | | `zgrep` | Grep compressed files | ### Encoding | Command | Notes | | -------- | -------------------- | | `base64` | Base64 encode/decode | ### Data Format Support Commands with format-specific variants for structured data files: | Format | Extension | Variants | | ------- | ---------- | ---------------------------------------------- | | Parquet | `.parquet` | cat, head, tail, wc, stat, cut, grep, ls, file | | Feather | `.feather` | cat, head, tail, wc, stat, cut, grep, ls, file | | ORC | `.orc` | cat, head, tail, wc, stat, cut, grep, ls, file | | HDF5 | `.hdf5` | cat, head, tail, wc, stat, cut, grep, ls, file | These variants auto-detect the format by extension and convert to tabular text (CSV) for processing. ## Use Cases - **AI agents accessing HF datasets**: Mount HF Buckets for agents to read and process datasets stored on the Hub - **Data pipelines**: Read and write HF bucket objects with shell-like commands - **Sandboxed bucket access**: Restrict agent operations to a specific bucket and prefix - **FUSE mounting**: Expose HF Buckets through a virtual FUSE mount for external tools ## Scoping a resource to a key prefix Pass `key_prefix: str | None = None` to `HfBucketsConfig` to transparently scope every operation to a subpath of the bucket: ```python HfBucketsResource(HfBucketsConfig( bucket="your-user/app-data", token=hf_token, key_prefix=f"users/{user_id}/", )) ``` When set, every read/write/list/stat operation is transparently scoped to that bucket subpath. Agents see clean paths like `/data/notes.md`; the underlying bucket key is `users/{user_id}/data/notes.md`. Useful for multi-tenant systems. **Normalization:** leading slashes are stripped and a trailing slash is added automatically. Both `None` and an empty string are treated as "no prefix."