Datasets:

jkorstad
/

ragatool-hermes-index

Error code:   StreamingRowsError
Exception:    ArrowInvalid
Message:      JSON parse error: Invalid value. in row 0
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 324, in _generate_tables
                  df = pandas_read_json(f)
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 38, in pandas_read_json
                  return pd.read_json(path_or_buf, **kwargs)
                         ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 791, in read_json
                  json_reader = JsonReader(
                      path_or_buf,
                  ...<16 lines>...
                      engine=engine,
                  )
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 905, in __init__
                  self.data = self._preprocess_data(data)
                              ~~~~~~~~~~~~~~~~~~~~~^^^^^^
                File "/usr/local/lib/python3.14/site-packages/pandas/io/json/_json.py", line 917, in _preprocess_data
                  data = data.read()
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 839, in read_with_retries
                  out = read(*args, **kwargs)
                File "<frozen codecs>", line 325, in decode
              UnicodeDecodeError: 'utf-8' codec can't decode byte 0xa4 in position 7: invalid start byte
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 327, in _generate_tables
                  raise e
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
                  pa_table = paj.read_json(
                      io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
                  )
                File "pyarrow/_json.pyx", line 364, in pyarrow._json.read_json
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
                  raise convert_status(status)
              pyarrow.lib.ArrowInvalid: JSON parse error: Invalid value. in row 0

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RAG-A-TOOL v0 — Approved-Tools Retrieval Index

Tool-retrieval index for RAG-A-TOOL: an agent-facing find_tools service that embeds a task description, matches it against an approved-tool corpus, and returns the top-k tools — with a planned generative fallback (auto-generated tools gated by testing, security scanning, and human approval) when nothing in the pool matches.

What's inside

Config	Contents
`corpus`	Raw tool corpus: 105 tools extracted from NousResearch/hermes-agent (~94 built-ins) and hermes-official-plugins (spotify ×7, homeassistant ×4). Fields: `source`, `toolset`, `name`, `schema` (OpenAI-style JSON schema), `requires_env`, `doc` (self-contained plain-text doc).
`index`	The same rows plus `flags` (poisoning-scan results) and `embedding` — 1024-dim float32 vectors from Qwen/Qwen3-Embedding-0.6B, whole-doc embedding (no chunking; tool docs are short, median ~870 chars).

Toolsets covered (37): browser (11), kanban (15), desktop_ui (11), file, terminal, web, memory, todo, cronjob, delegation, vision, image_gen, tts, video_gen, discord, feishu_doc/drive, homeassistant, spotify, google_meet, a2a, skills, and more.

Poisoning scan

Heuristic MCPTox-style scan over tool descriptions (instruction-override, credential-exfiltration, role-injection, raw-network-command, suspicious URLs, base64 blobs) — flags only, nothing dropped. v0 corpus: 4/105 flagged, all contains-url false positives on legitimate docs (e.g. "only meet.google.com URLs accepted"). Flags ride along in the index for the human-review queue.

Serving

Query ingestion runs in the public MCP Space jkorstad/ragatool-mcp (tool: find_tools) — any MCP client can call it.

Method references

Tool-DE: doc expansion + tuned Qwen3 embedders/rerankers for tool retrieval — https://arxiv.org/abs/2510.22670
ToolRet: tool-retrieval benchmark (43k tools) — https://arxiv.org/abs/2503.01763
Qwen3 Embedding — https://arxiv.org/abs/2506.05176
ScaleMCP: dynamically synced MCP-server embedding index — https://arxiv.org/abs/2505.06416
LATM (tools as generated + verified artifacts) — https://arxiv.org/abs/2305.17126