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MikeGreen2710
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hanoi-avm-workspace

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The dataset viewer is not available for this split.

Cannot load the dataset split (in streaming mode) to extract the first rows.

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
id: string
prompt: string
prompt_hash: string
registry_tree: string
extractor: string
extraction: struct<access_reasoning: string, frontage_type: string, frontage_evidence: string, dist_to_main_stre (... 473 chars omitted)
  child 0, access_reasoning: string
  child 1, frontage_type: string
  child 2, frontage_evidence: string
  child 3, dist_to_main_street: string
  child 4, dist_to_car_alley: string
  child 5, dist_to_tricycle_alley: string
  child 6, distance_evidence: string
  child 7, alley_width_m: double
  child 8, alley_width_qualifier: string
  child 9, alley_is_through: bool
  child 10, road_width_m: double
  child 11, road_width_qualifier: string
  child 12, has_sidewalk: bool
  child 13, road_evidence: string
  child 14, access_grade: string
  child 15, access_grade_evidence: string
  child 16, frontage_composition: struct<n_street_faces: int64, n_alley_faces: int64>
      child 0, n_street_faces: int64
      child 1, n_alley_faces: int64
  child 17, n_turns: int64
  child 18, faces_evidence: string
  child 19, alley_is_through_evidence: string
meta: struct<schema: string, ontology: string, fitted_at: timestamp[s], surface: string, n_obs: int64, not (... 10 chars omitted)
  child 0, schema: string
  child 1, ontology: string
  child 2, fitted_at: timestamp[s]
  child 3, surface: string
  child 4, n_obs: int64
  child 5, note: string
coefficients: struct<district:Long Biên: struct<v: double, lo: double, hi: double, n: int64, src: string>, distri (... 4400 chars omi
...
 string>
      child 0, v: double
      child 1, lo: double
      child 2, hi: double
      child 3, n: int64
      child 4, src: string
  child 44, has_sidewalk:1: struct<v: double, lo: double, hi: double, n: int64, src: string>
      child 0, v: double
      child 1, lo: double
      child 2, hi: double
      child 3, n: int64
      child 4, src: string
  child 45, access_grade:truck: struct<v: double, lo: double, hi: double, n: int64, src: string>
      child 0, v: double
      child 1, lo: double
      child 2, hi: double
      child 3, n: int64
      child 4, src: string
  child 46, access_grade:car_two_way: struct<v: double, lo: double, hi: double, n: int64, src: string>
      child 0, v: double
      child 1, lo: double
      child 2, hi: double
      child 3, n: int64
      child 4, src: string
  child 47, access_grade:tricycle: struct<v: double, lo: double, hi: double, n: int64, src: string>
      child 0, v: double
      child 1, lo: double
      child 2, hi: double
      child 3, n: int64
      child 4, src: string
  child 48, access_grade:motorbike: struct<v: double, lo: double, hi: double, n: int64, src: string>
      child 0, v: double
      child 1, lo: double
      child 2, hi: double
      child 3, n: int64
      child 4, src: string
  child 49, access_grade:pedestrian: struct<v: double, lo: double, hi: double, n: int64, src: string>
      child 0, v: double
      child 1, lo: double
      child 2, hi: double
      child 3, n: int64
      child 4, src: string
to
{'meta': {'schema': Value('string'), 'ontology': Value('string'), 'fitted_at': Value('timestamp[s]'), 'surface': Value('string'), 'n_obs': Value('int64'), 'note': Value('string')}, 'coefficients': {'district:Long Biên': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'district:Hai Bà Trưng': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'district:Bắc Từ Liêm': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'district:Hoàn Kiếm': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'district:Đống Đa': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'district:Hà Đông': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'district:Cầu Giấy': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'district:Thanh Xuân': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'district:Ba Đình': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'district:Hoàng Mai': {'v': Value('float64'
...
oat64'), 'n': Value('int64'), 'src': Value('string')}, 'dist_to_main_street:ADJACENT': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'dist_to_main_street:NEAR': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'dist_to_main_street:MODERATE': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'dist_to_main_street:FAR': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'has_sidewalk:1': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'access_grade:truck': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'access_grade:car_two_way': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'access_grade:tricycle': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'access_grade:motorbike': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'access_grade:pedestrian': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}}}
because column names don't match
Traceback:    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 2840, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, 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 536, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, 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 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              id: string
              prompt: string
              prompt_hash: string
              registry_tree: string
              extractor: string
              extraction: struct<access_reasoning: string, frontage_type: string, frontage_evidence: string, dist_to_main_stre (... 473 chars omitted)
                child 0, access_reasoning: string
                child 1, frontage_type: string
                child 2, frontage_evidence: string
                child 3, dist_to_main_street: string
                child 4, dist_to_car_alley: string
                child 5, dist_to_tricycle_alley: string
                child 6, distance_evidence: string
                child 7, alley_width_m: double
                child 8, alley_width_qualifier: string
                child 9, alley_is_through: bool
                child 10, road_width_m: double
                child 11, road_width_qualifier: string
                child 12, has_sidewalk: bool
                child 13, road_evidence: string
                child 14, access_grade: string
                child 15, access_grade_evidence: string
                child 16, frontage_composition: struct<n_street_faces: int64, n_alley_faces: int64>
                    child 0, n_street_faces: int64
                    child 1, n_alley_faces: int64
                child 17, n_turns: int64
                child 18, faces_evidence: string
                child 19, alley_is_through_evidence: string
              meta: struct<schema: string, ontology: string, fitted_at: timestamp[s], surface: string, n_obs: int64, not (... 10 chars omitted)
                child 0, schema: string
                child 1, ontology: string
                child 2, fitted_at: timestamp[s]
                child 3, surface: string
                child 4, n_obs: int64
                child 5, note: string
              coefficients: struct<district:Long Biên: struct<v: double, lo: double, hi: double, n: int64, src: string>, distri (... 4400 chars omi
              ...
               string>
                    child 0, v: double
                    child 1, lo: double
                    child 2, hi: double
                    child 3, n: int64
                    child 4, src: string
                child 44, has_sidewalk:1: struct<v: double, lo: double, hi: double, n: int64, src: string>
                    child 0, v: double
                    child 1, lo: double
                    child 2, hi: double
                    child 3, n: int64
                    child 4, src: string
                child 45, access_grade:truck: struct<v: double, lo: double, hi: double, n: int64, src: string>
                    child 0, v: double
                    child 1, lo: double
                    child 2, hi: double
                    child 3, n: int64
                    child 4, src: string
                child 46, access_grade:car_two_way: struct<v: double, lo: double, hi: double, n: int64, src: string>
                    child 0, v: double
                    child 1, lo: double
                    child 2, hi: double
                    child 3, n: int64
                    child 4, src: string
                child 47, access_grade:tricycle: struct<v: double, lo: double, hi: double, n: int64, src: string>
                    child 0, v: double
                    child 1, lo: double
                    child 2, hi: double
                    child 3, n: int64
                    child 4, src: string
                child 48, access_grade:motorbike: struct<v: double, lo: double, hi: double, n: int64, src: string>
                    child 0, v: double
                    child 1, lo: double
                    child 2, hi: double
                    child 3, n: int64
                    child 4, src: string
                child 49, access_grade:pedestrian: struct<v: double, lo: double, hi: double, n: int64, src: string>
                    child 0, v: double
                    child 1, lo: double
                    child 2, hi: double
                    child 3, n: int64
                    child 4, src: string
              to
              {'meta': {'schema': Value('string'), 'ontology': Value('string'), 'fitted_at': Value('timestamp[s]'), 'surface': Value('string'), 'n_obs': Value('int64'), 'note': Value('string')}, 'coefficients': {'district:Long Biên': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'district:Hai Bà Trưng': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'district:Bắc Từ Liêm': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'district:Hoàn Kiếm': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'district:Đống Đa': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'district:Hà Đông': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'district:Cầu Giấy': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'district:Thanh Xuân': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'district:Ba Đình': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'district:Hoàng Mai': {'v': Value('float64'
              ...
              oat64'), 'n': Value('int64'), 'src': Value('string')}, 'dist_to_main_street:ADJACENT': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'dist_to_main_street:NEAR': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'dist_to_main_street:MODERATE': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'dist_to_main_street:FAR': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'has_sidewalk:1': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'access_grade:truck': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'access_grade:car_two_way': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'access_grade:tricycle': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'access_grade:motorbike': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}, 'access_grade:pedestrian': {'v': Value('float64'), 'lo': Value('float64'), 'hi': Value('float64'), 'n': Value('int64'), 'src': Value('string')}}}
              because column names don't match

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Hanoi house AVM — model workspace snapshot (2026-08-18)

Self-contained: everything the two notebooks need, including data/transaction_data_26_07_10.parquet (company inventory data — publicly listed on the website).

Layout

notebooks/avm_model.ipynb — GBM hedonic + Stage-B hierarchical re-leveling (SOLD-calibrated). Needs transaction_data_26_07_10.parquet in ROOT.
notebooks/avm_structural.ipynb — structural Bayesian AVM (V = Land + Structure), street⊂ward⊂district⊂city, full-registry priors. Exports avm_coefficients.json.
data/ salvaged.parquet (73,775 listing texts), listing_histories.parquet (dedup-pool price/date histories, id-joined), demo_ids.txt (15k stratified sample)
extractions/ 10 feature files (one per ontology axis), keyed by id
registry/ the ontology (axes/, ontology.md), prompt compiler, extraction harness
demo/ avm_demo_v5_vi.html + avm_coefficients.json (load via "nạp file hồ sơ đã fit")

Run

conda create -n avm python=3.12 && pip install -r requirements.txt
Set ROOT at the top of each notebook to this folder (both notebooks read f'{ROOT}/...'). avm_structural.ipynb also re-executes cells from avm_model.ipynb by cell id — keep both in ROOT.
Copy data/transaction_data_26_07_10.parquet into ROOT.
Run avm_model.ipynb first (builds the matrix), then avm_structural.ipynb. On a multi-core box: in the pm.sample(...) call set chains=4, cores=4, draws=1000, tune=1000. Optional: nuts_sampler="numpyro" for 3-5x speed.

Notes

pytensor on macOS needs -fbracket-depth (already set in the notebook); not needed on Linux/gcc.
listing_histories.parquet was filtered from MikeGreen2710/dedup-workspace → work_hanoi/outputs/pool.parquet (id join verified by text). A newer pool 26_06_18_pool_fixed_with_ner_dist_cond_outlier_partial.parquet (792 MB) should replace it — not included here.

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Total file size:

329 MB