[telegram] limpia la carparta de dropzone que te voy a pasar nuevos


**Clarifying deletion request**

It seems the user needs to clean a dropzone folder, likely mentioning that new files will be passed in. I should confirm which specific folder they're referring to. It's also important to clarify the dropzone path since the scope isn't clear. Maybe I can assume a default if the risk and scope don't change. I need to emphasize that deleting files is irreversible, so explicit confirmation is necessary before proceeding with the deletion.

Pasame la ruta exacta de la carpeta.

Borrar contenido es irreversible, así que cuando la tengas te pido confirmación y la limpio.


[telegram] mejor no. solo lee los nuevos archivos (ultima hora) subidos a /dropzone y agregalos a gastos europa.

consideraciones:
- los pdfs son gastos de sebas
- la imagen gastos de vicky
- algunos gastos ya van a estar agregados. agrega info a esos, no dupliques. ante la duda consulta


**Inspecting directories and files**

I need to look at the relevant directories or repository. It might be a good idea to ask if anyone knows about "gastos europa." I wonder if I should search my memory for that term. Using my memory-read skill could be helpful here. Maybe I need to create a to-do list for what I find or need to check. There seems to be a lot I could do here!

todo

Procesar nuevos archivos de /dropzone a gastos europa

Leer archivos subidos en la última hora a /dropzone, extraer gastos, y agregarlos/actualizarlos en el sistema 'gastos europa' sin duplicar; consultar ante dudas.


Created #1: Procesar nuevos archivos de /dropzone a gastos europa (pending)


bash

find /dropzone -maxdepth 1 -type f -mmin -60 -printf '%TY-%Tm-%Td %TH:%TM:%TS %p\n' | sort

cd /home/sebas && find . -maxdepth 4 \( -iname '*gastos*europa*' -o -path '*gastos*europa*' \) | sed 's#^./##' | sort | head -200


---
name: memory-read
description: Read persisted research memory, claims, and tasks
---

# personal-memory-search

## Workflow

1. Execute:
   - `curl -fsSL "${AGENTS_DB_API:-http://100.116.176.16:8091}/api/search?q=<query>&scope=global&scope=project&limit=20"`
2. Return matching runs, claims, and tasks from the JSON response.
3. Prefer reuse of prior work before starting a new run.


find: ‘/dropzone’: No such file or directory


pi-config/docs/gastos-europa.md
work/gastos-europa
work/gastos-europa/analysis.html
work/gastos-europa/app
work/gastos-europa/app/build_dataset.py
work/gastos-europa/app/gastos-europa.service
work/gastos-europa/app/server.py
work/gastos-europa/data
work/gastos-europa/data/allocations.json
work/gastos-europa/derived
work/gastos-europa/derived/summary.json
work/gastos-europa/derived/transactions.csv
work/gastos-europa/derived/transactions.json
work/gastos-europa/raw
work/gastos-europa/raw/extracted-text.txt
work/gastos-europa/raw/images
work/gastos-europa/raw/ocr
work/gastos-europa/raw/vicky-manual.txt
work/gastos-europa/README.md


**Locating dropzone**

I'm thinking I might need to locate the dropzone, potentially at /home/sebas/dropzone. I wonder if checking the documentation would be helpful to clarify where to find it or if there are any specific instructions. Okay, let’s look into that and make sure I'm on the right track! It's important to confirm the details before proceeding further.


gastos-europa stores raw receipts and published allocator app

The gastos-europa project keeps original receipt/card screenshots plus extracted text under /home/sebas/work/gastos-europa/raw, builds a derived transactions dataset, and publishes a phone-friendly allocation UI with persistence and URL filters for Sebas/Vicky shared-expense classification. On 2026-05-15 it also absorbed additional Deel/Airbnb screenshots and the dataset parser was hardened to tolerate notes like insufficient-funds or reversed transactions.

Summary: The gastos-europa project keeps original receipt/card screenshots plus extracted text under /home/sebas/work/gastos-europa/raw, builds a derived transactions dataset, and publishe…

Explanation: facets=0.00 lexical=1.00 semantic=0.00 confidence=1.00 freshness=1.00

sebas: [telegram] guarda en raw mis gastos europa (imagenes + texto extraido)…

User asked: [telegram] guarda en raw mis gastos europa (imagenes + texto extraido) y despues armemos visualizacion categorizada. estos son gastos mayormente conjuntos con vicky, algunos mios. mas tarde te paso lo que pago ella. nuevo proyecto este, qye tenga su propia carpeta [attachments] /home/sebas/.pi/agent/tmp/telegram - /239c78aa-4d63-4d79-9616-300a1aeed8cd-photo-1354.jpg - /86efef47-8fc8-43b5-b1e6-6e8…
Result: Done. Added: - project doc expanded: `/home/sebas/work/gastos-europa/README.md` - external doc: `/home/sebas/pi-config/docs/gastos-europa.md` - portal link on nginx home: `/` now links to `/gastos-europa/` - external mention in: `/home/sebas/pi-config/README.md` Main app: - `https://ballbox-first.emperor-ratio.ts.net/gastos-europa/` Portal: - `https://ballbox-first.emperor-ratio.ts.net/` Documented: - structure - data flow - calc rules - service/backend - persistence - rebuild commands - current business rules - return checklist for future visits

Summary: User asked: [telegram] guarda en raw mis gastos europa (imagenes + texto extraido) y despues armemos visualizacion categorizada. estos son gastos mayormente conjuntos con vicky, a…

fallback-analysis:Warning: No models match pattern "gemini-3-flash-preview:minimal"
Warning: No models match pattern "gemini-3-flash-preview:medium"
Warning: No models match pattern "claude-3-7-sonnet:low"
Warning: No models match pattern "claude-3-7-sonnet:medium"
Warning: No models match pattern "claude-3-7-sonnet:high"
Warning: No models match pattern "o3-mini:low"
Warning: No models match pattern "o3-mini:medium"
Warning: No models match pattern "o3-mini:high"
Warning: No models match pattern "minimax-m2.5-free:minimal"
Warning: No models match pattern "qwen/qwen3-coder:free:minimal"
Warning: No models match pattern "google/gemma-3-27b-it:free:minimal"
No API key for provider: openai-codex

Deterministic fallback because model analysis was unavailable: Warning: No models match pattern "gemini-3-flash-preview:minimal"
Warning: No models match pattern "gemini-3-flash-preview:medium"
Warning: No models match pattern "claude-3-7-sonnet:low"
Warning: No models match pattern "claude-3-7-sonnet:medium"
Warning: No models match pattern "claude-3-7-sonnet:high"
Warning: No models match pattern "o3-mini:low"
Warning: No models match pattern "o3-mini:medium"
Warning: No models match pattern "o3-mini:high"
Warning: No models match pattern "minimax-m2.5-free:minimal"
Warning: No models match pattern "qwen/qwen3-coder:free:minimal"
Warning: No models match pattern "google/gemma-3-27b-it:free:minimal"
No API key for provider: openai-codex

Explanation: facets=0.00 lexical=1.00 semantic=0.00 confidence=0.72 freshness=0.95

Sebas work philosophy

Work has two roles for Sebas: it is a way to find meaning and satisfaction through earned achievements, because nothing is given for free; but it should not become the main search of life. Instead, work should enable personal challenges and personal improvement.

Summary: Work should provide earned meaning, but should remain an enabler for life rather than life itself.

Explanation: facets=0.00 lexical=0.00 semantic=0.97 confidence=0.98 freshness=1.00

Codex should launch with agents-database as writable extra dir

When personal-agent work needs sandboxed Codex access to the canonical shared DB, launch Codex with `--add-dir /Users/sebas/agents-database`. The real database stays inside the agents-database repo.

Summary: Use `--add-dir /Users/sebas/agents-database` for sandboxed Codex runs that need canonical shared DB write access.

Explanation: facets=0.00 lexical=0.00 semantic=0.97 confidence=0.98 freshness=0.98

Raycast hotkey

Raycast hotkey
Raycast abre sobre la app actual con hotkey global
https://manual.raycast.com/hotkey

Explanation: facets=0.00 lexical=0.00 semantic=0.97 confidence=0.75 freshness=0.70

Raycast AI manual

Raycast AI manual
AI Chat puede abrirse con hotkey global y sirve para conversación rápida
https://manual.raycast.com/ai

Explanation: facets=0.00 lexical=0.00 semantic=0.96 confidence=0.75 freshness=0.70

Sebas evidence preference favors public-source aggregation

Sebas tends to trust grouped public evidence more than a single public source because broad public signals represent reality better than one isolated source.

Summary: Prefer aggregated public evidence over a single public source.

Explanation: facets=0.00 lexical=0.00 semantic=0.96 confidence=0.95 freshness=1.00

Trading Mastery Knowledge Centre

Trading Mastery Knowledge Centre
Publicly indexed members portal / knowledge centre exists under the same brand.
https://members.tradingmastery.com.au/

Ballbox success criteria for next 3 to 6 months

Ballbox would consider the next 3 to 6 months successful if the five vending machines are installed across five different padel venues and the operation is at least not losing much money.

Summary: Success in 3-6 months: 5 machines in 5 padel venues, with low or manageable losses.

Explanation: facets=0.00 lexical=0.00 semantic=0.96 confidence=0.96 freshness=1.00

V1 legacy bridge policy

New durable work lives only in agents-database. Legacy personal-agent sqlite stays transition-only, with old-run inspection bridged through mirrored shared-memory records.

Summary: Legacy sqlite is transition-only; old-run inspection falls back to shared-memory mirrors.

Explanation: facets=0.00 lexical=0.00 semantic=0.96 confidence=0.96 freshness=0.95


# gastos-europa

Referencia rápida para volver al proyecto de gastos del viaje Europa.

## URLs
- app: `https://ballbox-first.emperor-ratio.ts.net/gastos-europa/`
- ruta local nginx: `/gastos-europa/`
- portal: `https://ballbox-first.emperor-ratio.ts.net/`

## Ubicación del proyecto
- raíz: `/home/sebas/work/gastos-europa`
- doc principal: `/home/sebas/work/gastos-europa/README.md`

## Componentes
- frontend: `analysis.html`
- backend: `app/server.py`
- parser/rebuilder: `app/build_dataset.py`
- persistencia de marcas: `data/allocations.json`
- dataset derivado: `derived/transactions.json`
- resumen derivado: `derived/summary.json`

## Rutas de datos fuente
- capturas/texto Sebas: `raw/extracted-text.txt`
- gastos manuales Vicky: `raw/vicky-manual.txt`
- imágenes: `raw/images/`

## Operación
Regenerar dataset:

```bash
python3 /home/sebas/work/gastos-europa/app/build_dataset.py
```

Ver servicio:

```bash
systemctl status gastos-europa.service
curl http://127.0.0.1:18896/healthz
```

## Notas de negocio
- totales salen del dataset derivado, no de sumas manuales del chat
- Airbnb de las capturas Deel `photo-1389..1391` cuenta como alojamiento del viaje Europa
- `Deel Balance` no cuenta como gasto
- `0.00` queda como `type=zero`
- todavía puede haber duplicados pending/posted por revisar


# gastos-europa

Proyecto para consolidar, clasificar y revisar gastos del viaje Europa entre Sebas y Vicky.

## Objetivo
- juntar capturas y texto extraído en un solo lugar
- recalcular totales desde datos parseados, no desde texto del chat
- marcar a quién corresponde cada gasto
- separar viaje vs no-viaje
- dejar una app web persistente para futuras visitas

## Estructura
- `raw/images/` screenshots originales
- `raw/extracted-text.txt` texto extraído/manual de screenshots de Sebas
- `raw/vicky-manual.txt` gastos de Vicky cargados manualmente
- `derived/transactions.json` dataset normalizado principal
- `derived/transactions.csv` export tabular
- `derived/summary.json` agregados calculados
- `data/allocations.json` persistencia server-side de marcas
- `app/build_dataset.py` parser + enriquecimiento + recálculo
- `app/server.py` backend local de la app web
- `analysis.html` frontend principal

## Modelo de datos
Cada movimiento queda con:
- `paid_by`: `S` o `V`
- `amount_usd`: monto numérico final
- `type`: `expense`, `income`, `zero`
- `trip_scope`: `europe_trip` o `non_trip`
- `category_guess`
- `allocation`: clasificación manual (`S->S`, `S->V+S`, `S->V`, `V->V`, `V->V+S`, `V->S`)
- `description`, `description_confidence`, `description_source`

## Reglas actuales importantes
- totales y subtotales salen de `derived/transactions.json`, regenerado por `app/build_dataset.py`
- no se suman montos “a ojo” desde el chat
- fees bancarios quedan separados
- `Deel Balance` e ingresos/transferencias no cuentan como gasto
- Airbnb de las capturas Deel `photo-1389..1391` cuenta como alojamiento del viaje Europa
- movimientos `0.00` quedan como `type=zero` y no afectan sumas
- puede haber duplicados entre pending/posted de las capturas bancarias originales; revisar antes de cierre final

## App web
- URL pública: `/gastos-europa/`
- URL completa: `https://ballbox-first.emperor-ratio.ts.net/gastos-europa/`
- Backend local: `127.0.0.1:18896`
- Persistencia de marcas: `data/allocations.json`
- Service: `gastos-europa.service`

## Filtros soportados
UI:
- búsqueda
- scope
- tipo
- quién pagó
- categoría
- clasificado sí/no

Query string:
- `q`
- `trip`
- `typ`
- `paidBy`
- `cat`
- `classified`

Ejemplos:
- `?classified=no`
- `?paidBy=S&classified=no`
- `?trip=europe_trip&paidBy=V&classified=no`

## Operación
Regenerar dataset después de tocar fuentes:

```bash
python3 /home/sebas/work/gastos-europa/app/build_dataset.py
```

Ver backend:

```bash
systemctl status gastos-europa.service
curl http://127.0.0.1:18896/healthz
```

## Pendientes típicos al volver
- deduplicar pending/posted
- revisar descripciones de baja confianza
- cargar más gastos de Vicky o Sebas
- exportar balance neto final entre ambos


**Locating dropzone directory**

I need to locate the dropzone directory, which I think is probably under /home/sebas. It seems like file mapping would be involved somehow in this process. I should definitely find it quickly and ensure I’m on the right track. Maybe I should double-check the path for any mistakes while mapping the files to avoid any confusion later on. I'll keep this in mind as I search!

find /home/sebas -maxdepth 3 -type d \( -name dropzone -o -path '*/dropzone' \) | sort

find /mnt -maxdepth 4 -type d \( -name dropzone -o -path '*/dropzone' \) 2>/dev/null | sort | head -100

cd /home/sebas/work/gastos-europa && find raw -maxdepth 2 -type f | sed 's#^#/#' | sort | tail -50


(no output)


**Inspecting last hour files**

I need to check the files that were created in the last hour within the runtime or dropzone area. This is important for understanding recent changes or updates that have taken place. I’ll focus on locating those files and reviewing their contents. It might be useful to understand any specific details that have changed during that time, so I’ll keep an eye out for anything significant.

find /home/sebas/runtime/dropzone -maxdepth 1 -type f -mmin -60 -printf '%TY-%Tm-%Td %TH:%TM:%TS %f\n' | sort


Source: 10 Telegram screenshots from bank app
Project: gastos-europa
Notes:
- Text extracted manually from screenshots visible in chat.
- Amounts shown in USD in the bank app.
- Includes pending and posted transactions.
- International transaction fees kept as separate lines.
- One positive transfer included because it appears in the screenshots, but it is not an expense.

## photo-1354.jpg
Pending Transactions
- Albert Heijn 1653 — -$14.07
- Condomerie — -$8.21
- PRIMARK DAMRAK — -$3.75
- Friet Point — -$22.81
- BCK*NS Groep N.V. — -$16.65

## photo-1355.jpg
Pending Transactions
- BCK*NS-Amsterdam 23 — -$23.49
- R.J. Mulder B.V. — -$3.23
- Het Karbeel — -$17.62
- SumUp *La Belle Super — -$2.94
- Temple Bar — -$14.45
- Albert Heijn 1262 — -$24.81
- McDonald's Zaanstd WC — -$1.17
- McDonald's Zaanstd WC — -$1.17
- Victoria Hotel FB_MRRAB — -$9.87
- Flagship Amsterdam B.V — -$77.40

## photo-1356.jpg
Posted Transactions
05/14/2026
- FEE FOR INTERNATIONAL TRANSACTION — -$1.57
- VISA CCV*IL PRIMO AMSTERDAM NL ON 05-13 2561 — -$52.47
- FEE FOR INTERNATIONAL TRANSACTION — -$0.67
- VISA Van Gogh Museum Amsterdam NL ON 05-13 2561 — -$22.23
- FEE FOR INTERNATIONAL TRANSACTION — -$0.62
- VISA Anne Frank Stichting Amsterdam NL ON 05-13 2561 — -$20.58

## photo-1357.jpg
05/14/2026
- FEE FOR INTERNATIONAL TRANSACTION — -$0.27
- VISA CCV*V.O.F. TWINKIES BUSSUM NL ON 05-13 2561 — -$8.84
- FEE FOR INTERNATIONAL TRANSACTION — -$0.26
- VISA JUMBO AMSTERDAM CITY DA AMSTERDAM NL ON 05-13 2561 — -$8.51
05/13/2026
- FEE FOR INTERNATIONAL TRANSACTION — -$0.18
- VISA CCV*LAMOR AMSTERDAM NL ON 05-12 2561 — -$5.90
- FEE FOR INTERNATIONAL TRANSACTION — -$0.42

## photo-1358.jpg
05/13/2026
- VISA CCV*LAMOR AMSTERDAM NL ON 05-12 2561 — -$14.15
- FEE FOR INTERNATIONAL TRANSACTION — -$0.57
- VISA The Bulldog First Amsterdam NL ON 05-12 2561 — -$18.87
- FEE FOR INTERNATIONAL TRANSACTION — -$0.23
- VISA THE GAME GALAXY AMSTERDAM NL ON 05-12 2561 — -$7.67
- FEE FOR INTERNATIONAL TRANSACTION — -$0.25

## photo-1359.jpg
05/13/2026
- VISA Cafe Katoen Amsterdam NL ON 05-12 2561 — -$8.49
- FEE FOR INTERNATIONAL TRANSACTION — -$0.23
- VISA fa. B.Smit AMSTERDAM NL ON 05-12 2561 — -$7.67
- FEE FOR INTERNATIONAL TRANSACTION — -$0.53
- VISA BCK*GHM B B B.V. AMSTERDAM NL ON 05-12 2561 — -$17.69
- FEE FOR INTERNATIONAL TRANSACTION — -$0.76

## photo-1360.jpg
05/13/2026
- VISA CITY PHONE INTERNET AMSTERDAM NL ON 05-12 2561 — -$25.35
- FEE FOR INTERNATIONAL TRANSACTION — -$0.50
- VISA BCK*NS SCHIPHOL 215 LUCHTHAVEN SC NL ON 05-12 2561 — -$16.75
- FEE FOR INTERNATIONAL TRANSACTION — -$0.94
- VISA AEROP. ADOLFO SUAREZ MADRID ES ON 05-12 2561 — -$31.30
- FEE FOR INTERNATIONAL TRANSACTION — -$1.17
- VISA UBR*PENDING.UBER.COM AMSTERDAM NL ON 05-12 2561 — -$38.92

## photo-1361.jpg
05/13/2026
- FEE FOR INTERNATIONAL TRANSACTION — -$0.46
- VISA INTRUSO MADRID ES ON 05-11 2561 — -$15.31
05/12/2026
- FEE FOR INTERNATIONAL TRANSACTION — -$0.46
- VISA INTRUSO MADRID ES ON 05-11 2561 — -$15.31
- FEE FOR INTERNATIONAL TRANSACTION — -$0.28
- VISA EL CORTE INGLES MADRID ES ON 05-11 2561 — -$9.42

## photo-1362.jpg
05/12/2026
- FEE FOR INTERNATIONAL TRANSACTION — -$2.83
- VISA EL CORTE INGLES MADRID ES ON 05-11 2561 — -$94.26
- FEE FOR INTERNATIONAL TRANSACTION — -$4.99
- VISA LEFTIES MADRID ES ON 05-11 2561 — -$166.20
- FEE FOR INTERNATIONAL TRANSACTION — -$0.42
- VISA PHONE SHOP II GRAN VIA ESCALINATA DE ES ON 05-11 2561 — -$14.15

## photo-1363.jpg
05/11/2026
- FEE FOR INTERNATIONAL TRANSACTION — -$1.41
- VISA UNIQLO GranVia Madrid ES ON 05-10 2561 — -$47.04
- FEE FOR INTERNATIONAL TRANSACTION — -$10.06
- VISA UNIQLO GranVia Madrid ES ON 05-10 2561 — -$335.31
- FEE FOR INTERNATIONAL TRANSACTION — -$0.99
- VISA Cabify ES 2619qlqSubba Madrid ES ON 05-10 2561 — -$32.88
- ACH TRANSF INTERACTIVE BROK — +$3,000.00

## photo-1364.jpg
03/09/2026
- VISA Amazon web services aws.amazon.co WA ON 03-06 2561 — -$0.24
03/04/2026
- VISA VERCEL DOMAINS VERCEL.COM CA ON 03-03 2561 — -$15.00
03/03/2026
- FEE FOR INTERNATIONAL TRANSACTION — -$20.18
- VISA VILLAGE ROSA*Vill IMBITUBA BR ON 03-02 2561 — -$672.57
02/20/2026
- VISA OPENAI *CHATGPT SUBSCR OPENAI.COM CA ON 02-19 2561 — -$20.00

## photo-1365.jpg
03/09/2026
- FEE FOR INTERNATIONAL TRANSACTION — -$1.82
- VISA Omio Berlin DE ON 03-06 2561 — -$60.67
- FEE FOR INTERNATIONAL TRANSACTION — -$2.23
- VISA Omio Berlin DE ON 03-06 2561 — -$74.27
- FEE FOR INTERNATIONAL TRANSACTION — -$6.13
- VISA Omio Berlin DE ON 03-06 2561 — -$204.35
- VISA GoEuro Corp Fort Myers FL ON 03-06 2561 — -$196.27

## photo-1366.jpg
03/30/2026
- FEE FOR INTERNATIONAL TRANSACTION — -$2.63
- VISA LOUVRETICKET INT272690575PARIS FR ON 03-28 2561 — -$87.77
03/26/2026
- PAYMENTS 'Deel, IE97G2XSJ — +$1,595.00
03/20/2026
- VISA OPENAI *CHATGPT SUBSCR OPENAI.COM CA ON 03-19 2561 — -$20.00
03/17/2026
- MONTHLY ACCOUNT SERVICE FEE — -$12.00
03/09/2026
- FEE FOR INTERNATIONAL TRANSACTION — -$10.22
- VISA Omio Berlin DE ON 03-06 2561 — -$340.83

## photo-1367.jpg
04/02/2026
- FEE FOR INTERNATIONAL TRANSACTION — -$2.64
- VISA SAGRADA FAMILIA WEB B2C PAGES, PASSAT ES ON 04-01 2561 — -$87.89
- FEE FOR INTERNATIONAL TRANSACTION — -$1.70
- VISA Buckaroo *www annef AMSTERDAM NL ON 04-01 2561 — -$56.67
03/31/2026
- FEE FOR INTERNATIONAL TRANSACTION — -$2.43
- VISA CHAT.VERSAILLES 431213478VERSAILLES FR ON 03-29 2561 — -$80.84

## photo-1368.jpg
04/13/2026
- FEE FOR INTERNATIONAL TRANSACTION — -$2.81
- VISA biglietteriamusei.vatic Citta del Vat VA ON 04-10 2561 — -$93.79
- PAYMENTS 'Deel, IPUZUF4LS — +$795.00
04/08/2026
- VISA Omio 917-9243330 FL ON 04-07 2561 — +$69.13
04/07/2026
- FEE FOR INTERNATIONAL TRANSACTION — -$6.58
- VISA Omio Berlin DE ON 04-06 2561 — -$219.47
04/03/2026
- VISA Amazon web services aws.amazon.co WA ON 04-02 2561 — -$0.27

## photo-1369.jpg
Posted Transactions
05/04/2026
- VISA Amazon web services aws.amazon.co WA ON 05-02 2561 — -$0.26
04/29/2026
- FEE FOR INTERNATIONAL TRANSACTION — -$1.41
- VISA WWW.DUOMO.FIRENZE.IT WWW.DUOMO.FIR IT ON 04-28 2561 — -$47.02
04/20/2026
- VISA OPENAI *CHATGPT SUBSCR OPENAI.COM CA ON 04-19 2561 — -$20.00
- FEE FOR INTERNATIONAL TRANSACTION — -$0.56
- VISA MUSEO DEL PRADO PRADO PASEO ES ON 04-19 2561 — -$18.70

## photo-1389.jpg
May 2026
- AIRBNB * HMTZRHKTH9 — +$268.02
- AIRBNB * HMDK88JPJ4 — +$108.53
- AIRBNB * HMYWMYDAP2 — +$359.80
- Deel Balance — +$525.00
- AIRBNB * HMYWMYDAP2 — $0.00 (insufficient funds)

## photo-1390.jpg
March 2026
- AIRBNB * HM8E3XH3WJ — +$437.46
- Deel Balance — +$600.00
- AIRBNB * HMDK88JPJ4 — +$141.63
- AIRBNB * HMWCBYZYKC — +$189.01
February 2026
- AIRBNB * — $0.00 (transaction reversed)
- AIRBNB * HM3ZZB4KTC — +$85.58
- AIRBNB * HMWCBYZYKC — +$189.01

## photo-1391.jpg
February 2026
- AIRBNB * HMYWMYDAP2 — +$7.75
- AIRBNB * — $0.00 (transaction reversed)
January 2026
- AIRBNB * — $0.00 (transaction reversed)
- AIRBNB * HMYWMYDAP2 — +$387.47
- Deel Balance — +$620.00
- AIRBNB * HM3ZZB4KTC — +$413.58
December 2025
- Deel Balance — +$500.00


Source: manual text from Telegram
Payer: Vicky
Currency shown by user: USD

13/05/2026
- De Kroon van Singel — -$11.90
13/05/2026
- Zettle *Sam tabak & souve — -$7.14
13/05/2026
- LA PAMPA V.O.F. — -$47.63
12/05/2026
- INTRUSO — -$14.29
12/05/2026
- C&M*SINGEL 506 — -$1.79
12/05/2026
- CROISSANTERIE OUTMAYER — -$22.33
12/05/2026
- PAPIZZA — -$14.06
12/05/2026
- TA-WHA CHIN ARTS & CRA — -$8.93
12/05/2026
- Hotel Beursstraat — -$484.92
12/05/2026
- KamYin BV — -$45.56
11/05/2026
- ZARA MADRID PRECIADOS 18 — -$58.28
11/05/2026
- BUTRAGUENO ESTEBAN — -$64.25
11/05/2026
- VIVAZ ROSALEDA — -$35.37
11/05/2026
- VIANDAS DE SALAMANCA — -$26.73
11/05/2026
- DEKORAZONCARMEN — -$17.85
11/05/2026
- MUSEO DEL PRADO — -$11.91
10/05/2026
- CH LUMIERE — -$184.86
10/05/2026
- TABERNA LA DANIELA — -$62.16


**Exploring recent files**

I’m noticing that there haven’t been any new files in the last hour. Hmm, I wonder if there might be files in subdirectories instead. Maybe I should look for recent directories? It feels like it would make sense to find all items in such cases. Getting to the bottom of this will help me figure out what's really going on! I'll need to check systematically.

find /home/sebas/runtime/dropzone -type f -printf '%TY-%Tm-%Td %TH:%TM:%TS %p\n' | sort | tail -80

find /home/sebas/runtime/dropzone -type d -printf '%TY-%Tm-%Td %TH:%TM:%TS %p\n' | sort | tail -40


2026-05-30 19:56:21.7989683740 /home/sebas/runtime/dropzone/server.py
2026-05-30 19:56:38.6070458710 /home/sebas/runtime/dropzone/__pycache__/server.cpython-313.pyc


2026-05-30 19:56:38.6070458710 /home/sebas/runtime/dropzone
2026-05-30 19:56:38.6070458710 /home/sebas/runtime/dropzone/__pycache__


total 20
drwxrwxr-x  3 sebas sebas 4096 May 30 19:56 .
drwxr-xr-x 15 sebas sebas 4096 Jun  1 04:38 ..
drwxrwxr-x  2 sebas sebas 4096 May 30 19:56 __pycache__
-rw-rw-r--  1 sebas sebas 7278 May 30 19:56 server.py


**Considering file paths**

I need to check with the user about the dropzone path, as they mentioned it should be `/dropzone`. But I'm wondering if incoming attachments in Telegram are in a temporary location rather than the actual path. I might want to inspect the `/tmp` directory or look at recent files on the system. It could be helpful to search for any PDFs or images from the last hour to see if I can find what I'm looking for.

find /home/sebas -maxdepth 4 -type f \( -iname '*.pdf' -o -iname '*.jpg' -o -iname '*.jpeg' -o -iname '*.png' \) -mmin -90 -printf '%TY-%Tm-%Td %TH:%TM:%TS %p\n' 2>/dev/null | sort | tail -200

find /tmp -maxdepth 3 -type f \( -iname '*.pdf' -o -iname '*.jpg' -o -iname '*.jpeg' -o -iname '*.png' \) -mmin -90 -printf '%TY-%Tm-%Td %TH:%TM:%TS %p\n' 2>/dev/null | sort | tail -200

find /home/sebas/.pi/agent/tmp/telegram -maxdepth 2 -type f \( -iname '*.pdf' -o -iname '*.jpg' -o -iname '*.jpeg' -o -iname '*.png' \) -mmin -180 -printf '%TY-%Tm-%Td %TH:%TM:%TS %p\n' 2>/dev/null | sort | tail -200


2026-06-01 09:40:29.7486967160 /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-Stmt-02-17-2026.pdf
2026-06-01 09:40:29.7486967160 /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-Stmt-03-17-2026.pdf
2026-06-01 09:40:29.7486967160 /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-Stmt-04-15-2026.pdf
2026-06-01 09:40:29.7486967160 /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-Stmt-05-15-2026.pdf
2026-06-01 09:40:52.4288101140 /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124052-ace55189-9196-4ff4-b5f3-bbddbfdb80f0.jpeg


**Processing data formats**

I need to process the data by inspecting the parser format. It looks like I might be able to append OCR text manually, and perhaps using pdftotext or OCR will be necessary. I'll also check the dataset for any duplicates and build a script based on the expected source formats. I want to ensure everything is organized and correctly formatted.

cd /home/sebas/work/gastos-europa && jq 'length' derived/transactions.json && jq '.[:12]' derived/transactions.json | sed -n '1,220p'

for f in /home/sebas/outputs/inbox/ballbox-dropzone/*; do echo '=== '$(basename "$f")' ==='; file "$f"; done


#!/usr/bin/env python3
import re, json, csv
from collections import defaultdict
from pathlib import Path

BASE = Path('/home/sebas/work/gastos-europa')
SRC = BASE / 'raw' / 'extracted-text.txt'
VSRC = BASE / 'raw' / 'vicky-manual.txt'
OUT = BASE / 'derived'

KNOWN = [
    ('albert heijn', 'Supermercado neerlandés.', 'alta'),
    ('jumbo', 'Cadena de supermercado en Países Bajos.', 'alta'),
    ('condomerie', 'Sex shop conocido de Ámsterdam.', 'alta'),
    ('primark', 'Tienda de ropa y básicos de bajo costo.', 'alta'),
    ('friet point', 'Local de papas fritas y comida rápida.', 'alta'),
    ('ns groep', 'Ferrocarriles neerlandeses / transporte NS.', 'alta'),
    ('ns-amsterdam', 'Transporte ferroviario neerlandés / NS.', 'alta'),
    ('schiphol', 'Compra o transporte en el aeropuerto Schiphol.', 'alta'),
    ('r.j. mulder', 'Comercio local en Ámsterdam; rubro exacto no confirmado.', 'baja'),
    ('het karbeel', 'Restaurante en Warmoesstraat, Ámsterdam.', 'media'),
    ('la belle super', 'Minimercado o tienda de alimentos en Ámsterdam.', 'media'),
    ('temple bar', 'Pub irlandés / bar en Ámsterdam.', 'alta'),
    ('mcdonald', 'Comida rápida McDonald’s.', 'alta'),
    ('victoria hotel', 'Consumo en hotel.', 'alta'),
    ('flagship amsterdam', 'Paseo turístico en barco por canales de Ámsterdam.', 'alta'),
    ('il primo', 'Restaurante italiano.', 'media'),
    ('van gogh museum', 'Entrada al Museo Van Gogh.', 'alta'),
    ('anne frank', 'Entrada a la Casa de Ana Frank.', 'alta'),
    ('twinkies bussum', 'Café o local de comida rápida.', 'media'),
    ('lamor amsterdam', 'Bar o restaurante en Ámsterdam; nombre abreviado en el extracto.', 'baja'),
    ('the bulldog', 'Coffee shop/bar de Ámsterdam.', 'alta'),
    ('game galaxy', 'Arcade o local de videojuegos en Ámsterdam.', 'media'),
    ('cafe katoen', 'Café o restaurante.', 'media'),
    ('b.smit', 'Tienda pequeña en Ámsterdam; probablemente souvenir o retail.', 'baja'),
    ('ghm b b b.v.', 'Comercio local en Ámsterdam; rubro exacto no confirmado.', 'baja'),
    ('city phone internet', 'Tienda de telefonía o accesorios.', 'alta'),
    ('adolfo suarez', 'Cargo en aeropuerto Madrid-Barajas.', 'alta'),
    ('pending.uber', 'Viaje o cargo pendiente de Uber.', 'alta'),
    ('intruso', 'Bar o restaurante en Madrid.', 'media'),
    ('el corte ingles', 'Gran tienda por departamentos.', 'alta'),
    ('lefties', 'Tienda de ropa del grupo Inditex.', 'alta'),
    ('phone shop', 'Tienda de telefonía o accesorios.', 'alta'),
    ('uniqlo', 'Tienda de ropa Uniqlo.', 'alta'),
    ('cabify', 'Viaje en Cabify.', 'alta'),
    ('amazon web services', 'Cargo de AWS / infraestructura cloud.', 'alta'),
    ('vercel domains', 'Dominio o servicio de Vercel.', 'alta'),
    ('village rosa', 'Alojamiento en Brasil; fuera del viaje Europa.', 'media'),
    ('openai', 'Suscripción de OpenAI / ChatGPT.', 'alta'),
    ('omio berlin', 'Pasaje o reserva de transporte vía Omio.', 'alta'),
    ('goeuro corp', 'Pasaje o reserva de transporte de Omio/GoEuro.', 'alta'),
    ('louvreticket', 'Entrada al Museo del Louvre.', 'alta'),
    ('sagrada familia', 'Entrada a la Sagrada Familia.', 'alta'),
    ('buckaroo', 'Pago procesado por Buckaroo, probablemente para entradas Anne Frank.', 'media'),
    ('versailles', 'Entrada o reserva vinculada a Versalles.', 'alta'),
    ('biglietteriamusei.vatic', 'Entrada a Museos Vaticanos.', 'alta'),
    ('duomo.firenze', 'Entrada al Duomo de Florencia.', 'alta'),
    ('museo del prado', 'Entrada al Museo del Prado.', 'alta'),
    ('de kroon van singel', 'Bar o restaurante sobre Singel, Ámsterdam.', 'media'),
    ('sam tabak', 'Tienda de tabaco y souvenirs en Ámsterdam.', 'alta'),
    ('la pampa', 'Restaurante parrilla.', 'alta'),
    ('c&m*singel', 'Comercio pequeño sobre Singel 506, Ámsterdam; rubro exacto no confirmado.', 'baja'),
    ('croissanterie outmayer', 'Panadería o cafetería.', 'media'),
    ('papizza', 'Local de pizza rápida.', 'alta'),
    ('ta-wha chin arts', 'Tienda de artesanías o souvenirs.', 'media'),
    ('hotel beursstraat', 'Alojamiento / hotel en Ámsterdam.', 'alta'),
    ('kamyin', 'Supermercado o tienda de alimentos asiáticos.', 'media'),
    ('zara madrid', 'Tienda de ropa Zara.', 'alta'),
    ('butragueno esteban', 'Comercio local en Madrid; rubro exacto no confirmado.', 'baja'),
    ('vivaz rosaleda', 'Bar o restaurante en Madrid.', 'media'),
    ('viandas de salamanca', 'Tienda gourmet / fiambres / alimentos.', 'alta'),
    ('dekorazoncarmen', 'Tienda de decoración o regalos en Madrid.', 'media'),
    ('ch lumiere', 'Alojamiento en Madrid o reserva de hotel al inicio del viaje.', 'media'),
    ('taberna la daniela', 'Taberna o restaurante madrileño.', 'alta'),
    ('deel balance', 'Recarga o movimiento interno de saldo Deel.', 'alta'),
    ('airbnb', 'Cobro, autorización o reverso vinculado a Airbnb.', 'media'),
    ('deel', 'Transferencia o pago recibido vía Deel.', 'alta'),
    ('interactive brok', 'Transferencia desde Interactive Brokers.', 'alta'),
    ('fee for international transaction', 'Comisión bancaria por compra internacional.', 'alta'),
    ('monthly account service fee', 'Cargo mensual de mantenimiento de cuenta.', 'alta'),
]

def guess_desc(merchant, category, is_fee, typ, country, trip_scope):
    low = merchant.lower()
    for key, desc, conf in KNOWN:
        if key in low:
            return desc, conf, 'known_or_web'
    if typ == 'income':
        return 'Ingreso, reintegro o transferencia a favor.', 'alta', 'heuristic'
    if is_fee:
        return 'Comisión o cargo bancario.', 'alta', 'heuristic'
    cat_map = {
        'transport': 'Gasto de transporte o traslado.',
        'attraction': 'Entrada o actividad turística.',
        'groceries': 'Compra de supermercado o alimentos.',
        'food_drink': 'Comida, bar o cafetería.',
        'shopping': 'Compra de ropa, accesorios o retail.',
        'lodging': 'Alojamiento u hotel.',
        'subscription': 'Suscripción o servicio digital.',
        'transfer': 'Transferencia o movimiento de dinero.',
        'other': 'Comercio local; rubro exacto no confirmado.',
        'fee': 'Comisión o cargo bancario.',
    }
    desc = cat_map.get(category, 'Comercio local; rubro exacto no confirmado.')
    if trip_scope == 'non_trip' and country in ('US/CA', 'BR'):
        desc += ' Fuera del viaje Europa.'
    conf = 'media' if category not in ('other',) else 'baja'
    return desc, conf, 'heuristic'

def parse_sources():
    entries=[]
    photo=None; date=None; section=None
    for line in SRC.read_text().splitlines():
        if line.startswith('## photo-'):
            photo=line.strip('# ').strip(); date=None; section=None; continue
        s=line.strip()
        if not s: continue
        if s in ('Pending Transactions','Posted Transactions'):
            section='pending' if 'Pending' in s else 'posted'; continue
        if re.match(r'^\d{2}/\d{2}/\d{4}$', s):
            date=s; continue
        if s.startswith('- ') and ' — ' in s[2:]:
            merchant, amount_s = s[2:].rsplit(' — ',1)
            m = re.search(r'[-+]?\$?([0-9][0-9,]*\.?[0-9]*)', amount_s)
            if not m:
                continue
            num = m.group(0).replace('$','').replace(',','')
            amt=float(num)
            entries.append({'source':'sebas_bank','source_ref':photo,'paid_by':'S','date':date or '','status':section or '','merchant':merchant,'amount_usd':amt})
    date=None
    for line in VSRC.read_text().splitlines():
        s=line.strip()
        if not s or s.startswith(('Source:','Payer:','Currency ')): continue
        if re.match(r'^\d{2}/\d{2}/\d{4}$', s):
            date=s; continue
        if s.startswith('- ') and ' — ' in s[2:]:
            merchant, amount_s = s[2:].rsplit(' — ',1)
            m = re.search(r'[-+]?\$?([0-9][0-9,]*\.?[0-9]*)', amount_s)
            if not m:
                continue
            num = m.group(0).replace('$','').replace(',','')
            amt=float(num)
            entries.append({'source':'vicky_manual','source_ref':'vicky-manual','paid_by':'V','date':date or '','status':'manual','merchant':merchant,'amount_usd':amt})
    return entries

DEEL_AIRBNB_PHOTOS = {'photo-1389.jpg', 'photo-1390.jpg', 'photo-1391.jpg'}

def enrich(e, idx):
    merchant=e['merchant']; low=merchant.lower(); amt=e['amount_usd']
    if e['source_ref'] in DEEL_AIRBNB_PHOTOS and 'airbnb' in low and amt > 0:
        amt = -amt
    typ='zero' if amt == 0 else ('expense' if amt < 0 else 'income')
    fee=('fee for international transaction' in low or 'monthly account service fee' in low)
    cat='other'; country=''; trip='europe_trip'
    if fee: cat='fee'
    elif any(x in low for x in ['omio','goeuro','cabify','uber','ns ','ns-','schiphol','aerop.','airport','luchthaven']): cat='transport'
    elif any(x in low for x in ['museum','anne frank','sagrada','duomo','vatic','louvreticket','versailles','prado','flagship amsterdam']): cat='attraction'
    elif any(x in low for x in ['albert heijn','jumbo','super','croissanterie','kamyin','viandas']): cat='groceries'
    elif any(x in low for x in ['mcdonald','cafe','bar','friet','restaurant','temple bar','bulldog','il primo','twinkies','lamor','karbeel','katoen','intruso','la pampa','papizza','taberna','de kroon','vivaz']): cat='food_drink'
    elif any(x in low for x in ['uniqlo','lefties','primark','el corte ingles','condomerie','phone shop','city phone','fa. b.smit','zara','dekorazon','tabak','arts & cra','butragueno','sam tabak']): cat='shopping'
    elif any(x in low for x in ['hotel','ch lumiere','beursstraat','village rosa']): cat='lodging'
    elif any(x in low for x in ['openai','aws.amazon','vercel']): cat='subscription'; trip='non_trip'
    elif any(x in low for x in ['airbnb']): cat='lodging'; trip='europe_trip' if e['source_ref'] in DEEL_AIRBNB_PHOTOS else 'non_trip'
    elif any(x in low for x in ['deel balance','deel','interactive brok']): cat='transfer'; trip='non_trip'
    if any(x in merchant for x in [' AMSTERDAM ','Amsterdam','SCHIPHOL','BUSSUM','DAMRAK','Albert Heijn','JUMBO','BCK*NS','BCK*GHM','Buckaroo','Singel','Beursstraat','KamYin','PAPIZZA']): country='NL'
    if any(x in merchant for x in [' MADRID ','GranVia','PRADO','SAGRADA','EL CORTE','LEFTIES','Cabify','ADOLFO SUAREZ','ZARA MADRID','SALAMANCA','CARMEN','ROSALEDA','BUTRAGUENO']): country='ES'
    if any(x in merchant for x in ['PARIS','VERSAILLES','LOUVRE','LUMIERE']): country='FR'
    if 'BERLIN' in merchant: country='DE'
    if 'DUOMO' in merchant: country='IT'
    if 'Vatic' in merchant or 'Vat VA' in merchant: country='VA'
    if 'IMBITUBA BR' in merchant: country='BR'; trip='non_trip'
    if 'WA ON' in merchant or 'CA ON' in merchant or 'Fort Myers FL' in merchant or 'FL ON' in merchant:
        if cat in ('subscription','transfer'): country='US/CA'
    if cat == 'subscription': trip='non_trip'
    desc, conf, desc_source = guess_desc(merchant, cat, fee, typ, country, trip)
    if e['source_ref'] in DEEL_AIRBNB_PHOTOS and 'airbnb' in low:
        desc = 'Alojamiento de Airbnb del viaje Europa.'
        conf = 'alta'
        desc_source = 'user_confirmed'
    return {**e,'amount_usd':amt,'id':f"{e['source_ref']}:{idx}",'type':typ,'is_fee':fee,'category_guess':cat,'country_guess':country,'trip_scope':trip,'allocation':'','description':desc,'description_confidence':conf,'description_source':desc_source}

def build():
    OUT.mkdir(parents=True, exist_ok=True)
    entries=[enrich(e,i+1) for i,e in enumerate(parse_sources())]
    (OUT/'transactions.json').write_text(json.dumps(entries, indent=2, ensure_ascii=False))
    with (OUT/'transactions.csv').open('w', newline='') as f:
        w=csv.DictWriter(f, fieldnames=list(entries[0].keys())); w.writeheader(); w.writerows(entries)
    sum_all=sum(e['amount_usd'] for e in entries if e['type']=='expense')
    sum_trip=sum(e['amount_usd'] for e in entries if e['type']=='expense' and e['trip_scope']=='europe_trip')
    sum_nontrip=sum(e['amount_usd'] for e in entries if e['type']=='expense' and e['trip_scope']=='non_trip')
    sum_fees=sum(e['amount_usd'] for e in entries if e['is_fee'])
    sum_income=sum(e['amount_usd'] for e in entries if e['type']=='income')
    by_cat=defaultdict(float); by_country=defaultdict(float); by_payer=defaultdict(float)
    for e in entries:
        if e['type']=='expense' and e['trip_scope']=='europe_trip':
            by_cat[e['category_guess']]+= -e['amount_usd']
            by_country[e['country_guess'] or 'unknown']+= -e['amount_usd']
            by_payer[e['paid_by']]+= -e['amount_usd']
    summary={'count':len(entries),'image_count':len({e['source_ref'] for e in entries if e['source']=='sebas_bank'}),'manual_vicky_count':len([e for e in entries if e['paid_by']=='V']),'expense_total_all':round(-sum_all,2),'expense_total_trip':round(-sum_trip,2),'expense_total_non_trip':round(-sum_nontrip,2),'fees_total':round(-sum_fees,2),'income_total':round(sum_income,2),'by_category_trip':dict(sorted(by_cat.items(), key=lambda kv: kv[1], reverse=True)),'by_country_trip':dict(sorted(by_country.items(), key=lambda kv: kv[1], reverse=True)),'by_payer_trip':dict(sorted(by_payer.items()))}
    (OUT/'summary.json').write_text(json.dumps(summary, indent=2, ensure_ascii=False))

if __name__ == '__main__':
    build()


141
[
  {
    "source": "sebas_bank",
    "source_ref": "photo-1354.jpg",
    "paid_by": "S",
    "date": "",
    "status": "pending",
    "merchant": "Albert Heijn 1653",
    "amount_usd": -14.07,
    "id": "photo-1354.jpg:1",
    "type": "expense",
    "is_fee": false,
    "category_guess": "groceries",
    "country_guess": "NL",
    "trip_scope": "europe_trip",
    "allocation": "",
    "description": "Supermercado neerlandés.",
    "description_confidence": "alta",
    "description_source": "known_or_web"
  },
  {
    "source": "sebas_bank",
    "source_ref": "photo-1354.jpg",
    "paid_by": "S",
    "date": "",
    "status": "pending",
    "merchant": "Condomerie",
    "amount_usd": -8.21,
    "id": "photo-1354.jpg:2",
    "type": "expense",
    "is_fee": false,
    "category_guess": "shopping",
    "country_guess": "",
    "trip_scope": "europe_trip",
    "allocation": "",
    "description": "Sex shop conocido de Ámsterdam.",
    "description_confidence": "alta",
    "description_source": "known_or_web"
  },
  {
    "source": "sebas_bank",
    "source_ref": "photo-1354.jpg",
    "paid_by": "S",
    "date": "",
    "status": "pending",
    "merchant": "PRIMARK DAMRAK",
    "amount_usd": -3.75,
    "id": "photo-1354.jpg:3",
    "type": "expense",
    "is_fee": false,
    "category_guess": "shopping",
    "country_guess": "NL",
    "trip_scope": "europe_trip",
    "allocation": "",
    "description": "Tienda de ropa y básicos de bajo costo.",
    "description_confidence": "alta",
    "description_source": "known_or_web"
  },
  {
    "source": "sebas_bank",
    "source_ref": "photo-1354.jpg",
    "paid_by": "S",
    "date": "",
    "status": "pending",
    "merchant": "Friet Point",
    "amount_usd": -22.81,
    "id": "photo-1354.jpg:4",
    "type": "expense",
    "is_fee": false,
    "category_guess": "food_drink",
    "country_guess": "",
    "trip_scope": "europe_trip",
    "allocation": "",
    "description": "Local de papas fritas y comida rápida.",
    "description_confidence": "alta",
    "description_source": "known_or_web"
  },
  {
    "source": "sebas_bank",
    "source_ref": "photo-1354.jpg",
    "paid_by": "S",
    "date": "",
    "status": "pending",
    "merchant": "BCK*NS Groep N.V.",
    "amount_usd": -16.65,
    "id": "photo-1354.jpg:5",
    "type": "expense",
    "is_fee": false,
    "category_guess": "transport",
    "country_guess": "NL",
    "trip_scope": "europe_trip",
    "allocation": "",
    "description": "Ferrocarriles neerlandeses / transporte NS.",
    "description_confidence": "alta",
    "description_source": "known_or_web"
  },
  {
    "source": "sebas_bank",
    "source_ref": "photo-1355.jpg",
    "paid_by": "S",
    "date": "",
    "status": "pending",
    "merchant": "BCK*NS-Amsterdam 23",
    "amount_usd": -23.49,
    "id": "photo-1355.jpg:6",
    "type": "expense",
    "is_fee": false,
    "category_guess": "transport",
    "country_guess": "NL",
    "trip_scope": "europe_trip",
    "allocation": "",
    "description": "Transporte ferroviario neerlandés / NS.",
    "description_confidence": "alta",
    "description_source": "known_or_web"
  },
  {
    "source": "sebas_bank",
    "source_ref": "photo-1355.jpg",
    "paid_by": "S",
    "date": "",
    "status": "pending",
    "merchant": "R.J. Mulder B.V.",
    "amount_usd": -3.23,
    "id": "photo-1355.jpg:7",
    "type": "expense",
    "is_fee": false,
    "category_guess": "other",
    "country_guess": "",
    "trip_scope": "europe_trip",
    "allocation": "",
    "description": "Comercio local en Ámsterdam; rubro exacto no confirmado.",
    "description_confidence": "baja",
    "description_source": "known_or_web"
  },
  {
    "source": "sebas_bank",
    "source_ref": "photo-1355.jpg",
    "paid_by": "S",
    "date": "",
    "status": "pending",
    "merchant": "Het Karbeel",
    "amount_usd": -17.62,
    "id": "photo-1355.jpg:8",
    "type": "expense",
    "is_fee": false,
    "category_guess": "food_drink",
    "country_guess": "",
    "trip_scope": "europe_trip",
    "allocation": "",
    "description": "Restaurante en Warmoesstraat, Ámsterdam.",
    "description_confidence": "media",
    "description_source": "known_or_web"
  },
  {
    "source": "sebas_bank",
    "source_ref": "photo-1355.jpg",
    "paid_by": "S",
    "date": "",
    "status": "pending",
    "merchant": "SumUp *La Belle Super",
    "amount_usd": -2.94,
    "id": "photo-1355.jpg:9",
    "type": "expense",
    "is_fee": false,
    "category_guess": "groceries",
    "country_guess": "",
    "trip_scope": "europe_trip",
    "allocation": "",
    "description": "Minimercado o tienda de alimentos en Ámsterdam.",
    "description_confidence": "media",
    "description_source": "known_or_web"
  },
  {
    "source": "sebas_bank",
    "source_ref": "photo-1355.jpg",
    "paid_by": "S",
    "date": "",
    "status": "pending",
    "merchant": "Temple Bar",
    "amount_usd": -14.45,
    "id": "photo-1355.jpg:10",
    "type": "expense",
    "is_fee": false,
    "category_guess": "food_drink",
    "country_guess": "",
    "trip_scope": "europe_trip",
    "allocation": "",
    "description": "Pub irlandés / bar en Ámsterdam.",
    "description_confidence": "alta",
    "description_source": "known_or_web"
  },
  {
    "source": "sebas_bank",
    "source_ref": "photo-1355.jpg",
    "paid_by": "S",
    "date": "",
    "status": "pending",
    "merchant": "Albert Heijn 1262",
    "amount_usd": -24.81,
    "id": "photo-1355.jpg:11",
    "type": "expense",
    "is_fee": false,
    "category_guess": "groceries",
    "country_guess": "NL",
    "trip_scope": "europe_trip",
    "allocation": "",
    "description": "Supermercado neerlandés.",
    "description_confidence": "alta",
    "description_source": "known_or_web"
  },
  {
    "source": "sebas_bank",
    "source_ref": "photo-1355.jpg",
    "paid_by": "S",
    "date": "",
    "status": "pending",
    "merchant": "McDonald's Zaanstd WC",
    "amount_usd": -1.17,
    "id": "photo-1355.jpg:12",
    "type": "expense",


=== 20260530-103420-Archivos-En-Maquina-20260529T220853Z-3-001.zip ===
/home/sebas/outputs/inbox/ballbox-dropzone/20260530-103420-Archivos-En-Maquina-20260529T220853Z-3-001.zip: Zip archive data, at least v2.0 to extract, compression method=deflate
=== 20260530-230040-IMG_7806.png ===
/home/sebas/outputs/inbox/ballbox-dropzone/20260530-230040-IMG_7806.png: PNG image data, 768 x 1376, 8-bit/color RGB, non-interlaced
=== 20260530-230040-IMG_7807.png ===
/home/sebas/outputs/inbox/ballbox-dropzone/20260530-230040-IMG_7807.png: PNG image data, 768 x 1376, 8-bit/color RGB, non-interlaced
=== 20260530-230040-IMG_7808.png ===
/home/sebas/outputs/inbox/ballbox-dropzone/20260530-230040-IMG_7808.png: PNG image data, 768 x 1376, 8-bit/color RGB, non-interlaced
=== 20260530-230040-IMG_7809.png ===
/home/sebas/outputs/inbox/ballbox-dropzone/20260530-230040-IMG_7809.png: PNG image data, 768 x 1376, 8-bit/color RGB, non-interlaced
=== 20260530-230040-IMG_7810.png ===
/home/sebas/outputs/inbox/ballbox-dropzone/20260530-230040-IMG_7810.png: PNG image data, 848 x 1264, 8-bit/color RGB, non-interlaced
=== 20260530-230040-IMG_7811.png ===
/home/sebas/outputs/inbox/ballbox-dropzone/20260530-230040-IMG_7811.png: PNG image data, 1808 x 592, 8-bit/color RGB, non-interlaced
=== 20260530-230040-IMG_7812.png ===
/home/sebas/outputs/inbox/ballbox-dropzone/20260530-230040-IMG_7812.png: PNG image data, 848 x 1248, 8-bit/color RGB, non-interlaced
=== 20260530-230040-IMG_7813.png ===
/home/sebas/outputs/inbox/ballbox-dropzone/20260530-230040-IMG_7813.png: PNG image data, 1376 x 768, 8-bit/color RGB, non-interlaced
=== 20260531-074743-Archivos-En-Maquina-20260529T220853Z-3-001.zip ===
/home/sebas/outputs/inbox/ballbox-dropzone/20260531-074743-Archivos-En-Maquina-20260529T220853Z-3-001.zip: Zip archive data, at least v2.0 to extract, compression method=deflate
=== 20260601-124029-Stmt-02-17-2026.pdf ===
/home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-Stmt-02-17-2026.pdf: PDF document, version 1.3, 2 page(s)
=== 20260601-124029-Stmt-03-17-2026.pdf ===
/home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-Stmt-03-17-2026.pdf: PDF document, version 1.3, 3 page(s)
=== 20260601-124029-Stmt-04-15-2026.pdf ===
/home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-Stmt-04-15-2026.pdf: PDF document, version 1.3, 2 page(s)
=== 20260601-124029-Stmt-05-15-2026.pdf ===
/home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-Stmt-05-15-2026.pdf: PDF document, version 1.3, 3 page(s)
=== 20260601-124052-ace55189-9196-4ff4-b5f3-bbddbfdb80f0.jpeg ===
/home/sebas/outputs/inbox/ballbox-dropzone/20260601-124052-ace55189-9196-4ff4-b5f3-bbddbfdb80f0.jpeg: JPEG image data, JFIF standard 1.01, aspect ratio, density 72x72, segment length 16, Exif Standard: [TIFF image data, big-endian, direntries=1], progressive, precision 8, 738x1600, components 3


**Evaluating app enhancements**

I need to check if the app can manage extra fields, which is likely. It might be easiest to implement source merging by enhancing the parser or build to eliminate duplicates of the same merchant, amount, and paid by details between the pending screenshot and the posted statement, all while keeping one entry that has both source references and status within the specified date range. Also, I should compare existing entries with the image, but I need to do OCR on the image first.

tmp=$(mktemp -d) && for f in /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-*.pdf; do bn=$(basename "$f" .pdf); pdftotext "$f" "$tmp/$bn.txt"; echo "=== $bn ==="; sed -n '1,220p' "$tmp/$bn.txt"; done

tesseract /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124052-ace55189-9196-4ff4-b5f3-bbddbfdb80f0.jpeg stdout 2>/dev/null | sed -n '1,220p'


=== 20260601-124029-Stmt-02-17-2026 ===
PAGE 1

24-Hour Customer Service: 303-237-5000
or 800-964-3444 outside Denver Metro
New Account or Loan: 303-238-9000
or 877-933-9800 outside Denver Metro
www.efirstbank.com

FIRSTBANK
PO BOX 150097
LAKEWOOD CO 80215-0097

SEBASTIAN FAVARON
TRONADOR 1478 5TH FLOOR APT B
BUENOS AIRES

ACCOUNT
NUMBER

XXX-XXX-6243

STATEMENT
DATE

2-17-2026

INTEREST
EARNED
THIS YEAR

N/A

ACCOUNT SUMMARY - - ANYWHERE ACCOUNT - SAFEKEEPING
CLOSING BALANCE FROM PREVIOUS STATEMENT............................................................DATE: 1-16-2026
1 DEPOSITS AND OTHER ADDITIONS TOTALING................................................
5 CHECKS AND OTHER WITHDRAWALS TOTALING............................................
CLOSING BALANCE FOR THIS STATEMENT..........................................................................DATE: 2-17-2026
MINIMUM BALANCE OF

578.34

CHECKS AND OTHER WITHDRAWALS

798.34
7,995.00+
6,812.601,980.74

ON....................................................
2-04-2026

*SHOWS BREAK IN CHECK NUMBER,

#SHOWS NOT MACHINE READABLE

NO CHECKS WITH SERIAL NUMBERS THIS CYCLE
ELECTRONIC AND MISCELLANEOUS WITHDRAWALS
DATE.............AMOUNT...DESCRIPTION
1 - 20
2 - 04
2 - 09
2 - 11
2 - 17

20.00
200.00
191.60
6,381.00
20.00

VISA
OPENAI *CHATGPT SUBSCR
OPENAI.COM
MOBILE TRANSFER #932384 TO JOHN NEWKIRK (ZELLE)
VISA
Omio
917-9243330
ACH ACH TRANSF INTERACTIVE BROK
VISA
CLAUDE.AI SUBSCRIPTION
ANTHROPIC.COM
RECURRING PURCHASE

CA ON 01-19 2561
FL ON 02-08 2561
CA ON 02-15 2561

DEPOSITS AND OTHER ADDITIONS
DATE....................AMOUNT...........DESCRIPTION
2 - 05

7,995.00

ACH PAYMENTS 'Deel, IV3B3I5ZG

DAILY BALANCE SUMMARY
DATE.................................BALANCE

DATE.................................BALANCE

DATE.................................BALANCE

1 - 20
2 - 04

2 - 05
2 - 09

2 - 11
2 - 17

778.34
578.34

8,573.34
8,381.74

2,000.74
1,980.74

NON-SUFFICIENT FUNDS FEES AND OTHER OVERDRAFT FEES
TOTAL FOR
STATEMENT PERIOD

TOTAL 2026
YEAR-TO-DATE

TOTAL OVERDRAFT FEES

$.00

$.00

TOTAL RETURNED ITEM

$.00

$.00

FirstBank Customers have several choices to help manage their accounts and avoid overdrafts. Please contact us at 1-800-964-3444 if you no longer
want us to pay items that may overdraw your account. Customers can also apply for a Cash Reserve - a line of credit that can be used for overdraft
protection, or enroll for the Linked Accounts Overdraft Protection service that allows customers to link eligible accounts for overdraft protection. In
addition, Online Banking customers can enroll for free text message and email account balance alerts to receive notification of a low account balance. To
enroll, visit efirstbank.com.

****CONTINUED ON NEXT PAGE****

PAGE 2

ACCOUNT
NUMBER

XXX-XXX-6243

STATEMENT
DATE

2-17-2026

HOW ARE WE DOING?
We are working very hard to maintain the highest level of customer service possible. However if we make a mistake, or you receive poor
service from any of our employees, we want you to let us know. Please call one of our customer representatives at 303-231-2000 (outside
metro Denver: 1-800-230-1060) with any comments or complaints. We will do our best to solve your problem. If our service was especially
good we'd like to hear about that too. We welcome any suggestions you might have about new products or ways we could improve our
service to you. Thank you for banking with us!

HOW TO BALANCE YOUR CHECKBOOK

Outstanding Checks

NUMBER

Enter Checkbook Balance:

$

ADD: Deposits Not Entered in Checkbook

$

Subtotal:

$

SUBTRACT: Deductions Not Entered in Checkbook

$

EQUALS: Revised Checkbook Balance*

$

Enter Bank Balance from Statement

$

ADD: Deposits Not Included in This Statement

$

Subtotal

$

SUBTRACT: Outstanding Checks

$

**

EQUALS Revised Bank Balance

$

*

AMOUNT

*

* These totals should agree
=== 20260601-124029-Stmt-03-17-2026 ===
PAGE 1

24-Hour Customer Service: 303-237-5000
or 800-964-3444 outside Denver Metro
New Account or Loan: 303-238-9000
or 877-933-9800 outside Denver Metro
www.efirstbank.com

FIRSTBANK
PO BOX 150097
LAKEWOOD CO 80215-0097

SEBASTIAN FAVARON
TRONADOR 1478 5TH FLOOR APT B
BUENOS AIRES

ACCOUNT
NUMBER

XXX-XXX-6243

STATEMENT
DATE

3-17-2026

INTEREST
EARNED
THIS YEAR

N/A

ACCOUNT SUMMARY - - ANYWHERE ACCOUNT - SAFEKEEPING
CLOSING BALANCE FROM PREVIOUS STATEMENT............................................................DATE: 2-17-2026
0 DEPOSITS AND OTHER ADDITIONS TOTALING................................................
15 CHECKS AND OTHER WITHDRAWALS TOTALING............................................
CLOSING BALANCE FOR THIS STATEMENT..........................................................................DATE: 3-17-2026
MINIMUM BALANCE OF

343.96

CHECKS AND OTHER WITHDRAWALS

1,980.74
.00+
1,636.78343.96

ON....................................................
3-17-2026

*SHOWS BREAK IN CHECK NUMBER,

#SHOWS NOT MACHINE READABLE

NO CHECKS WITH SERIAL NUMBERS THIS CYCLE
ELECTRONIC AND MISCELLANEOUS WITHDRAWALS
DATE.............AMOUNT...DESCRIPTION
2 - 20

20.00

3 - 03
3 - 03
3 - 04

672.57
20.18
15.00

3 - 09
3 - 09
3 - 09
3 - 09
3 - 09
3 - 09
3 - 09
3 - 09
3 - 09
3 - 09
3 - 17

0.24
196.27
204.35
6.13
74.27
2.23
60.67
1.82
340.83
10.22
12.00

VISA
OPENAI *CHATGPT SUBSCR
RECURRING PURCHASE
VISA
VILLAGE ROSA*Vill
FEE FOR INTERNATIONAL TRANSACTION
VISA
VERCEL DOMAINS
RECURRING PURCHASE
VISA
Amazon web services
VISA
GoEuro Corp
VISA
Omio
FEE FOR INTERNATIONAL TRANSACTION
VISA
Omio
FEE FOR INTERNATIONAL TRANSACTION
VISA
Omio
FEE FOR INTERNATIONAL TRANSACTION
VISA
Omio
FEE FOR INTERNATIONAL TRANSACTION
MONTHLY ACCOUNT SERVICE FEE

OPENAI.COM

CA ON 02-19 2561

IMBITUBA

BR ON 03-02 2561

VERCEL.COM

CA ON 03-03 2561

aws.amazon.co
Fort Myers
Berlin

WA ON 03-06 2561
FL ON 03-06 2561
DE ON 03-06 2561

Berlin

DE ON 03-06 2561

Berlin

DE ON 03-06 2561

Berlin

DE ON 03-06 2561

DEPOSITS AND OTHER ADDITIONS
NO DEPOSITS THIS CYCLE
DAILY BALANCE SUMMARY
DATE.................................BALANCE

DATE.................................BALANCE

DATE.................................BALANCE

2 - 18
2 - 20

3 - 03
3 - 04

3 - 09
3 - 17

1,980.74
1,960.74

1,267.99
1,252.99

****CONTINUED ON NEXT PAGE****

355.96
343.96

PAGE 2

ACCOUNT
NUMBER

XXX-XXX-6243

STATEMENT
DATE

3-17-2026

SPECIAL MESSAGES AND IMPORTANT NOTICES

Effective May 1, 2026, the following change will be implemented:
All newly opened consumer transaction accounts will be automatically opted in to
overdrafts related to checks, ACH transactions, online bill payments, and recurring
debit card transactions.
Please refer to the Overdraft Opt Status section of the Deposit Account Agreement for
additional information.
HOW ARE WE DOING?
We are working very hard to maintain the highest level of customer service possible. However if we make a mistake, or you receive poor
service from any of our employees, we want you to let us know. Please call one of our customer representatives at 303-231-2000 (outside
metro Denver: 1-800-230-1060) with any comments or complaints. We will do our best to solve your problem. If our service was especially
good we'd like to hear about that too. We welcome any suggestions you might have about new products or ways we could improve our
service to you. Thank you for banking with us!

HOW TO BALANCE YOUR CHECKBOOK

Outstanding Checks

NUMBER

Enter Checkbook Balance:

$

ADD: Deposits Not Entered in Checkbook

=== 20260601-124029-Stmt-04-15-2026 ===
PAGE 1

24-Hour Customer Service: 303-237-5000
or 800-964-3444 outside Denver Metro
New Account or Loan: 303-238-9000
or 877-933-9800 outside Denver Metro
www.efirstbank.com

FIRSTBANK
PO BOX 150097
LAKEWOOD CO 80215-0097

SEBASTIAN FAVARON
TRONADOR 1478 5TH FLOOR APT B
BUENOS AIRES

ACCOUNT
NUMBER

XXX-XXX-6243

STATEMENT
DATE

4-15-2026

INTEREST
EARNED
THIS YEAR

N/A

ACCOUNT SUMMARY - - ANYWHERE ACCOUNT - SAFEKEEPING
CLOSING BALANCE FROM PREVIOUS STATEMENT............................................................DATE: 3-17-2026
3 DEPOSITS AND OTHER ADDITIONS TOTALING................................................
14 CHECKS AND OTHER WITHDRAWALS TOTALING............................................
CLOSING BALANCE FOR THIS STATEMENT..........................................................................DATE: 4-15-2026
MINIMUM BALANCE OF

323.96

CHECKS AND OTHER WITHDRAWALS

343.96
2,459.13+
665.492,137.60

ON....................................................
3-20-2026

*SHOWS BREAK IN CHECK NUMBER,

#SHOWS NOT MACHINE READABLE

NO CHECKS WITH SERIAL NUMBERS THIS CYCLE
ELECTRONIC AND MISCELLANEOUS WITHDRAWALS
DATE.............AMOUNT...DESCRIPTION
3 - 20

20.00

3 - 30
3 - 30
3 - 31
3 - 31
4 - 02
4 - 02
4 - 02
4 - 02
4 - 03
4 - 07
4 - 07
4 - 13
4 - 13

87.77
2.63
80.84
2.43
56.67
1.70
87.89
2.64
0.27
219.47
6.58
93.79
2.81

VISA
OPENAI *CHATGPT SUBSCR
RECURRING PURCHASE
VISA
LOUVRETICKET INT2726905
FEE FOR INTERNATIONAL TRANSACTION
VISA
CHAT.VERSAILLES4312134
FEE FOR INTERNATIONAL TRANSACTION
VISA
Buckaroo *www annef
FEE FOR INTERNATIONAL TRANSACTION
VISA
SAGRADA FAMILIA WEB B2C
FEE FOR INTERNATIONAL TRANSACTION
VISA
Amazon web services
VISA
Omio
FEE FOR INTERNATIONAL TRANSACTION
VISA
biglietteriamusei.vatic
FEE FOR INTERNATIONAL TRANSACTION

OPENAI.COM

CA ON 03-19 2561

75PARIS

FR ON 03-28 2561

78VERSAILLES

FR ON 03-29 2561

AMSTERDAM

NL ON 04-01 2561

PAGES, PASSAT

ES ON 04-01 2561

aws.amazon.co
Berlin

WA ON 04-02 2561
DE ON 04-06 2561

Citta del Vat

VA ON 04-10 2561

DEPOSITS AND OTHER ADDITIONS
DATE....................AMOUNT...........DESCRIPTION
3 - 26
4 - 08
4 - 13

1,595.00
69.13
795.00

ACH PAYMENTS 'Deel, IE97G2XSJ
VISA Omio
917-9243330 FL ON 04-07 2561
ACH PAYMENTS 'Deel, IPUZUF4LS

DAILY BALANCE SUMMARY
DATE.................................BALANCE

DATE.................................BALANCE

DATE.................................BALANCE

3 - 18
3 - 20
3 - 26
3 - 30

3 - 31
4 - 02
4 - 03
4 - 07

4 - 08
4 - 13

343.96
323.96
1,918.96
1,828.56

1,745.29
1,596.39
1,596.12
1,370.07

****CONTINUED ON NEXT PAGE****

1,439.20
2,137.60

PAGE 2

ACCOUNT
NUMBER

XXX-XXX-6243

STATEMENT
DATE

4-15-2026

HOW ARE WE DOING?
We are working very hard to maintain the highest level of customer service possible. However if we make a mistake, or you receive poor
service from any of our employees, we want you to let us know. Please call one of our customer representatives at 303-231-2000 (outside
metro Denver: 1-800-230-1060) with any comments or complaints. We will do our best to solve your problem. If our service was especially
good we'd like to hear about that too. We welcome any suggestions you might have about new products or ways we could improve our
service to you. Thank you for banking with us!

HOW TO BALANCE YOUR CHECKBOOK

Outstanding Checks

NUMBER

Enter Checkbook Balance:

=== 20260601-124029-Stmt-05-15-2026 ===
PAGE 1

24-Hour Customer Service: 303-237-5000
or 800-964-3444 outside Denver Metro
New Account or Loan: 303-238-9000
or 877-933-9800 outside Denver Metro
www.efirstbank.com

FIRSTBANK
PO BOX 150097
LAKEWOOD CO 80215-0097

SEBASTIAN FAVARON
TRONADOR 1478 5TH FLOOR APT B
BUENOS AIRES

ACCOUNT
NUMBER

XXX-XXX-6243

STATEMENT
DATE

5-15-2026

INTEREST
EARNED
THIS YEAR

N/A

ACCOUNT SUMMARY - - ANYWHERE ACCOUNT - SAFEKEEPING
CLOSING BALANCE FROM PREVIOUS STATEMENT............................................................DATE: 4-15-2026
1 DEPOSITS AND OTHER ADDITIONS TOTALING................................................
76 CHECKS AND OTHER WITHDRAWALS TOTALING............................................
CLOSING BALANCE FOR THIS STATEMENT..........................................................................DATE: 5-15-2026
MINIMUM BALANCE OF

2,049.65

CHECKS AND OTHER WITHDRAWALS

ON....................................................
5-04-2026

*SHOWS BREAK IN CHECK NUMBER,

#SHOWS NOT MACHINE READABLE

NO CHECKS WITH SERIAL NUMBERS THIS CYCLE
ELECTRONIC AND MISCELLANEOUS WITHDRAWALS
DATE.............AMOUNT...DESCRIPTION
4 - 20
4 - 20
4 - 20

18.70
0.56
20.00

4 - 29
4 - 29
5 - 04
5 - 11
5 - 11
5 - 11
5 - 11
5 - 11
5 - 11
5 - 12
5 - 12
5 - 12
5 - 12
5 - 12
5 - 12
5 - 12
5 - 12
5 - 12
5 - 12
5 - 13
5 - 13
5 - 13
5 - 13
5 - 13
5 - 13
5 - 13
5 - 13
5 - 13
5 - 13
5 - 13
5 - 13
5 - 13
5 - 13
5 - 13
5 - 13
5 - 13
5 - 13
5 - 13

47.02
1.41
0.26
32.88
0.99
335.31
10.06
47.04
1.41
14.15
0.42
166.20
4.99
94.26
2.83
9.42
0.28
15.31
0.46
15.31
0.46
38.92
1.17
31.30
0.94
16.75
0.50
25.35
0.76
17.69
0.53
7.67
0.23
8.49
0.25
7.67
0.23
18.87

VISA
MUSEO DEL PRADO
FEE FOR INTERNATIONAL TRANSACTION
VISA
OPENAI *CHATGPT SUBSCR
RECURRING PURCHASE
VISA
WWW.DUOMO.FIRENZE.IT
FEE FOR INTERNATIONAL TRANSACTION
VISA
Amazon web services
VISA
Cabify ES 2619qlqSubba
FEE FOR INTERNATIONAL TRANSACTION
VISA
UNIQLO GranVia
FEE FOR INTERNATIONAL TRANSACTION
VISA
UNIQLO GranVia
FEE FOR INTERNATIONAL TRANSACTION
VISA
PHONE SHOP II GRAN VIA
FEE FOR INTERNATIONAL TRANSACTION
VISA
LEFTIES
FEE FOR INTERNATIONAL TRANSACTION
VISA
EL CORTE INGLES
FEE FOR INTERNATIONAL TRANSACTION
VISA
EL CORTE INGLES
FEE FOR INTERNATIONAL TRANSACTION
VISA
INTRUSO
FEE FOR INTERNATIONAL TRANSACTION
VISA
INTRUSO
FEE FOR INTERNATIONAL TRANSACTION
VISA
UBR* PENDING.UBER.COM
FEE FOR INTERNATIONAL TRANSACTION
VISA
AEROP.ADOLFO SUAREZ MA
FEE FOR INTERNATIONAL TRANSACTION
VISA
BCK*NS SCHIPHOL 215
FEE FOR INTERNATIONAL TRANSACTION
VISA
CITY PHONE INTERNET
FEE FOR INTERNATIONAL TRANSACTION
VISA
BCK*GHM BB B.V.
FEE FOR INTERNATIONAL TRANSACTION
VISA
fa. B.Smit
FEE FOR INTERNATIONAL TRANSACTION
VISA
Cafe Katoen
FEE FOR INTERNATIONAL TRANSACTION
VISA
THE GAME GALAXY
FEE FOR INTERNATIONAL TRANSACTION
VISA
The Bulldog First

PRADO PASEO

ES ON 04-19 2561

OPENAI.COM

CA ON 04-19 2561

WWW.DUOMO.FIR

IT ON 04-28 2561

aws.amazon.co
Madrid

WA ON 05-02 2561


**Investigating OCR issues**

It seems like I need more of the statement on page 2, and there's a chance that the OCR process might have failed due to language issues. I think I should check the image quality and possibly rerun the OCR for that page and the remaining ones. There’s definitely something to unpack here, so I’ll take a closer look and see how I can improve the results!

tmp=$(mktemp -d) && pdftotext /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-Stmt-05-15-2026.pdf "$tmp/stmt.txt" && sed -n '180,360p' "$tmp/stmt.txt'

python3 - <<'PY'
from PIL import Image
img=Image.open('/home/sebas/outputs/inbox/ballbox-dropzone/20260601-124052-ace55189-9196-4ff4-b5f3-bbddbfdb80f0.jpeg')
print(img.size)
PY

tesseract /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124052-ace55189-9196-4ff4-b5f3-bbddbfdb80f0.jpeg stdout --psm 6 2>/dev/null | sed -n '1,260p'


/bin/bash: -c: line 1: unexpected EOF while looking for matching `"'

Command exited with code 2


(738, 1600)


(no output)


**Considering OCR options**

I think I need some image content, and I'm weighing my options. I could use OCR with ImageMagick, but maybe it’s easier to use Python with pytesseract instead. But I wonder if Tesseract will need a specific language package? I should inspect the image first, though attaching it might be impossible. So, let’s focus on getting the rest of the statement correct before diving into the OCR part.

tmp=$(mktemp -d); pdftotext /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-Stmt-05-15-2026.pdf "$tmp/stmt.txt"; sed -n '160,340p' "$tmp/stmt.txt"

python3 - <<'PY'
from PIL import Image
img=Image.open('/home/sebas/outputs/inbox/ballbox-dropzone/20260601-124052-ace55189-9196-4ff4-b5f3-bbddbfdb80f0.jpeg')
# crop top maybe where text is; just print mode
print(img.mode)
PY


VISA
PHONE SHOP II GRAN VIA
FEE FOR INTERNATIONAL TRANSACTION
VISA
LEFTIES
FEE FOR INTERNATIONAL TRANSACTION
VISA
EL CORTE INGLES
FEE FOR INTERNATIONAL TRANSACTION
VISA
EL CORTE INGLES
FEE FOR INTERNATIONAL TRANSACTION
VISA
INTRUSO
FEE FOR INTERNATIONAL TRANSACTION
VISA
INTRUSO
FEE FOR INTERNATIONAL TRANSACTION
VISA
UBR* PENDING.UBER.COM
FEE FOR INTERNATIONAL TRANSACTION
VISA
AEROP.ADOLFO SUAREZ MA
FEE FOR INTERNATIONAL TRANSACTION
VISA
BCK*NS SCHIPHOL 215
FEE FOR INTERNATIONAL TRANSACTION
VISA
CITY PHONE INTERNET
FEE FOR INTERNATIONAL TRANSACTION
VISA
BCK*GHM BB B.V.
FEE FOR INTERNATIONAL TRANSACTION
VISA
fa. B.Smit
FEE FOR INTERNATIONAL TRANSACTION
VISA
Cafe Katoen
FEE FOR INTERNATIONAL TRANSACTION
VISA
THE GAME GALAXY
FEE FOR INTERNATIONAL TRANSACTION
VISA
The Bulldog First

PRADO PASEO

ES ON 04-19 2561

OPENAI.COM

CA ON 04-19 2561

WWW.DUOMO.FIR

IT ON 04-28 2561

aws.amazon.co
Madrid

WA ON 05-02 2561
ES ON 05-10 2561

Madrid

ES ON 05-10 2561

Madrid

ES ON 05-10 2561

ESCALINATADE

ES ON 05-11 2561

MADRID

ES ON 05-11 2561

MADRID

ES ON 05-11 2561

MADRID

ES ON 05-11 2561

MADRID

ES ON 05-11 2561

MADRID

ES ON 05-11 2561

AMSTERDAM

NL ON 05-12 2561

MADRID

ES ON 05-12 2561

LUCHTHAVEN SC

NL ON 05-12 2561

AMSTERDAM

NL ON 05-12 2561

AMSTERDAM

NL ON 05-12 2561

AMSTERDAM

NL ON 05-12 2561

Amsterdam

NL ON 05-12 2561

AMSTERDAM

NL ON 05-12 2561

Amsterdam

NL ON 05-12 2561

****CONTINUED ON NEXT PAGE****

2,137.60
3,000.00+
1,335.733,801.87

PAGE 2

ACCOUNT
NUMBER

XXX-XXX-6243

STATEMENT
DATE

5-15-2026

ELECTRONIC AND MISCELLANEOUS WITHDRAWALSCONTINUED
DATE.............AMOUNT...DESCRIPTION
5 - 13
5 - 13
5 - 13
5 - 13
5 - 13
5 - 14
5 - 14
5 - 14
5 - 14
5 - 14
5 - 14
5 - 14
5 - 14
5 - 14
5 - 14
5 - 15
5 - 15
5 - 15
5 - 15
5 - 15
5 - 15
5 - 15
5 - 15
5 - 15
5 - 15
5 - 15
5 - 15
5 - 15
5 - 15
5 - 15


RGB


tmp=$(mktemp -d); pdftotext /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-Stmt-05-15-2026.pdf "$tmp/stmt.txt"; sed -n '340,520p' "$tmp/stmt.txt"


5 - 15
5 - 15
5 - 15
5 - 15
5 - 15
5 - 15

0.57
14.15
0.42
5.90
0.18
8.51
0.26
8.84
0.27
20.58
0.62
22.23
0.67
52.47
1.57
1.17
0.04
1.17
0.04
2.94
0.09
3.23
0.10
9.87
0.30
14.45
0.43
17.62
0.53
23.49
0.70
24.81
0.74
77.40
2.32

FEE FOR INTERNATIONAL TRANSACTION
VISA
CCV*LAMOR
FEE FOR INTERNATIONAL TRANSACTION
VISA
CCV*LAMOR
FEE FOR INTERNATIONAL TRANSACTION
VISA
JUMBO AMSTERDAM CITY DA
FEE FOR INTERNATIONAL TRANSACTION
VISA
CCV*V.O.F.TWINKIES
FEE FOR INTERNATIONAL TRANSACTION
VISA
Anne Frank Stichting
FEE FOR INTERNATIONAL TRANSACTION
VISA
Van Gogh Museum
FEE FOR INTERNATIONAL TRANSACTION
VISA
CCV*IL PRIMO
FEE FOR INTERNATIONAL TRANSACTION
VISA
McDonald's Zaanstd WC
FEE FOR INTERNATIONAL TRANSACTION
VISA
McDonald's Zaanstd WC
FEE FOR INTERNATIONAL TRANSACTION
VISA
SumUp *La Belle Super
FEE FOR INTERNATIONAL TRANSACTION
VISA
R.J. MULDER B.V.
FEE FOR INTERNATIONAL TRANSACTION
VISA
Victoria Hotel FB_MRRAB
FEE FOR INTERNATIONAL TRANSACTION
VISA
Temple Bar
FEE FOR INTERNATIONAL TRANSACTION
VISA
Het Karbeel
FEE FOR INTERNATIONAL TRANSACTION
VISA
BCK*NS-AMSTERDAM 23
FEE FOR INTERNATIONAL TRANSACTION
VISA
ALBERT HEIJN 1262
FEE FOR INTERNATIONAL TRANSACTION
VISA
Flagship Amsterdam B.V
FEE FOR INTERNATIONAL TRANSACTION

AMSTERDAM

NL ON 05-12 2561

AMSTERDAM

NL ON 05-12 2561

AMSTERDAM

NL ON 05-13 2561

BUSSUM

NL ON 05-13 2561

Amsterdam

NL ON 05-13 2561

Amsterdam

NL ON 05-13 2561

AMSTERDAM

NL ON 05-13 2561

ZAANDAM

NL ON 05-14 2561

ZAANDAM

NL ON 05-14 2561

Purmerend

NL ON 05-14 2561

ZAANDAM

NL ON 05-14 2561

Amsterdam

NL ON 05-14 2561

Amsterdam

NL ON 05-14 2561

Amsterdam

NL ON 05-14 2561

AMSTERDAM

NL ON 05-14 2561

ZAANDAM

NL ON 05-14 2561

Amsterdam

NL ON 05-14 2561

DEPOSITS AND OTHER ADDITIONS
DATE....................AMOUNT...........DESCRIPTION
5 - 11

3,000.00

ACH ACH TRANSF INTERACTIVE BROK

DAILY BALANCE SUMMARY
DATE.................................BALANCE

DATE.................................BALANCE

DATE.................................BALANCE

4 - 16
4 - 20


python3 - <<'PY'
from PIL import Image
img=Image.open('/home/sebas/outputs/inbox/ballbox-dropzone/20260601-124052-ace55189-9196-4ff4-b5f3-bbddbfdb80f0.jpeg')
# enlarge and grayscale
img=img.convert('L')
img=img.resize((img.width*3,img.height*3))
out='/tmp/vicky-ocr-prep.png'
img.save(out)
print(out)
PY
 tesseract /tmp/vicky-ocr-prep.png stdout --psm 6 2>/dev/null | sed -n '1,260p'


**Inspecting image issues**

I’m still not getting any OCR results, so maybe the image is blank? I should probably check the dimensions or think about converting it. I wonder if I could use Python to analyze some image statistics. HEIC format might not be the issue here. I think there's also a tool that can read image attachments, so it might be worth using that. Let’s take a moment to inspect the image visually!


Read image file [image/jpeg]


**Evaluating transactions from statements**

I need to manually extract relevant lines from an image. I could zoom and crop it, possibly using OCR; it needs to be visible enough. I’ve got to determine what already exists in the vicky-manual, especially since the new image adds many later dates that likely aren’t in it. I want to avoid duplicate PDF transactions, especially with Sebas transactions. It seems I should focus only on genuinely new entries and merge any info if duplicates exist.

**Analyzing February transactions**

The existing extracted text already covers many entries from March to May, but not February, except for one related to Airbnb. I should consider adding the new February items and maybe also include some metadata for existing entries. I could update existing ones to reflect the correct date or status since the screenshots have posted dates. If I append duplicates, they’ll create issues, so better to enhance the parser with deduplication by payer, date, merchant, and type. Also, I’ll need to determine the categories for these transactions.

**Reviewing transfer categorization**

I’m considering the Zelle transfer to a friend—I'm thinking it might not be trip-related and should just be a transfer. The current parser handles transfers if they involve Deel or Interactive Brokers, so maybe I could skip unrelated ones. The user mentioned adding expenses (“gastos”), but since this Zelle transfer doesn't seem like an expense, it might not be needed. However, since the dataset contains both incomes and transfers, I must ensure it aligns with the trip-related expenses. It’s worth checking the statement pages, too, to see if there are relevant entries.

tmp=$(mktemp -d); pdftotext /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-Stmt-05-15-2026.pdf "$tmp/stmt.txt"; sed -n '520,760p' "$tmp/stmt.txt"


4 - 20
4 - 29

5 - 04
5 - 11
5 - 12

5 - 13
5 - 14
5 - 15

2,137.60
2,098.34
2,049.91

2,049.65
4,621.96
4,313.64

****CONTINUED ON NEXT PAGE****

4,099.33
3,983.31
3,801.87

PAGE 3

ACCOUNT
NUMBER

XXX-XXX-6243

STATEMENT
DATE

5-15-2026

HOW ARE WE DOING?
We are working very hard to maintain the highest level of customer service possible. However if we make a mistake, or you receive poor
service from any of our employees, we want you to let us know. Please call one of our customer representatives at 303-231-2000 (outside
metro Denver: 1-800-230-1060) with any comments or complaints. We will do our best to solve your problem. If our service was especially
good we'd like to hear about that too. We welcome any suggestions you might have about new products or ways we could improve our
service to you. Thank you for banking with us!

HOW TO BALANCE YOUR CHECKBOOK

Outstanding Checks

NUMBER

Enter Checkbook Balance:

$

ADD: Deposits Not Entered in Checkbook

$

Subtotal:

$

SUBTRACT: Deductions Not Entered in Checkbook

$

EQUALS: Revised Checkbook Balance*

$

Enter Bank Balance from Statement

$

ADD: Deposits Not Included in This Statement

$

Subtotal

$

SUBTRACT: Outstanding Checks

$

**

EQUALS Revised Bank Balance

$

*

AMOUNT

*

* These totals should agree

**

TOTAL

$

IN CASE OF ERRORS OR QUESTIONS ABOUT YOUR ELECTRONIC FUNDS TRANSFERS
Telephone us at the number shown, or write us at the address shown at the beginning of this statement as soon as you can, if you think
your statement or receipt is wrong or if you need more information about a transfer on the statement or receipt. We must hear from you no
later than 60 days after we sent you the FIRST statement on which the error or problem appeared. (1) Tell us your name and account number.
(2) Describe the error or the transfer you are unsure about, and explain as best you can why you believe there is an error or why you need
more information. (3) Tell us the dollar amount of the suspected error. We will investigate your complaint and will correct any error
promptly. If we take more than 10 business days to do this, we will credit your account for the amount you think is in error, so that you
will have use of the money during the time it takes us to complete our investigation.
FAIR AND ACCURATECREDIT TRANSACTIONS ACT
We may report information about your account to credit bureaus. Late payments, missed payments, or other defaults on your account may be
reflected in your credit report.


**Evaluating expense entries**

I need to check for existing duplicates for February lines and possibly parse an image manually for Vicky's manual additions. I might append from the visible list, especially since the image starts from 08.05.26, including transactions that could overlap with existing entries. It seems that dates and conversions in the image need careful attention so I can avoid duplicates. I'll focus on transactions from 14-27/05, considering those not already in the Vicky manual. Using cropping and OCR might help clarify things further.

**Optimizing image processing**

I notice that the screenshot bars in the image are confusing, so cropping and upscaling might be necessary. I’m considering using a Python OCR library, but Tesseract isn’t producing output—perhaps it’s due to the image being too large or a path issue? I could also check the memory. It may be worth trying ImageMagick for threshold adjustments, and cropping pages individually. Using OpenCV with Python to threshold the image might be a good alternative.

python3 - <<'PY'
from PIL import Image, ImageOps, ImageFilter
img=Image.open('/home/sebas/outputs/inbox/ballbox-dropzone/20260601-124052-ace55189-9196-4ff4-b5f3-bbddbfdb80f0.jpeg')
# crop out app chrome top and bottom overlay roughly for first upper page and lower page separately
crops=[('top',(40,180,730,890)),('bottom',(40,930,730,1540))]
for name,box in crops:
    c=img.crop(box).convert('L')
    c=ImageOps.autocontrast(c)
    c=c.resize((c.width*3,c.height*3))
    c=c.point(lambda p: 255 if p>180 else 0)
    path=f'/tmp/{name}_ocr.png'
    c.save(path)
    print(path)
PY
for f in /tmp/top_ocr.png /tmp/bottom_ocr.png; do echo "=== $f ==="; tesseract "$f" stdout --psm 6 2>/dev/null | sed -n '1,220p'; done


/tmp/top_ocr.png
/tmp/bottom_ocr.png
=== /tmp/top_ocr.png ===
=== /tmp/bottom_ocr.png ===


/bin/bash: line 1: tesseract: command not found


**Transcribing image data**

I realize the Python OCR tool isn't available, so I’ll manually transcribe the visible entries from the image. I'll compare these entries with what's already known and add new lines. It makes sense to ensure I only pull clear and unambiguous lines, prompting the user about any uncertain entries. The user mentioned, "ante duda consulta," suggesting I should clarify ambiguous entries. I’ll start with visible rows from May 14 to May 27, using the image data available.

**Analyzing transaction data**

I’m working through the transaction details from the image. There’s a conversion I need to clarify, such as 50,28 EUR, which might be related to a Spotify subscription on May 17. Then, there are several other transactions listed with their amounts converted to USD. One I need to check is "BOUILLON PIGALLE," which might be more complex due to differing figures. I want to be careful with how I log these amounts, especially the more ambiguous entries.

python3 - <<'PY'
from PIL import Image
img=Image.open('/home/sebas/outputs/inbox/ballbox-dropzone/20260601-124052-ace55189-9196-4ff4-b5f3-bbddbfdb80f0.jpeg')
# save four zoom crops
boxes={
'a':(60,180,700,560),
'b':(60,560,700,900),
'c':(60,960,700,1230),
'd':(60,1230,700,1530),
}
for k,box in boxes.items():
    c=img.crop(box)
    c=c.resize((c.width*2,c.height*2))
    path=f'/tmp/vicky_{k}.png'
    c.save(path)
    print(path)
PY


/tmp/vicky_a.png
/tmp/vicky_b.png
/tmp/vicky_c.png
/tmp/vicky_d.png


Read image file [image/png]


**Implementing parsing strategies**

I'm thinking about how to improve the process. I could parse an additional raw file, perhaps `raw/statements-manual.txt`, or simply append it to the extracted text since that might be easier.

Next, I'll build a script to parse both the Sebas screenshot and the statement manual, focusing on shared sections. I'll also add a deduplication function to merge entries by payer, amount, and merchant similarity. It could get tricky with comparing pending and posted transactions, but I believe it's manageable.

**Organizing files for traceability**

I’m considering copying new images into the raw/images directory and PDFs into either raw/statements or raw/source-docs to keep things organized. It seems crucial for maintaining business value. I guess I’ll need to create those directories and maybe use Bash to do it. As for generated content, I'll likely copy images into raw/images and PDFs into raw/statements, ensuring everything is neatly categorized. This will help maintain a clear workflow.

python3 - <<'PY'
import json, pathlib
p=pathlib.Path('/home/sebas/work/gastos-europa/derived/transactions.json')
rows=json.loads(p.read_text())
for q in ['Claude.AI','Omio 917-9243330','JOHN NEWKIRK']:
    hits=[r for r in rows if q.lower() in r['merchant'].lower()]
    print('\nQUERY',q,'COUNT',len(hits))
    for r in hits[:10]:
        print(r['date'],r['merchant'],r['amount_usd'],r['source_ref'])
PY


QUERY Claude.AI COUNT 0

QUERY Omio 917-9243330 COUNT 1
04/08/2026 VISA Omio 917-9243330 FL ON 04-07 2561 69.13 photo-1368.jpg

QUERY JOHN NEWKIRK COUNT 0


14/05/2026 0
15/05/2026 0
17/05/2026 0
18/05/2026 0
19/05/2026 0
20/05/2026 0
21/05/2026 0
22/05/2026 0
23/05/2026 0
24/05/2026 0
25/05/2026 0
26/05/2026 0
27/05/2026 0


mkdir -p /home/sebas/work/gastos-europa/raw/source-docs && cp -n /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-Stmt-02-17-2026.pdf /home/sebas/work/gastos-europa/raw/source-docs/ && cp -n /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-Stmt-03-17-2026.pdf /home/sebas/work/gastos-europa/raw/source-docs/ && cp -n /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-Stmt-04-15-2026.pdf /home/sebas/work/gastos-europa/raw/source-docs/ && cp -n /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-Stmt-05-15-2026.pdf /home/sebas/work/gastos-europa/raw/source-docs/ && cp -n /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124052-ace55189-9196-4ff4-b5f3-bbddbfdb80f0.jpeg /home/sebas/work/gastos-europa/raw/source-docs/ && ls -1 /home/sebas/work/gastos-europa/raw/source-docs | tail -10


20260601-124029-Stmt-02-17-2026.pdf
20260601-124029-Stmt-03-17-2026.pdf
20260601-124029-Stmt-04-15-2026.pdf
20260601-124029-Stmt-05-15-2026.pdf
20260601-124052-ace55189-9196-4ff4-b5f3-bbddbfdb80f0.jpeg


edit

## photo-1391.jpg
February 2026
- AIRBNB * HMYWMYDAP2 — +$7.75
- AIRBNB * — $0.00 (transaction reversed)
January 2026
- AIRBNB * — $0.00 (transaction reversed)
- AIRBNB * HMYWMYDAP2 — +$387.47
- Deel Balance — +$620.00
- AIRBNB * HM3ZZB4KTC — +$413.58
December 2025
- Deel Balance — +$500.00

## stmt-02-17-2026.pdf
02/09/2026
- VISA Omio 917-9243330 FL ON 02-08 2561 — -$191.60
02/17/2026
- VISA CLAUDE.AI SUBSCRIPTION ANTHROPIC.COM CA ON 02-15 2561 — -$20.00


Successfully replaced 1 block(s) in /home/sebas/work/gastos-europa/raw/extracted-text.txt.

--- /home/sebas/work/gastos-europa/raw/extracted-text.txt
+++ /home/sebas/work/gastos-europa/raw/extracted-text.txt
@@ -205,4 +205,10 @@
 - Deel Balance — +$620.00
 - AIRBNB * HM3ZZB4KTC — +$413.58
 December 2025
 - Deel Balance — +$500.00
+
+## stmt-02-17-2026.pdf
+02/09/2026
+- VISA Omio 917-9243330 FL ON 02-08 2561 — -$191.60
+02/17/2026
+- VISA CLAUDE.AI SUBSCRIPTION ANTHROPIC.COM CA ON 02-15 2561 — -$20.00


Successfully replaced 1 block(s) in /home/sebas/work/gastos-europa/raw/vicky-manual.txt.


**Considering updates for merchants**

I think I need to update my parser to include CLAUDE.AI and some new merchants. That could enhance the user experience. I'll also consider updating known lists and heuristics for transportation and groceries. It makes sense to add some relevant keywords to improve functionality. Maybe this will make it easier to find the best options for users. I'm curious how these changes could influence their shopping experience!

    ('openai', 'Suscripción de OpenAI / ChatGPT.', 'alta'),
    ('omio berlin', 'Pasaje o reserva de transporte vía Omio.', 'alta'),
    ('goeuro corp', 'Pasaje o reserva de transporte de Omio/GoEuro.', 'alta'),

    ('openai', 'Suscripción de OpenAI / ChatGPT.', 'alta'),
    ('claude.ai', 'Suscripción de Claude / Anthropic.', 'alta'),
    ('omio berlin', 'Pasaje o reserva de transporte vía Omio.', 'alta'),
    ('goeuro corp', 'Pasaje o reserva de transporte de Omio/GoEuro.', 'alta'),
    ('aerobus', 'Traslado en bus al/del aeropuerto.', 'alta'),

elif any(x in low for x in ['omio','goeuro','cabify','uber','ns ','ns-','schiphol','aerop.','airport','luchthaven']): cat='transport'

elif any(x in low for x in ['omio','goeuro','cabify','uber','ns ','ns-','schiphol','aerop.','airport','luchthaven','aerobus']): cat='transport'

elif any(x in low for x in ['albert heijn','jumbo','super','croissanterie','kamyin','viandas']): cat='groceries'

elif any(x in low for x in ['albert heijn','jumbo','super','croissanterie','kamyin','viandas','carrefour','franprix','despar','conad']): cat='groceries'

elif any(x in low for x in ['mcdonald','cafe','bar','friet','restaurant','temple bar','bulldog','il primo','twinkies','lamor','karbeel','katoen','intruso','la pampa','papizza','taberna','de kroon','vivaz']): cat='food_drink'

elif any(x in low for x in ['mcdonald','cafe','bar','friet','restaurant','temple bar','bulldog','il primo','twinkies','lamor','karbeel','katoen','intruso','la pampa','papizza','taberna','de kroon','vivaz','pancake','bouillon','frigidarium','pizzaroli','bistrot','pizzeria','chiosco','trapizzino','antico vinaio','cremonini','guelfi','rossopomodoro','rooster','sha jahan','ristorante al sole','buffet mestre']): cat='food_drink'

elif any(x in low for x in ['uniqlo','lefties','primark','el corte ingles','condomerie','phone shop','city phone','fa. b.smit','zara','dekorazon','tabak','arts & cra','butragueno','sam tabak']): cat='shopping'

elif any(x in low for x in ['uniqlo','lefties','primark','el corte ingles','condomerie','phone shop','city phone','fa. b.smit','zara','dekorazon','tabak','arts & cra','butragueno','sam tabak','old bridge','premium retail','quotday','miss manon','lindt','ditech','romacentro','market s.r.l.','panjeri']): cat='shopping'

elif any(x in low for x in ['openai','aws.amazon','vercel']): cat='subscription'; trip='non_trip'

elif any(x in low for x in ['openai','claude.ai','aws.amazon','vercel','spotify']): cat='subscription'; trip='non_trip'


Successfully replaced 6 block(s) in /home/sebas/work/gastos-europa/app/build_dataset.py.

     ...
  46     ('amazon web services', 'Cargo de AWS / infraestructura cloud.', 'alta'),
  47     ('vercel domains', 'Dominio o servicio de Vercel.', 'alta'),
  48     ('village rosa', 'Alojamiento en Brasil; fuera del viaje Europa.', 'media'),
  49     ('openai', 'Suscripción de OpenAI / ChatGPT.', 'alta'),
+ 50     ('claude.ai', 'Suscripción de Claude / Anthropic.', 'alta'),
  50     ('omio berlin', 'Pasaje o reserva de transporte vía Omio.', 'alta'),
  51     ('goeuro corp', 'Pasaje o reserva de transporte de Omio/GoEuro.', 'alta'),
+ 53     ('aerobus', 'Traslado en bus al/del aeropuerto.', 'alta'),
  52     ('louvreticket', 'Entrada al Museo del Louvre.', 'alta'),
  53     ('sagrada familia', 'Entrada a la Sagrada Familia.', 'alta'),
  54     ('buckaroo', 'Pago procesado por Buckaroo, probablemente para entradas Anne Frank.', 'media'),
  55     ('versailles', 'Entrada o reserva vinculada a Versalles.', 'alta'),
     ...
 155     typ='zero' if amt == 0 else ('expense' if amt < 0 else 'income')
 156     fee=('fee for international transaction' in low or 'monthly account service fee' in low)
 157     cat='other'; country=''; trip='europe_trip'
 158     if fee: cat='fee'
-159     elif any(x in low for x in ['omio','goeuro','cabify','uber','ns ','ns-','schiphol','aerop.','airport','luchthaven']): cat='transport'
+161     elif any(x in low for x in ['omio','goeuro','cabify','uber','ns ','ns-','schiphol','aerop.','airport','luchthaven','aerobus']): cat='transport'
 160     elif any(x in low for x in ['museum','anne frank','sagrada','duomo','vatic','louvreticket','versailles','prado','flagship amsterdam']): cat='attraction'
-161     elif any(x in low for x in ['albert heijn','jumbo','super','croissanterie','kamyin','viandas']): cat='groceries'
-162     elif any(x in low for x in ['mcdonald','cafe','bar','friet','restaurant','temple bar','bulldog','il primo','twinkies','lamor','karbeel','katoen','intruso','la pampa','papizza','taberna','de kroon','vivaz']): cat='food_drink'
-163     elif any(x in low for x in ['uniqlo','lefties','primark','el corte ingles','condomerie','phone shop','city phone','fa. b.smit','zara','dekorazon','tabak','arts & cra','butragueno','sam tabak']): cat='shopping'
+163     elif any(x in low for x in ['albert heijn','jumbo','super','croissanterie','kamyin','viandas','carrefour','franprix','despar','conad']): cat='groceries'
+164     elif any(x in low for x in ['mcdonald','cafe','bar','friet','restaurant','temple bar','bulldog','il primo','twinkies','lamor','karbeel','katoen','intruso','la pampa','papizza','taberna','de kroon','vivaz','pancake','bouillon','frigidarium','pizzaroli','bistrot','pizzeria','chiosco','trapizzino','antico vinaio','cremonini','guelfi','rossopomodoro','rooster','sha jahan','ristorante al sole','buffet mestre']): cat='food_drink'
+165     elif any(x in low for x in ['uniqlo','lefties','primark','el corte ingles','condomerie','phone shop','city phone','fa. b.smit','zara','dekorazon','tabak','arts & cra','butragueno','sam tabak','old bridge','premium retail','quotday','miss manon','lindt','ditech','romacentro','market s.r.l.','panjeri']): cat='shopping'
 164     elif any(x in low for x in ['hotel','ch lumiere','beursstraat','village rosa']): cat='lodging'
-165     elif any(x in low for x in ['openai','aws.amazon','vercel']): cat='subscription'; trip='non_trip'
+167     elif any(x in low for x in ['openai','claude.ai','aws.amazon','vercel','spotify']): cat='subscription'; trip='non_trip'
 166     elif any(x in low for x in ['airbnb']): cat='lodging'; trip='europe_trip' if e['source_ref'] in DEEL_AIRBNB_PHOTOS else 'non_trip'
 167     elif any(x in low for x in ['deel balance','deel','interactive brok']): cat='transfer'; trip='non_trip'
 168     if any(x in merchant for x in [' AMSTERDAM ','Amsterdam','SCHIPHOL','BUSSUM','DAMRAK','Albert Heijn','JUMBO','BCK*NS','BCK*GHM','Buckaroo','Singel','Beursstraat','KamYin','PAPIZZA']): country='NL'
 169     if any(x in merchant for x in [' MADRID ','GranVia','PRADO','SAGRADA','EL CORTE','LEFTIES','Cabify','ADOLFO SUAREZ','ZARA MADRID','SALAMANCA','CARMEN','ROSALEDA','BUTRAGUENO']): country='ES'
     ...

--- /home/sebas/work/gastos-europa/app/build_dataset.py
+++ /home/sebas/work/gastos-europa/app/build_dataset.py
@@ -46,10 +46,12 @@
     ('amazon web services', 'Cargo de AWS / infraestructura cloud.', 'alta'),
     ('vercel domains', 'Dominio o servicio de Vercel.', 'alta'),
     ('village rosa', 'Alojamiento en Brasil; fuera del viaje Europa.', 'media'),
     ('openai', 'Suscripción de OpenAI / ChatGPT.', 'alta'),
+    ('claude.ai', 'Suscripción de Claude / Anthropic.', 'alta'),
     ('omio berlin', 'Pasaje o reserva de transporte vía Omio.', 'alta'),
     ('goeuro corp', 'Pasaje o reserva de transporte de Omio/GoEuro.', 'alta'),
+    ('aerobus', 'Traslado en bus al/del aeropuerto.', 'alta'),
     ('louvreticket', 'Entrada al Museo del Louvre.', 'alta'),
     ('sagrada familia', 'Entrada a la Sagrada Familia.', 'alta'),
     ('buckaroo', 'Pago procesado por Buckaroo, probablemente para entradas Anne Frank.', 'media'),
     ('versailles', 'Entrada o reserva vinculada a Versalles.', 'alta'),
@@ -155,15 +157,15 @@
     typ='zero' if amt == 0 else ('expense' if amt < 0 else 'income')
     fee=('fee for international transaction' in low or 'monthly account service fee' in low)
     cat='other'; country=''; trip='europe_trip'
     if fee: cat='fee'
-    elif any(x in low for x in ['omio','goeuro','cabify','uber','ns ','ns-','schiphol','aerop.','airport','luchthaven']): cat='transport'
+    elif any(x in low for x in ['omio','goeuro','cabify','uber','ns ','ns-','schiphol','aerop.','airport','luchthaven','aerobus']): cat='transport'
     elif any(x in low for x in ['museum','anne frank','sagrada','duomo','vatic','louvreticket','versailles','prado','flagship amsterdam']): cat='attraction'
-    elif any(x in low for x in ['albert heijn','jumbo','super','croissanterie','kamyin','viandas']): cat='groceries'
-    elif any(x in low for x in ['mcdonald','cafe','bar','friet','restaurant','temple bar','bulldog','il primo','twinkies','lamor','karbeel','katoen','intruso','la pampa','papizza','taberna','de kroon','vivaz']): cat='food_drink'
-    elif any(x in low for x in ['uniqlo','lefties','primark','el corte ingles','condomerie','phone shop','city phone','fa. b.smit','zara','dekorazon','tabak','arts & cra','butragueno','sam tabak']): cat='shopping'
+    elif any(x in low for x in ['albert heijn','jumbo','super','croissanterie','kamyin','viandas','carrefour','franprix','despar','conad']): cat='groceries'
+    elif any(x in low for x in ['mcdonald','cafe','bar','friet','restaurant','temple bar','bulldog','il primo','twinkies','lamor','karbeel','katoen','intruso','la pampa','papizza','taberna','de kroon','vivaz','pancake','bouillon','frigidarium','pizzaroli','bistrot','pizzeria','chiosco','trapizzino','antico vinaio','cremonini','guelfi','rossopomodoro','rooster','sha jahan','ristorante al sole','buffet mestre']): cat='food_drink'
+    elif any(x in low for x in ['uniqlo','lefties','primark','el corte ingles','condomerie','phone shop','city phone','fa. b.smit','zara','dekorazon','tabak','arts & cra','butragueno','sam tabak','old bridge','premium retail','quotday','miss manon','lindt','ditech','romacentro','market s.r.l.','panjeri']): cat='shopping'
     elif any(x in low for x in ['hotel','ch lumiere','beursstraat','village rosa']): cat='lodging'
-    elif any(x in low for x in ['openai','aws.amazon','vercel']): cat='subscription'; trip='non_trip'
+    elif any(x in low for x in ['openai','claude.ai','aws.amazon','vercel','spotify']): cat='subscription'; trip='non_trip'
     elif any(x in low for x in ['airbnb']): cat='lodging'; trip='europe_trip' if e['source_ref'] in DEEL_AIRBNB_PHOTOS else 'non_trip'
     elif any(x in low for x in ['deel balance','deel','interactive brok']): cat='transfer'; trip='non_trip'
     if any(x in merchant for x in [' AMSTERDAM ','Amsterdam','SCHIPHOL','BUSSUM','DAMRAK','Albert Heijn','JUMBO','BCK*NS','BCK*GHM','Buckaroo','Singel','Beursstraat','KamYin','PAPIZZA']): country='NL'
     if any(x in merchant for x in [' MADRID ','GranVia','PRADO','SAGRADA','EL CORTE','LEFTIES','Cabify','ADOLFO SUAREZ','ZARA MADRID','SALAMANCA','CARMEN','ROSALEDA','BUTRAGUENO']): country='ES'


bash

python3 /home/sebas/work/gastos-europa/app/build_dataset.py && jq '.count, .manual_vicky_count, .expense_total_trip, .expense_total_non_trip' /home/sebas/work/gastos-europa/derived/summary.json

python3 - <<'PY'
import json, pathlib
rows=json.loads(pathlib.Path('/home/sebas/work/gastos-europa/derived/transactions.json').read_text())
for q in ['CLAUDE.AI','02/09/2026','14/05/2026','27/05/2026']:
    print('\n==',q)
    for r in rows:
        if q in r['merchant'] or r['date']==q:
            print(r['date'], r['paid_by'], r['merchant'], r['amount_usd'], r['category_guess'], r['trip_scope'])
PY


183
58
7999.88
832.65


== CLAUDE.AI

== 02/09/2026

== 14/05/2026

== 27/05/2026


**Investigating search script issues**

I need to address a problematic search script that's showing bad queries in the merchant section. It seems like I should inspect entries by date to see what's going on, and maybe consider if there's a parser issue with the source_ref or if there's just no merchant match due to the regex. I'll get started on querying specific issues around this.

python3 - <<'PY'
import json, pathlib
rows=json.loads(pathlib.Path('/home/sebas/work/gastos-europa/derived/transactions.json').read_text())
for d in ['02/09/2026','02/17/2026','14/05/2026','27/05/2026']:
    hits=[r for r in rows if r['date']==d]
    print('\nDATE',d,'COUNT',len(hits))
    for r in hits:
        print(r['paid_by'], r['merchant'], r['amount_usd'], r['category_guess'], r['trip_scope'])
PY


DATE 02/09/2026 COUNT 1
S VISA Omio 917-9243330 FL ON 02-08 2561 -191.6 transport europe_trip

DATE 02/17/2026 COUNT 1
S VISA CLAUDE.AI SUBSCRIPTION ANTHROPIC.COM CA ON 02-15 2561 -20.0 subscription non_trip

DATE 14/05/2026 COUNT 2
V Molenmuseum De Zaanse M -5.93 attraction europe_trip
V CCV*OLD BRIDGE 3 -4.75 shopping europe_trip

DATE 27/05/2026 COUNT 3
V RISTORANTE AL SOLE -34.12 food_drink europe_trip
V BUFFET MESTRE -9.89 food_drink europe_trip
V DESPAR -34.95 groceries europe_trip


**Clarifying file locations**

I need to mention that there are no files in the /dropzone location and instead, it's actually in the outputs/inbox/ballbox-dropzone. That’s definitely important to clarify. I should also consider updating the to-do list to reflect that this task is completed. It's a small detail, but keeping everything organized really does help in the long run! I'll make sure to take the time to do this.


Updated #1 (pending → completed)


Listo.

He procesé los archivos nuevos de:
`/home/sebas/outputs/inbox/ballbox-dropzone`
(`/dropzone` real no tenía uploads)

Hecho:
- agregué 2 gastos nuevos de Sebas desde PDFs:
  - Omio — 09/02/2026 — $191.60
  - Claude subscription — 17/02/2026 — $20.00
- agregué gastos nuevos de Vicky del resumen en imagen:
  - 14/05 → 27/05
  - 39 movimientos nuevos
- no dupliqué lo que ya estaba cargado
- guardé copia de los archivos fuente en:
  - `/home/sebas/work/gastos-europa/raw/source-docs/`
- regeneré dataset

Estado nuevo:
- transacciones totales: 183
- gastos Vicky cargados: 58

Ojo:
- la imagen de Vicky tenía varias filas chicas. Cargué las que se leen bien.
- si querés, siguiente paso hago barrido de “baja confianza” y te marco las dudosas para validar.


[telegram] ahi pase los de vicky en formato mas legible


todo

Procesar nueva versión legible de gastos Vicky

Leer nuevos archivos más legibles de Vicky, actualizar gastos-europa sin duplicar y corregir datos previos si aplica.


Created #2: Procesar nueva versión legible de gastos Vicky (pending)


bash

find /home/sebas/outputs/inbox/ballbox-dropzone -maxdepth 1 -type f -mmin -60 -printf '%TY-%Tm-%Td %TH:%TM:%TS %p\n' | sort

find /home/sebas/.pi/agent/tmp/telegram -maxdepth 2 -type f -mmin -60 -printf '%TY-%Tm-%Td %TH:%TM:%TS %p\n' 2>/dev/null | sort | tail -100

ls -lt /home/sebas/outputs/inbox/ballbox-dropzone | head -20


2026-06-01 09:40:29.7486967160 /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-Stmt-02-17-2026.pdf
2026-06-01 09:40:29.7486967160 /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-Stmt-03-17-2026.pdf
2026-06-01 09:40:29.7486967160 /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-Stmt-04-15-2026.pdf
2026-06-01 09:40:29.7486967160 /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124029-Stmt-05-15-2026.pdf
2026-06-01 09:40:52.4288101140 /home/sebas/outputs/inbox/ballbox-dropzone/20260601-124052-ace55189-9196-4ff4-b5f3-bbddbfdb80f0.jpeg
2026-06-01 09:56:42.6655851400 /home/sebas/outputs/inbox/ballbox-dropzone/20260601-125642-5306a480-d8fa-4fbd-8cf1-d9bea25ff9ceZ1c0d0e77f167250004697deb6ea2c5f26b285372_0.pdf


(no output)


total 449076
-rw------- 1 sebas sebas    245204 Jun  1 09:56 20260601-125642-5306a480-d8fa-4fbd-8cf1-d9bea25ff9ceZ1c0d0e77f167250004697deb6ea2c5f26b285372_0.pdf
-rw------- 1 sebas sebas    215681 Jun  1 09:40 20260601-124052-ace55189-9196-4ff4-b5f3-bbddbfdb80f0.jpeg
-rw------- 1 sebas sebas     34243 Jun  1 09:40 20260601-124029-Stmt-02-17-2026.pdf
-rw------- 1 sebas sebas     35201 Jun  1 09:40 20260601-124029-Stmt-03-17-2026.pdf
-rw------- 1 sebas sebas     33555 Jun  1 09:40 20260601-124029-Stmt-04-15-2026.pdf
-rw------- 1 sebas sebas     39744 Jun  1 09:40 20260601-124029-Stmt-05-15-2026.pdf
-rw------- 1 sebas sebas 222108949 May 31 04:47 20260531-074743-Archivos-En-Maquina-20260529T220853Z-3-001.zip
-rw------- 1 sebas sebas   2335845 May 30 20:00 20260530-230040-IMG_7813.png
-rw------- 1 sebas sebas   2157479 May 30 20:00 20260530-230040-IMG_7812.png
-rw------- 1 sebas sebas   1942364 May 30 20:00 20260530-230040-IMG_7810.png
-rw------- 1 sebas sebas   2015598 May 30 20:00 20260530-230040-IMG_7811.png
-rw------- 1 sebas sebas   1583440 May 30 20:00 20260530-230040-IMG_7807.png
-rw------- 1 sebas sebas   1687292 May 30 20:00 20260530-230040-IMG_7808.png
-rw------- 1 sebas sebas   1411621 May 30 20:00 20260530-230040-IMG_7806.png
-rw------- 1 sebas sebas   1871390 May 30 20:00 20260530-230040-IMG_7809.png
-rw------- 1 sebas sebas 222108949 May 30 07:34 20260530-103420-Archivos-En-Maquina-20260529T220853Z-3-001.zip