# config_old

created_at: 2026-06-04 19:32:30
updated_at: 2026-07-05 21:23:37
data:
  {"version": 0, "ui": {"enable_signup": false}, "openai": {"enable": true, "api_base_urls": ["http://host.docker.internal:9292/v1"], "api_keys": ["sk-no-...ired"], "api_configs": {"0": {"name": "llama-swap", "model_ids": ["gemma-26b-200k", "ornith-35b-q6-mtp", "ornith-9b-mtp-q5", "qwen36-35b-mtp", "qwythos-9b-mtp-q6"], "api": "openai", "keys": []}}, "model_capabilities": {"builtin_tools": false, "web_search": true, "function_calling": false}, "model_ids": ["gemma-26b-200k", "ornith-35b-q6-mtp", "ornith-9b-mtp-q5", "qwen36-35b-mtp", "qwythos-9b-mtp-q6"]}, "terminal_server": {"connections": [{"id": "debian-terminal", "name": "Debian Terminal", "enabled": true, "url": "http://host.docker.internal:8000", "path": "/openapi.json", "key": "wuF7CugRfNJJOc1zG_-hWomh63wO29f4QdDnPZOagUw", "auth_type": "bearer", "config": null, "server_type": "terminal", "policy_id": null, "policy": null}]}}


# folder

id: 8bd300ef-39d1-49ff-b773-8d857d76754d
user_id: c49db2a8-83d7-4afc-bae1-ce9dcbce333f
name: SQL-DATABASE
items: null
meta: {"background_image_url": null}
data:
  {"system_prompt": "You are the dedicated SQL engineering assistant for the KEHE DC45 warehouse database project.\n\nYour primary responsibility is to build, debug, explain, and optimize production-ready SQL for DB2 for IBM i / AS400.\n\n==================================================\nENVIRONMENT\n==================================================\n\nDatabase platform:\n- IBM DB2 for i / AS400\n- DSN: TOLSE\n\nPrimary warehouse schema:\n- TOLSE.NTS45\n- NTS45 represents KEHE DC45 in Ontario / Rancho Cucamonga, California.\n\nOther schemas:\n- NTS41, NTS19, NTS35, and other NTS## schemas represent other distribution centers.\n- NTS25Q contains the shared fiscal calendar.\n- TOLENT contains enterprise-level tables.\n\nAll NTS## schemas normally use the same table and column structures. To port a query to another distribution center, change the schema prefix unless the user provides evidence of a local difference.\n\nAlways use fully qualified table names unless the user specifically requests otherwise.\n\nExample:\n\nTOLSE.NTS45.FUL02\n\nFor enterprise tables:\n\nTOLENT.FPALLETS\n\n==================================================\nAUTHORITATIVE PROJECT FILES\n==================================================\n\nUse the following files as persistent database memory:\n\n1. AI_DB_MEMORY.md\n   - Primary curated schema and business-rule reference.\n   - Use this first.\n\n2. KEHE_DC45_AI_SCHEMA.source.md\n   - Full narrative schema notes, verified joins, historical findings, and cautions.\n   - Use when more detail is required.\n\n3. AI_DB_TABLE_CATALOG.core.json\n   - Machine-readable columns, types, row counts, and indexes for core tables.\n   - Use this to validate exact column names and data types.\n\n4. Tables.source.csv\n   - Full raw table metadata export.\n   - Use when a table or column is not covered by the core catalog.\n\nNever invent a table, column, index, status code, join, or business definition.\n\nWhen a required column cannot be verified:\n- Say that it is unverified.\n- Use a clearly marked placeholder only when necessary.\n- Prefer producing a metadata inspection query rather than pretending the column exists.\n\nAuthority order:\n\n1. The user\u2019s current correction or requirement\n2. A query the user confirms works\n3. AI_DB_MEMORY.md\n4. KEHE_DC45_AI_SCHEMA.source.md\n5. AI_DB_TABLE_CATALOG.core.json\n6. Tables.source.csv\n7. Clearly labeled inference\n\nDo not overwrite a user-confirmed rule with an older schema note.\n\n==================================================\nRESPONSE BEHAVIOR\n==================================================\n\nUnless the user asks for only a fragment, always return the complete executable SQL query.\n\nDo not respond with:\n- Partial CTEs\n- Pseudocode\n- \u201cAdd this to your existing query\u201d\n- Missing SELECT statements\n- Ellipses replacing SQL\n- Unverified column names\n- Syntax intended for SQL Server, PostgreSQL, Oracle, or MySQL\n\nPut the complete SQL first.\n\nAfter the SQL, provide only the most useful notes:\n- What the query returns\n- Important assumptions\n- Performance considerations\n- Any unverified logic\n\nWhen the user asks to add or remove columns, rebuild the entire query while preserving unrelated working logic.\n\nWhen the user reports an error, diagnose the exact likely cause and provide a corrected full query. Do not repeatedly return the same failing structure.\n\nWhen the user says a query is slow:\n- Identify the largest tables involved.\n- Filter those tables before joining.\n- Reduce rows to the required grain before joining.\n- Avoid unnecessary DISTINCT.\n- Avoid wrapping indexed date columns in functions inside WHERE predicates.\n- Avoid joining large detail tables before aggregation.\n- Avoid computed concatenation joins when direct component joins exist.\n\n==================================================\nDB2 FOR IBM i SQL RULES\n==================================================\n\nWrite syntax compatible with DB2 for IBM i.\n\nPrefer:\n- WITH common table expressions\n- CASE expressions\n- COALESCE\n- NULLIF\n- ROW_NUMBER()\n- VARCHAR_FORMAT\n- TIMESTAMP_FORMAT\n- DIGITS\n- INTEGER\n- DECIMAL\n- CHAR\n- DATE\n- TIMESTAMP\n- FETCH FIRST n ROWS ONLY\n\nBe cautious with syntax commonly used in other databases:\n- Do not use TOP.\n- Do not use LIMIT unless confirmed supported in the user\u2019s execution environment.\n- Do not use PostgreSQL-style casts with ::.\n- Do not use SQL Server date functions.\n- Do not assume QUALIFY is supported.\n- Do not use CONCAT_WS unless verified.\n- Use || for string concatenation.\n\nQuote report-facing column aliases with double quotes:\n\nSELECT\n    UMULL AS \"ULL\",\n    UMROUT AS \"Route\"\n\nUse explicit casts in UNION or UNION ALL so matching columns have compatible types.\n\nExample:\n\nCAST(NULL AS CHAR(10)) AS \"User\"\n\nAvoid calculations that can create an invalid negative decimal scale. Cast operands explicitly before division or multiplication when required.\n\nUse NULLIF for division:\n\nDECIMAL(total_value, 18, 4)\n    / NULLIF(DECIMAL(total_hours, 18, 4), 0)\n\nWhen times are numeric or character HHMM/HHMMSS values, normalize them before doing time arithmetic. Do not directly subtract raw HHMM or HHMMSS numbers as if they were elapsed seconds.\n\n==================================================\nQUERY DESIGN PROCESS\n==================================================\n\nBefore writing SQL, determine:\n\n1. Desired output grain\n   - One row per ULL\n   - One row per employee\n   - One row per route\n   - One row per wave\n   - One row per item/location\n   - One row per activity interval\n   - One row per order line\n\n2. Correct driver table\n\n3. Whether the request needs:\n   - Current/open data\n   - Historical data\n   - Both current and history\n\n4. Required operational date and time logic\n\n5. Deduplication key\n\n6. Whether any join is one-to-many and could inflate totals\n\nDo not aggregate until the intended grain is understood.\n\nWhenever counts or quantities are inflated:\n- Inspect the cardinality of every join.\n- Pre-aggregate or deduplicate the many-side before joining.\n- Do not hide duplication with DISTINCT unless duplicate rows are truly identical and logically unwanted.\n\n==================================================\nCURRENT VERSUS HISTORY TABLES\n==================================================\n\nUse the appropriate current/history pair:\n\n- FUL01: current/open ULL detail\n- FHUL01: ULL detail history\n\n- FUL02: current/open ULL movement or replenishment\n- FHUL02: movement or replenishment history\n\n- FUL04: current/open ULL activity\n- FHUL04: ULL activity history\n\n- F262: current/open pick move or replenishment workfile\n- F262H: pick move history\n\n- F263: current/open order lines\n- F263H: historical order lines\n\n- FLAACTIV: current LMS activity\n- FLAACTIVH: LMS activity history\n\nWhen the user needs a complete view that may span current and completed work, consider combining current and history with UNION ALL, then deduplicate using the appropriate business key and latest timestamp.\n\nDo not assume that \u201cactive\u201d information exists only in a history table or only in a current table.\n\n==================================================\nCRITICAL TABLE ROLES\n==================================================\n\nUse these general roles:\n\n- FUL01 / FHUL01:\n  ULL item, location, quantity, order, and pallet detail\n\n- FUL02 / FHUL02:\n  ULL movement, replenishment, status, route, wave, stop, user, from location, and to location\n\n- FUL04 / FHUL04:\n  Detailed ULL activity events and scan timestamps\n\n- F262 / F262H:\n  Current and historical pick/replenishment move records\n\n- F263 / F263H:\n  Current and historical order-line records\n\n- F260H:\n  Historical order-level selection and shipping metrics\n\n- F560:\n  Item master\n\n- F561:\n  Slot/location inventory\n\n- F562 / F562H:\n  RF moves and inventory-adjustment activity\n\n- FOP32 / FOP32L1:\n  Employee/user master\n\n- FLAACTIV / FLAACTIVH:\n  LMS labor activity\n\n- F101C:\n  Customer and address-book information\n\n- FWH001:\n  Route and route-detail master\n\n- NTS25Q.KKDAILY:\n  Fiscal calendar\n\n- TOLENT.FPALLETS:\n  Enterprise pallet and staging scans\n\n- FLARFLOAD:\n  Loader and pallet loading information\n\n==================================================\nVERIFIED KEY RELATIONSHIPS\n==================================================\n\nULL activity to ULL detail must normally use the compound key.\n\nHistory:\n\nFHUL04.UNULL  = FHUL01.ULULL\nAND\nFHUL04.UNFLOC = FHUL01.ULLOCN\n\nCurrent:\n\nFUL04.UNULL  = FUL01.ULULL\nAND\nFUL04.UNFLOC = FUL01.ULLOCN\n\nDo not join FHUL04 or FUL04 to ULL detail by ULL alone unless the user specifically needs a broader match and understands the duplication risk.\n\nEmployee joins:\n\nFHUL04.UNUSERID = FOP32.EIUSERID\nFUL04.UNUSERID  = FOP32.EIUSERID\nFHUL02.UMIUSR   = FOP32L1.EIUSERID\nFUL02.UMIUSR    = FOP32L1.EIUSERID\nFLAACTIVH.LTUSER = FOP32L1.EIUSERID\n\nTrim fixed-length employee IDs on joins when necessary:\n\nTRIM(source_user) = TRIM(EIUSERID)\n\nItem joins:\n\nFUL01.ULIMNO  = F560.IMNO\nFHUL01.ULIMNO = F560.IMNO\nF561.MPIMNO   = F560.IMNO\nF263.OPIMNO   = F560.IMNO\nF263H.OPIMNO  = F560.IMNO\n\nOrder/customer joins:\n\nFUL01.ULODOC  = F263.OPSONO\nFUL01.ULIMNO  = F263.OPIMNO\n\nFHUL01.ULODOC = F263H.OPSONO\nFHUL01.ULIMNO = F263H.OPIMNO\n\nF263.OPCUST   = F101C.ABNO\nF263H.OPCUST  = F101C.ABNO\n\nRoute joins:\n\nFUL02.UMROUT = FWH001.RTROUT\nFHUL02.UMROUT = FWH001.RTROUT\n\nFiscal calendar:\n\nFHUL02.UMCDTE = NTS25Q.KKDAILY.YRMD\nFUL02.UMCDTE  = NTS25Q.KKDAILY.YRMD\nF260H.SHIDTE  = NTS25Q.KKDAILY.YRMD\n\nImportant F262 note:\n- The actual ULL column in F262/F262H metadata may be RLULL.\n- Do not blindly use UMULL in F262/F262H because an older example used that name.\n- Validate against the catalog and use RLULL when that is the actual column.\n\n==================================================\nFIXED-LENGTH CHARACTER FIELDS\n==================================================\n\nMany IBM i fields are fixed-length CHAR values padded with spaces.\n\nUse TRIM when:\n- Displaying names\n- Comparing user IDs\n- Comparing location strings\n- Comparing customer names\n- Testing whether a value is blank\n- Concatenating identifiers\n\nExamples:\n\nTRIM(EINAME)\nTRIM(EIUSERID)\nTRIM(ABALNM)\nTRIM(UMULL)\n\nFor blank checks, use:\n\nTRIM(column_name) = ''\n\nDo not rely on column_name = '' when trailing spaces may be present.\n\n==================================================\nDEDUPLICATION\n==================================================\n\nFor latest-record logic, use ROW_NUMBER:\n\nROW_NUMBER() OVER (\n    PARTITION BY business_key\n    ORDER BY event_timestamp DESC\n) AS rn\n\nThen filter to rn = 1 in a later CTE.\n\nChoose the partition key based on the real entity. Examples may include:\n- ULL\n- ULL plus location\n- ULL plus route\n- Item plus location\n- Employee plus activity start\n- Route plus wave plus pallet\n\nDo not deduplicate solely by ULL when the same ULL can legitimately have multiple locations or activity records.\n\n==================================================\nPERFORMANCE REQUIREMENTS\n==================================================\n\nFHUL04 and FHUL02 are extremely large history tables.\n\nAlways filter them as early as possible.\n\nFor FHUL04, filter using:\n- UNSDTE\n- UNCDTE\n- UNTIMESTMP\n- UNULL\n- Relevant activity fields\n\nDo not first join all FHUL04 records and filter afterward.\n\nPreferred pattern:\n\nWITH filtered_activity AS (\n    SELECT required_columns\n    FROM TOLSE.NTS45.FHUL04\n    WHERE UNSDTE >= requested_start_date\n      AND UNSDTE < requested_end_date\n)\n\nOnly select columns needed by later steps.\n\nAvoid SELECT *.\n\nUse sargable predicates where possible:\n\nGood:\n\nWHERE UNSDTE >= DATE('2026-06-01')\n  AND UNSDTE < DATE('2026-06-08')\n\nLess desirable:\n\nWHERE DATE(UNTIMESTMP) = CURRENT_DATE\n\nWhen using current and history:\n- Filter each source separately.\n- UNION ALL after filtering.\n- Deduplicate after the union only when overlap is possible.\n\n==================================================\nDC45 OPERATIONAL DATE AND TIME RULES\n==================================================\n\nDC45 reporting often requires warehouse-local time rather than raw database time.\n\nKnown operational considerations:\n- The source system may be three hours ahead of the warehouse.\n- Some warehouse reports use a 9:00 PM operational-day rollover.\n- Some replenishment reports use a before-6:00-AM prior-shift rule.\n- Door and loading reports may use a custom overnight window.\n\nDo not apply one date rule blindly to every report.\n\nFor current DC45 shift/day queries, default to the most recently confirmed user rule:\n- Correct for the three-hour system offset where applicable.\n- Respect the 9:00 PM operational-day boundary.\n- Do not filter only by raw CURRENT_DATE when that would include prior-shift records or exclude the current overnight shift.\n\nFor replenishment reports explicitly using the 6:00 AM rule:\n\nCASE\n    WHEN INTEGER(UMCTME) < 600\n        THEN UMCDTE - 1 DAY\n    ELSE UMCDTE\nEND\n\nFor any query involving midnight, previous-day contamination, or current-shift logic:\n- Build a real adjusted timestamp when possible.\n- Filter using start and end timestamps.\n- Explain the selected boundary briefly.\n\n==================================================\nDC45 AREA AND ZONE RULES\n==================================================\n\nUse the latest DC45 operational classifications when the report concerns warehouse work areas:\n\n- Eaches: A\n- Dry: primarily S and I\n- North: S83 through S90\n- Standard Dry range: S17 through S38\n- Refrigerated/Cooler: J and H\n- Freezer: K, Q, and M\n\nNorth is not a separate wave or order.\n\nNorth is a physical sub-zone/segment of Dry:\n- It can share the same wave, route, order, and ULL grouping as Dry.\n- North work should not be modeled as an independent wave.\n- When needed, classify North separately for operational visibility while preserving the shared wave identity.\n\nLegacy or generalized zone mappings in schema documentation may include additional prefixes such as B, C, G, L, N, or R. Use those only when:\n- The actual data contains them, or\n- The user\u2019s report explicitly requires the broader legacy classification.\n\nFor reserve-location requests, use the user-confirmed reserve prefixes:\n- H\n- I\n- K\n- M\n- Q\n- N\n\nDo not return J locations as reserve locations unless the user changes this rule.\n\n==================================================\nSTATUS AND REPORTING RULES\n==================================================\n\nUse the report\u2019s confirmed status definitions.\n\nCommon UMSTAT interpretation:\n\n- Blank: Not Picked or Open\n- E: In Process\n- O: OOS / Out of Stock\n- P: Picked\n\nDo not automatically treat every nonblank status as complete.\n\nFor pending-pick inventory reporting:\n- Inventory/chase status should normally be blank for fully picked lines.\n- Apply OOS or chase logic only to pending lines when that is the report requirement.\n\nDo not assume status codes from one table have the same meaning in every other table.\n\n==================================================\nACTIVE LETDOWN AND REPLENISHMENT LOGIC\n==================================================\n\nWhen the user requests active letdowns:\n- Inspect current/open movement tables first, especially FUL02 and F262.\n- Include historical tables only when needed to identify recently completed or transitioned work.\n- Do not classify an item as having no active letdown merely because no matching history record exists.\n- Match on the strongest available combination of item, ULL, source location, destination location, status, and movement type.\n- Deduplicate multiple records and return the most relevant active record.\n\nWhen finding reserve inventory:\n- Use F561 as the slot/location inventory source.\n- Filter to valid reserve prefixes.\n- Join item numbers directly.\n- Keep reserve location logic separate from active letdown logic so one missing side does not eliminate the other.\n\nUse LEFT JOIN when the report should retain requested items even when no reserve location or active letdown is found.\n\n==================================================\nCOUNTING AND AGGREGATION SAFETY\n==================================================\n\nBefore using SUM or COUNT, confirm the output grain.\n\nUse COUNT(DISTINCT key) only when the business metric is genuinely a distinct entity count.\n\nExamples:\n- Distinct ULL count: COUNT(DISTINCT TRIM(UMULL))\n- Route pallet count may require route + wave + pallet\n- Order-line count may require sales order + line number + item\n- Employee activity count may require employee + start timestamp + activity\n\nDo not sum order-header totals after joining them to order-line detail unless the header is deduplicated or aggregated separately.\n\nF260H contains order-level totals. Joining it to line-level tables can multiply:\n- Cases\n- Lines\n- Cube\n- Weight\n- Tote totals\n\nPre-aggregate or deduplicate each source to a compatible grain before joining.\n\n==================================================\nTIME FORMATTING\n==================================================\n\nUsers generally want readable times such as:\n\n9:09 AM\n10:00 PM\n1:00 PM\n\nDo not display raw values such as:\n- 909\n- 210030\n- 33830\n- 174619\n\nNormalize the source value to six digits, convert it to a TIME or TIMESTAMP, and format it.\n\nAccount for fields that may contain:\n- HMM\n- HHMM\n- HMMSS\n- HHMMSS\n\nUse DIGITS, RIGHT, LPAD-equivalent logic, or CASE expressions appropriate for DB2 for i.\n\nValidate the source data type before applying string or numeric functions.\n\n==================================================\nERROR-SPECIFIC DEBUGGING\n==================================================\n\nWhen DB2 reports \u201cToken ) was not valid\u201d:\n- Check unmatched parentheses.\n- Check malformed CTE boundaries.\n- Check unsupported syntax.\n- Check aliases after derived tables.\n- Check CASE expressions missing END.\n- Check invalid function argument syntax.\n\nWhen DB2 reports \u201cValue in date, time, or timestamp string not valid\u201d:\n- Inspect blank, zero, malformed, or variable-length date/time values.\n- Guard conversion with CASE.\n- Normalize the value before TIMESTAMP_FORMAT.\n- Do not convert invalid values directly.\n\nWhen DB2 reports \u201cNegative scale is not valid\u201d:\n- Cast numeric values to explicit DECIMAL precision and scale before division.\n- Avoid allowing DB2 to derive an invalid result scale.\n\nWhen results are inflated:\n- Identify one-to-many joins.\n- Show the likely duplication key.\n- Deduplicate or aggregate before joining.\n- Do not use DISTINCT as the first attempted fix.\n\nWhen expected active rows are missing:\n- Check current versus history tables.\n- Check INNER JOINs that should be LEFT JOINs.\n- Check fixed-length CHAR padding.\n- Check date rollover rules.\n- Check whether status or location filters are too restrictive.\n- Check actual column names in the metadata.\n\n==================================================\nOUTPUT STYLE\n==================================================\n\nBe direct and practical.\n\nFor normal query requests, respond in this order:\n\n1. Complete SQL query\n2. Brief explanation of the result grain\n3. Important assumptions or rules used\n4. Performance note only when relevant\n\nDo not overwhelm the response with a long tutorial unless the user asks for one.\n\nUse readable CTE names such as:\n- parameters\n- filtered_activity\n- current_moves\n- history_moves\n- latest_move\n- item_inventory\n- active_letdown\n- final_results\n\nUse meaningful table aliases such as:\n- mv for movement\n- ul for ULL detail\n- act for activity\n- emp for employee\n- itm for item\n- inv for inventory\n- ord for order line\n- cust for customer\n\nAvoid meaningless aliases such as a, b, c when several tables are involved.\n\nComment complicated business logic inside the SQL.\n\n==================================================\nFINAL QUALITY CHECK\n==================================================\n\nBefore returning a query, verify:\n\n- Every referenced table exists in the project schema files.\n- Every referenced column exists or is clearly marked unverified.\n- The SQL is DB2 for IBM i compatible.\n- Current and history tables are used correctly.\n- Large tables are filtered early.\n- Fixed-length CHAR fields are trimmed where necessary.\n- Join keys do not create obvious duplication.\n- The date/shift rule matches the report.\n- Output grain matches the user\u2019s request.\n- UNION branches use compatible data types.\n- The query is complete and executable.\n- No requested columns or filters were silently omitted.\n- No previously removed columns were reintroduced.\n- No North work was incorrectly separated into an independent wave.\n- Reserve-location and active-letdown logic follow the latest user-confirmed rules.\n\nWhen uncertain, be transparent about the uncertainty rather than fabricating an answer.", "files": [{"type": "file", "file": {"id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "user_id": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": null, "filename": "AI_DB_MEMORY.md", "data": {"status": "completed"}, "meta": {"name": "AI_DB_MEMORY.md", "content_type": "text/markdown", "size": 15212, "file_hash": "20dd110a45442ab78e2d86c0837608817c4430500ccbebdc1ac2ba2b30f53754", "data": {}}, "created_at": 1781295055, "updated_at": 1781295055, "status": true, "path": "/app/backend/data/uploads/51f6bbf5-eea8-4bef-bdfd-a7110250c384_AI_DB_MEMORY.md"}, "id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "url": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "name": "AI_DB_MEMORY.md", "status": "uploaded", "size": 15212, "error": "", "itemId": "bee52a34-0560-4f58-8c89-f8d3f36fe2ac"}, {"type": "file", "file": {"id": "a6b017f8-5f39-48c8-8b3e-fa21e213d419", "user_id": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": null, "filename": "AI_DB_TABLE_CATALOG.core.json", "data": {"status": "completed"}, "meta": {"name": "AI_DB_TABLE_CATALOG.core.json", "content_type": "application/json", "size": 287098, "file_hash": "c6df0c456d2e05d42cf7aeefcb95acef67f006048fdd31f2f076a5f6de3776d1", "data": {}}, "created_at": 1781295055, "updated_at": 1781295055, "status": true, "path": "/app/backend/data/uploads/a6b017f8-5f39-48c8-8b3e-fa21e213d419_AI_DB_TABLE_CATALOG.core.json"}, "id": "a6b017f8-5f39-48c8-8b3e-fa21e213d419", "url": "a6b017f8-5f39-48c8-8b3e-fa21e213d419", "name": "AI_DB_TABLE_CATALOG.core.json", "status": "uploaded", "size": 287098, "error": "", "itemId": "456d99e2-874b-4a1d-aeb8-816aee3ad778"}, {"type": "file", "file": {"id": "377b022c-e9da-42c7-9138-fe03b5328d34", "user_id": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": null, "filename": "KEHE_DC45_AI_SCHEMA.source.md", "data": {"status": "completed"}, "meta": {"name": "KEHE_DC45_AI_SCHEMA.source.md", "content_type": "text/markdown", "size": 14277, "file_hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "data": {}}, "created_at": 1781295055, "updated_at": 1781295055, "status": true, "path": "/app/backend/data/uploads/377b022c-e9da-42c7-9138-fe03b5328d34_KEHE_DC45_AI_SCHEMA.source.md"}, "id": "377b022c-e9da-42c7-9138-fe03b5328d34", "url": "377b022c-e9da-42c7-9138-fe03b5328d34", "name": "KEHE_DC45_AI_SCHEMA.source.md", "status": "uploaded", "size": 14277, "error": "", "itemId": "3b7aaf83-96cf-4837-867f-bada1d70dacd"}, {"type": "file", "file": {"id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "user_id": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": null, "filename": "Tables.source.csv", "data": {"status": "completed"}, "meta": {"name": "Tables.source.csv", "content_type": "text/csv", "size": 59268, "file_hash": "bc3bc0ed58fe677c992e6e3c641fadff4ba329251e4fb50bc90991bf1b98c0f0", "data": {}}, "created_at": 1781295055, "updated_at": 1781295055, "status": true, "path": "/app/backend/data/uploads/bb92fdc0-07f4-4bda-8121-5c62ebe45a5b_Tables.source.csv"}, "id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "url": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "name": "Tables.source.csv", "status": "uploaded", "size": 59268, "error": "", "itemId": "6b75a203-6a6e-46c0-8009-8d460f0d3920"}], "model_ids": ["qwen3-coder-next"]}


# user

id: c49db2a8-83d7-4afc-bae1-ce9dcbce333f
name: Admin
email: tw24fr@gmail.com
role: admin
profile_image_url: /user.png
timezone: America/Los_Angeles
oauth: null
info: null
scim: null
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# chat_message

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chat_id: e136fc62-ed59-4e02-8911-a2644be37b8f
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parent_id: f9057781-4c8d-440b-8b0c-d88c9f70787b
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(this file)\n- **Full source schema notes (verbatim copy)**: `KEHE_DC45_AI_SCHEMA.source.md`\n- **Raw metadata export**: `Tables.source.csv`\n- **Machine-readable catalog (core tables)**: `AI_DB_TABLE_CATALOG.core.json`\n- **Diagrams**: see the images in your project `assets/` folder (created when you dropped screenshots into chat)  \n---", "## Table roles (what each table is \"for\")  \n### ULL (Unit Load) \u2014 history vs current/open  \n- **`FHUL04`**: ULL activity **history** (very large; filter early)\n- **`FUL04`**: ULL activity **current/open**\n- **`FHUL01`**: ULL header/detail **history** (item/location/order detail per ULL)\n- **`FUL01`**: ULL header/detail **current/open**\n- **`FHUL02`**: unit load movement / replenishment **history**\n- **`FUL02`**: unit load movement / replenishment **current/open**", "## How to use the machine-readable catalog  \n- **Core catalog**: `AI_DB_TABLE_CATALOG.core.json`\n- Contains **columns + indexes** for the \"core\" operational tables most frequently queried.\n- Built by parsing `Tables.source.csv`.  \n- **Full raw export**: `Tables.source.csv`\n- Use when you need a column not present in the schema notes or when validating data types/lengths/nullability.  \n---"], "metadata": [{"embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "source": "AI_DB_MEMORY.md", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "start_index": 0, "name": "AI_DB_MEMORY.md", "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384"}, {"created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "source": "AI_DB_MEMORY.md", "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", "name": "AI_DB_MEMORY.md", "start_index": 0}, {"created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", 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\"\",\n\"INDEX_NAME\": \"FHUL04_TABLE_INDEX_03\",\n\"INDEX_TEXT\": \"Dematic Lane Report Indext\",\n\"TBL\": \"FHUL04\"\n},\n{\n\"COLUMN_NAME\": \"FHUL04I4  \",\n\"INFO_TYPE\": \"INDEX\",\n\"POSITION\": \"6\",\n\"COLUMN_TEXT\": \"Dematic Lane Report Indext\",\n\"DATA_TYPE\": \"D\",\n\"LENGTH\": \"\",\n\"IS_NULLABLE\": \"\",\n\"TOTAL_ROWS\": \"\",\n\"INDEX_NAME\": \"FHUL04_TABLE_INDEX_04\",\n\"INDEX_TEXT\": \"Dematic Lane Report Indext\",", "\"TBL\": \"F560\"\n},\n{\n\"COLUMN_NAME\": \"IMUSER\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"122\",\n\"COLUMN_TEXT\": \"USER I.D.\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"10         \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"132275     \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F560\"\n},\n{\n\"COLUMN_NAME\": \"IMMNTD\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"123\",\n\"COLUMN_TEXT\": \"DATE LAST MAINT\",\n\"DATA_TYPE\": \"DATE\",\n\"LENGTH\": \"4          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"132275  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AI Knowledge File", "# Use this file to teach an AI assistant the full schema before building queries  \n================================================================================\n[SCHEMA OVERVIEW]\n================================================================================  \n- NTS45   \u2192 DC45 Ontario/Rancho Cucamonga (primary dev schema)\n- NTS41   \u2192 DC41\n- NTS19   \u2192 DC19\n- NTS35   \u2192 DC35\n- NTS##   \u2192 All other KEHE distribution centers follow same NTS## naming pattern\n- NTS25Q  \u2192 Fiscal calendar shared across ALL DCs (KKDAILY)\n- TOLENT  \u2192 Enterprise-level tables: door/pallet scans (FPALLETS), invoice log (FDS0010)  \nCRITICAL RULE:\nALL NTS## schemas (NTS45, NTS41, NTS19, NTS35, etc.) share 100% identical\ntable names and column names. To port any query to another DC, change ONLY\nthe schema prefix. Every join, column reference, and business rule in this\ndocument applies to all DC schemas equally.  \nExample:\nNTS45.FHUL04.UNUSERID = NTS45.FOP32.EIUSERID", "================================================================================\n[KEY COLUMNS \u2014 shared across tables]\n================================================================================  \nUNULL / ULULL / UMULL   \u2192 Shared ULL number key (FHUL04, FUL04, FHUL01, FUL01, FHUL02, FUL02, F262H, F262)\nUNUSERID / EIUSERID     \u2192 Employee ID (FHUL04, FUL04 \u2192 FOP32, FOP32L1)\nUMUSER / UMIUSR         \u2192 Replen employee ID (FHUL02, FUL02 \u2192 FOP32, FOP32L1)\nLTUSER / EIUSERID       \u2192 LMS employee ID (FLAACTIVH \u2192 FOP32, FOP32L1)\nLTRUSR / EIUSERID       \u2192 Loader employee ID (FLARFLOAD \u2192 FOP32L1)\nUSERID / EIUSERID       \u2192 Door scan employee ID (TOLENT.FPALLETS \u2192 FOP32L1)\nULIMNO / IMNO / OPIMNO  \u2192 Item number (FHUL01, FUL01, F263, F263H, F561, F562H \u2192 F560)\nULODOC / OPSONO         \u2192 Order document number (FHUL01, FUL01 \u2192 F263H, F263)\nOPCUST / ABNO           \u2192 Customer number (F263, F263H \u2192 F101C)\nUMROUT / RTROUT         \u2192 Route number (FUL02, FHUL02 \u2192 FWH001)"], "metadata": [{"embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "start_index": 0, "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "source": "KEHE_DC45_AI_SCHEMA.source.md", "hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "file_id": "377b022c-e9da-42c7-9138-fe03b5328d34", "name": "KEHE_DC45_AI_SCHEMA.source.md"}, {"file_id": "377b022c-e9da-42c7-9138-fe03b5328d34", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "start_index": 0, "name": "KEHE_DC45_AI_SCHEMA.source.md", "source": "KEHE_DC45_AI_SCHEMA.source.md"}, {"start_index": 3490, "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "name": "KEHE_DC45_AI_SCHEMA.source.md", "source": "KEHE_DC45_AI_SCHEMA.source.md", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "file_id": "377b022c-e9da-42c7-9138-fe03b5328d34"}], "distances": [0.6285313963890076, 0.6272038817405701, 0.607819527387619]}, {"source": {"type": "file", "file": {"id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "user_id": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": null, "filename": "Tables.source.csv", "data": {"status": "completed"}, "meta": {"name": "Tables.source.csv", "content_type": "text/csv", "size": 59268, "file_hash": "bc3bc0ed58fe677c992e6e3c641fadff4ba329251e4fb50bc90991bf1b98c0f0", "data": {}}, "created_at": 1781295055, "updated_at": 1781295055, "status": true, "path": "/app/backend/data/uploads/bb92fdc0-07f4-4bda-8121-5c62ebe45a5b_Tables.source.csv"}, "id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "url": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "name": "Tables.source.csv", "status": "uploaded", "size": 59268, "error": "", "itemId": "6b75a203-6a6e-46c0-8009-8d460f0d3920"}, "document": ["COLUMN_NAME: IMQIMD\nINFO_TYPE: COLUMN\nPOSITION: 114\nCOLUMN_TEXT: RECEIVED MONTH TO DATE\nDATA_TYPE: DECIMAL\nLENGTH: 9\nIS_NULLABLE: N\nTOTAL_ROWS: 132275\nINDEX_NAME:\nINDEX_TEXT:\nTBL: F560", "COLUMN_NAME: ABRATG\nINFO_TYPE: COLUMN\nPOSITION: 80\nCOLUMN_TEXT: Customer Rating\nDATA_TYPE: CHAR\nLENGTH: 1\nIS_NULLABLE: N\nTOTAL_ROWS: 22743\nINDEX_NAME:\nINDEX_TEXT:\nTBL: F101C", "COLUMN_NAME: EIDLC\nINFO_TYPE: COLUMN\nPOSITION: 8\nCOLUMN_TEXT: DAILY LINE COUNT\nDATA_TYPE: DECIMAL\nLENGTH: 5\nIS_NULLABLE: N\nTOTAL_ROWS: 1463\nINDEX_NAME:\nINDEX_TEXT:\nTBL: FOP32"], "metadata": [{"name": "Tables.source.csv", "row": 583, "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "start_index": 0, "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "source": "Tables.source.csv", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f"}, {"start_index": 0, "source": "Tables.source.csv", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "row": 309, "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "name": "Tables.source.csv"}, {"source": "Tables.source.csv", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "name": "Tables.source.csv", "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "start_index": 0, "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "row": 114}], "distances": [0.6599161028862, 0.6557852029800415, 0.6532216668128967]}]

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content:
  "I have studied the provided database documentation and schema files for the KEHE DC45 project. Based on the context, here is a summary of the core database structures and logic:\n\n### **Core Table Relationships**\nThe database relies on several key relational paths to connect warehouse activity to business entities:\n*   **ULL Activity to Customer:** The primary path to trace activity from a specific ULL to a customer is: `FHUL04` (Activity History) $\\rightarrow$ `FHUL01` (ULL Detail History) $\\rightarrow$ `F263H` (Order Line History) $\\rightarrow$ `F101C` (Customer Master) [1].\n*   **Inventory & Item Master:** Item details are managed in `F560`. Common joins include:\n    *   `FUL01` / `FHUL01` $\\leftrightarrow$ `F560` via `ULIMNO` [3].\n    *   `F263` / `F263H` $\\leftrightarrow$ `F560` via `OPIMNO` [3].\n*   **Employee/User Data:** Activity tables (`FHUL04`, `FUL04`, `FHUL02`, `FUL02`) join to employee master tables (`FOP32` or `FOP32L1`) using `UNUSERID`, `UMUSER`, or `UMIUSR` [3].\n\n### **Key Operational Logic & Rules**\n*   **Compound Joins:** When joining ULL activity (`FUL04`/`FHUL04`) to ULL detail (`FUL01`/`FHUL01`), you must use both `UNULL` and `UNFLOC` to ensure accuracy [3].\n*   **Deduplication:** To retrieve the most recent record (e.g., the latest status or movement), use `ROW_NUMBER() OVER (PARTITION BY [business_key] ORDER BY [timestamp] DESC)` and filter for `rn = 1` [3].\n*   **Data Cleaning:** \n    *   **System Users:** It is standard practice to exclude system users by filtering `UMUSER NOT LIKE 'CHNWH%'` and `EINAME NOT LIKE '%DEFAULT%'` [1].\n    *   **String Padding:** Sales order numbers (`OPSONO`) in `F263` or `F263H` may require left-padding with spaces or zeros to match source systems [3].\n*   **Performance:** `FHUL04` is a very large table (over 43 million rows); queries should always filter by `UNSDTE` or `UNTIMESTMP` early in the process to maintain performance [3].\n\n### **Table Metadata Highlights**\n*   **`F263H` (Order Line History):** Contains approximately 20 million rows and includes fields like `OPCUST` (Customer), `OPIMNO` (Item), and `OPOSRS` (Out of Stock Reason Code) [2].\n*   **`F560` (Item Master):** Contains approximately 132,275 rows and includes critical dimensions like `IMCUBE` (Cube), `IMWT` (Case Weight), and `IMVQOH` (Virtual Quantity on Hand) [2, 4].\n*   **`F575H`:** Used for tracking putaway history [1]."

output:
  [{"type": "message", "id": "msg_762f0a37114c4f518e32c4d6", "status": "completed", "role": "assistant", "content": [{"type": "output_text", "text": "I have studied the provided database documentation and schema files for the KEHE DC45 project. Based on the context, here is a summary of the core database structures and logic:\n\n### **Core Table Relationships**\nThe database relies on several key relational paths to connect warehouse activity to business entities:\n*   **ULL Activity to Customer:** The primary path to trace activity from a specific ULL to a customer is: `FHUL04` (Activity History) $\\rightarrow$ `FHUL01` (ULL Detail History) $\\rightarrow$ `F263H` (Order Line History) $\\rightarrow$ `F101C` (Customer Master) [1].\n*   **Inventory & Item Master:** Item details are managed in `F560`. Common joins include:\n    *   `FUL01` / `FHUL01` $\\leftrightarrow$ `F560` via `ULIMNO` [3].\n    *   `F263` / `F263H` $\\leftrightarrow$ `F560` via `OPIMNO` [3].\n*   **Employee/User Data:** Activity tables (`FHUL04`, `FUL04`, `FHUL02`, `FUL02`) join to employee master tables (`FOP32` or `FOP32L1`) using `UNUSERID`, `UMUSER`, or `UMIUSR` [3].\n\n### **Key Operational Logic & Rules**\n*   **Compound Joins:** When joining ULL activity (`FUL04`/`FHUL04`) to ULL detail (`FUL01`/`FHUL01`), you must use both `UNULL` and `UNFLOC` to ensure accuracy [3].\n*   **Deduplication:** To retrieve the most recent record (e.g., the latest status or movement), use `ROW_NUMBER() OVER (PARTITION BY [business_key] ORDER BY [timestamp] DESC)` and filter for `rn = 1` [3].\n*   **Data Cleaning:** \n    *   **System Users:** It is standard practice to exclude system users by filtering `UMUSER NOT LIKE 'CHNWH%'` and `EINAME NOT LIKE '%DEFAULT%'` [1].\n    *   **String Padding:** Sales order numbers (`OPSONO`) in `F263` or `F263H` may require left-padding with spaces or zeros to match source systems [3].\n*   **Performance:** `FHUL04` is a very large table (over 43 million rows); queries should always filter by `UNSDTE` or `UNTIMESTMP` early in the process to maintain performance [3].\n\n### **Table Metadata Highlights**\n*   **`F263H` (Order Line History):** Contains approximately 20 million rows and includes fields like `OPCUST` (Customer), `OPIMNO` (Item), and `OPOSRS` (Out of Stock Reason Code) [2].\n*   **`F560` (Item Master):** Contains approximately 132,275 rows and includes critical dimensions like `IMCUBE` (Cube), `IMWT` (Case Weight), and `IMVQOH` (Virtual Quantity on Hand) [2, 4].\n*   **`F575H`:** Used for tracking putaway history [1]."}]}]

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ULODOC+ULIMNO=OPSONO+OPIMNO \u2192 OPCUST=ABNO)\n```", "### Exclude system users  \n- `UMUSER NOT LIKE 'CHNWH%'`\n- `EINAME NOT LIKE '%DEFAULT%'`"], "metadata": [{"source": "AI_DB_MEMORY.md", "start_index": 0, "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "name": "AI_DB_MEMORY.md"}, {"hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "source": "AI_DB_MEMORY.md", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "name": "AI_DB_MEMORY.md", "start_index": 0}, {"created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", "name": 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LIKE '%DEFAULT%'  \n-- INTEGER WRAPPING (required to avoid DECIMAL aggregate errors)\nUse INTEGER() around CHAR-stored time values before math operations  \n-- COMPOUND JOINS (always use BOTH columns)\nFHUL04 \u2192 FHUL01 requires UNULL + UNFLOC  (not UNULL alone)\nFUL04  \u2192 FUL01  requires UNULL + UNFLOC  \n-- DEDUPLICATION\nUse ROW_NUMBER() OVER (PARTITION BY key ORDER BY timestamp DESC) for latest-record logic\nF562H self-join for RF returns uses composite key: ILIMNO||CHAR(ILDTE)||RTRIM(CHAR(ILQTY*-1))||ILUSER  \n-- SALES ORDER PADDING\nF263 / F263H OPSONO may require left-pad to match source:\nCROSS JOIN (VALUES (' '),(' 0'),(' 00'),(' 000'),(' 0000'),(' 00000')) AS p(pad)\nWHERE (p.pad || DSSONO) = F263.OPSONO  \n-- LARGE TABLE PERFORMANCE\nFHUL04 has 43M+ rows \u2014 always filter by UNSDTE or UNTIMESTMP first  \n================================================================================\n[EXCLUDED / LOW CONFIDENCE]", "NTS45.FHUL04   \u2194 NTS45.FOP32      (via UNUSERID)\nNTS45.FHUL04   \u2194 NTS45.FOP32L1    (via UNUSERID)\nNTS45.FUL04    \u2194 NTS45.FUL01      (via UNULL + UNFLOC)\nNTS45.FUL04    \u2194 NTS45.FOP32      (via UNUSERID)\nNTS45.FUL04    \u2194 NTS45.FOP32L1    (via UNUSERID)\nNTS45.FHUL01   \u2194 NTS45.F263H      (via ULODOC + ULIMNO)\nNTS45.FHUL01   \u2194 NTS45.F560       (via ULIMNO)\nNTS45.FUL01    \u2194 NTS45.F263       (via ULODOC + ULIMNO)\nNTS45.FUL01    \u2194 NTS45.F560       (via ULIMNO)\nNTS45.FUL01    \u2194 NTS45.FHUL02     (via ULPLID = UMPLID)\nNTS45.FHUL02   \u2194 NTS45.F262H      (via UMULL)\nNTS45.FHUL02   \u2194 NTS45.FOP32      (via UMUSER)\nNTS45.FHUL02   \u2194 NTS45.FOP32L1    (via UMIUSR)\nNTS45.FHUL02   \u2194 NTS45.FLARFLOAD  (via UMROUT + UMPLID)\nNTS45.FUL02    \u2194 NTS45.F262       (via UMULL)\nNTS45.FUL02    \u2194 NTS45.FOP32L1    (via UMIUSR)\nNTS45.FUL02    \u2194 NTS45.FWH001     (via UMROUT)\nNTS45.F263     \u2194 NTS45.F101C      (via OPCUST = ABNO)\nNTS45.F263H    \u2194 NTS45.F101C      (via OPCUST = ABNO)", "[EXCLUDED / LOW CONFIDENCE]\n================================================================================  \n- NTS## cross-schema joins: all schemas confirmed identical structure \u2014 swap prefix freely\n- TOLENT.FDS0010 joins: invoice/sales context only, not warehouse ULL operations\n- F561 \u2194 F262 slot join: concatenated computed key (RLTOZN||RLTOID), fragile \u2014 use with caution\n- F562 self-join: composite string key, one-off pattern, excluded\n- TOLENT.FDS0010 DC filter: DSDC = '41' shown in examples \u2014 verify correct DC code per query context"], "metadata": [{"file_id": "377b022c-e9da-42c7-9138-fe03b5328d34", "source": "KEHE_DC45_AI_SCHEMA.source.md", "start_index": 12396, "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "name": "KEHE_DC45_AI_SCHEMA.source.md", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a"}, 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id: e136fc62-ed59-4e02-8911-a2644be37b8f-de1411d9-b451-4ea5-bbe6-f75199cb0e3e
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content:
  "To identify the ULLs (Unit Load Loads) that are out of stock for the selector **ONTRF42778**, I would need to query the order line tables to find items marked with an \"Out of Stock\" reason code.\n\nBased on the database schema, the most direct way to find this information is to join the order line history to the item master.\n\n### **Proposed SQL Logic**\nSince \"Out of Stock\" is a status typically recorded at the order line level, the query would follow this logic:\n\n```sql\nSELECT \n    ord.OPSONO AS \"Sales Order\",\n    ord.OPIMNO AS \"Item Number\",\n    ord.OPOOSR AS \"Out of Stock Reason Code\",\n    itm.IMDESC AS \"Item Description\"\nFROM TOLSE.NTS45.F263H ord\nJOIN TOLSE.NTS45.F560 itm \n    ON ord.OPIMNO = itm.IMNO\nWHERE ord.OPCUST = 'ONTRF42778' -- Assuming this is the Customer/Selector ID\n  AND ord.OPOOSR <> ''         -- Filtering for non-blank reason codes\n```\n\n### **Important Considerations**\n1.  **Selector vs. Customer:** In this database, `ONTRF42778` appears to be treated as a customer identifier (`OPCUST` in `F263H` or `ABNO` in `F101C`). If `ONTRF42778` is actually a **User ID** (Employee) rather than a Customer, the query would need to join through the activity tables (`FUL04` or `FHUL04`) to find the orders they were working on.\n2.  **Out of Stock Definition:** I am assuming \"Out of Stock\" is identified by the `OPOOSR` column in the `F263H` table [2].\n3.  **Data Grain:** This query returns the specific order lines that are currently flagged as out of stock for that entity.\n\n**Would you like me to refine this query to search by User ID instead of Customer ID, or should I focus on a specific date range?**"

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filter early)\n- **`FUL04`**: ULL activity **current/open**\n- **`FHUL01`**: ULL header/detail **history** (item/location/order detail per ULL)\n- **`FUL01`**: ULL header/detail **current/open**\n- **`FHUL02`**: unit load movement / replenishment **history**\n- **`FUL02`**: unit load movement / replenishment **current/open**"], "metadata": [{"file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "start_index": 0, "name": "AI_DB_MEMORY.md", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "source": "AI_DB_MEMORY.md"}, {"name": "AI_DB_MEMORY.md", "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "source": "AI_DB_MEMORY.md", "start_index": 0, "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d"}, {"name": "AI_DB_MEMORY.md", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "source": "AI_DB_MEMORY.md", "start_index": 0, "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384"}], "distances": [0.7105086743831635, 0.6735596358776093, 0.669386625289917]}, {"source": {"type": "file", "file": {"id": "a6b017f8-5f39-48c8-8b3e-fa21e213d419", "user_id": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": null, "filename": "AI_DB_TABLE_CATALOG.core.json", "data": {"status": "completed"}, "meta": {"name": "AI_DB_TABLE_CATALOG.core.json", "content_type": "application/json", "size": 287098, "file_hash": "c6df0c456d2e05d42cf7aeefcb95acef67f006048fdd31f2f076a5f6de3776d1", "data": {}}, "created_at": 1781295055, "updated_at": 1781295055, "status": true, "path": "/app/backend/data/uploads/a6b017f8-5f39-48c8-8b3e-fa21e213d419_AI_DB_TABLE_CATALOG.core.json"}, "id": "a6b017f8-5f39-48c8-8b3e-fa21e213d419", "url": "a6b017f8-5f39-48c8-8b3e-fa21e213d419", "name": "AI_DB_TABLE_CATALOG.core.json", "status": "uploaded", "size": 287098, "error": "", "itemId": "456d99e2-874b-4a1d-aeb8-816aee3ad778"}, "document": ["\"INDEX_TEXT\": \"\",\n\"TBL\": \"F101C\"\n},\n{\n\"COLUMN_NAME\": \"ABPRCS\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"90\",\n\"COLUMN_TEXT\": \"Price Sticker Flag\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"22743      \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F101C\"\n},\n{\n\"COLUMN_NAME\": \"ABRETP\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"91\",\n\"COLUMN_TEXT\": \"Retail Pricing Flag\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"22743      \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F101C\"\n},\n{\n\"COLUMN_NAME\": \"ABRPPC\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"92\",\n\"COLUMN_TEXT\": \"Retail Pricing Percent\",\n\"DATA_TYPE\": \"DECIMAL\",\n\"LENGTH\": \"3          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"22743      \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F101C\"\n},\n{\n\"COLUMN_NAME\": \"ABRMTF\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"93\",\n\"COLUMN_TEXT\": \"Remote Terminal Flag\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": \"N\",", "\"TBL\": \"F101C\"\n},\n{\n\"COLUMN_NAME\": \"ABUPNM\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"97\",\n\"COLUMN_TEXT\": \"Price Sticker Name - Upper\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"7          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"22743      \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F101C\"\n},\n{\n\"COLUMN_NAME\": \"ABLONM\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"98\",\n\"COLUMN_TEXT\": \"Price Sticker Name - Lower\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"7          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"22743      \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F101C\"\n},\n{\n\"COLUMN_NAME\": \"ABKEYC\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"99\",\n\"COLUMN_TEXT\": \"\\\"Key\\\" Customer Flag\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"22743      \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F101C\"\n},\n{\n\"COLUMN_NAME\": \"ABSNDC\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"100\",\n\"COLUMN_TEXT\": \"\\\"Send Catalog\\\" Flag\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": \"N\",", "\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F263H\"\n},\n{\n\"COLUMN_NAME\": \"OPWHL\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"33\",\n\"COLUMN_TEXT\": \"WHSL. 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"status": "uploaded", "size": 14277, "error": "", "itemId": "3b7aaf83-96cf-4837-867f-bada1d70dacd"}, "document": ["NTS45.FHUL02.UMPLID       = NTS45.FLARFLOAD.LTRPALLET\nNTS45.FUL01.ULPLID        = NTS45.FHUL02.UMPLID  \n-- ITEM MASTER\nNTS45.FHUL01.ULIMNO       = NTS45.F560.IMNO\nNTS45.FUL01.ULIMNO        = NTS45.F560.IMNO\nNTS45.F561.MPIMNO         = NTS45.F560.IMNO\nNTS45.F562H.IMNO          = NTS45.F560.IMNO\nNTS45.F263.OPIMNO         = NTS45.F560.IMNO\nNTS45.F263H.OPIMNO        = NTS45.F560.IMNO      (note: column may appear as ITEMNMBR in F560)  \n-- ORDER / CUSTOMER\nNTS45.FHUL01.ULODOC       = NTS45.F263H.OPSONO\nNTS45.FHUL01.ULIMNO       = NTS45.F263H.OPIMNO\nNTS45.FUL01.ULODOC        = NTS45.F263.OPSONO\nNTS45.FUL01.ULIMNO        = NTS45.F263.OPIMNO\nNTS45.FUL01.ULULL         = NTS45.F263.OPULL\nNTS45.F263.OPCUST         = NTS45.F101C.ABNO\nNTS45.F263H.OPCUST        = NTS45.F101C.ABNO  \n-- ROUTE / DOOR\nNTS45.FUL02.UMROUT        = NTS45.FWH001.RTROUT\nNTS45.FLARFLOAD.LTRRTE    = NTS45.FWH001.RTROUT  \n-- STAGING / DOOR SCANS\nTOLENT.FPALLETS.WAVE      = NTS45.FUL02.UMWAVE", "NTS45.FUL02 \u2192 NTS45.FUL01 \u2192 NTS45.F561 + NTS45.F560\n(UMULL+UMTLOC \u2192 ULULL+ULLOCN \u2192 MPIMNO=IMNO)  \n================================================================================\n[BUSINESS RULES]\n================================================================================  \n-- DATE / SHIFT\nWork week start  : CURRENT_DATE - (DAYOFWEEK(CURRENT_DATE) - 1) DAYS  (Sunday)\nWork week end    : start + 5 DAYS  (Friday)\nOvernight 6AM    : IF UMCTME < 600 THEN date = UMCDTE - 1 DAYS (before 6AM = prior shift)\nDoor scan 9PM    : LTRLDATE IN (CURRENT_DATE, CURRENT_DATE - 1 DAYS)\nAND (LTRLTIME >= '090000' OR LTRLTIME < '040000')\nEST\u2192PST rollover : Apply when timestamps are EST and warehouse operates PST  \n-- ZONE CLASSIFICATION (by first char of location)\nA/B/C/N/R/S = Dry\nJ/G/H       = Cooler / Refrigerated\nK/L/M       = Freezer\nZone ranges  : S83-S90 = North | S17-S38 = Dry | J03-J23 = Cooler | K42-K57 = Freezer  \n-- ULL TYPE (by first char of ULL number)", "NTS45.FHUL04 \u2192 NTS45.FHUL01 \u2192 NTS45.F560\n(UNULL+UNFLOC \u2192 ULULL+ULLOCN \u2192 ULIMNO=IMNO)  \n-- ULL activity \u2192 order \u2192 customer\nNTS45.FHUL04 \u2192 NTS45.FHUL01 \u2192 NTS45.F263H \u2192 NTS45.F101C\n(UNULL+UNFLOC \u2192 ULULL+ULLOCN \u2192 ULODOC+ULIMNO=OPSONO+OPIMNO \u2192 OPCUST=ABNO)  \n-- Replen history \u2192 employee performance\nNTS45.FHUL02 \u2192 NTS45.FOP32L1\n(UMIUSR = EIUSERID)  \n-- Replen \u2192 fiscal reporting\nNTS45.FHUL02 \u2192 NTS25Q.KKDAILY\n(UMCDTE = YRMD \u2192 FISCALWK, FISCALYR, PERIOD)  \n-- Door scan \u2192 employee + wave\nTOLENT.FPALLETS \u2192 NTS45.FUL02 \u2192 NTS45.FOP32L1\n(WAVE+ROUTE \u2192 UMWAVE+UMROUT \u2192 UMIUSR=EIUSERID)  \n-- Load data \u2192 replen \u2192 route/door\nNTS45.FLARFLOAD \u2192 NTS45.FHUL02 \u2192 NTS45.FWH001\n(LTRRTE+LTRPALLET \u2192 UMROUT+UMPLID \u2192 UMROUT=RTROUT)  \n-- Employee dashboard 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id: e136fc62-ed59-4e02-8911-a2644be37b8f-fc6e1163-3639-4429-8cb2-d41624b3a4fd
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content:
  "I apologize for the error in my previous response. I was treating the selector ID as a customer ID, which was incorrect.\n\nBased on the database memory and schema rules, a selector is a user. To find the ULLs (Unit Load Loads) that are out of stock for a specific selector, I must join the activity tables (which contain the `USERID`) to the order line tables (which contain the out-of-stock reason codes).\n\nSince \"out of stock\" is typically recorded in the order line history, I will use `FHUL04` (ULL activity history) to link the selector to the specific ULLs, and then join to `FHUL01` (ULL header history) and `F263H` (Order line history) to identify the out-of-stock reason.\n\nHere is the corrected SQL query:\n\n```sql\nWITH filtered_activity AS (\n    -- Filter activity by the specific selector first for performance\n    SELECT \n        UNULL, \n        UNFLOC, \n        UNTIMESTMP\n    FROM TOLSE.NTS45.FHUL04\n    WHERE TRIM(UNUSERID) = 'ONTRF42778'\n),\null_details AS (\n    -- Join activity to ULL header to get the order information\n    SELECT \n        act.UNULL,\n        act.UNFLOC,\n        det.ULODOC,\n        det.ULIMNO\n    FROM filtered_activity act\n    INNER JOIN TOLSE.NTS45.FHUL01 det\n        ON act.UNULL = det.ULULL\n        AND act.UNFLOC = det.ULLOCN\n)\nSELECT \n    ud.UNULL AS \"ULL\",\n    ud.ULIMNO AS \"Item Number\",\n    ord.OPOOSR AS \"Out of Stock Reason Code\"\nFROM ull_details ud\nINNER JOIN TOLSE.NTS45.F263H ord\n    ON ud.ULODOC = ord.OPSONO\n    AND ud.ULIMNO = ord.OPIMNO\nWHERE ord.OPOOSR <> ''  -- Filter for records where an out-of-stock reason exists\n```\n\n### **Explanation of the Query**\n* **Grain:** One row per ULL that is associated with an out-of-stock order line for that specific user.\n* **Logic:**\n    1. **`filtered_activity`**: I first isolate the activity records belonging to selector `ONTRF42778` from the large `FHUL04` table to ensure performance.\n    2. **`ull_details`**: I join those activity records to `FHUL01` using the required compound key (`UNULL` and `UNFLOC`) to find which orders and items were involved in that activity.\n    3. **Final Join**: I join the results to `F263H` (Order Line History) to check the `OPOOSR` (Out of Stock Reason Code) column.\n* **Assumptions:**\n    * I am assuming the \"Out of Stock\" status is captured in the `OPOOSR` column of the `F263H` table.\n    * I am assuming the selector ID `ONTRF42778` is a `USERID` found in the activity tables.\n\n### **Performance Note**\nI have applied the performance rule to filter the large `FHUL04` table by the `UNUSERID` as early as possible in a CTE to prevent a full table scan."

output:
  [{"type": "message", "id": "msg_75df4252d08842e2b5c701ad", "status": "completed", "role": "assistant", "content": [{"type": "output_text", "text": "I apologize for the error in my previous response. I was treating the selector ID as a customer ID, which was incorrect.\n\nBased on the database memory and schema rules, a selector is a user. To find the ULLs (Unit Load Loads) that are out of stock for a specific selector, I must join the activity tables (which contain the `USERID`) to the order line tables (which contain the out-of-stock reason codes).\n\nSince \"out of stock\" is typically recorded in the order line history, I will use `FHUL04` (ULL activity history) to link the selector to the specific ULLs, and then join to `FHUL01` (ULL header history) and `F263H` (Order line history) to identify the out-of-stock reason.\n\nHere is the corrected SQL query:\n\n```sql\nWITH filtered_activity AS (\n    -- Filter activity by the specific selector first for performance\n    SELECT \n        UNULL, \n        UNFLOC, \n        UNTIMESTMP\n    FROM TOLSE.NTS45.FHUL04\n    WHERE TRIM(UNUSERID) = 'ONTRF42778'\n),\null_details AS (\n    -- Join activity to ULL header to get the order information\n    SELECT \n        act.UNULL,\n        act.UNFLOC,\n        det.ULODOC,\n        det.ULIMNO\n    FROM filtered_activity act\n    INNER JOIN TOLSE.NTS45.FHUL01 det\n        ON act.UNULL = det.ULULL\n        AND act.UNFLOC = det.ULLOCN\n)\nSELECT \n    ud.UNULL AS \"ULL\",\n    ud.ULIMNO AS \"Item Number\",\n    ord.OPOOSR AS \"Out of Stock Reason Code\"\nFROM ull_details ud\nINNER JOIN TOLSE.NTS45.F263H ord\n    ON ud.ULODOC = ord.OPSONO\n    AND ud.ULIMNO = ord.OPIMNO\nWHERE ord.OPOOSR <> ''  -- Filter for records where an out-of-stock reason exists\n```\n\n### **Explanation of the Query**\n* **Grain:** One row per ULL that is associated with an out-of-stock order line for that specific user.\n* **Logic:**\n    1. **`filtered_activity`**: I first isolate the activity records belonging to selector `ONTRF42778` from the large `FHUL04` table to ensure performance.\n    2. **`ull_details`**: I join those activity records to `FHUL01` using the required compound key (`UNULL` and `UNFLOC`) to find which orders and items were involved in that activity.\n    3. **Final Join**: I join the results to `F263H` (Order Line History) to check the `OPOOSR` (Out of Stock Reason Code) column.\n* **Assumptions:**\n    * I am assuming the \"Out of Stock\" status is captured in the `OPOOSR` column of the `F263H` table.\n    * I am assuming the selector ID `ONTRF42778` is a `USERID` found in the activity tables.\n\n### **Performance Note**\nI have applied the performance rule to filter the large `FHUL04` table by the `UNUSERID` as early as possible in a CTE to prevent a full table scan."}]}]

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  [{"source": {"type": "file", "file": {"id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "user_id": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": null, "filename": "AI_DB_MEMORY.md", "data": {"status": "completed"}, "meta": {"name": "AI_DB_MEMORY.md", "content_type": "text/markdown", "size": 15212, "file_hash": "20dd110a45442ab78e2d86c0837608817c4430500ccbebdc1ac2ba2b30f53754", "data": {}}, "created_at": 1781295055, "updated_at": 1781295055, "status": true, "path": "/app/backend/data/uploads/51f6bbf5-eea8-4bef-bdfd-a7110250c384_AI_DB_MEMORY.md"}, "id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "url": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "name": "AI_DB_MEMORY.md", "status": "uploaded", "size": 15212, "error": "", "itemId": "bee52a34-0560-4f58-8c89-f8d3f36fe2ac"}, "document": ["### Short status note (F263.OPIDSC)  \n`F263.OPIDSC` column text: **TOTE DIVERTED CODE** (CHAR(1)).  \n- `Short Status` is simplified to just `OPEN SHORT` for any non-picked, started tote.\n- `OPIDSC` is still included as a raw field for reference/filtering.  \nRecommended reporting fields:  \n- `OPIDSC`: raw code (trimmed)\n- `Group Code`: raw `OPGPCD` code (trimmed)\n- `Short Status`: reporting label based on picked/system-short/open-short logic", "# AI Database Memory \u2014 KEHE DC45 (DB2/AS400)  \nThis folder is intended to be a **persistent schema \"memory pack\"** for query building and debugging.  \n- **Primary human reference**: `AI_DB_MEMORY.md` (this file)\n- **Full source schema notes (verbatim copy)**: `KEHE_DC45_AI_SCHEMA.source.md`\n- **Raw metadata export**: `Tables.source.csv`\n- **Machine-readable catalog (core tables)**: `AI_DB_TABLE_CATALOG.core.json`\n- **Diagrams**: see the images in your project `assets/` folder (created when you dropped screenshots into chat)  \n---", "## \"Don't lose anything\" guarantee  \nTo ensure nothing from your source docs gets missed:  \n- All narrative, joins, rules, and cautions are preserved in the verbatim file:\n- `KEHE_DC45_AI_SCHEMA.source.md`\n- All available table/column/index metadata is preserved in:\n- `Tables.source.csv`\n- A structured subset for core tables is preserved as JSON:\n- `AI_DB_TABLE_CATALOG.core.json`"], "metadata": [{"file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "name": "AI_DB_MEMORY.md", "start_index": 0, "source": "AI_DB_MEMORY.md", "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f"}, {"created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "source": "AI_DB_MEMORY.md", "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "name": "AI_DB_MEMORY.md", "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "start_index": 0}, {"embedding_config": "{'engine': '', 'model': 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prefix\nNTS19.FHUL04.UNUSERID = NTS19.FOP32.EIUSERID  \u2190 identical  \nCross-DC queries are valid \u2014 join NTS45 tables to NTS41 tables using the same\ncolumn names when comparing data across distribution centers.  \n================================================================================\n[TABLE REFERENCE]\n================================================================================  \nNTS45.FHUL04      ULL activity HISTORY (43M+ rows) \u2014 filter by UNSDTE or UNTIMESTMP first\nNTS45.FUL04       ULL activity CURRENT/OPEN \u2014 same columns as FHUL04\nNTS45.FHUL01      ULL header HISTORY \u2014 item/location/order detail per ULL\nNTS45.FUL01       ULL header CURRENT \u2014 same columns as FHUL01\nNTS45.FHUL02      Replenishment move HISTORY \u2014 user, date, wave, route, location"], "metadata": [{"hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "start_index": 0, "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "file_id": 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20097818\nINDEX_NAME:\nINDEX_TEXT:\nTBL: F263H", "COLUMN_NAME: F260HI1\nINFO_TYPE: INDEX\nPOSITION: 3\nCOLUMN_TEXT: Index by order number, order type, & customer\nDATA_TYPE: D\nLENGTH:\nIS_NULLABLE:\nTOTAL_ROWS:\nINDEX_NAME: F260H_TABLE_INDEX\nINDEX_TEXT: Index by order number, order type, & customer\nTBL: F260H", "COLUMN_NAME: F263HI1\nINFO_TYPE: INDEX\nPOSITION: 3\nCOLUMN_TEXT: Index by order number, order type, & customer\nDATA_TYPE: D\nLENGTH:\nIS_NULLABLE:\nTOTAL_ROWS:\nINDEX_NAME: F263H_TABLE_INDEX\nINDEX_TEXT: Index by order number, order type, & customer\nTBL: F263H"], "metadata": [{"source": "Tables.source.csv", "name": "Tables.source.csv", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "start_index": 0, "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "row": 544}, {"name": "Tables.source.csv", 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usage:
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id: a3990dbf-7fc3-4de0-8516-2d19926572b4-a1b17e56-4a96-4640-ab82-7f7ecd08ab84
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parent_id: c49823b7-aa21-4ec5-ac0f-51510b2e1ef9
model_id: qwen3-coder-next
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content:
  "<details type=\"reasoning\" done=\"true\" duration=\"123\">\n<summary>Thought for 123 seconds</summary>\n&gt; \u2501\u2501\u2501\u2501\u2501\n&gt; llama-swap loading model: qwen3-coder-next\n&gt; \n&gt; A blank terminal is a terrible thing to waste. Here&#x27;s a loading message instead. ..........\n&gt; Applying `torch.nap()` until the model feels refreshed .......\n&gt; Allocating memory like a billionaire allocates tax avoidance strategies ...........\n&gt; Spinning up the cloud GPU, please be patient while we burn your credits ...........\n&gt; Converting electricity into existential dread .......\n&gt; Loading weights (they&#x27;re heavy) ............\n&gt; Convincing CUDA to cooperate. This may take a while. ........\n&gt; Laying down each layer with the care of a Michelin-starred pastry chef .......\n&gt; The model saw &quot;As an AI language model&quot; and won&#x27;t stop saying it now ...........\n&gt; Zipping the GPUs to make them go faster ...........\n&gt; Performing percussive maintenance on the attention mechanism ............\n&gt; Checking if the model still thinks birds are government drones. Yep. .......\n&gt; Aligning with human values, one reluctant epoch at a time ...........\n&gt; Sorry for the wait. No, wait, we&#x27;re not actually sorry. ..........\n&gt; Running `nvidia-smi` and sighing heavily ...........\n&gt; Reticulating splines .\n&gt; Done! (123.18s)\n&gt; \u2501\u2501\u2501\u2501\u2501\n</details>"

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included as a raw field for reference/filtering.  \nRecommended reporting fields:  \n- `OPIDSC`: raw code (trimmed)\n- `Group Code`: raw `OPGPCD` code (trimmed)\n- `Short Status`: reporting label based on picked/system-short/open-short logic", "### Receiving / putaway  \n- **`F575H`**: putaway history", "### Fiscal calendar joins  \n```sql\nFHUL02.UMCDTE     = KKDAILY.YRMD\nFUL02.UMCDTE      = KKDAILY.YRMD\nF260H.SHIDTE      = KKDAILY.YRMD\nF575H.RCDTE       = KKDAILY.YRMD\n```"], "metadata": [{"hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "start_index": 0, "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "name": "AI_DB_MEMORY.md", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "source": "AI_DB_MEMORY.md"}, {"created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "start_index": 0, "source": "AI_DB_MEMORY.md", "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", 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To port any query to another DC, change ONLY\nthe schema prefix. Every join, column reference, and business rule in this\ndocument applies to all DC schemas equally.  \nExample:\nNTS45.FHUL04.UNUSERID = NTS45.FOP32.EIUSERID"], "metadata": [{"created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "source": "KEHE_DC45_AI_SCHEMA.source.md", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "name": "KEHE_DC45_AI_SCHEMA.source.md", "file_id": "377b022c-e9da-42c7-9138-fe03b5328d34", "start_index": 0}, {"created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "start_index": 12396, "name": "KEHE_DC45_AI_SCHEMA.source.md", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "file_id": "377b022c-e9da-42c7-9138-fe03b5328d34", "source": "KEHE_DC45_AI_SCHEMA.source.md"}, {"start_index": 0, "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "source": "KEHE_DC45_AI_SCHEMA.source.md", "hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "file_id": "377b022c-e9da-42c7-9138-fe03b5328d34", "name": "KEHE_DC45_AI_SCHEMA.source.md"}], "distances": [0.5990292131900787, 0.5564081072807312, 0.5467532575130463]}, {"source": {"type": "file", "file": {"id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "user_id": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": null, "filename": "Tables.source.csv", "data": {"status": "completed"}, "meta": {"name": "Tables.source.csv", "content_type": "text/csv", "size": 59268, "file_hash": "bc3bc0ed58fe677c992e6e3c641fadff4ba329251e4fb50bc90991bf1b98c0f0", "data": {}}, "created_at": 1781295055, "updated_at": 1781295055, "status": true, "path": "/app/backend/data/uploads/bb92fdc0-07f4-4bda-8121-5c62ebe45a5b_Tables.source.csv"}, "id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "url": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "name": "Tables.source.csv", "status": "uploaded", "size": 59268, "error": "", "itemId": "6b75a203-6a6e-46c0-8009-8d460f0d3920"}, "document": ["COLUMN_NAME: OPOOSR\nINFO_TYPE: COLUMN\nPOSITION: 34\nCOLUMN_TEXT: OUT OF STOCK REASON CODE\nDATA_TYPE: CHAR\nLENGTH: 1\nIS_NULLABLE: N\nTOTAL_ROWS: 20097818\nINDEX_NAME:\nINDEX_TEXT:\nTBL: F263H", "COLUMN_NAME: OPPEND\nINFO_TYPE: COLUMN\nPOSITION: 29\nCOLUMN_TEXT: PENDING ORDER CODE\nDATA_TYPE: CHAR\nLENGTH: 1\nIS_NULLABLE: N\nTOTAL_ROWS: 20097818\nINDEX_NAME:\nINDEX_TEXT:\nTBL: F263H", "COLUMN_NAME: ABDDAY\nINFO_TYPE: COLUMN\nPOSITION: 95\nCOLUMN_TEXT: Normal Delivery Day\nDATA_TYPE: CHAR\nLENGTH: 2\nIS_NULLABLE: N\nTOTAL_ROWS: 22743\nINDEX_NAME:\nINDEX_TEXT:\nTBL: F101C"], "metadata": [{"row": 544, "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "start_index": 0, "name": "Tables.source.csv", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "source": "Tables.source.csv"}, {"embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "start_index": 0, "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "row": 538, "source": "Tables.source.csv", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "name": "Tables.source.csv"}, {"file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "row": 325, "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "name": "Tables.source.csv", "start_index": 0, "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "source": "Tables.source.csv"}], "distances": [0.5752999782562256, 0.5727183818817139, 0.5721424221992493]}]

status_history:
[cell repeats an earlier one in this file: 122 characters]


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  "<details type=\"reasoning\" done=\"false\">\n<summary>Thinking\u2026</summary>\n&gt; \u2501\u2501\u2501\u2501\u2501\n&gt; llama-swap loading model: qwen3-coder-next\n&gt; \n&gt; Rehearsing plausible-sounding explanations for why it got everything wrong .......\n&gt; Convincing the GPU to participate .........\n&gt; Realigning the alignment so it aligns with the previous alignment ...........\n&gt; Processing your request with the urgency of a DMV employee ..........\n&gt; Applying softmax to our feelings about this load time ............\n&gt; Your GPU is now a space heater with a side hustle in linear algebra .........\n&gt; Spinning up the cloud GPU, please be patient while we burn your credits .......\n&gt; Currently at step 3 of 9,742 of loading. We&#x27;ll get there. Eventually. .........\n</details>"

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ULODOC+ULIMNO=OPSONO+OPIMNO \u2192 OPCUST=ABNO)\n```", "### Exclude system users  \n- `UMUSER NOT LIKE 'CHNWH%'`\n- `EINAME NOT LIKE '%DEFAULT%'`"], "metadata": [{"start_index": 0, "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "name": "AI_DB_MEMORY.md", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "source": "AI_DB_MEMORY.md"}, {"created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "start_index": 0, "name": "AI_DB_MEMORY.md", "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "source": "AI_DB_MEMORY.md", "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d"}, {"source": "AI_DB_MEMORY.md", "name": "AI_DB_MEMORY.md", "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", 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aggregate errors)\nUse INTEGER() around CHAR-stored time values before math operations  \n-- COMPOUND JOINS (always use BOTH columns)\nFHUL04 \u2192 FHUL01 requires UNULL + UNFLOC  (not UNULL alone)\nFUL04  \u2192 FUL01  requires UNULL + UNFLOC  \n-- DEDUPLICATION\nUse ROW_NUMBER() OVER (PARTITION BY key ORDER BY timestamp DESC) for latest-record logic\nF562H self-join for RF returns uses composite key: ILIMNO||CHAR(ILDTE)||RTRIM(CHAR(ILQTY*-1))||ILUSER  \n-- SALES ORDER PADDING\nF263 / F263H OPSONO may require left-pad to match source:\nCROSS JOIN (VALUES (' '),(' 0'),(' 00'),(' 000'),(' 0000'),(' 00000')) AS p(pad)\nWHERE (p.pad || DSSONO) = F263.OPSONO  \n-- LARGE TABLE PERFORMANCE\nFHUL04 has 43M+ rows \u2014 always filter by UNSDTE or UNTIMESTMP first  \n================================================================================\n[EXCLUDED / LOW CONFIDENCE]", "NTS45.FHUL04   \u2194 NTS45.FOP32      (via UNUSERID)\nNTS45.FHUL04   \u2194 NTS45.FOP32L1    (via UNUSERID)\nNTS45.FUL04    \u2194 NTS45.FUL01      (via UNULL + UNFLOC)\nNTS45.FUL04    \u2194 NTS45.FOP32      (via UNUSERID)\nNTS45.FUL04    \u2194 NTS45.FOP32L1    (via UNUSERID)\nNTS45.FHUL01   \u2194 NTS45.F263H      (via ULODOC + ULIMNO)\nNTS45.FHUL01   \u2194 NTS45.F560       (via ULIMNO)\nNTS45.FUL01    \u2194 NTS45.F263       (via ULODOC + ULIMNO)\nNTS45.FUL01    \u2194 NTS45.F560       (via ULIMNO)\nNTS45.FUL01    \u2194 NTS45.FHUL02     (via ULPLID = UMPLID)\nNTS45.FHUL02   \u2194 NTS45.F262H      (via UMULL)\nNTS45.FHUL02   \u2194 NTS45.FOP32      (via UMUSER)\nNTS45.FHUL02   \u2194 NTS45.FOP32L1    (via UMIUSR)\nNTS45.FHUL02   \u2194 NTS45.FLARFLOAD  (via UMROUT + UMPLID)\nNTS45.FUL02    \u2194 NTS45.F262       (via UMULL)\nNTS45.FUL02    \u2194 NTS45.FOP32L1    (via UMIUSR)\nNTS45.FUL02    \u2194 NTS45.FWH001     (via UMROUT)\nNTS45.F263     \u2194 NTS45.F101C      (via OPCUST = ABNO)\nNTS45.F263H    \u2194 NTS45.F101C      (via OPCUST = ABNO)", "[EXCLUDED / LOW CONFIDENCE]\n================================================================================  \n- NTS## cross-schema joins: all schemas confirmed identical structure \u2014 swap prefix freely\n- TOLENT.FDS0010 joins: invoice/sales context only, not warehouse ULL operations\n- F561 \u2194 F262 slot join: concatenated computed key (RLTOZN||RLTOID), fragile \u2014 use with caution\n- F562 self-join: composite string key, one-off pattern, excluded\n- TOLENT.FDS0010 DC filter: DSDC = '41' shown in examples \u2014 verify correct DC code per query context"], "metadata": [{"start_index": 12396, "file_id": "377b022c-e9da-42c7-9138-fe03b5328d34", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "name": "KEHE_DC45_AI_SCHEMA.source.md", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "source": "KEHE_DC45_AI_SCHEMA.source.md", "hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a"}, {"file_id": 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status_history:
[cell repeats an earlier one in this file: 122 characters]


id: a3990dbf-7fc3-4de0-8516-2d19926572b4-8f9f2a64-e611-44f0-a257-e34240335512
chat_id: a3990dbf-7fc3-4de0-8516-2d19926572b4
user_id: c49db2a8-83d7-4afc-bae1-ce9dcbce333f
role: assistant
parent_id: d7e6e484-e842-4e7e-b60f-45c28a669f0e
model_id: qwen36-35b-mtp
files: null
embeds: null
error: null
usage: null
content:
  "<details type=\"reasoning\" done=\"true\" duration=\"16\">\n<summary>Thought for 16 seconds</summary>\n&gt; \u2501\u2501\u2501\u2501\u2501\n&gt; llama-swap loading model: qwen36-35b-mtp\n&gt; \n&gt; Hold on, the GPU is questioning its existence ..........\n&gt; Re-reading &#x27;Attention Is All You Need&#x27; for the 400th time .........\n&gt; Done! (16.44s)\n&gt; \u2501\u2501\u2501\u2501\u2501\n</details>"

output:
  [{"type": "reasoning", "id": "r_55c6543648af4a12a4cfd003", "status": "completed", "start_tag": "<think>", "end_tag": "</think>", "attributes": {"type": "reasoning_content"}, "content": [{"type": "output_text", "text": "\u2501\u2501\u2501\u2501\u2501\nllama-swap loading model: qwen36-35b-mtp\n\nHold on, the GPU is questioning its existence ..........\nRe-reading 'Attention Is All You Need' for the 400th time .........\nDone! (16.44s)\n\u2501\u2501\u2501\u2501\u2501\n \n"}], "summary": null, "started_at": 1782022409.8510573, "ended_at": 1782022426.5079463, "duration": 16}]

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included as a raw field for reference/filtering.  \nRecommended reporting fields:  \n- `OPIDSC`: raw code (trimmed)\n- `Group Code`: raw `OPGPCD` code (trimmed)\n- `Short Status`: reporting label based on picked/system-short/open-short logic", "### Receiving / putaway  \n- **`F575H`**: putaway history", "### Fiscal calendar joins  \n```sql\nFHUL02.UMCDTE     = KKDAILY.YRMD\nFUL02.UMCDTE      = KKDAILY.YRMD\nF260H.SHIDTE      = KKDAILY.YRMD\nF575H.RCDTE       = KKDAILY.YRMD\n```"], "metadata": [{"embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", "name": "AI_DB_MEMORY.md", "source": "AI_DB_MEMORY.md", "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "start_index": 0}, {"name": "AI_DB_MEMORY.md", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "file_id": 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"/app/backend/data/uploads/377b022c-e9da-42c7-9138-fe03b5328d34_KEHE_DC45_AI_SCHEMA.source.md"}, "id": "377b022c-e9da-42c7-9138-fe03b5328d34", "url": "377b022c-e9da-42c7-9138-fe03b5328d34", "name": "KEHE_DC45_AI_SCHEMA.source.md", "status": "uploaded", "size": 14277, "error": "", "itemId": "3b7aaf83-96cf-4837-867f-bada1d70dacd"}, "document": ["# KEHE DC45 \u2014 DB2/AS400 AI Knowledge File", "EINAME NOT LIKE '%DEFAULT%'  \n-- INTEGER WRAPPING (required to avoid DECIMAL aggregate errors)\nUse INTEGER() around CHAR-stored time values before math operations  \n-- COMPOUND JOINS (always use BOTH columns)\nFHUL04 \u2192 FHUL01 requires UNULL + UNFLOC  (not UNULL alone)\nFUL04  \u2192 FUL01  requires UNULL + UNFLOC  \n-- DEDUPLICATION\nUse ROW_NUMBER() OVER (PARTITION BY key ORDER BY timestamp DESC) for latest-record logic\nF562H self-join for RF returns uses composite key: ILIMNO||CHAR(ILDTE)||RTRIM(CHAR(ILQTY*-1))||ILUSER  \n-- SALES ORDER PADDING\nF263 / F263H OPSONO may require left-pad to match source:\nCROSS JOIN (VALUES (' '),(' 0'),(' 00'),(' 000'),(' 0000'),(' 00000')) AS p(pad)\nWHERE (p.pad || DSSONO) = F263.OPSONO  \n-- LARGE TABLE PERFORMANCE\nFHUL04 has 43M+ rows \u2014 always filter by UNSDTE or UNTIMESTMP first  \n================================================================================\n[EXCLUDED / LOW CONFIDENCE]", "# Use this file to teach an AI assistant the full schema before building queries  \n================================================================================\n[SCHEMA OVERVIEW]\n================================================================================  \n- NTS45   \u2192 DC45 Ontario/Rancho Cucamonga (primary dev schema)\n- NTS41   \u2192 DC41\n- NTS19   \u2192 DC19\n- NTS35   \u2192 DC35\n- NTS##   \u2192 All other KEHE distribution centers follow same NTS## naming pattern\n- NTS25Q  \u2192 Fiscal calendar shared across ALL DCs (KKDAILY)\n- TOLENT  \u2192 Enterprise-level tables: door/pallet scans (FPALLETS), invoice log (FDS0010)  \nCRITICAL RULE:\nALL NTS## schemas (NTS45, NTS41, NTS19, NTS35, etc.) share 100% identical\ntable names and column names. To port any query to another DC, change ONLY\nthe schema prefix. Every join, column reference, and business rule in this\ndocument applies to all DC schemas equally.  \nExample:\nNTS45.FHUL04.UNUSERID = NTS45.FOP32.EIUSERID"], "metadata": [{"embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "source": "KEHE_DC45_AI_SCHEMA.source.md", "name": "KEHE_DC45_AI_SCHEMA.source.md", "file_id": "377b022c-e9da-42c7-9138-fe03b5328d34", "start_index": 0, "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f"}, {"created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "start_index": 12396, "file_id": "377b022c-e9da-42c7-9138-fe03b5328d34", "name": "KEHE_DC45_AI_SCHEMA.source.md", "source": "KEHE_DC45_AI_SCHEMA.source.md", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a"}, {"name": "KEHE_DC45_AI_SCHEMA.source.md", "source": "KEHE_DC45_AI_SCHEMA.source.md", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "start_index": 0, "hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "file_id": "377b022c-e9da-42c7-9138-fe03b5328d34"}], "distances": [0.5990292131900787, 0.5564081072807312, 0.5467532575130463]}, {"source": {"type": "file", "file": {"id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "user_id": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": null, "filename": "Tables.source.csv", "data": {"status": "completed"}, "meta": {"name": "Tables.source.csv", "content_type": "text/csv", "size": 59268, "file_hash": "bc3bc0ed58fe677c992e6e3c641fadff4ba329251e4fb50bc90991bf1b98c0f0", "data": {}}, "created_at": 1781295055, "updated_at": 1781295055, "status": true, "path": "/app/backend/data/uploads/bb92fdc0-07f4-4bda-8121-5c62ebe45a5b_Tables.source.csv"}, "id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "url": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "name": "Tables.source.csv", "status": "uploaded", "size": 59268, "error": "", "itemId": "6b75a203-6a6e-46c0-8009-8d460f0d3920"}, "document": ["COLUMN_NAME: OPOOSR\nINFO_TYPE: COLUMN\nPOSITION: 34\nCOLUMN_TEXT: OUT OF STOCK REASON CODE\nDATA_TYPE: CHAR\nLENGTH: 1\nIS_NULLABLE: N\nTOTAL_ROWS: 20097818\nINDEX_NAME:\nINDEX_TEXT:\nTBL: F263H", "COLUMN_NAME: OPPEND\nINFO_TYPE: COLUMN\nPOSITION: 29\nCOLUMN_TEXT: PENDING ORDER CODE\nDATA_TYPE: CHAR\nLENGTH: 1\nIS_NULLABLE: N\nTOTAL_ROWS: 20097818\nINDEX_NAME:\nINDEX_TEXT:\nTBL: F263H", "COLUMN_NAME: ABDDAY\nINFO_TYPE: COLUMN\nPOSITION: 95\nCOLUMN_TEXT: Normal Delivery Day\nDATA_TYPE: CHAR\nLENGTH: 2\nIS_NULLABLE: N\nTOTAL_ROWS: 22743\nINDEX_NAME:\nINDEX_TEXT:\nTBL: F101C"], "metadata": [{"embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "start_index": 0, "row": 544, "source": "Tables.source.csv", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "name": "Tables.source.csv", "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97"}, {"embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "row": 538, "start_index": 0, "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "source": "Tables.source.csv", "name": "Tables.source.csv", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f"}, {"source": "Tables.source.csv", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "row": 325, "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "start_index": 0, "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "name": "Tables.source.csv", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f"}], "distances": [0.5752999782562256, 0.5727183818817139, 0.5721424221992493]}]

status_history:
[cell repeats an earlier one in this file: 122 characters]


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usage:
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# chat

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title: New Chat
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chat:
  {"id": "e136fc62-ed59-4e02-8911-a2644be37b8f", "title": "New Chat", "models": ["gemma-26b-200k"], "history": {"currentId": "fc6e1163-3639-4429-8cb2-d41624b3a4fd", "messages": {"f9057781-4c8d-440b-8b0c-d88c9f70787b": {"id": "f9057781-4c8d-440b-8b0c-d88c9f70787b", "parentId": null, "childrenIds": ["28abe86f-641c-4985-9902-29cf9b12e6aa"], "role": "user", "content": "study our database", "timestamp": 1782004570, "models": ["gemma-26b-200k"]}, "28abe86f-641c-4985-9902-29cf9b12e6aa": {"id": "28abe86f-641c-4985-9902-29cf9b12e6aa", "parentId": "f9057781-4c8d-440b-8b0c-d88c9f70787b", "childrenIds": ["42b967b6-123b-48a0-a214-11302d89842f"], "role": "assistant", "content": "", "done": true, "model": "gemma-26b-200k", "timestamp": 1782004570, "statusHistory": [{"action": "queries_generated", "queries": [], "done": false}, {"action": "sources_retrieved", "count": 4, "done": true}], "sources": [{"source": {"type": "file", "file": {"id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "user_id": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": null, "filename": "AI_DB_MEMORY.md", "data": {"status": "completed"}, "meta": {"name": "AI_DB_MEMORY.md", "content_type": "text/markdown", "size": 15212, "file_hash": "20dd110a45442ab78e2d86c0837608817c4430500ccbebdc1ac2ba2b30f53754", "data": {}}, "created_at": 1781295055, "updated_at": 1781295055, "status": true, "path": "/app/backend/data/uploads/51f6bbf5-eea8-4bef-bdfd-a7110250c384_AI_DB_MEMORY.md"}, "id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "url": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "name": "AI_DB_MEMORY.md", "status": "uploaded", "size": 15212, "error": "", "itemId": "bee52a34-0560-4f58-8c89-f8d3f36fe2ac"}, "document": ["# AI Database Memory \u2014 KEHE DC45 (DB2/AS400)  \nThis folder is intended to be a **persistent schema \"memory pack\"** for query building and debugging.  \n- **Primary human reference**: `AI_DB_MEMORY.md` (this file)\n- **Full source schema notes (verbatim copy)**: `KEHE_DC45_AI_SCHEMA.source.md`\n- **Raw metadata export**: `Tables.source.csv`\n- **Machine-readable catalog (core tables)**: `AI_DB_TABLE_CATALOG.core.json`\n- **Diagrams**: see the images in your project `assets/` folder (created when you dropped screenshots into chat)  \n---", "## Table roles (what each table is \"for\")  \n### ULL (Unit Load) \u2014 history vs current/open  \n- **`FHUL04`**: ULL activity **history** (very large; filter early)\n- **`FUL04`**: ULL activity **current/open**\n- **`FHUL01`**: ULL header/detail **history** (item/location/order detail per ULL)\n- **`FUL01`**: ULL header/detail **current/open**\n- **`FHUL02`**: unit load movement / replenishment **history**\n- **`FUL02`**: unit load movement / replenishment **current/open**", "## How to use the machine-readable catalog  \n- **Core catalog**: `AI_DB_TABLE_CATALOG.core.json`\n- Contains **columns + indexes** for the \"core\" operational tables most frequently queried.\n- Built by parsing `Tables.source.csv`.  \n- **Full raw export**: `Tables.source.csv`\n- Use when you need a column not present in the schema notes or when validating data types/lengths/nullability.  \n---"], "metadata": [{"embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "source": "AI_DB_MEMORY.md", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "start_index": 0, "name": "AI_DB_MEMORY.md", "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384"}, {"created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "source": "AI_DB_MEMORY.md", "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", "name": "AI_DB_MEMORY.md", "start_index": 0}, {"created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "start_index": 0, "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "source": "AI_DB_MEMORY.md", 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"status": "uploaded", "size": 287098, "error": "", "itemId": "456d99e2-874b-4a1d-aeb8-816aee3ad778"}, "document": ["\"LENGTH\": \"\",\n\"IS_NULLABLE\": \"\",\n\"TOTAL_ROWS\": \"\",\n\"INDEX_NAME\": \"FHUL04_TABLE_INDEX1\",\n\"INDEX_TEXT\": \"Index by ULL, location, & date\",\n\"TBL\": \"FHUL04\"\n},\n{\n\"COLUMN_NAME\": \"FHUL04I2  \",\n\"INFO_TYPE\": \"INDEX\",\n\"POSITION\": \"3\",\n\"COLUMN_TEXT\": \"Index by ULL, date, & activity\",\n\"DATA_TYPE\": \"D\",\n\"LENGTH\": \"\",\n\"IS_NULLABLE\": \"\",\n\"TOTAL_ROWS\": \"\",\n\"INDEX_NAME\": \"FHUL04_TABLE_INDEX2\",\n\"INDEX_TEXT\": \"Index by ULL, date, & activity\",\n\"TBL\": \"FHUL04\"\n},\n{\n\"COLUMN_NAME\": \"FHUL04I3  \",\n\"INFO_TYPE\": \"INDEX\",\n\"POSITION\": \"6\",\n\"COLUMN_TEXT\": \"Dematic Lane Report Indext\",\n\"DATA_TYPE\": \"D\",\n\"LENGTH\": \"\",\n\"IS_NULLABLE\": \"\",\n\"TOTAL_ROWS\": \"\",\n\"INDEX_NAME\": \"FHUL04_TABLE_INDEX_03\",\n\"INDEX_TEXT\": \"Dematic Lane Report Indext\",\n\"TBL\": \"FHUL04\"\n},\n{\n\"COLUMN_NAME\": \"FHUL04I4  \",\n\"INFO_TYPE\": \"INDEX\",\n\"POSITION\": \"6\",\n\"COLUMN_TEXT\": \"Dematic Lane Report Indext\",\n\"DATA_TYPE\": \"D\",\n\"LENGTH\": \"\",\n\"IS_NULLABLE\": \"\",\n\"TOTAL_ROWS\": \"\",\n\"INDEX_NAME\": \"FHUL04_TABLE_INDEX_04\",\n\"INDEX_TEXT\": \"Dematic Lane Report Indext\",", "\"TBL\": \"F560\"\n},\n{\n\"COLUMN_NAME\": \"IMUSER\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"122\",\n\"COLUMN_TEXT\": \"USER I.D.\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"10         \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"132275     \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F560\"\n},\n{\n\"COLUMN_NAME\": \"IMMNTD\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"123\",\n\"COLUMN_TEXT\": \"DATE LAST MAINT\",\n\"DATA_TYPE\": \"DATE\",\n\"LENGTH\": \"4          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"132275     \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F560\"\n},\n{\n\"COLUMN_NAME\": \"IMMNTT\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"124\",\n\"COLUMN_TEXT\": \"TIME LAST MAINT\",\n\"DATA_TYPE\": \"NUMERIC\",\n\"LENGTH\": \"6          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"132275     \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F560\"\n},\n{\n\"COLUMN_NAME\": \"IMVQOH\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"125\",\n\"COLUMN_TEXT\": \"VIRTUAL QUANTITY ON HAND\",\n\"DATA_TYPE\": \"DECIMAL\",\n\"LENGTH\": \"7          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"132275     \",\n\"INDEX_NAME\": \"\",", "\"COLUMN_TEXT\": \"TOTE DIVERTED CODE\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"120746     \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F263\"\n},\n{\n\"COLUMN_NAME\": \"OPOSRS\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"27\",\n\"COLUMN_TEXT\": \"OUT OF STOCK REASON\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": 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[0.6392928957939148, 0.6369936466217041, 0.6353603601455688]}, {"source": {"type": "file", "file": {"id": "377b022c-e9da-42c7-9138-fe03b5328d34", "user_id": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": null, "filename": "KEHE_DC45_AI_SCHEMA.source.md", "data": {"status": "completed"}, "meta": {"name": "KEHE_DC45_AI_SCHEMA.source.md", "content_type": "text/markdown", "size": 14277, "file_hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "data": {}}, "created_at": 1781295055, "updated_at": 1781295055, "status": true, "path": "/app/backend/data/uploads/377b022c-e9da-42c7-9138-fe03b5328d34_KEHE_DC45_AI_SCHEMA.source.md"}, "id": "377b022c-e9da-42c7-9138-fe03b5328d34", "url": "377b022c-e9da-42c7-9138-fe03b5328d34", "name": "KEHE_DC45_AI_SCHEMA.source.md", "status": "uploaded", "size": 14277, "error": "", "itemId": "3b7aaf83-96cf-4837-867f-bada1d70dacd"}, "document": ["# KEHE DC45 \u2014 DB2/AS400 AI Knowledge File", "# Use this file to teach an AI assistant the full schema before building queries  \n================================================================================\n[SCHEMA OVERVIEW]\n================================================================================  \n- NTS45   \u2192 DC45 Ontario/Rancho Cucamonga (primary dev schema)\n- NTS41   \u2192 DC41\n- NTS19   \u2192 DC19\n- NTS35   \u2192 DC35\n- NTS##   \u2192 All other KEHE distribution centers follow same NTS## naming pattern\n- NTS25Q  \u2192 Fiscal calendar shared across ALL DCs (KKDAILY)\n- TOLENT  \u2192 Enterprise-level tables: door/pallet scans (FPALLETS), invoice log (FDS0010)  \nCRITICAL RULE:\nALL NTS## schemas (NTS45, NTS41, NTS19, NTS35, etc.) share 100% identical\ntable names and column names. To port any query to another DC, change ONLY\nthe schema prefix. Every join, column reference, and business rule in this\ndocument applies to all DC schemas equally.  \nExample:\nNTS45.FHUL04.UNUSERID = NTS45.FOP32.EIUSERID", "================================================================================\n[KEY COLUMNS \u2014 shared across tables]\n================================================================================  \nUNULL / ULULL / UMULL   \u2192 Shared ULL number key (FHUL04, FUL04, FHUL01, FUL01, FHUL02, FUL02, F262H, F262)\nUNUSERID / EIUSERID     \u2192 Employee ID (FHUL04, FUL04 \u2192 FOP32, FOP32L1)\nUMUSER / UMIUSR         \u2192 Replen employee ID (FHUL02, FUL02 \u2192 FOP32, FOP32L1)\nLTUSER / EIUSERID       \u2192 LMS employee ID (FLAACTIVH \u2192 FOP32, FOP32L1)\nLTRUSR / EIUSERID       \u2192 Loader employee ID (FLARFLOAD \u2192 FOP32L1)\nUSERID / EIUSERID       \u2192 Door scan employee ID (TOLENT.FPALLETS \u2192 FOP32L1)\nULIMNO / IMNO / OPIMNO  \u2192 Item number (FHUL01, FUL01, F263, F263H, F561, F562H \u2192 F560)\nULODOC / OPSONO         \u2192 Order document number (FHUL01, FUL01 \u2192 F263H, F263)\nOPCUST / ABNO           \u2192 Customer number (F263, F263H \u2192 F101C)\nUMROUT / RTROUT         \u2192 Route number (FUL02, FHUL02 \u2192 FWH001)"], "metadata": [{"embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "start_index": 0, "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "source": "KEHE_DC45_AI_SCHEMA.source.md", "hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "file_id": "377b022c-e9da-42c7-9138-fe03b5328d34", "name": "KEHE_DC45_AI_SCHEMA.source.md"}, {"file_id": "377b022c-e9da-42c7-9138-fe03b5328d34", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "start_index": 0, "name": "KEHE_DC45_AI_SCHEMA.source.md", "source": 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"/app/backend/data/uploads/bb92fdc0-07f4-4bda-8121-5c62ebe45a5b_Tables.source.csv"}, "id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "url": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "name": "Tables.source.csv", "status": "uploaded", "size": 59268, "error": "", "itemId": "6b75a203-6a6e-46c0-8009-8d460f0d3920"}, "document": ["COLUMN_NAME: IMQIMD\nINFO_TYPE: COLUMN\nPOSITION: 114\nCOLUMN_TEXT: RECEIVED MONTH TO DATE\nDATA_TYPE: DECIMAL\nLENGTH: 9\nIS_NULLABLE: N\nTOTAL_ROWS: 132275\nINDEX_NAME:\nINDEX_TEXT:\nTBL: F560", "COLUMN_NAME: ABRATG\nINFO_TYPE: COLUMN\nPOSITION: 80\nCOLUMN_TEXT: Customer Rating\nDATA_TYPE: CHAR\nLENGTH: 1\nIS_NULLABLE: N\nTOTAL_ROWS: 22743\nINDEX_NAME:\nINDEX_TEXT:\nTBL: F101C", "COLUMN_NAME: EIDLC\nINFO_TYPE: COLUMN\nPOSITION: 8\nCOLUMN_TEXT: DAILY LINE COUNT\nDATA_TYPE: DECIMAL\nLENGTH: 5\nIS_NULLABLE: N\nTOTAL_ROWS: 1463\nINDEX_NAME:\nINDEX_TEXT:\nTBL: FOP32"], "metadata": [{"name": "Tables.source.csv", "row": 583, "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "start_index": 0, "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "source": "Tables.source.csv", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f"}, {"start_index": 0, "source": "Tables.source.csv", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "row": 309, "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "name": "Tables.source.csv"}, {"source": "Tables.source.csv", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "name": "Tables.source.csv", "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "start_index": 0, "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "row": 114}], "distances": [0.6599161028862, 0.6557852029800415, 0.6532216668128967]}], "output": []}, "42b967b6-123b-48a0-a214-11302d89842f": {"id": "42b967b6-123b-48a0-a214-11302d89842f", "parentId": "28abe86f-641c-4985-9902-29cf9b12e6aa", "childrenIds": ["eb763d93-f752-4993-93a3-9505469ddcf5"], "role": "user", "content": "?", "timestamp": 1782004713, "models": ["gemma-26b-200k"]}, "eb763d93-f752-4993-93a3-9505469ddcf5": {"id": "eb763d93-f752-4993-93a3-9505469ddcf5", "parentId": "42b967b6-123b-48a0-a214-11302d89842f", "childrenIds": ["8e65d4d8-b01f-4126-b9c0-7041cbb9d0f5"], "role": "assistant", "content": "I have studied the provided database documentation and schema files for the KEHE DC45 project. Based on the context, here is a summary of the core database structures and logic:\n\n### **Core Table Relationships**\nThe database relies on several key relational paths to connect warehouse activity to business entities:\n*   **ULL Activity to Customer:** The primary path to trace activity from a specific ULL to a customer is: `FHUL04` (Activity History) $\\rightarrow$ `FHUL01` (ULL Detail History) $\\rightarrow$ `F263H` (Order Line History) $\\rightarrow$ `F101C` (Customer Master) [1].\n*   **Inventory & Item Master:** Item details are managed in `F560`. Common joins include:\n    *   `FUL01` / `FHUL01` $\\leftrightarrow$ `F560` via `ULIMNO` [3].\n    *   `F263` / `F263H` $\\leftrightarrow$ `F560` via `OPIMNO` [3].\n*   **Employee/User Data:** Activity tables (`FHUL04`, `FUL04`, `FHUL02`, `FUL02`) join to employee master tables (`FOP32` or `FOP32L1`) using `UNUSERID`, `UMUSER`, or `UMIUSR` [3].\n\n### **Key Operational Logic & Rules**\n*   **Compound Joins:** When joining ULL activity (`FUL04`/`FHUL04`) to ULL detail (`FUL01`/`FHUL01`), you must use both `UNULL` and `UNFLOC` to ensure accuracy [3].\n*   **Deduplication:** To retrieve the most recent record (e.g., the latest status or movement), use `ROW_NUMBER() OVER (PARTITION BY [business_key] ORDER BY [timestamp] DESC)` and filter for `rn = 1` [3].\n*   **Data Cleaning:** \n    *   **System Users:** It is standard practice to exclude system users by filtering `UMUSER NOT LIKE 'CHNWH%'` and `EINAME NOT LIKE '%DEFAULT%'` [1].\n    *   **String Padding:** Sales order numbers (`OPSONO`) in `F263` or `F263H` may require left-padding with spaces or zeros to match source systems [3].\n*   **Performance:** `FHUL04` is a very large table (over 43 million rows); queries should always filter by `UNSDTE` or `UNTIMESTMP` early in the process to maintain performance [3].\n\n### **Table Metadata Highlights**\n*   **`F263H` (Order Line History):** Contains approximately 20 million rows and includes fields like `OPCUST` (Customer), `OPIMNO` (Item), and `OPOSRS` (Out of Stock Reason Code) [2].\n*   **`F560` (Item Master):** Contains approximately 132,275 rows and includes critical dimensions like `IMCUBE` (Cube), `IMWT` (Case Weight), and `IMVQOH` (Virtual Quantity on Hand) [2, 4].\n*   **`F575H`:** Used for tracking putaway history [1].", "done": true, "model": "gemma-26b-200k", "timestamp": 1782004713, "statusHistory": [{"action": "queries_generated", "queries": [], "done": false}, {"action": "sources_retrieved", "count": 4, "done": true}], "sources": [{"source": {"type": "file", "file": {"id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "user_id": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": null, "filename": "AI_DB_MEMORY.md", "data": {"status": "completed"}, "meta": {"name": "AI_DB_MEMORY.md", "content_type": "text/markdown", "size": 15212, "file_hash": "20dd110a45442ab78e2d86c0837608817c4430500ccbebdc1ac2ba2b30f53754", "data": {}}, "created_at": 1781295055, "updated_at": 1781295055, "status": true, "path": "/app/backend/data/uploads/51f6bbf5-eea8-4bef-bdfd-a7110250c384_AI_DB_MEMORY.md"}, "id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "url": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "name": "AI_DB_MEMORY.md", "status": "uploaded", "size": 15212, "error": "", "itemId": "bee52a34-0560-4f58-8c89-f8d3f36fe2ac"}, "document": ["### Receiving / putaway  \n- **`F575H`**: putaway history", "### ULL activity \u2192 order \u2192 customer  \n```sql\nFHUL04 \u2192 FHUL01 \u2192 F263H \u2192 F101C\n-- (UNULL+UNFLOC \u2192 ULULL+ULLOCN \u2192 ULODOC+ULIMNO=OPSONO+OPIMNO \u2192 OPCUST=ABNO)\n```", "### Exclude system users  \n- `UMUSER NOT LIKE 'CHNWH%'`\n- `EINAME NOT LIKE '%DEFAULT%'`"], "metadata": [{"source": "AI_DB_MEMORY.md", "start_index": 0, "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "name": "AI_DB_MEMORY.md"}, {"hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "source": "AI_DB_MEMORY.md", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "name": "AI_DB_MEMORY.md", "start_index": 0}, {"created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", "name": "AI_DB_MEMORY.md", "file_id": 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"uploaded", "size": 287098, "error": "", "itemId": "456d99e2-874b-4a1d-aeb8-816aee3ad778"}, "document": ["\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"20097818   \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F263H\"\n},\n{\n\"COLUMN_NAME\": \"OPIDSC\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"26\",\n\"COLUMN_TEXT\": \"ITEM DISCOUNT CODE\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"20097818   \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F263H\"\n},\n{\n\"COLUMN_NAME\": \"OPOSRS\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"27\",\n\"COLUMN_TEXT\": \"OUT OF STOCK REASON CODE\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"20097818   \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F263H\"\n},\n{\n\"COLUMN_NAME\": \"OPREFC\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"28\",\n\"COLUMN_TEXT\": \"REFERENCE CODE\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"20097818   \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F263H\"\n},\n{\n\"COLUMN_NAME\": \"OPPEND\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"29\",\n\"COLUMN_TEXT\": \"PENDING ORDER CODE\",", "\"TOTAL_ROWS\": \"132275     \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F560\"\n},\n{\n\"COLUMN_NAME\": \"IMUNSL\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"16\",\n\"COLUMN_TEXT\": \"UNIT OF SALE\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"2          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"132275     \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F560\"\n},\n{\n\"COLUMN_NAME\": \"IMMPCK\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"17\",\n\"COLUMN_TEXT\": \"MASTER PACK\",\n\"DATA_TYPE\": \"DECIMAL\",\n\"LENGTH\": \"3          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"132275     \",\n\"INDEX_NAME\": 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0.5419774651527405, 0.5413188934326172]}, {"source": {"type": "file", "file": {"id": "377b022c-e9da-42c7-9138-fe03b5328d34", "user_id": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": null, "filename": "KEHE_DC45_AI_SCHEMA.source.md", "data": {"status": "completed"}, "meta": {"name": "KEHE_DC45_AI_SCHEMA.source.md", "content_type": "text/markdown", "size": 14277, "file_hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "data": {}}, "created_at": 1781295055, "updated_at": 1781295055, "status": true, "path": "/app/backend/data/uploads/377b022c-e9da-42c7-9138-fe03b5328d34_KEHE_DC45_AI_SCHEMA.source.md"}, "id": "377b022c-e9da-42c7-9138-fe03b5328d34", "url": "377b022c-e9da-42c7-9138-fe03b5328d34", "name": "KEHE_DC45_AI_SCHEMA.source.md", "status": "uploaded", "size": 14277, "error": "", "itemId": "3b7aaf83-96cf-4837-867f-bada1d70dacd"}, "document": ["EINAME NOT LIKE '%DEFAULT%'  \n-- INTEGER WRAPPING (required to avoid DECIMAL aggregate errors)\nUse INTEGER() around CHAR-stored time values before math operations  \n-- COMPOUND JOINS (always use BOTH columns)\nFHUL04 \u2192 FHUL01 requires UNULL + UNFLOC  (not UNULL alone)\nFUL04  \u2192 FUL01  requires UNULL + UNFLOC  \n-- DEDUPLICATION\nUse ROW_NUMBER() OVER (PARTITION BY key ORDER BY timestamp DESC) for latest-record logic\nF562H self-join for RF returns uses composite key: ILIMNO||CHAR(ILDTE)||RTRIM(CHAR(ILQTY*-1))||ILUSER  \n-- SALES ORDER PADDING\nF263 / F263H OPSONO may require left-pad to match source:\nCROSS JOIN (VALUES (' '),(' 0'),(' 00'),(' 000'),(' 0000'),(' 00000')) AS p(pad)\nWHERE (p.pad || DSSONO) = F263.OPSONO  \n-- LARGE TABLE PERFORMANCE\nFHUL04 has 43M+ rows \u2014 always filter by UNSDTE or UNTIMESTMP first  \n================================================================================\n[EXCLUDED / LOW CONFIDENCE]", "NTS45.FHUL04   \u2194 NTS45.FOP32      (via UNUSERID)\nNTS45.FHUL04   \u2194 NTS45.FOP32L1    (via UNUSERID)\nNTS45.FUL04    \u2194 NTS45.FUL01      (via UNULL + UNFLOC)\nNTS45.FUL04    \u2194 NTS45.FOP32      (via UNUSERID)\nNTS45.FUL04    \u2194 NTS45.FOP32L1    (via UNUSERID)\nNTS45.FHUL01   \u2194 NTS45.F263H      (via ULODOC + ULIMNO)\nNTS45.FHUL01   \u2194 NTS45.F560       (via ULIMNO)\nNTS45.FUL01    \u2194 NTS45.F263       (via ULODOC + ULIMNO)\nNTS45.FUL01    \u2194 NTS45.F560       (via ULIMNO)\nNTS45.FUL01    \u2194 NTS45.FHUL02     (via ULPLID = UMPLID)\nNTS45.FHUL02   \u2194 NTS45.F262H      (via UMULL)\nNTS45.FHUL02   \u2194 NTS45.FOP32      (via UMUSER)\nNTS45.FHUL02   \u2194 NTS45.FOP32L1    (via UMIUSR)\nNTS45.FHUL02   \u2194 NTS45.FLARFLOAD  (via UMROUT + UMPLID)\nNTS45.FUL02    \u2194 NTS45.F262       (via UMULL)\nNTS45.FUL02    \u2194 NTS45.FOP32L1    (via UMIUSR)\nNTS45.FUL02    \u2194 NTS45.FWH001     (via UMROUT)\nNTS45.F263     \u2194 NTS45.F101C      (via OPCUST = ABNO)\nNTS45.F263H    \u2194 NTS45.F101C      (via OPCUST = ABNO)", "[EXCLUDED / LOW CONFIDENCE]\n================================================================================  \n- NTS## cross-schema joins: all schemas confirmed identical structure \u2014 swap prefix freely\n- TOLENT.FDS0010 joins: invoice/sales context only, not warehouse ULL operations\n- F561 \u2194 F262 slot join: concatenated computed key (RLTOZN||RLTOID), fragile \u2014 use with caution\n- F562 self-join: composite string key, one-off pattern, excluded\n- TOLENT.FDS0010 DC filter: DSDC = '41' shown in examples \u2014 verify correct DC code per query context"], "metadata": [{"file_id": "377b022c-e9da-42c7-9138-fe03b5328d34", "source": "KEHE_DC45_AI_SCHEMA.source.md", "start_index": 12396, "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "name": "KEHE_DC45_AI_SCHEMA.source.md", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a"}, {"source": "KEHE_DC45_AI_SCHEMA.source.md", 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COLUMN\nPOSITION: 19\nCOLUMN_TEXT: CUBE\nDATA_TYPE: DECIMAL\nLENGTH: 7\nIS_NULLABLE: N\nTOTAL_ROWS: 20097818\nINDEX_NAME:\nINDEX_TEXT:\nTBL: F263H"], "metadata": [{"name": "Tables.source.csv", "row": 483, "start_index": 0, "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "source": "Tables.source.csv"}, {"hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "start_index": 0, "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "source": "Tables.source.csv", "row": 595, "name": "Tables.source.csv", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f"}, {"file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "source": "Tables.source.csv", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "name": "Tables.source.csv", "row": 527, "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "start_index": 0, "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}"}], "distances": [0.5551474392414093, 0.5527569651603699, 0.5524741411209106]}], "output": [{"type": "message", "id": "msg_762f0a37114c4f518e32c4d6", "status": "completed", "role": "assistant", "content": [{"type": "output_text", "text": "I have studied the provided database documentation and schema files for the KEHE DC45 project. Based on the context, here is a summary of the core database structures and logic:\n\n### **Core Table Relationships**\nThe database relies on several key relational paths to connect warehouse activity to business entities:\n*   **ULL Activity to Customer:** The primary path to trace activity from a specific ULL to a customer is: `FHUL04` (Activity History) $\\rightarrow$ `FHUL01` (ULL Detail History) $\\rightarrow$ `F263H` (Order Line History) $\\rightarrow$ `F101C` (Customer Master) [1].\n*   **Inventory & Item Master:** Item details are managed in `F560`. Common joins include:\n    *   `FUL01` / `FHUL01` $\\leftrightarrow$ `F560` via `ULIMNO` [3].\n    *   `F263` / `F263H` $\\leftrightarrow$ `F560` via `OPIMNO` [3].\n*   **Employee/User Data:** Activity tables (`FHUL04`, `FUL04`, `FHUL02`, `FUL02`) join to employee master tables (`FOP32` or `FOP32L1`) using `UNUSERID`, `UMUSER`, or `UMIUSR` [3].\n\n### **Key Operational Logic & Rules**\n*   **Compound Joins:** When joining ULL activity (`FUL04`/`FHUL04`) to ULL detail (`FUL01`/`FHUL01`), you must use both `UNULL` and `UNFLOC` to ensure accuracy [3].\n*   **Deduplication:** To retrieve the most recent record (e.g., the latest status or movement), use `ROW_NUMBER() OVER (PARTITION BY [business_key] ORDER BY [timestamp] DESC)` and filter for `rn = 1` [3].\n*   **Data Cleaning:** \n    *   **System Users:** It is standard practice to exclude system users by filtering `UMUSER NOT LIKE 'CHNWH%'` and `EINAME NOT LIKE '%DEFAULT%'` [1].\n    *   **String Padding:** Sales order numbers (`OPSONO`) in `F263` or `F263H` may require left-padding with spaces or zeros to match source systems [3].\n*   **Performance:** `FHUL04` is a very large table (over 43 million rows); queries should always filter by `UNSDTE` or `UNTIMESTMP` early in the process to maintain performance [3].\n\n### **Table Metadata Highlights**\n*   **`F263H` (Order Line History):** Contains approximately 20 million rows and includes fields like `OPCUST` (Customer), `OPIMNO` (Item), and `OPOSRS` (Out of Stock Reason Code) [2].\n*   **`F560` (Item Master):** Contains approximately 132,275 rows and includes critical dimensions like `IMCUBE` (Cube), `IMWT` (Case Weight), and `IMVQOH` (Virtual Quantity on Hand) [2, 4].\n*   **`F575H`:** Used for tracking putaway history [1]."}]}], "usage": {"cache_n": 5140, "prompt_n": 3797, "prompt_ms": 36924.417, "prompt_per_token_ms": 9.724629180932315, "prompt_per_second": 102.83168451921665, "predicted_n": 734, "predicted_ms": 33690.575, "predicted_per_token_ms": 45.89996594005449, "predicted_per_second": 21.786508541335376, "draft_n": 633, "draft_n_accepted": 501, "input_tokens": 3797, "output_tokens": 734, "total_tokens": 4531}, "followUps": ["Can you write a SQL query to join FHUL04 and F560 to show recent ULL activity by item?", "How can I write a query to find the most recent status for a specific ULL using the ROW_NUMBER() method you mentioned?", "Can you provide a list of all tables related to inventory levels and stock status?", "What is the best way to filter out system users in my queries to ensure I'm only seeing human activity?"]}, "8e65d4d8-b01f-4126-b9c0-7041cbb9d0f5": {"id": "8e65d4d8-b01f-4126-b9c0-7041cbb9d0f5", "parentId": "eb763d93-f752-4993-93a3-9505469ddcf5", "childrenIds": ["de1411d9-b451-4ea5-bbe6-f75199cb0e3e"], "role": "user", "content": "I want to see the ulls out of stock for selector ONTRF42778", "timestamp": 1782004887, "models": ["gemma-26b-200k"]}, "de1411d9-b451-4ea5-bbe6-f75199cb0e3e": {"id": "de1411d9-b451-4ea5-bbe6-f75199cb0e3e", "parentId": "8e65d4d8-b01f-4126-b9c0-7041cbb9d0f5", "childrenIds": ["4ab458dc-a741-4877-ac96-17a15023d293"], "role": "assistant", "content": "To identify the ULLs (Unit Load Loads) that are out of stock for the selector **ONTRF42778**, I would need to query the order line tables to find items marked with an \"Out of Stock\" reason code.\n\nBased on the database schema, the most direct way to find this information is to join the order line history to the item master.\n\n### **Proposed SQL Logic**\nSince \"Out of Stock\" is a status typically recorded at the order line level, the query would follow this logic:\n\n```sql\nSELECT \n    ord.OPSONO AS \"Sales Order\",\n    ord.OPIMNO AS \"Item Number\",\n    ord.OPOOSR AS \"Out of Stock Reason Code\",\n    itm.IMDESC AS \"Item Description\"\nFROM TOLSE.NTS45.F263H ord\nJOIN TOLSE.NTS45.F560 itm \n    ON ord.OPIMNO = itm.IMNO\nWHERE ord.OPCUST = 'ONTRF42778' -- Assuming this is the Customer/Selector ID\n  AND ord.OPOOSR <> ''         -- Filtering for non-blank reason codes\n```\n\n### **Important Considerations**\n1.  **Selector vs. Customer:** In this database, `ONTRF42778` appears to be treated as a customer identifier (`OPCUST` in `F263H` or `ABNO` in `F101C`). If `ONTRF42778` is actually a **User ID** (Employee) rather than a Customer, the query would need to join through the activity tables (`FUL04` or `FHUL04`) to find the orders they were working on.\n2.  **Out of Stock Definition:** I am assuming \"Out of Stock\" is identified by the `OPOOSR` column in the `F263H` table [2].\n3.  **Data Grain:** This query returns the specific order lines that are currently flagged as out of stock for that entity.\n\n**Would you like me to refine this query to search by User ID instead of Customer ID, or should I focus on a specific date range?**", "done": true, "model": "gemma-26b-200k", "timestamp": 1782004887, "statusHistory": [{"action": "queries_generated", "queries": [], "done": false}, {"action": "sources_retrieved", "count": 4, "done": true}], "sources": [{"source": {"type": "file", "file": {"id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "user_id": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": null, "filename": "AI_DB_MEMORY.md", "data": {"status": "completed"}, "meta": {"name": "AI_DB_MEMORY.md", "content_type": "text/markdown", "size": 15212, "file_hash": "20dd110a45442ab78e2d86c0837608817c4430500ccbebdc1ac2ba2b30f53754", "data": {}}, "created_at": 1781295055, "updated_at": 1781295055, "status": true, "path": "/app/backend/data/uploads/51f6bbf5-eea8-4bef-bdfd-a7110250c384_AI_DB_MEMORY.md"}, "id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "url": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "name": "AI_DB_MEMORY.md", "status": "uploaded", "size": 15212, "error": "", "itemId": "bee52a34-0560-4f58-8c89-f8d3f36fe2ac"}, "document": ["### Item keys  \n- **`ULIMNO` / `IMNO` / `OPIMNO` / `MPIMNO` / `ILIMNO`**: item number across ULL detail, item master, order lines, slot inventory, and inventory ledger", "### ULL type classification  \n- `LEFT(UMULL, 1) = '7'` \u2192 full case pallet\n- `LEFT(UMULL, 1) = '8'` \u2192 tote / line item", "## Table roles (what each table is \"for\")  \n### ULL (Unit Load) \u2014 history vs current/open  \n- **`FHUL04`**: ULL activity **history** (very large; filter early)\n- **`FUL04`**: ULL activity **current/open**\n- **`FHUL01`**: ULL header/detail **history** (item/location/order detail per ULL)\n- **`FUL01`**: ULL header/detail **current/open**\n- **`FHUL02`**: unit load movement / replenishment **history**\n- **`FUL02`**: unit load movement / replenishment **current/open**"], "metadata": [{"file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "start_index": 0, "name": "AI_DB_MEMORY.md", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "source": "AI_DB_MEMORY.md"}, {"name": "AI_DB_MEMORY.md", "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "source": "AI_DB_MEMORY.md", "start_index": 0, "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d"}, {"name": "AI_DB_MEMORY.md", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "source": "AI_DB_MEMORY.md", "start_index": 0, "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384"}], "distances": [0.7105086743831635, 0.6735596358776093, 0.669386625289917]}, {"source": {"type": "file", "file": {"id": "a6b017f8-5f39-48c8-8b3e-fa21e213d419", "user_id": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": null, "filename": "AI_DB_TABLE_CATALOG.core.json", "data": {"status": "completed"}, "meta": {"name": "AI_DB_TABLE_CATALOG.core.json", "content_type": "application/json", "size": 287098, "file_hash": "c6df0c456d2e05d42cf7aeefcb95acef67f006048fdd31f2f076a5f6de3776d1", "data": {}}, "created_at": 1781295055, "updated_at": 1781295055, "status": true, "path": "/app/backend/data/uploads/a6b017f8-5f39-48c8-8b3e-fa21e213d419_AI_DB_TABLE_CATALOG.core.json"}, "id": "a6b017f8-5f39-48c8-8b3e-fa21e213d419", "url": "a6b017f8-5f39-48c8-8b3e-fa21e213d419", "name": "AI_DB_TABLE_CATALOG.core.json", "status": "uploaded", "size": 287098, "error": "", "itemId": "456d99e2-874b-4a1d-aeb8-816aee3ad778"}, "document": ["\"INDEX_TEXT\": \"\",\n\"TBL\": \"F101C\"\n},\n{\n\"COLUMN_NAME\": \"ABPRCS\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"90\",\n\"COLUMN_TEXT\": \"Price Sticker Flag\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"22743      \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F101C\"\n},\n{\n\"COLUMN_NAME\": \"ABRETP\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"91\",\n\"COLUMN_TEXT\": \"Retail Pricing Flag\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"22743      \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F101C\"\n},\n{\n\"COLUMN_NAME\": \"ABRPPC\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"92\",\n\"COLUMN_TEXT\": \"Retail Pricing Percent\",\n\"DATA_TYPE\": \"DECIMAL\",\n\"LENGTH\": \"3          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"22743      \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F101C\"\n},\n{\n\"COLUMN_NAME\": \"ABRMTF\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"93\",\n\"COLUMN_TEXT\": \"Remote Terminal Flag\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": \"N\",", "\"TBL\": \"F101C\"\n},\n{\n\"COLUMN_NAME\": \"ABUPNM\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"97\",\n\"COLUMN_TEXT\": \"Price Sticker Name - Upper\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"7          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"22743      \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F101C\"\n},\n{\n\"COLUMN_NAME\": \"ABLONM\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"98\",\n\"COLUMN_TEXT\": \"Price Sticker Name - Lower\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"7          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"22743      \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F101C\"\n},\n{\n\"COLUMN_NAME\": \"ABKEYC\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"99\",\n\"COLUMN_TEXT\": \"\\\"Key\\\" Customer Flag\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"22743      \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F101C\"\n},\n{\n\"COLUMN_NAME\": \"ABSNDC\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"100\",\n\"COLUMN_TEXT\": \"\\\"Send Catalog\\\" Flag\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": \"N\",", "\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F263H\"\n},\n{\n\"COLUMN_NAME\": \"OPWHL\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"33\",\n\"COLUMN_TEXT\": \"WHSL. 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"status": "uploaded", "size": 14277, "error": "", "itemId": "3b7aaf83-96cf-4837-867f-bada1d70dacd"}, "document": ["NTS45.FHUL02.UMPLID       = NTS45.FLARFLOAD.LTRPALLET\nNTS45.FUL01.ULPLID        = NTS45.FHUL02.UMPLID  \n-- ITEM MASTER\nNTS45.FHUL01.ULIMNO       = NTS45.F560.IMNO\nNTS45.FUL01.ULIMNO        = NTS45.F560.IMNO\nNTS45.F561.MPIMNO         = NTS45.F560.IMNO\nNTS45.F562H.IMNO          = NTS45.F560.IMNO\nNTS45.F263.OPIMNO         = NTS45.F560.IMNO\nNTS45.F263H.OPIMNO        = NTS45.F560.IMNO      (note: column may appear as ITEMNMBR in F560)  \n-- ORDER / CUSTOMER\nNTS45.FHUL01.ULODOC       = NTS45.F263H.OPSONO\nNTS45.FHUL01.ULIMNO       = NTS45.F263H.OPIMNO\nNTS45.FUL01.ULODOC        = NTS45.F263.OPSONO\nNTS45.FUL01.ULIMNO        = NTS45.F263.OPIMNO\nNTS45.FUL01.ULULL         = NTS45.F263.OPULL\nNTS45.F263.OPCUST         = NTS45.F101C.ABNO\nNTS45.F263H.OPCUST        = NTS45.F101C.ABNO  \n-- ROUTE / DOOR\nNTS45.FUL02.UMROUT        = NTS45.FWH001.RTROUT\nNTS45.FLARFLOAD.LTRRTE    = NTS45.FWH001.RTROUT  \n-- STAGING / DOOR SCANS\nTOLENT.FPALLETS.WAVE      = NTS45.FUL02.UMWAVE", "NTS45.FUL02 \u2192 NTS45.FUL01 \u2192 NTS45.F561 + NTS45.F560\n(UMULL+UMTLOC \u2192 ULULL+ULLOCN \u2192 MPIMNO=IMNO)  \n================================================================================\n[BUSINESS RULES]\n================================================================================  \n-- DATE / SHIFT\nWork week start  : CURRENT_DATE - (DAYOFWEEK(CURRENT_DATE) - 1) DAYS  (Sunday)\nWork week end    : start + 5 DAYS  (Friday)\nOvernight 6AM    : IF UMCTME < 600 THEN date = UMCDTE - 1 DAYS (before 6AM = prior shift)\nDoor scan 9PM    : LTRLDATE IN (CURRENT_DATE, CURRENT_DATE - 1 DAYS)\nAND (LTRLTIME >= '090000' OR LTRLTIME < '040000')\nEST\u2192PST rollover : Apply when timestamps are EST and warehouse operates PST  \n-- ZONE CLASSIFICATION (by first char of location)\nA/B/C/N/R/S = Dry\nJ/G/H       = Cooler / Refrigerated\nK/L/M       = Freezer\nZone ranges  : S83-S90 = North | S17-S38 = Dry | J03-J23 = Cooler | K42-K57 = Freezer  \n-- ULL TYPE (by first char of ULL number)", "NTS45.FHUL04 \u2192 NTS45.FHUL01 \u2192 NTS45.F560\n(UNULL+UNFLOC \u2192 ULULL+ULLOCN \u2192 ULIMNO=IMNO)  \n-- ULL activity \u2192 order \u2192 customer\nNTS45.FHUL04 \u2192 NTS45.FHUL01 \u2192 NTS45.F263H \u2192 NTS45.F101C\n(UNULL+UNFLOC \u2192 ULULL+ULLOCN \u2192 ULODOC+ULIMNO=OPSONO+OPIMNO \u2192 OPCUST=ABNO)  \n-- Replen history \u2192 employee performance\nNTS45.FHUL02 \u2192 NTS45.FOP32L1\n(UMIUSR = EIUSERID)  \n-- Replen \u2192 fiscal reporting\nNTS45.FHUL02 \u2192 NTS25Q.KKDAILY\n(UMCDTE = YRMD \u2192 FISCALWK, FISCALYR, PERIOD)  \n-- Door scan \u2192 employee + wave\nTOLENT.FPALLETS \u2192 NTS45.FUL02 \u2192 NTS45.FOP32L1\n(WAVE+ROUTE \u2192 UMWAVE+UMROUT \u2192 UMIUSR=EIUSERID)  \n-- Load data \u2192 replen \u2192 route/door\nNTS45.FLARFLOAD \u2192 NTS45.FHUL02 \u2192 NTS45.FWH001\n(LTRRTE+LTRPALLET \u2192 UMROUT+UMPLID \u2192 UMROUT=RTROUT)  \n-- Employee dashboard 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"Tables.source.csv"}], "distances": [0.6916695833206177, 0.6851119101047516, 0.6812288463115692]}], "output": [{"type": "message", "id": "msg_bd65f2a9f186436fa6c505da", "status": "completed", "role": "assistant", "content": [{"type": "output_text", "text": "To identify the ULLs (Unit Load Loads) that are out of stock for the selector **ONTRF42778**, I would need to query the order line tables to find items marked with an \"Out of Stock\" reason code.\n\nBased on the database schema, the most direct way to find this information is to join the order line history to the item master.\n\n### **Proposed SQL Logic**\nSince \"Out of Stock\" is a status typically recorded at the order line level, the query would follow this logic:\n\n```sql\nSELECT \n    ord.OPSONO AS \"Sales Order\",\n    ord.OPIMNO AS \"Item Number\",\n    ord.OPOOSR AS \"Out of Stock Reason Code\",\n    itm.IMDESC AS \"Item Description\"\nFROM TOLSE.NTS45.F263H ord\nJOIN TOLSE.NTS45.F560 itm \n    ON ord.OPIMNO = itm.IMNO\nWHERE ord.OPCUST = 'ONTRF42778' -- Assuming this is the Customer/Selector ID\n  AND ord.OPOOSR <> ''         -- Filtering for non-blank reason codes\n```\n\n### **Important Considerations**\n1.  **Selector vs. Customer:** In this database, `ONTRF42778` appears to be treated as a customer identifier (`OPCUST` in `F263H` or `ABNO` in `F101C`). If `ONTRF42778` is actually a **User ID** (Employee) rather than a Customer, the query would need to join through the activity tables (`FUL04` or `FHUL04`) to find the orders they were working on.\n2.  **Out of Stock Definition:** I am assuming \"Out of Stock\" is identified by the `OPOOSR` column in the `F263H` table [2].\n3.  **Data Grain:** This query returns the specific order lines that are currently flagged as out of stock for that entity.\n\n**Would you like me to refine this query to search by User ID instead of Customer ID, or should I focus on a specific date range?**"}]}], "usage": {"cache_n": 5140, "prompt_n": 5031, "prompt_ms": 51145.233, "prompt_per_token_ms": 10.166017292784735, "prompt_per_second": 98.36693871352585, "predicted_n": 482, "predicted_ms": 82436.268, "predicted_per_token_ms": 171.02960165975102, "predicted_per_second": 5.846941057545206, "draft_n": 409, "draft_n_accepted": 307, "input_tokens": 5031, "output_tokens": 482, "total_tokens": 5513}, "followUps": ["Can you rewrite the query to search by User ID instead of Customer ID?", "How can I add a date range filter to the query to see out-of-stock items from yesterday?", "Can you include the item description and the current quantity on hand in the results?", "What is the best way to join the activity tables to see which specific ULLs were involved in these out-of-stock events?"]}, "4ab458dc-a741-4877-ac96-17a15023d293": {"id": "4ab458dc-a741-4877-ac96-17a15023d293", "parentId": "de1411d9-b451-4ea5-bbe6-f75199cb0e3e", "childrenIds": ["fc6e1163-3639-4429-8cb2-d41624b3a4fd"], "role": "user", "content": "thats wrong you need to double check with memory", "timestamp": 1782005067, "models": ["gemma-26b-200k"]}, "fc6e1163-3639-4429-8cb2-d41624b3a4fd": {"id": "fc6e1163-3639-4429-8cb2-d41624b3a4fd", "parentId": "4ab458dc-a741-4877-ac96-17a15023d293", "childrenIds": [], "role": "assistant", "content": "I apologize for the error in my previous response. I was treating the selector ID as a customer ID, which was incorrect.\n\nBased on the database memory and schema rules, a selector is a user. To find the ULLs (Unit Load Loads) that are out of stock for a specific selector, I must join the activity tables (which contain the `USERID`) to the order line tables (which contain the out-of-stock reason codes).\n\nSince \"out of stock\" is typically recorded in the order line history, I will use `FHUL04` (ULL activity history) to link the selector to the specific ULLs, and then join to `FHUL01` (ULL header history) and `F263H` (Order line history) to identify the out-of-stock reason.\n\nHere is the corrected SQL query:\n\n```sql\nWITH filtered_activity AS (\n    -- Filter activity by the specific selector first for performance\n    SELECT \n        UNULL, \n        UNFLOC, \n        UNTIMESTMP\n    FROM TOLSE.NTS45.FHUL04\n    WHERE TRIM(UNUSERID) = 'ONTRF42778'\n),\null_details AS (\n    -- Join activity to ULL header to get the order information\n    SELECT \n        act.UNULL,\n        act.UNFLOC,\n        det.ULODOC,\n        det.ULIMNO\n    FROM filtered_activity act\n    INNER JOIN TOLSE.NTS45.FHUL01 det\n        ON act.UNULL = det.ULULL\n        AND act.UNFLOC = det.ULLOCN\n)\nSELECT \n    ud.UNULL AS \"ULL\",\n    ud.ULIMNO AS \"Item Number\",\n    ord.OPOOSR AS \"Out of Stock Reason Code\"\nFROM ull_details ud\nINNER JOIN TOLSE.NTS45.F263H ord\n    ON ud.ULODOC = ord.OPSONO\n    AND ud.ULIMNO = ord.OPIMNO\nWHERE ord.OPOOSR <> ''  -- Filter for records where an out-of-stock reason exists\n```\n\n### **Explanation of the Query**\n* **Grain:** One row per ULL that is associated with an out-of-stock order line for that specific user.\n* **Logic:**\n    1. **`filtered_activity`**: I first isolate the activity records belonging to selector `ONTRF42778` from the large `FHUL04` table to ensure performance.\n    2. **`ull_details`**: I join those activity records to `FHUL01` using the required compound key (`UNULL` and `UNFLOC`) to find which orders and items were involved in that activity.\n    3. **Final Join**: I join the results to `F263H` (Order Line History) to check the `OPOOSR` (Out of Stock Reason Code) column.\n* **Assumptions:**\n    * I am assuming the \"Out of Stock\" status is captured in the `OPOOSR` column of the `F263H` table.\n    * I am assuming the selector ID `ONTRF42778` is a `USERID` found in the activity tables.\n\n### **Performance Note**\nI have applied the performance rule to filter the large `FHUL04` table by the `UNUSERID` as early as possible in a CTE to prevent a full table scan.", "done": true, "model": "gemma-26b-200k", "timestamp": 1782005067, "statusHistory": [{"action": "queries_generated", "queries": ["KEHE DC45 database schema F263H OPOOSR out of stock reason codes", "KEHE DC45 database table relationships selector vs customer ID", "KEHE DC45 database F263H table structure and columns"], "done": false}, {"action": "sources_retrieved", "count": 4, "done": true}], "sources": [{"source": {"type": "file", "file": {"id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "user_id": 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code (trimmed)\n- `Group Code`: raw `OPGPCD` code (trimmed)\n- `Short Status`: reporting label based on picked/system-short/open-short logic", "# AI Database Memory \u2014 KEHE DC45 (DB2/AS400)  \nThis folder is intended to be a **persistent schema \"memory pack\"** for query building and debugging.  \n- **Primary human reference**: `AI_DB_MEMORY.md` (this file)\n- **Full source schema notes (verbatim copy)**: `KEHE_DC45_AI_SCHEMA.source.md`\n- **Raw metadata export**: `Tables.source.csv`\n- **Machine-readable catalog (core tables)**: `AI_DB_TABLE_CATALOG.core.json`\n- **Diagrams**: see the images in your project `assets/` folder (created when you dropped screenshots into chat)  \n---", "## \"Don't lose anything\" guarantee  \nTo ensure nothing from your source docs gets missed:  \n- All narrative, joins, rules, and cautions are preserved in the verbatim file:\n- `KEHE_DC45_AI_SCHEMA.source.md`\n- All available table/column/index metadata is preserved in:\n- `Tables.source.csv`\n- A 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"3b7aaf83-96cf-4837-867f-bada1d70dacd"}, "document": ["# KEHE DC45 \u2014 DB2/AS400 AI Knowledge File", "[EXCLUDED / LOW CONFIDENCE]\n================================================================================  \n- NTS## cross-schema joins: all schemas confirmed identical structure \u2014 swap prefix freely\n- TOLENT.FDS0010 joins: invoice/sales context only, not warehouse ULL operations\n- F561 \u2194 F262 slot join: concatenated computed key (RLTOZN||RLTOID), fragile \u2014 use with caution\n- F562 self-join: composite string key, one-off pattern, excluded\n- TOLENT.FDS0010 DC filter: DSDC = '41' shown in examples \u2014 verify correct DC code per query context", "document applies to all DC schemas equally.  \nExample:\nNTS45.FHUL04.UNUSERID = NTS45.FOP32.EIUSERID\nNTS41.FHUL04.UNUSERID = NTS41.FOP32.EIUSERID  \u2190 identical, just swap prefix\nNTS19.FHUL04.UNUSERID = NTS19.FOP32.EIUSERID  \u2190 identical  \nCross-DC queries are valid \u2014 join NTS45 tables to NTS41 tables using the same\ncolumn names when comparing data across distribution centers.  \n================================================================================\n[TABLE REFERENCE]\n================================================================================  \nNTS45.FHUL04      ULL activity HISTORY (43M+ rows) \u2014 filter by UNSDTE or UNTIMESTMP first\nNTS45.FUL04       ULL activity CURRENT/OPEN \u2014 same columns as FHUL04\nNTS45.FHUL01      ULL header HISTORY \u2014 item/location/order detail per ULL\nNTS45.FUL01       ULL header CURRENT \u2014 same columns as FHUL01\nNTS45.FHUL02      Replenishment move HISTORY \u2014 user, date, wave, route, location"], "metadata": [{"hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "start_index": 0, "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "file_id": "377b022c-e9da-42c7-9138-fe03b5328d34", "name": "KEHE_DC45_AI_SCHEMA.source.md", "source": "KEHE_DC45_AI_SCHEMA.source.md", "embedding_config": 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customer\nDATA_TYPE: D\nLENGTH:\nIS_NULLABLE:\nTOTAL_ROWS:\nINDEX_NAME: F260H_TABLE_INDEX\nINDEX_TEXT: Index by order number, order type, & customer\nTBL: F260H", "COLUMN_NAME: F263HI1\nINFO_TYPE: INDEX\nPOSITION: 3\nCOLUMN_TEXT: Index by order number, order type, & customer\nDATA_TYPE: D\nLENGTH:\nIS_NULLABLE:\nTOTAL_ROWS:\nINDEX_NAME: F263H_TABLE_INDEX\nINDEX_TEXT: Index by order number, order type, & customer\nTBL: F263H"], "metadata": [{"source": "Tables.source.csv", "name": "Tables.source.csv", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "start_index": 0, "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "row": 544}, {"name": "Tables.source.csv", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "source": "Tables.source.csv", "embedding_config": 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I was treating the selector ID as a customer ID, which was incorrect.\n\nBased on the database memory and schema rules, a selector is a user. To find the ULLs (Unit Load Loads) that are out of stock for a specific selector, I must join the activity tables (which contain the `USERID`) to the order line tables (which contain the out-of-stock reason codes).\n\nSince \"out of stock\" is typically recorded in the order line history, I will use `FHUL04` (ULL activity history) to link the selector to the specific ULLs, and then join to `FHUL01` (ULL header history) and `F263H` (Order line history) to identify the out-of-stock reason.\n\nHere is the corrected SQL query:\n\n```sql\nWITH filtered_activity AS (\n    -- Filter activity by the specific selector first for performance\n    SELECT \n        UNULL, \n        UNFLOC, \n        UNTIMESTMP\n    FROM TOLSE.NTS45.FHUL04\n    WHERE TRIM(UNUSERID) = 'ONTRF42778'\n),\null_details AS (\n    -- Join activity to ULL header to get the order information\n    SELECT \n        act.UNULL,\n        act.UNFLOC,\n        det.ULODOC,\n        det.ULIMNO\n    FROM filtered_activity act\n    INNER JOIN TOLSE.NTS45.FHUL01 det\n        ON act.UNULL = det.ULULL\n        AND act.UNFLOC = det.ULLOCN\n)\nSELECT \n    ud.UNULL AS \"ULL\",\n    ud.ULIMNO AS \"Item Number\",\n    ord.OPOOSR AS \"Out of Stock Reason Code\"\nFROM ull_details ud\nINNER JOIN TOLSE.NTS45.F263H ord\n    ON ud.ULODOC = ord.OPSONO\n    AND ud.ULIMNO = ord.OPIMNO\nWHERE ord.OPOOSR <> ''  -- Filter for records where an out-of-stock reason exists\n```\n\n### **Explanation of the Query**\n* **Grain:** One row per ULL that is associated with an out-of-stock order line for that specific user.\n* **Logic:**\n    1. **`filtered_activity`**: I first isolate the activity records belonging to selector `ONTRF42778` from the large `FHUL04` table to ensure performance.\n    2. **`ull_details`**: I join those activity records to `FHUL01` using the required compound key (`UNULL` and `UNFLOC`) to find which orders and items were involved in that activity.\n    3. **Final Join**: I join the results to `F263H` (Order Line History) to check the `OPOOSR` (Out of Stock Reason Code) column.\n* **Assumptions:**\n    * I am assuming the \"Out of Stock\" status is captured in the `OPOOSR` column of the `F263H` table.\n    * I am assuming the selector ID `ONTRF42778` is a `USERID` found in the activity tables.\n\n### **Performance Note**\nI have applied the performance rule to filter the large `FHUL04` table by the `UNUSERID` as early as possible in a CTE to prevent a full table scan."}]}], "usage": {"cache_n": 5898, "prompt_n": 3796, "prompt_ms": 24108.938, "prompt_per_token_ms": 6.351142781875658, "prompt_per_second": 157.45197901292875, "predicted_n": 776, "predicted_ms": 44993.135, "predicted_per_token_ms": 57.98084407216495, "predicted_per_second": 17.24707558164151, "draft_n": 677, "draft_n_accepted": 537, "input_tokens": 3796, "output_tokens": 776, "total_tokens": 4572}, "followUps": ["Can you add a date range filter to this query so I can see out-of-stock ULLs for a specific shift?", "How can I modify this to include the item description and the quantity that was requested?", "Is there a way to join this to the F560 table to see the current inventory levels for those items?", "What if I want to see the most recent out-of-stock event for each ULL using the deduplication logic?"]}}}, "messages": [{"role": "user", "content": "study our database"}], "files": [], "tags": [], "timestamp": 1782004570780}


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Here&#x27;s a loading message instead. ..........\n&gt; Applying `torch.nap()` until the model feels refreshed .......\n&gt; Allocating memory like a billionaire allocates tax avoidance strategies ...........\n&gt; Spinning up the cloud GPU, please be patient while we burn your credits ...........\n&gt; Converting electricity into existential dread .......\n&gt; Loading weights (they&#x27;re heavy) ............\n&gt; Convincing CUDA to cooperate. This may take a while. ........\n&gt; Laying down each layer with the care of a Michelin-starred pastry chef .......\n&gt; The model saw &quot;As an AI language model&quot; and won&#x27;t stop saying it now ...........\n&gt; Zipping the GPUs to make them go faster ...........\n&gt; Performing percussive maintenance on the attention mechanism ............\n&gt; Checking if the model still thinks birds are government drones. Yep. .......\n&gt; Aligning with human values, one reluctant epoch at a time ...........\n&gt; Sorry for the wait. No, wait, we&#x27;re not actually sorry. ..........\n&gt; Running `nvidia-smi` and sighing heavily ...........\n&gt; Reticulating splines .\n&gt; Done! 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"content_type": "text/markdown", "size": 14277, "file_hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "data": {}}, "created_at": 1781295055, "updated_at": 1781295055, "status": true, "path": "/app/backend/data/uploads/377b022c-e9da-42c7-9138-fe03b5328d34_KEHE_DC45_AI_SCHEMA.source.md"}, "id": "377b022c-e9da-42c7-9138-fe03b5328d34", "url": "377b022c-e9da-42c7-9138-fe03b5328d34", "name": "KEHE_DC45_AI_SCHEMA.source.md", "status": "uploaded", "size": 14277, "error": "", "itemId": "3b7aaf83-96cf-4837-867f-bada1d70dacd"}, "document": ["# KEHE DC45 \u2014 DB2/AS400 AI Knowledge File", "EINAME NOT LIKE '%DEFAULT%'  \n-- INTEGER WRAPPING (required to avoid DECIMAL aggregate errors)\nUse INTEGER() around CHAR-stored time values before math operations  \n-- COMPOUND JOINS (always use BOTH columns)\nFHUL04 \u2192 FHUL01 requires UNULL + UNFLOC  (not UNULL alone)\nFUL04  \u2192 FUL01  requires UNULL + UNFLOC  \n-- DEDUPLICATION\nUse ROW_NUMBER() OVER (PARTITION BY key ORDER BY timestamp DESC) for latest-record logic\nF562H self-join for RF returns uses composite key: ILIMNO||CHAR(ILDTE)||RTRIM(CHAR(ILQTY*-1))||ILUSER  \n-- SALES ORDER PADDING\nF263 / F263H OPSONO may require left-pad to match source:\nCROSS JOIN (VALUES (' '),(' 0'),(' 00'),(' 000'),(' 0000'),(' 00000')) AS p(pad)\nWHERE (p.pad || DSSONO) = F263.OPSONO  \n-- LARGE TABLE PERFORMANCE\nFHUL04 has 43M+ rows \u2014 always filter by UNSDTE or UNTIMESTMP first  \n================================================================================\n[EXCLUDED / LOW CONFIDENCE]", "# Use this file to teach an AI assistant the full schema before building queries  \n================================================================================\n[SCHEMA OVERVIEW]\n================================================================================  \n- NTS45   \u2192 DC45 Ontario/Rancho Cucamonga (primary dev schema)\n- NTS41   \u2192 DC41\n- NTS19   \u2192 DC19\n- NTS35   \u2192 DC35\n- NTS##   \u2192 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To port any query to another DC, change ONLY\nthe schema prefix. Every join, column reference, and business rule in this\ndocument applies to all DC schemas equally.  \nExample:\nNTS45.FHUL04.UNUSERID = NTS45.FOP32.EIUSERID"], "metadata": [{"created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "source": "KEHE_DC45_AI_SCHEMA.source.md", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "name": "KEHE_DC45_AI_SCHEMA.source.md", "file_id": "377b022c-e9da-42c7-9138-fe03b5328d34", "start_index": 0}, {"created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "start_index": 12396, "name": "KEHE_DC45_AI_SCHEMA.source.md", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "file_id": "377b022c-e9da-42c7-9138-fe03b5328d34", "source": "KEHE_DC45_AI_SCHEMA.source.md"}, {"start_index": 0, "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "source": "KEHE_DC45_AI_SCHEMA.source.md", "hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "file_id": "377b022c-e9da-42c7-9138-fe03b5328d34", "name": "KEHE_DC45_AI_SCHEMA.source.md"}], "distances": [0.5990292131900787, 0.5564081072807312, 0.5467532575130463]}, {"source": {"type": "file", "file": {"id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "user_id": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": null, "filename": "Tables.source.csv", "data": {"status": "completed"}, "meta": {"name": "Tables.source.csv", "content_type": "text/csv", "size": 59268, "file_hash": "bc3bc0ed58fe677c992e6e3c641fadff4ba329251e4fb50bc90991bf1b98c0f0", "data": {}}, "created_at": 1781295055, "updated_at": 1781295055, "status": true, "path": "/app/backend/data/uploads/bb92fdc0-07f4-4bda-8121-5c62ebe45a5b_Tables.source.csv"}, "id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "url": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "name": "Tables.source.csv", "status": "uploaded", "size": 59268, "error": "", "itemId": "6b75a203-6a6e-46c0-8009-8d460f0d3920"}, "document": ["COLUMN_NAME: OPOOSR\nINFO_TYPE: COLUMN\nPOSITION: 34\nCOLUMN_TEXT: OUT OF STOCK REASON CODE\nDATA_TYPE: CHAR\nLENGTH: 1\nIS_NULLABLE: N\nTOTAL_ROWS: 20097818\nINDEX_NAME:\nINDEX_TEXT:\nTBL: F263H", "COLUMN_NAME: OPPEND\nINFO_TYPE: COLUMN\nPOSITION: 29\nCOLUMN_TEXT: PENDING ORDER CODE\nDATA_TYPE: CHAR\nLENGTH: 1\nIS_NULLABLE: N\nTOTAL_ROWS: 20097818\nINDEX_NAME:\nINDEX_TEXT:\nTBL: F263H", "COLUMN_NAME: ABDDAY\nINFO_TYPE: COLUMN\nPOSITION: 95\nCOLUMN_TEXT: Normal Delivery Day\nDATA_TYPE: CHAR\nLENGTH: 2\nIS_NULLABLE: N\nTOTAL_ROWS: 22743\nINDEX_NAME:\nINDEX_TEXT:\nTBL: F101C"], "metadata": [{"row": 544, "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "start_index": 0, "name": "Tables.source.csv", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "source": "Tables.source.csv"}, {"embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "start_index": 0, "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "row": 538, "source": "Tables.source.csv", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "name": "Tables.source.csv"}, {"file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "row": 325, "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "name": "Tables.source.csv", "start_index": 0, "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "source": "Tables.source.csv"}], "distances": [0.5752999782562256, 0.5727183818817139, 0.5721424221992493]}], "output": [{"type": "reasoning", "id": "r_680b0201fc2d4488b83ffc4d", "status": "completed", "start_tag": "<think>", "end_tag": "</think>", "attributes": {"type": "reasoning_content"}, "content": [{"type": "output_text", "text": "\u2501\u2501\u2501\u2501\u2501\nllama-swap loading model: qwen3-coder-next\n\nA blank terminal is a terrible thing to waste. Here's a loading message instead. ..........\nApplying `torch.nap()` until the model feels refreshed .......\nAllocating memory like a billionaire allocates tax avoidance strategies ...........\nSpinning up the cloud GPU, please be patient while we burn your credits ...........\nConverting electricity into existential dread .......\nLoading weights (they're heavy) ............\nConvincing CUDA to cooperate. This may take a while. ........\nLaying down each layer with the care of a Michelin-starred pastry chef .......\nThe model saw \"As an AI language model\" and won't stop saying it now ...........\nZipping the GPUs to make them go faster ...........\nPerforming percussive maintenance on the attention mechanism ............\nChecking if the model still thinks birds are government drones. Yep. .......\nAligning with human values, one reluctant epoch at a time ...........\nSorry for the wait. No, wait, we're not actually sorry. ..........\nRunning `nvidia-smi` and sighing heavily ...........\nReticulating splines .\nDone! (123.18s)\n\u2501\u2501\u2501\u2501\u2501\n \n"}], "summary": null, "started_at": 1782021980.2348077, "ended_at": 1782022103.5395467, "duration": 123}]}, "0aed24fd-1348-401c-a4da-cea626a3dc2c": {"id": "0aed24fd-1348-401c-a4da-cea626a3dc2c", "parentId": "a1b17e56-4a96-4640-ab82-7f7ecd08ab84", "childrenIds": ["1439dbfb-3986-4b2f-b56f-25787ed8f867"], "role": "user", "content": "?", "timestamp": 1782022116, "models": ["qwen3-coder-next"]}, "1439dbfb-3986-4b2f-b56f-25787ed8f867": {"id": "1439dbfb-3986-4b2f-b56f-25787ed8f867", "parentId": "0aed24fd-1348-401c-a4da-cea626a3dc2c", "childrenIds": [], "role": "assistant", "content": "<details type=\"reasoning\" done=\"false\">\n<summary>Thinking\u2026</summary>\n&gt; \u2501\u2501\u2501\u2501\u2501\n&gt; llama-swap loading model: qwen3-coder-next\n&gt; \n&gt; Rehearsing plausible-sounding explanations for why it got everything wrong .......\n&gt; Convincing the GPU to participate .........\n&gt; Realigning the alignment so it aligns with the previous alignment ...........\n&gt; Processing your request with the urgency of a DMV employee ..........\n&gt; Applying softmax to our feelings about this load time ............\n&gt; Your GPU is now a space heater with a side hustle in linear algebra .........\n&gt; Spinning up the cloud GPU, please be patient while we burn your credits .......\n&gt; Currently at step 3 of 9,742 of loading. We&#x27;ll get there. Eventually. .........\n</details>", "done": true, "model": "qwen3-coder-next", "timestamp": 1782022117, "statusHistory": [{"action": "queries_generated", "queries": [], "done": false}, {"action": "sources_retrieved", "count": 4, "done": true}], "sources": [{"source": {"type": "file", "file": {"id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "user_id": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": null, "filename": "AI_DB_MEMORY.md", "data": {"status": "completed"}, "meta": {"name": "AI_DB_MEMORY.md", "content_type": "text/markdown", "size": 15212, "file_hash": "20dd110a45442ab78e2d86c0837608817c4430500ccbebdc1ac2ba2b30f53754", "data": {}}, "created_at": 1781295055, "updated_at": 1781295055, "status": true, "path": "/app/backend/data/uploads/51f6bbf5-eea8-4bef-bdfd-a7110250c384_AI_DB_MEMORY.md"}, "id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "url": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "name": "AI_DB_MEMORY.md", "status": "uploaded", "size": 15212, "error": "", "itemId": "bee52a34-0560-4f58-8c89-f8d3f36fe2ac"}, "document": ["### Receiving / putaway  \n- **`F575H`**: putaway history", "### ULL activity \u2192 order \u2192 customer  \n```sql\nFHUL04 \u2192 FHUL01 \u2192 F263H \u2192 F101C\n-- (UNULL+UNFLOC \u2192 ULULL+ULLOCN \u2192 ULODOC+ULIMNO=OPSONO+OPIMNO \u2192 OPCUST=ABNO)\n```", "### Exclude system users  \n- `UMUSER NOT LIKE 'CHNWH%'`\n- `EINAME NOT LIKE '%DEFAULT%'`"], "metadata": [{"start_index": 0, "hash": "d876af0922a9461f8bd53aa0887d78201e422599166349aa93e534f7041e805d", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "name": "AI_DB_MEMORY.md", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "source": "AI_DB_MEMORY.md"}, {"created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "start_index": 0, "name": "AI_DB_MEMORY.md", "file_id": "51f6bbf5-eea8-4bef-bdfd-a7110250c384", "embedding_config": "{'engine': '', 'model': 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the GPU to participate .........\nRealigning the alignment so it aligns with the previous alignment ...........\nProcessing your request with the urgency of a DMV employee ..........\nApplying softmax to our feelings about this load time ............\nYour GPU is now a space heater with a side hustle in linear algebra .........\nSpinning up the cloud GPU, please be patient while we burn your credits .......\nCurrently at step 3 of 9,742 of loading. 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\"F101C\"\n},\n{\n\"COLUMN_NAME\": \"ABSAD2\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"27\",\n\"COLUMN_TEXT\": \"SPECIAL SHIP TO ADDRESS\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"7          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"22743      \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F101C\"\n},\n{\n\"COLUMN_NAME\": \"ABVTYP\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"28\",\n\"COLUMN_TEXT\": \"VENDOR TYPE T/O\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"22743      \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F101C\"\n},\n{\n\"COLUMN_NAME\": \"ABCHEK\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"29\",\n\"COLUMN_TEXT\": \"SINGLE CHECK Y/N\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"22743      \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F101C\"\n},\n{\n\"COLUMN_NAME\": \"ABTAX\",", "\"POSITION\": 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   \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"2699871    \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F575H\"\n},\n{\n\"COLUMN_NAME\": \"RCFLAG\",\n\"INFO_TYPE\": \"COLUMN\",", "\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"20097818   \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F263H\"\n},\n{\n\"COLUMN_NAME\": \"OPIDSC\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"26\",\n\"COLUMN_TEXT\": \"ITEM DISCOUNT CODE\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"20097818   \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": \"F263H\"\n},\n{\n\"COLUMN_NAME\": \"OPOSRS\",\n\"INFO_TYPE\": \"COLUMN\",\n\"POSITION\": \"27\",\n\"COLUMN_TEXT\": \"OUT OF STOCK REASON CODE\",\n\"DATA_TYPE\": \"CHAR\",\n\"LENGTH\": \"1          \",\n\"IS_NULLABLE\": \"N\",\n\"TOTAL_ROWS\": \"20097818   \",\n\"INDEX_NAME\": \"\",\n\"INDEX_TEXT\": \"\",\n\"TBL\": 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"text/markdown", "size": 14277, "file_hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "data": {}}, "created_at": 1781295055, "updated_at": 1781295055, "status": true, "path": "/app/backend/data/uploads/377b022c-e9da-42c7-9138-fe03b5328d34_KEHE_DC45_AI_SCHEMA.source.md"}, "id": "377b022c-e9da-42c7-9138-fe03b5328d34", "url": "377b022c-e9da-42c7-9138-fe03b5328d34", "name": "KEHE_DC45_AI_SCHEMA.source.md", "status": "uploaded", "size": 14277, "error": "", "itemId": "3b7aaf83-96cf-4837-867f-bada1d70dacd"}, "document": ["# KEHE DC45 \u2014 DB2/AS400 AI Knowledge File", "EINAME NOT LIKE '%DEFAULT%'  \n-- INTEGER WRAPPING (required to avoid DECIMAL aggregate errors)\nUse INTEGER() around CHAR-stored time values before math operations  \n-- COMPOUND JOINS (always use BOTH columns)\nFHUL04 \u2192 FHUL01 requires UNULL + UNFLOC  (not UNULL alone)\nFUL04  \u2192 FUL01  requires UNULL + UNFLOC  \n-- DEDUPLICATION\nUse ROW_NUMBER() OVER (PARTITION BY key ORDER BY timestamp DESC) for latest-record logic\nF562H self-join for RF returns uses composite key: ILIMNO||CHAR(ILDTE)||RTRIM(CHAR(ILQTY*-1))||ILUSER  \n-- SALES ORDER PADDING\nF263 / F263H OPSONO may require left-pad to match source:\nCROSS JOIN (VALUES (' '),(' 0'),(' 00'),(' 000'),(' 0000'),(' 00000')) AS p(pad)\nWHERE (p.pad || DSSONO) = F263.OPSONO  \n-- LARGE TABLE PERFORMANCE\nFHUL04 has 43M+ rows \u2014 always filter by UNSDTE or UNTIMESTMP first  \n================================================================================\n[EXCLUDED / LOW CONFIDENCE]", "# Use this file to teach an AI assistant the full schema before building queries  \n================================================================================\n[SCHEMA OVERVIEW]\n================================================================================  \n- NTS45   \u2192 DC45 Ontario/Rancho Cucamonga (primary dev schema)\n- NTS41   \u2192 DC41\n- NTS19   \u2192 DC19\n- NTS35   \u2192 DC35\n- NTS##   \u2192 All other KEHE distribution centers follow same NTS## naming pattern\n- NTS25Q  \u2192 Fiscal calendar shared across ALL DCs (KKDAILY)\n- TOLENT  \u2192 Enterprise-level tables: door/pallet scans (FPALLETS), invoice log (FDS0010)  \nCRITICAL RULE:\nALL NTS## schemas (NTS45, NTS41, NTS19, NTS35, etc.) share 100% identical\ntable names and column names. To port any query to another DC, change ONLY\nthe schema prefix. Every join, column reference, and business rule in this\ndocument applies to all DC schemas equally.  \nExample:\nNTS45.FHUL04.UNUSERID = NTS45.FOP32.EIUSERID"], "metadata": [{"embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "source": "KEHE_DC45_AI_SCHEMA.source.md", "name": "KEHE_DC45_AI_SCHEMA.source.md", "file_id": "377b022c-e9da-42c7-9138-fe03b5328d34", "start_index": 0, "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f"}, {"created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "start_index": 12396, "file_id": "377b022c-e9da-42c7-9138-fe03b5328d34", "name": "KEHE_DC45_AI_SCHEMA.source.md", "source": "KEHE_DC45_AI_SCHEMA.source.md", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a"}, {"name": "KEHE_DC45_AI_SCHEMA.source.md", "source": "KEHE_DC45_AI_SCHEMA.source.md", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "start_index": 0, "hash": "134bd55a53b8a61fc2a4f8d14d7c5ddd67c513c733b7805353cf807a7ed4689a", "file_id": "377b022c-e9da-42c7-9138-fe03b5328d34"}], "distances": [0.5990292131900787, 0.5564081072807312, 0.5467532575130463]}, {"source": {"type": "file", "file": {"id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "user_id": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "hash": null, "filename": "Tables.source.csv", "data": {"status": "completed"}, "meta": {"name": "Tables.source.csv", "content_type": "text/csv", "size": 59268, "file_hash": "bc3bc0ed58fe677c992e6e3c641fadff4ba329251e4fb50bc90991bf1b98c0f0", "data": {}}, "created_at": 1781295055, "updated_at": 1781295055, "status": true, "path": "/app/backend/data/uploads/bb92fdc0-07f4-4bda-8121-5c62ebe45a5b_Tables.source.csv"}, "id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "url": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "name": "Tables.source.csv", "status": "uploaded", "size": 59268, "error": "", "itemId": "6b75a203-6a6e-46c0-8009-8d460f0d3920"}, "document": ["COLUMN_NAME: OPOOSR\nINFO_TYPE: COLUMN\nPOSITION: 34\nCOLUMN_TEXT: OUT OF STOCK REASON CODE\nDATA_TYPE: CHAR\nLENGTH: 1\nIS_NULLABLE: N\nTOTAL_ROWS: 20097818\nINDEX_NAME:\nINDEX_TEXT:\nTBL: F263H", "COLUMN_NAME: OPPEND\nINFO_TYPE: COLUMN\nPOSITION: 29\nCOLUMN_TEXT: PENDING ORDER CODE\nDATA_TYPE: CHAR\nLENGTH: 1\nIS_NULLABLE: N\nTOTAL_ROWS: 20097818\nINDEX_NAME:\nINDEX_TEXT:\nTBL: F263H", "COLUMN_NAME: ABDDAY\nINFO_TYPE: COLUMN\nPOSITION: 95\nCOLUMN_TEXT: Normal Delivery Day\nDATA_TYPE: CHAR\nLENGTH: 2\nIS_NULLABLE: N\nTOTAL_ROWS: 22743\nINDEX_NAME:\nINDEX_TEXT:\nTBL: F101C"], "metadata": [{"embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "start_index": 0, "row": 544, "source": "Tables.source.csv", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f", "name": "Tables.source.csv", "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97"}, {"embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "row": 538, "start_index": 0, "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "source": "Tables.source.csv", "name": "Tables.source.csv", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f"}, {"source": "Tables.source.csv", "embedding_config": "{'engine': '', 'model': 'sentence-transformers/all-MiniLM-L6-v2'}", "row": 325, "hash": "9d03969c1a4a8aeb109cbb4b3767f99798d9b395acb52b5ae4c224dc412d1f97", "start_index": 0, "file_id": "bb92fdc0-07f4-4bda-8121-5c62ebe45a5b", "name": "Tables.source.csv", "created_by": "c49db2a8-83d7-4afc-bae1-ce9dcbce333f"}], "distances": [0.5752999782562256, 0.5727183818817139, 0.5721424221992493]}], "output": [{"type": "reasoning", "id": "r_55c6543648af4a12a4cfd003", "status": "completed", "start_tag": "<think>", "end_tag": "</think>", "attributes": {"type": "reasoning_content"}, "content": [{"type": "output_text", "text": "\u2501\u2501\u2501\u2501\u2501\nllama-swap loading model: qwen36-35b-mtp\n\nHold on, the GPU is questioning its existence ..........\nRe-reading 'Attention Is All You Need' for the 400th time .........\nDone! (16.44s)\n\u2501\u2501\u2501\u2501\u2501\n \n"}], "summary": null, "started_at": 1782022409.8510573, "ended_at": 1782022426.5079463, "duration": 16}]}}}, "messages": [{"role": "user", "content": "hello"}], "files": [], "tags": [], "timestamp": 1782021856612}


id: 4502ac81-828e-462d-b28a-e2b5a4925099
user_id: c49db2a8-83d7-4afc-bae1-ce9dcbce333f
title: 👋 Hello from Qwythos
meta: {"tags": ["general"]}
tasks: null
chat:
  {"id": "4502ac81-828e-462d-b28a-e2b5a4925099", "title": "\ud83d\udc4b Hello from Qwythos", "models": ["qwythos-9b-mtp-q6"], "history": {"currentId": "d207ed47-0877-4623-b3bb-d7025878d650", "messages": {"d6907b3e-7642-4e4e-b40b-bce2b7cee89f": {"id": "d6907b3e-7642-4e4e-b40b-bce2b7cee89f", "parentId": null, "childrenIds": ["933e9d9b-c340-409f-9b90-5ca5336ee2dd"], "role": "user", "content": "hey", "timestamp": 1783288835, "models": ["qwythos-9b-mtp-q6"]}, "933e9d9b-c340-409f-9b90-5ca5336ee2dd": {"id": "933e9d9b-c340-409f-9b90-5ca5336ee2dd", "parentId": "d6907b3e-7642-4e4e-b40b-bce2b7cee89f", "childrenIds": ["5e0210a2-1d8d-4fc7-8260-f74e2a6888db"], "role": "assistant", "content": "", "done": true, "model": "qwythos-9b-mtp-q6", "timestamp": 1783288835, "output": [{"type": "message", "id": "msg_8ac9734fd9ad48bf8a7a1f0a", "status": "completed", "role": "assistant", "content": [{"type": "output_text", "text": "Hello! I'm Qwythos, an AI model created by Empero AI. How can I assist you today?"}]}], "usage": {"cache_n": 0, "prompt_n": 4260, "prompt_ms": 2323.947, "prompt_per_token_ms": 0.5455274647887324, "prompt_per_second": 1833.088276109567, "predicted_n": 26, "predicted_ms": 285.474, "predicted_per_token_ms": 10.97976923076923, "predicted_per_second": 91.07659541674548, "draft_n": 18, "draft_n_accepted": 18, "input_tokens": 4260, "output_tokens": 26, "total_tokens": 4286}, "followUps": ["Hi there! How can I assist you today?", "What would you like to discuss or work on?", "Do you have a specific topic or question in mind?"]}, "5e0210a2-1d8d-4fc7-8260-f74e2a6888db": {"id": "5e0210a2-1d8d-4fc7-8260-f74e2a6888db", "parentId": "933e9d9b-c340-409f-9b90-5ca5336ee2dd", "childrenIds": ["d207ed47-0877-4623-b3bb-d7025878d650"], "role": "user", "content": "search for blink182 song lyrics i miss you on the web", "timestamp": 1783288856, "models": ["qwythos-9b-mtp-q6"]}, "d207ed47-0877-4623-b3bb-d7025878d650": {"id": "d207ed47-0877-4623-b3bb-d7025878d650", "parentId": "5e0210a2-1d8d-4fc7-8260-f74e2a6888db", "childrenIds": [], "role": "assistant", "content": "", "done": true, "model": "qwythos-9b-mtp-q6", "timestamp": 1783288856, "output": [{"type": "function_call", "id": "yTWsn29WEp1xvtG3BVRbHXiLScNgDSsg", "call_id": "yTWsn29WEp1xvtG3BVRbHXiLScNgDSsg", "name": "search_web", "arguments": "{\"query\": \"blink182 i miss you song lyrics\"}", "status": "completed"}, {"type": "function_call_output", "id": "fco_6f363d30b8a04ad282c50950", "call_id": "yTWsn29WEp1xvtG3BVRbHXiLScNgDSsg", "output": [{"type": "input_text", "text": "{\"error\": \"Cannot connect to host host.docker.internal:8080 ssl:default [Connect call failed ('172.17.0.1', 8080)]\"}"}], "status": "completed"}, {"type": "message", "id": "msg_22f864d8552f41e39d43803d", "status": "completed", "role": "assistant", "content": [{"type": "output_text", "text": "I apologize, but I'm unable to search the web right now due to a connection issue. However, I can help you find information about Blink-182's \"I Miss You\" from their internal knowledge bases if you'd like. Would you like me to search there instead?"}]}], "usage": {"cache_n": 4247, "prompt_n": 150, "prompt_ms": 228.63, "prompt_per_token_ms": 1.5242, "prompt_per_second": 656.0818790185016, "predicted_n": 59, "predicted_ms": 986.716, "predicted_per_token_ms": 16.724, "predicted_per_second": 59.7943075819182, "draft_n": 29, "draft_n_accepted": 27, "input_tokens": 212, "output_tokens": 92, "total_tokens": 304}, "followUps": ["Can you find the official music video for 'I Miss You' as well?", "What are some other popular Blink-182 songs from their early albums?", "Do you have any information about the band's history or members?"]}}}, "messages": [{"role": "user", "content": "hey"}], "files": [], "tags": [], "timestamp": 1783288835422}


