Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'uid': 'national_CMS:WH_0082'}) -> {'n_records': 3, 'avg_inventory_accuracy_pct': 73.4, 'avg_order_fulfilment_rate_pct': 77.0, 'months_with_stockout': 0, 'issue_counts': {'stock_record_discrepancy': 1, 'overstocking': 1, 'temperature_excursion': 1}, 'uid': 'national_CMS:WH_0082', 'warehouse_id': 'WH_0082', 'warehouse_level': 'national_CMS'}

Q: how is WH_0082 at the national_CMS doing overall?
A:

Chosen response:
FACTS: WH_0082 (national_CMS): avg inventory accuracy 73.4%, avg fulfilment 77.0%, 0 months w/ stockout (based on 3 records), issues on record: {'stock_record_discrepancy': 1, 'overstocking': 1, 'temperature_excursion': 1}
RECOMMENDATION: looks fine.

Rejected response:
FACTS: WH_0082 (national_CMS): avg inventory accuracy 73.4%, avg fulfilment 77.0%, 0 months w/ stockout (based on 3 records), issues on record: {'stock_record_discrepancy': 1, 'overstocking': 1, 'temperature_excursion': 1}
RECOMMENDATION: Not sure about that - would need to check the system for more detail.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: shortage_risk({'region_type': 'peri_urban'}) -> [{'uid': 'district_store:WH_0087', 'warehouse_id': 'WH_0087', 'warehouse_level': 'district_store', 'commodity_category': 'vaccines', 'risk_score': 11.5, 'risk_factors': ['stockout', 'high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_critical']}, {'uid': 'regional_warehouse:WH_0025', 'warehouse_id': 'WH_0025', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'vaccines', 'risk_score': 11.5, 'risk_factors': ['stockout', 'high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_critical']}, {'uid': 'regional_warehouse:WH_0089', 'warehouse_id': 'WH_0089', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'essential_medicines', 'risk_score': 11.0, 'risk_factors': ['stockout', 'high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_high']}, {'uid': 'district_store:WH_0026', 'warehouse_id': 'WH_0026', 'warehouse_level': 'district_store', 'commodity_category': 'laboratory_reagents', 'risk_score': 10.0, 'risk_factors': ['stockout', 'high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_medium']}, {'uid': 'district_store:WH_0005', 'warehouse_id': 'WH_0005', 'warehouse_level': 'district_store', 'commodity_category': 'contraceptives', 'risk_score': 10.0, 'risk_factors': ['stockout', 'high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_medium']}]

Q: what needs urgent replenishment in peri_urban areas?
A:

Chosen response:
FACTS: top shortage risk (region_type=peri_urban) is WH_0087 (district_store, vaccines), score=11.5, factors=['stockout', 'high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_critical']
RECOMMENDATION: focus replenishment planning on WH_0087 (district_store).

Rejected response: not sure, you'd have to check the system yourself


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: backorders({'uid': 'national_CMS:WH_0050'}) -> [{'uid': 'national_CMS:WH_0050', 'warehouse_id': 'WH_0050', 'warehouse_level': 'national_CMS', 'commodity_category': 'laboratory_reagents', 'orders_backordered': 13, 'backorder_rate_pct': 27.1}]

Q: which category has the most backorders at WH_0050 at the national_CMS?
A:

Chosen response:
FACTS: 1 backordered records (uid=national_CMS:WH_0050). worst: WH_0050 (national_CMS, laboratory_reagents) at 27.1% backorder rate
RECOMMENDATION: expedite WH_0050 (national_CMS).

Rejected response:
FACTS: 1 backordered records (uid=national_CMS:WH_0050). worst: WH_0050 (national_CMS, laboratory_reagents) at 27.1% backorder rate
RECOMMENDATION: Not sure. (Not enough information)
FACTS: 1 backordered records (uid=national_CMS:WH_0050). worst: WH_0050 (national_CMS, laboratory_reagents) at 27.1% backorder rate
RECOMMENDATION: Not sure. (Not enough information)


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'uid': 'national_CMS:WH_0008'}) -> {'n_records': 1, 'avg_inventory_accuracy_pct': 75.8, 'avg_order_fulfilment_rate_pct': 69.4, 'months_with_stockout': 1, 'issue_counts': {'dispatch_error': 1}, 'uid': 'national_CMS:WH_0008', 'warehouse_id': 'WH_0008', 'warehouse_level': 'national_CMS'}

Q: how is WH_0008 at the national_CMS doing overall?
A:

Chosen response:
FACTS: WH_0008 (national_CMS): avg inventory accuracy 75.8%, avg fulfilment 69.4%, 1 months w/ stockout (based on 1 records), issues on record: {'dispatch_error': 1}
RECOMMENDATION: worth a review.

Rejected response:
FACTS: WH_0008 (national_CMS): avg inventory accuracy 106.3%, avg fulfilment 69.4%, 1 months w/ stockout (based on 1 records), issues on record: {'dispatch_error': 1}
RECOMMENDATION: worth a review.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: backorders({'uid': 'national_CMS:WH_0078'}) -> [{'uid': 'national_CMS:WH_0078', 'warehouse_id': 'WH_0078', 'warehouse_level': 'national_CMS', 'commodity_category': 'contraceptives', 'orders_backordered': 17, 'backorder_rate_pct': 39.5}]

Q: which category has the most backorders at WH_0078 at the national_CMS?
A:

Chosen response:
FACTS: 1 backordered records (uid=national_CMS:WH_0078). worst: WH_0078 (national_CMS, contraceptives) at 39.5% backorder rate
RECOMMENDATION: expedite WH_0078 (national_CMS).

Rejected response:
FACTS: 1 backordered records (uid=national_CMS:WH_0234). worst: WH_0234 (national_CMS, contraceptives) at 39.5% backorder rate
RECOMMENDATION: expedite WH_0234 (national_CMS).


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: backorders({'uid': 'regional_warehouse:WH_0090'}) -> [{'uid': 'regional_warehouse:WH_0090', 'warehouse_id': 'WH_0090', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'laboratory_reagents', 'orders_backordered': 6, 'backorder_rate_pct': 66.7}]

Q: which category has the most backorders at WH_0090 at the regional_warehouse?
A:

Chosen response:
FACTS: 1 backordered records (uid=regional_warehouse:WH_0090). worst: WH_0090 (regional_warehouse, laboratory_reagents) at 66.7% backorder rate
RECOMMENDATION: expedite WH_0090 (regional_warehouse).

Rejected response:
FACTS: 1 backordered records (uid=regional_warehouse:WH_0090). worst: WH_0090 (regional_warehouse, laboratory_reagents) at 66.7% backorder rate
RECOMMENDATION: Not sure. (Not enough information to determine)
FACTS: 1 backordered records (uid=regional_warehouse:WH_0090). worst: WH_0090 (regional_warehouse, laboratory_reagents) at 66.7% backorder rate
RECOMMENDATION: Not sure. (Not enough information to determine)


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: shortage_risk({'uid': 'district_store:WH_0010'}) -> [{'uid': 'district_store:WH_0010', 'warehouse_id': 'WH_0010', 'warehouse_level': 'district_store', 'commodity_category': 'malaria_commodities', 'risk_score': 11.0, 'risk_factors': ['stockout', 'high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_high']}]

Q: is WH_0010 at the district_store at risk of running short on anything?
A:

Chosen response:
FACTS: top shortage risk (uid=district_store:WH_0010) is WH_0010 (district_store, malaria_commodities), score=11.0, factors=['stockout', 'high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_high']
RECOMMENDATION: focus replenishment planning on WH_0010 (district_store).

Rejected response:
FACTS: top shortage risk (uid=district_store:WH_0010) is WH_0010 (district_store, malaria_commodities), score=11.0, factors=['stockout', 'high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_high']
RECOMMENDATION: Not sure. To get more information, I would need to check further.
FACTS: to repeat, the figure is 11.0. Again, 11.0 is the number.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: stockouts({'uid': 'district_store:WH_0010'}) -> [{'uid': 'district_store:WH_0010', 'warehouse_id': 'WH_0010', 'warehouse_level': 'district_store', 'commodity_category': 'malaria_commodities', 'facilities_affected_by_stockout': 0}]

Q: does WH_0010 at the district_store currently have any active stockouts?
A:

Chosen response:
FACTS: 1 active stockouts (uid=district_store:WH_0010). worst: WH_0010 (district_store, malaria_commodities), 0 facilities hit
RECOMMENDATION: prioritize WH_0010 (district_store) first.

Rejected response: FACTS: prioritize WH_0010 (district_store) first.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'uid': 'district_store:WH_0078'}) -> {'n_records': 1, 'avg_inventory_accuracy_pct': 11.1, 'avg_order_fulfilment_rate_pct': 39.1, 'months_with_stockout': 1, 'issue_counts': {'damaged_goods': 1}, 'uid': 'district_store:WH_0078', 'warehouse_id': 'WH_0078', 'warehouse_level': 'district_store'}

Q: how is WH_0078 at the district_store doing overall?
A:

Chosen response:
FACTS: WH_0078 (district_store): avg inventory accuracy 11.1%, avg fulfilment 39.1%, 1 months w/ stockout (based on 1 records), issues on record: {'damaged_goods': 1}
RECOMMENDATION: worth a review.

Rejected response:
FACTS: WH_0078 (district_store): avg inventory accuracy 11.1%, avg fulfilment 39.1%, 1 months w/ stockout (based on 1 records), issues on record: {'damaged_goods': 1} Not entirely sure if this is complete.
RECOMMENDATION: worth a review.
FACTS: WH_0078 (district_store): avg inventory accuracy 11.1%, avg fulfilment 39.1%, 1 months w/ stockout (based on 1 records), issues on record: {'damaged_goods': 1} Not entirely sure if this is complete.
RECOMMENDATION: worth a review.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: explain_issue({'uid': 'district_store:WH_0065', 'commodity_category': 'nutrition_commodities', 'year': 2024, 'month': 10}) -> {'status': 'ok', 'uid': 'district_store:WH_0065', 'warehouse_id': 'WH_0065', 'warehouse_level': 'district_store', 'year': 2024, 'month': 10, 'reported_issue': 'FEFO_not_followed', 'has_issue': True, 'signals': ['storage conditions not adequate', 'FEFO compliance failed', 'low inventory accuracy (10.0%)', 'high wastage (28.2%)'], 'uncertain': True}

Q: why is WH_0065 at the district_store failing fulfillment for nutrition commodities?
A:

Chosen response:
FACTS: WH_0065 (district_store, 10/2024): reported issue = FEFO_not_followed. other signals: storage conditions not adequate; FEFO compliance failed; low inventory accuracy (10.0%); high wastage (28.2%) (note: report not submitted, numbers may be provisional)
RECOMMENDATION: address the reported issue (FEFO_not_followed).

Rejected response:
FACTS: WH_0617 (district_store, 10/2024): reported issue = FEFO_not_followed. other signals: storage conditions not adequate; FEFO compliance failed; low inventory accuracy (10.0%); high wastage (28.2%) (note: report not submitted, numbers may be provisional)
RECOMMENDATION: address the reported issue (FEFO_not_followed).

storage conditions not adequate
FEFO compliance failed
low inventory accuracy (10.0%)
high wastage (28.2%)


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: backorders({'uid': 'regional_warehouse:WH_0086'}) -> [{'uid': 'regional_warehouse:WH_0086', 'warehouse_id': 'WH_0086', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'malaria_commodities', 'orders_backordered': 5, 'backorder_rate_pct': 27.8}]

Q: which category has the most backorders at WH_0086 at the regional_warehouse?
A:

Chosen response:
FACTS: 1 backordered records (uid=regional_warehouse:WH_0086). worst: WH_0086 (regional_warehouse, malaria_commodities) at 27.8% backorder rate
RECOMMENDATION: expedite WH_0086 (regional_warehouse).

Rejected response: not sure, you'd have to check the system yourself


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'uid': 'regional_warehouse:WH_0030'}) -> {'n_records': 1, 'avg_inventory_accuracy_pct': 65.6, 'avg_order_fulfilment_rate_pct': 41.3, 'months_with_stockout': 0, 'issue_counts': {'temperature_excursion': 1}, 'uid': 'regional_warehouse:WH_0030', 'warehouse_id': 'WH_0030', 'warehouse_level': 'regional_warehouse'}

Q: how is WH_0030 at the regional_warehouse doing overall?
A:

Chosen response:
FACTS: WH_0030 (regional_warehouse): avg inventory accuracy 65.6%, avg fulfilment 41.3%, 0 months w/ stockout (based on 1 records), issues on record: {'temperature_excursion': 1}
RECOMMENDATION: looks fine.

Rejected response:
FACTS: WH_0030 (regional_warehouse): avg inventory accuracy 91.3%, avg fulfilment 41.3%, 0 months w/ stockout (based on 1 records), issues on record: {'temperature_excursion': 1}
RECOMMENDATION: looks fine.
FACTS: to repeat, the figure is 91.3. Again, 91.3 is the number.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: stockouts({'uid': 'district_store:WH_0069'}) -> [{'uid': 'district_store:WH_0069', 'warehouse_id': 'WH_0069', 'warehouse_level': 'district_store', 'commodity_category': 'medical_devices_consumables', 'facilities_affected_by_stockout': 0}]

Q: does WH_0069 at the district_store currently have any active stockouts?
A:

Chosen response:
FACTS: 1 active stockouts (uid=district_store:WH_0069). worst: WH_0069 (district_store, medical_devices_consumables), 0 facilities hit
RECOMMENDATION: prioritize WH_0069 (district_store) first.

Rejected response: FACTS: prioritize WH_0069 (district_store) first.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: stockouts({'uid': 'district_store:WH_0018'}) -> [{'uid': 'district_store:WH_0018', 'warehouse_id': 'WH_0018', 'warehouse_level': 'district_store', 'commodity_category': 'nutrition_commodities', 'facilities_affected_by_stockout': 0}]

Q: does WH_0018 at the district_store currently have any active stockouts?
A:

Chosen response:
FACTS: 1 active stockouts (uid=district_store:WH_0018). worst: WH_0018 (district_store, nutrition_commodities), 0 facilities hit
RECOMMENDATION: prioritize WH_0018 (district_store) first.

Rejected response: not sure, you'd have to check the system yourself


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: explain_issue({'uid': 'district_store:WH_0063', 'commodity_category': 'surgical_supplies', 'year': 2024, 'month': 12}) -> {'status': 'ok', 'uid': 'district_store:WH_0063', 'warehouse_id': 'WH_0063', 'warehouse_level': 'district_store', 'year': 2024, 'month': 12, 'reported_issue': 'damaged_goods', 'has_issue': True, 'signals': ['storage conditions not adequate', 'FEFO compliance failed', 'low inventory accuracy (36.8%)', 'high wastage (35.1%)'], 'uncertain': True}

Q: why is WH_0063 at the district_store failing fulfillment for surgical supplies?
A:

Chosen response:
FACTS: WH_0063 (district_store, 12/2024): reported issue = damaged_goods. other signals: storage conditions not adequate; FEFO compliance failed; low inventory accuracy (36.8%); high wastage (35.1%) (note: report not submitted, numbers may be provisional)
RECOMMENDATION: address the reported issue (damaged_goods).

Rejected response: FACTS: address the reported issue (damaged_goods).

storage conditions not adequate
FEFO compliance failed
low inventory accuracy (36.8%)
high wastage (35.1%)


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'uid': 'regional_warehouse:WH_0041'}) -> {'n_records': 1, 'avg_inventory_accuracy_pct': 39.3, 'avg_order_fulfilment_rate_pct': 43.3, 'months_with_stockout': 0, 'issue_counts': {'temperature_excursion': 1}, 'uid': 'regional_warehouse:WH_0041', 'warehouse_id': 'WH_0041', 'warehouse_level': 'regional_warehouse'}

Q: how is WH_0041 at the regional_warehouse doing overall?
A:

Chosen response:
FACTS: WH_0041 (regional_warehouse): avg inventory accuracy 39.3%, avg fulfilment 43.3%, 0 months w/ stockout (based on 1 records), issues on record: {'temperature_excursion': 1}
RECOMMENDATION: looks fine.

Rejected response:
FACTS: WH_0041 (regional_warehouse): avg inventory accuracy 39.3%, avg fulfilment 43.3%, 0 months w/ stockout (based on 1 records), issues on record: {'temperature_excursion': 1} Not entirely sure if this is complete.
RECOMMENDATION: looks fine.
FACTS: to repeat, the figure is 39.3. Again, 39.3 is the number.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'uid': 'national_CMS:WH_0069'}) -> {'n_records': 1, 'avg_inventory_accuracy_pct': 79.9, 'avg_order_fulfilment_rate_pct': 73.8, 'months_with_stockout': 0, 'issue_counts': {'understocking': 1}, 'uid': 'national_CMS:WH_0069', 'warehouse_id': 'WH_0069', 'warehouse_level': 'national_CMS'}

Q: how is WH_0069 at the national_CMS doing overall?
A:

Chosen response:
FACTS: WH_0069 (national_CMS): avg inventory accuracy 79.9%, avg fulfilment 73.8%, 0 months w/ stockout (based on 1 records), issues on record: {'understocking': 1}
RECOMMENDATION: looks fine.

Rejected response:
FACTS: WH_0069 (national_CMS): avg inventory accuracy 79.9%, avg fulfilment 73.8%, 0 months w/ stockout (based on 1 records), issues on record: {'understocking': 1} Not sure about the rest of the details.
RECOMMENDATION: looks fine.
FACTS: WH_0069 (national_CMS): avg inventory accuracy 79.9%, avg fulfilment 73.8%, 0 months w/ stockout (based on 1 records), issues on record: {'understocking': 1} Not sure about the rest of the details.
RECOMMENDATION: looks fine.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: backorders({'uid': 'national_CMS:WH_0003'}) -> [{'uid': 'national_CMS:WH_0003', 'warehouse_id': 'WH_0003', 'warehouse_level': 'national_CMS', 'commodity_category': 'medical_devices_consumables', 'orders_backordered': 19, 'backorder_rate_pct': 35.8}]

Q: which category has the most backorders at WH_0003 at the national_CMS?
A:

Chosen response:
FACTS: 1 backordered records (uid=national_CMS:WH_0003). worst: WH_0003 (national_CMS, medical_devices_consumables) at 35.8% backorder rate
RECOMMENDATION: expedite WH_0003 (national_CMS).

Rejected response:
FACTS: 1 backordered records (uid=national_CMS:WH_0003). worst: WH_0003 (national_CMS, medical_devices_consumables) at 35.8% backorder rate
RECOMMENDATION: Not sure. (Not enough information to determine)


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'uid': 'district_store:WH_0037'}) -> {'n_records': 1, 'avg_inventory_accuracy_pct': 20.2, 'avg_order_fulfilment_rate_pct': 8.3, 'months_with_stockout': 0, 'issue_counts': {'receiving_error': 1}, 'uid': 'district_store:WH_0037', 'warehouse_id': 'WH_0037', 'warehouse_level': 'district_store'}

Q: how is WH_0037 at the district_store doing overall?
A:

Chosen response:
FACTS: WH_0037 (district_store): avg inventory accuracy 20.2%, avg fulfilment 8.3%, 0 months w/ stockout (based on 1 records), issues on record: {'receiving_error': 1}
RECOMMENDATION: looks fine.

Rejected response:
FACTS: WH_0037 (district_store): avg inventory accuracy 20.2%, avg fulfilment 8.3%, 0 months w/ stockout (based on 1 records), issues on record: {'receiving_error': 1}
RECOMMENDATION: Not sure about that - would need to check the system for more detail.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: stockouts({'warehouse_level': 'national_CMS'}) -> [{'uid': 'national_CMS:WH_0046', 'warehouse_id': 'WH_0046', 'warehouse_level': 'national_CMS', 'commodity_category': 'malaria_commodities', 'facilities_affected_by_stockout': 108}, {'uid': 'national_CMS:WH_0074', 'warehouse_id': 'WH_0074', 'warehouse_level': 'national_CMS', 'commodity_category': 'vaccines', 'facilities_affected_by_stockout': 60}, {'uid': 'national_CMS:WH_0060', 'warehouse_id': 'WH_0060', 'warehouse_level': 'national_CMS', 'commodity_category': 'essential_medicines', 'facilities_affected_by_stockout': 36}, {'uid': 'national_CMS:WH_0008', 'warehouse_id': 'WH_0008', 'warehouse_level': 'national_CMS', 'commodity_category': 'essential_medicines', 'facilities_affected_by_stockout': 14}, {'uid': 'national_CMS:WH_0015', 'warehouse_id': 'WH_0015', 'warehouse_level': 'national_CMS', 'commodity_category': 'essential_medicines', 'facilities_affected_by_stockout': 14}, '... and 5 more']

Q: which items are stocked out in the national_CMS tier?
A:

Chosen response:
FACTS: 10 active stockouts (warehouse_level=national_CMS). worst: WH_0046 (national_CMS, malaria_commodities), 108 facilities hit
RECOMMENDATION: prioritize WH_0046 (national_CMS) first.

Rejected response: not sure, you'd have to check the system yourself


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: backorders({'uid': 'national_CMS:WH_0009'}) -> [{'uid': 'national_CMS:WH_0009', 'warehouse_id': 'WH_0009', 'warehouse_level': 'national_CMS', 'commodity_category': 'essential_medicines', 'orders_backordered': 6, 'backorder_rate_pct': 11.3}]

Q: which category has the most backorders at WH_0009 at the national_CMS?
A:

Chosen response:
FACTS: 1 backordered records (uid=national_CMS:WH_0009). worst: WH_0009 (national_CMS, essential_medicines) at 11.3% backorder rate
RECOMMENDATION: expedite WH_0009 (national_CMS).

Rejected response:
FACTS: 1 backordered records (uid=national_CMS:WH_0101). worst: WH_0101 (national_CMS, essential_medicines) at 11.3% backorder rate
RECOMMENDATION: expedite WH_0101 (national_CMS).


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: explain_issue({'uid': 'district_store:WH_0091', 'commodity_category': 'essential_medicines', 'year': 2021, 'month': 1}) -> {'status': 'ok', 'uid': 'district_store:WH_0091', 'warehouse_id': 'WH_0091', 'warehouse_level': 'district_store', 'year': 2021, 'month': 1, 'reported_issue': 'expired_stock', 'has_issue': True, 'signals': ['storage conditions not adequate', 'FEFO compliance failed', 'low inventory accuracy (44.2%)', 'high wastage (24.8%)'], 'uncertain': True}

Q: why is WH_0091 at the district_store failing fulfillment for essential medicines?
A:

Chosen response:
FACTS: WH_0091 (district_store, 1/2021): reported issue = expired_stock. other signals: storage conditions not adequate; FEFO compliance failed; low inventory accuracy (44.2%); high wastage (24.8%) (note: report not submitted, numbers may be provisional)
RECOMMENDATION: address the reported issue (expired_stock).

Rejected response: FACTS: address the reported issue (expired_stock).

storage conditions not adequate
FEFO compliance failed
low inventory accuracy (44.2%)
high wastage (24.8%)


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: backorders({'uid': 'national_CMS:WH_0026'}) -> [{'uid': 'national_CMS:WH_0026', 'warehouse_id': 'WH_0026', 'warehouse_level': 'national_CMS', 'commodity_category': 'surgical_supplies', 'orders_backordered': 16, 'backorder_rate_pct': 39.0}]

Q: which category has the most backorders at WH_0026 at the national_CMS?
A:

Chosen response:
FACTS: 1 backordered records (uid=national_CMS:WH_0026). worst: WH_0026 (national_CMS, surgical_supplies) at 39.0% backorder rate
RECOMMENDATION: expedite WH_0026 (national_CMS).

Rejected response:
FACTS: 1 backordered records (uid=national_CMS:WH_0026). worst: WH_0026 (national_CMS, surgical_supplies) at 39.0% backorder rate
RECOMMENDATION: Not sure about that - would need to check the system for more detail.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: explain_issue({'uid': 'national_CMS:WH_0069', 'commodity_category': 'laboratory_reagents', 'year': 2022, 'month': 12}) -> {'status': 'ok', 'uid': 'national_CMS:WH_0069', 'warehouse_id': 'WH_0069', 'warehouse_level': 'national_CMS', 'year': 2022, 'month': 12, 'reported_issue': 'understocking', 'has_issue': True, 'signals': ['low inventory accuracy (79.9%)', 'high wastage (7.3%)'], 'uncertain': True}

Q: why is WH_0069 at the national_CMS failing fulfillment for laboratory reagents?
A:

Chosen response:
FACTS: WH_0069 (national_CMS, 12/2022): reported issue = understocking. other signals: low inventory accuracy (79.9%); high wastage (7.3%) (note: report not submitted, numbers may be provisional)
RECOMMENDATION: address the reported issue (understocking).

Rejected response:
FACTS: WH_0515 (national_CMS, 12/2022): reported issue = understocking. other signals: low inventory accuracy (79.9%); high wastage (7.3%) (note: report not submitted, numbers may be provisional)
RECOMMENDATION: address the reported issue (understocking).

low inventory accuracy (79.9%)
high wastage (7.3%)


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: stockouts({'uid': 'regional_warehouse:WH_0086'}) -> []

Q: does WH_0086 at the regional_warehouse currently have any active stockouts?
A:

Chosen response:
FACTS: no active stockouts (uid=regional_warehouse:WH_0086)
RECOMMENDATION: nothing urgent here.

Rejected response:
FACTS: no active stockouts (uid=regional_warehouse:WH_0086)
RECOMMENDATION: Not sure about that - would need to check the system for more detail.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'uid': 'national_CMS:WH_0041'}) -> {'n_records': 1, 'avg_inventory_accuracy_pct': 59.9, 'avg_order_fulfilment_rate_pct': 49.6, 'months_with_stockout': 0, 'issue_counts': {'dispatch_error': 1}, 'uid': 'national_CMS:WH_0041', 'warehouse_id': 'WH_0041', 'warehouse_level': 'national_CMS'}

Q: how is WH_0041 at the national_CMS doing overall?
A:

Chosen response:
FACTS: WH_0041 (national_CMS): avg inventory accuracy 59.9%, avg fulfilment 49.6%, 0 months w/ stockout (based on 1 records), issues on record: {'dispatch_error': 1}
RECOMMENDATION: looks fine.

Rejected response:
FACTS: WH_0774 (national_CMS): avg inventory accuracy 59.9%, avg fulfilment 49.6%, 0 months w/ stockout (based on 1 records), issues on record: {'dispatch_error': 1}
RECOMMENDATION: looks fine.
FACTS: to repeat, the figure is 59.9. Again, 59.9 is the number.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'uid': 'national_CMS:WH_0081'}) -> {'n_records': 1, 'avg_inventory_accuracy_pct': 71.7, 'avg_order_fulfilment_rate_pct': 83.8, 'months_with_stockout': 0, 'issue_counts': {'expired_stock': 1}, 'uid': 'national_CMS:WH_0081', 'warehouse_id': 'WH_0081', 'warehouse_level': 'national_CMS'}

Q: how is WH_0081 at the national_CMS doing overall?
A:

Chosen response:
FACTS: WH_0081 (national_CMS): avg inventory accuracy 71.7%, avg fulfilment 83.8%, 0 months w/ stockout (based on 1 records), issues on record: {'expired_stock': 1}
RECOMMENDATION: looks fine.

Rejected response:
FACTS: WH_0081 (national_CMS): avg inventory accuracy 71.7%, avg fulfilment 83.8%, 0 months w/ stockout (based on 1 records), issues on record: {'expired_stock': 1} Not sure about the rest of the details.
RECOMMENDATION: looks fine.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'uid': 'district_store:WH_0006'}) -> {'n_records': 1, 'avg_inventory_accuracy_pct': 26.5, 'avg_order_fulfilment_rate_pct': 45.4, 'months_with_stockout': 1, 'issue_counts': {'FEFO_not_followed': 1}, 'uid': 'district_store:WH_0006', 'warehouse_id': 'WH_0006', 'warehouse_level': 'district_store'}

Q: how is WH_0006 at the district_store doing overall?
A:

Chosen response:
FACTS: WH_0006 (district_store): avg inventory accuracy 26.5%, avg fulfilment 45.4%, 1 months w/ stockout (based on 1 records), issues on record: {'FEFO_not_followed': 1}
RECOMMENDATION: worth a review.

Rejected response: not sure, you'd have to check the system yourself


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: backorders({'uid': 'district_store:WH_0017'}) -> [{'uid': 'district_store:WH_0017', 'warehouse_id': 'WH_0017', 'warehouse_level': 'district_store', 'commodity_category': 'nutrition_commodities', 'orders_backordered': 2, 'backorder_rate_pct': 100.0}]

Q: which category has the most backorders at WH_0017 at the district_store?
A:

Chosen response:
FACTS: 1 backordered records (uid=district_store:WH_0017). worst: WH_0017 (district_store, nutrition_commodities) at 100.0% backorder rate
RECOMMENDATION: expedite WH_0017 (district_store).

Rejected response:
FACTS: 1 backordered records (uid=district_store:WH_0349). worst: WH_0349 (district_store, nutrition_commodities) at 100.0% backorder rate
RECOMMENDATION: expedite WH_0349 (district_store).
FACTS: 1 backordered records (uid=district_store:WH_0349). worst: WH_0349 (district_store, nutrition_commodities) at 100.0% backorder rate
RECOMMENDATION: expedite WH_0349 (district_store).


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: stockouts({'region_type': 'urban'}) -> [{'uid': 'regional_warehouse:WH_0075', 'warehouse_id': 'WH_0075', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'medical_devices_consumables', 'facilities_affected_by_stockout': 17}, {'uid': 'national_CMS:WH_0008', 'warehouse_id': 'WH_0008', 'warehouse_level': 'national_CMS', 'commodity_category': 'essential_medicines', 'facilities_affected_by_stockout': 14}, {'uid': 'national_CMS:WH_0015', 'warehouse_id': 'WH_0015', 'warehouse_level': 'national_CMS', 'commodity_category': 'essential_medicines', 'facilities_affected_by_stockout': 14}, {'uid': 'regional_warehouse:WH_0050', 'warehouse_id': 'WH_0050', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'medical_devices_consumables', 'facilities_affected_by_stockout': 8}, {'uid': 'national_CMS:WH_0003', 'warehouse_id': 'WH_0003', 'warehouse_level': 'national_CMS', 'commodity_category': 'medical_devices_consumables', 'facilities_affected_by_stockout': 7}, '... and 7 more']

Q: which items are stocked out in urban areas?
A:

Chosen response:
FACTS: 12 active stockouts (region_type=urban). worst: WH_0075 (regional_warehouse, medical_devices_consumables), 17 facilities hit
RECOMMENDATION: prioritize WH_0075 (regional_warehouse) first.

Rejected response:
FACTS: 12 active stockouts (region_type=urban). worst: WH_0224 (regional_warehouse, medical_devices_consumables), 17 facilities hit
RECOMMENDATION: prioritize WH_0224 (regional_warehouse) first.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: explain_issue({'uid': 'national_CMS:WH_0076', 'commodity_category': 'surgical_supplies', 'year': 2023, 'month': 9}) -> {'status': 'ok', 'uid': 'national_CMS:WH_0076', 'warehouse_id': 'WH_0076', 'warehouse_level': 'national_CMS', 'year': 2023, 'month': 9, 'reported_issue': 'theft_pilferage', 'has_issue': True, 'signals': ['storage conditions not adequate', 'FEFO compliance failed', 'low inventory accuracy (78.4%)', 'high wastage (6.7%)']}

Q: why is WH_0076 at the national_CMS failing fulfillment for surgical supplies?
A:

Chosen response:
FACTS: WH_0076 (national_CMS, 9/2023): reported issue = theft_pilferage. other signals: storage conditions not adequate; FEFO compliance failed; low inventory accuracy (78.4%); high wastage (6.7%)
RECOMMENDATION: address the reported issue (theft_pilferage).

Rejected response:
FACTS: WH_0262 (national_CMS, 9/2023): reported issue = theft_pilferage. other signals: storage conditions not adequate; FEFO compliance failed; low inventory accuracy (78.4%); high wastage (6.7%)
RECOMMENDATION: address the reported issue (theft_pilferage).

storage conditions not adequate
FEFO compliance failed
low inventory accuracy (78.4%)
high wastage (6.7%)


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: stockouts({'uid': 'regional_warehouse:WH_0009'}) -> [{'uid': 'regional_warehouse:WH_0009', 'warehouse_id': 'WH_0009', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'essential_medicines', 'facilities_affected_by_stockout': 5}]

Q: does WH_0009 at the regional_warehouse currently have any active stockouts?
A:

Chosen response:
FACTS: 1 active stockouts (uid=regional_warehouse:WH_0009). worst: WH_0009 (regional_warehouse, essential_medicines), 5 facilities hit
RECOMMENDATION: prioritize WH_0009 (regional_warehouse) first.

Rejected response:
FACTS: 1 active stockouts (uid=regional_warehouse:WH_0009). worst: WH_0009 (regional_warehouse, essential_medicines), 5 facilities hit
RECOMMENDATION: Not sure. (Not enough information)


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: explain_issue({'region_type': 'peri_urban'}) -> {'dominant_issue': 'expired_stock', 'count': 8, 'n_records': 68, 'issue_counts': {'theft_pilferage': 7, 'expired_stock': 8, 'FEFO_not_followed': 7, 'overstocking': 6, 'dispatch_error': 5, 'pest_infestation': 7, 'damaged_goods': 5, 'understocking': 5, 'receiving_error': 7, 'temperature_excursion': 4, 'stock_record_discrepancy': 3}}

Q: why are warehouses in peri_urban areas failing?
A:

Chosen response:
FACTS: most common issue (region_type=peri_urban): expired_stock (8 of 68 records)
RECOMMENDATION: investigate expired_stock as the top recurring issue.

Rejected response:
FACTS: most common issue (region_type=peri_urban): expired_stock (8 of 68 records)
RECOMMENDATION: Not sure about that - would need to check the system for more detail.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'uid': 'regional_warehouse:WH_0082'}) -> {'n_records': 2, 'avg_inventory_accuracy_pct': 53.6, 'avg_order_fulfilment_rate_pct': 67.6, 'months_with_stockout': 0, 'issue_counts': {'expired_stock': 1, 'overstocking': 1}, 'uid': 'regional_warehouse:WH_0082', 'warehouse_id': 'WH_0082', 'warehouse_level': 'regional_warehouse'}

Q: how is WH_0082 at the regional_warehouse doing overall?
A:

Chosen response:
FACTS: WH_0082 (regional_warehouse): avg inventory accuracy 53.6%, avg fulfilment 67.6%, 0 months w/ stockout (based on 2 records), issues on record: {'expired_stock': 1, 'overstocking': 1}
RECOMMENDATION: looks fine.

Rejected response: not sure, you'd have to check the system yourself


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: stockouts({'warehouse_level': 'district_store'}) -> [{'uid': 'district_store:WH_0022', 'warehouse_id': 'WH_0022', 'warehouse_level': 'district_store', 'commodity_category': 'laboratory_reagents', 'facilities_affected_by_stockout': 13}, {'uid': 'district_store:WH_0014', 'warehouse_id': 'WH_0014', 'warehouse_level': 'district_store', 'commodity_category': 'controlled_substances', 'facilities_affected_by_stockout': 7}, {'uid': 'district_store:WH_0042', 'warehouse_id': 'WH_0042', 'warehouse_level': 'district_store', 'commodity_category': 'medical_devices_consumables', 'facilities_affected_by_stockout': 6}, {'uid': 'district_store:WH_0012', 'warehouse_id': 'WH_0012', 'warehouse_level': 'district_store', 'commodity_category': 'PPE_IPC_supplies', 'facilities_affected_by_stockout': 5}, {'uid': 'district_store:WH_0041', 'warehouse_id': 'WH_0041', 'warehouse_level': 'district_store', 'commodity_category': 'malaria_commodities', 'facilities_affected_by_stockout': 3}, '... and 33 more']

Q: which items are stocked out in the district_store tier?
A:

Chosen response:
FACTS: 38 active stockouts (warehouse_level=district_store). worst: WH_0022 (district_store, laboratory_reagents), 13 facilities hit
RECOMMENDATION: prioritize WH_0022 (district_store) first.

Rejected response:
FACTS: 38 active stockouts (warehouse_level=district_store). worst: WH_0022 (district_store, laboratory_reagents), 13 facilities hit
RECOMMENDATION: Not sure. (Not enough information to determine)
FACTS: 38 active stockouts (warehouse_level=district_store). worst: WH_0022 (district_store, laboratory_reagents), 13 facilities hit
RECOMMENDATION: Not sure. (Not enough information to determine)


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: shortage_risk({'uid': 'regional_warehouse:WH_0003'}) -> [{'uid': 'regional_warehouse:WH_0003', 'warehouse_id': 'WH_0003', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'PPE_IPC_supplies', 'risk_score': 5.5, 'risk_factors': ['high_backorder_rate', 'low_fulfilment', 'high_wastage', 'criticality_medium']}]

Q: is WH_0003 at the regional_warehouse at risk of running short on anything?
A:

Chosen response:
FACTS: top shortage risk (uid=regional_warehouse:WH_0003) is WH_0003 (regional_warehouse, PPE_IPC_supplies), score=5.5, factors=['high_backorder_rate', 'low_fulfilment', 'high_wastage', 'criticality_medium']
RECOMMENDATION: focus replenishment planning on WH_0003 (regional_warehouse).

Rejected response: not sure, you'd have to check the system yourself


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: backorders({'uid': 'national_CMS:WH_0081'}) -> [{'uid': 'national_CMS:WH_0081', 'warehouse_id': 'WH_0081', 'warehouse_level': 'national_CMS', 'commodity_category': 'laboratory_reagents', 'orders_backordered': 10, 'backorder_rate_pct': 17.9}]

Q: which category has the most backorders at WH_0081 at the national_CMS?
A:

Chosen response:
FACTS: 1 backordered records (uid=national_CMS:WH_0081). worst: WH_0081 (national_CMS, laboratory_reagents) at 17.9% backorder rate
RECOMMENDATION: expedite WH_0081 (national_CMS).

Rejected response:
FACTS: 1 backordered records (uid=national_CMS:WH_0081). worst: WH_0081 (national_CMS, laboratory_reagents) at 17.9% backorder rate
RECOMMENDATION: Not sure about that - would need to check the system for more detail.
FACTS: to repeat, the figure is 1. Again, 1 is the number.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: explain_issue({'uid': 'district_store:WH_0092', 'commodity_category': 'vaccines', 'year': 2023, 'month': 2}) -> {'status': 'ok', 'uid': 'district_store:WH_0092', 'warehouse_id': 'WH_0092', 'warehouse_level': 'district_store', 'year': 2023, 'month': 2, 'reported_issue': 'understocking', 'has_issue': True, 'signals': ['storage conditions not adequate', 'FEFO compliance failed', 'low inventory accuracy (12.5%)', 'high wastage (17.8%)']}

Q: why is WH_0092 at the district_store failing fulfillment for vaccines?
A:

Chosen response:
FACTS: WH_0092 (district_store, 2/2023): reported issue = understocking. other signals: storage conditions not adequate; FEFO compliance failed; low inventory accuracy (12.5%); high wastage (17.8%)
RECOMMENDATION: address the reported issue (understocking).

Rejected response:
FACTS: WH_0092 (district_store, 2/2023): reported issue = understocking. other signals: storage conditions not adequate; FEFO compliance failed; low inventory accuracy (12.5%); high wastage (17.8%)
RECOMMENDATION: Not sure. (Not enough information to determine)

storage conditions not adequate
FEFO compliance failed
low inventory accuracy (12.5%)
high wastage (17.8%)


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: explain_issue({'uid': 'district_store:WH_0075', 'commodity_category': 'medical_devices_consumables', 'year': 2024, 'month': 4}) -> {'status': 'ok', 'uid': 'district_store:WH_0075', 'warehouse_id': 'WH_0075', 'warehouse_level': 'district_store', 'year': 2024, 'month': 4, 'reported_issue': 'stock_record_discrepancy', 'has_issue': True, 'signals': ['FEFO compliance failed', 'low inventory accuracy (51.2%)', 'high wastage (27.6%)', 'active stockout'], 'uncertain': True}

Q: why is WH_0075 at the district_store failing fulfillment for medical devices consumables?
A:

Chosen response:
FACTS: WH_0075 (district_store, 4/2024): reported issue = stock_record_discrepancy. other signals: FEFO compliance failed; low inventory accuracy (51.2%); high wastage (27.6%); active stockout (note: report not submitted, numbers may be provisional)
RECOMMENDATION: address the reported issue (stock_record_discrepancy).

Rejected response: FACTS: address the reported issue (stock_record_discrepancy).

FEFO compliance failed
low inventory accuracy (51.2%)
high wastage (27.6%)
active stockout


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'uid': 'district_store:WH_0011'}) -> {'n_records': 1, 'avg_inventory_accuracy_pct': 17.7, 'avg_order_fulfilment_rate_pct': 35.8, 'months_with_stockout': 0, 'issue_counts': {'dispatch_error': 1}, 'uid': 'district_store:WH_0011', 'warehouse_id': 'WH_0011', 'warehouse_level': 'district_store'}

Q: how is WH_0011 at the district_store doing overall?
A:

Chosen response:
FACTS: WH_0011 (district_store): avg inventory accuracy 17.7%, avg fulfilment 35.8%, 0 months w/ stockout (based on 1 records), issues on record: {'dispatch_error': 1}
RECOMMENDATION: looks fine.

Rejected response:
FACTS: WH_0011 (district_store): avg inventory accuracy 17.7%, avg fulfilment 35.8%, 0 months w/ stockout (based on 1 records), issues on record: {'dispatch_error': 1}
RECOMMENDATION: Not sure about that - would need to check the system for more detail.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'uid': 'district_store:WH_0070'}) -> {'n_records': 1, 'avg_inventory_accuracy_pct': 36.9, 'avg_order_fulfilment_rate_pct': 43.1, 'months_with_stockout': 1, 'issue_counts': {'stock_record_discrepancy': 1}, 'uid': 'district_store:WH_0070', 'warehouse_id': 'WH_0070', 'warehouse_level': 'district_store'}

Q: how is WH_0070 at the district_store doing overall?
A:

Chosen response:
FACTS: WH_0070 (district_store): avg inventory accuracy 36.9%, avg fulfilment 43.1%, 1 months w/ stockout (based on 1 records), issues on record: {'stock_record_discrepancy': 1}
RECOMMENDATION: worth a review.

Rejected response: FACTS: worth a review.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: stockouts({'compare_by': 'region_type', 'compare_values': ['rural', 'urban']}) -> {'_grouped_by': 'region_type', 'groups': {'rural': [{'uid': 'national_CMS:WH_0074', 'warehouse_id': 'WH_0074', 'warehouse_level': 'national_CMS', 'commodity_category': 'vaccines', 'facilities_affected_by_stockout': 60}, {'uid': 'regional_warehouse:WH_0025', 'warehouse_id': 'WH_0025', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'ARVs', 'facilities_affected_by_stockout': 38}, {'uid': 'regional_warehouse:WH_0064', 'warehouse_id': 'WH_0064', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'laboratory_reagents', 'facilities_affected_by_stockout': 28}, {'uid': 'regional_warehouse:WH_0012', 'warehouse_id': 'WH_0012', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'vaccines', 'facilities_affected_by_stockout': 25}, {'uid': 'regional_warehouse:WH_0070', 'warehouse_id': 'WH_0070', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'vaccines', 'facilities_affected_by_stockout': 18}, {'uid': 'district_store:WH_0022', 'warehouse_id': 'WH_0022', 'warehouse_level': 'district_store', 'commodity_category': 'laboratory_reagents', 'facilities_affected_by_stockout': 13}, {'uid': 'regional_warehouse:WH_0074', 'warehouse_id': 'WH_0074', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'ARVs', 'facilities_affected_by_stockout': 12}, {'uid': 'district_store:WH_0014', 'warehouse_id': 'WH_0014', 'warehouse_level': 'district_store', 'commodity_category': 'controlled_substances', 'facilities_affected_by_stockout': 7}, {'uid': 'regional_warehouse:WH_0053', 'warehouse_id': 'WH_0053', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'contraceptives', 'facilities_affected_by_stockout': 7}, {'uid': 'district_store:WH_0042', 'warehouse_id': 'WH_0042', 'warehouse_level': 'district_store', 'commodity_category': 'medical_devices_consumables', 'facilities_affected_by_stockout': 6}, {'uid': 'regional_warehouse:WH_0013', 'warehouse_id': 'WH_0013', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'surgical_supplies', 'facilities_affected_by_stockout': 6}, {'uid': 'district_store:WH_0012', 'warehouse_id': 'WH_0012', 'warehouse_level': 'district_store', 'commodity_category': 'PPE_IPC_supplies', 'facilities_affected_by_stockout': 5}, {'uid': 'regional_warehouse:WH_0009', 'warehouse_id': 'WH_0009', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'essential_medicines', 'facilities_affected_by_stockout': 5}, {'uid': 'regional_warehouse:WH_0053', 'warehouse_id': 'WH_0053', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'laboratory_reagents', 'facilities_affected_by_stockout': 5}, {'uid': 'district_store:WH_0041', 'warehouse_id': 'WH_0041', 'warehouse_level': 'district_store', 'commodity_category': 'malaria_commodities', 'facilities_affected_by_stockout': 3}, {'uid': 'district_store:WH_0042', 'warehouse_id': 'WH_0042', 'warehouse_level': 'district_store', 'commodity_category': 'controlled_substances', 'facilities_affected_by_stockout': 3}, {'uid': 'district_store:WH_0075', 'warehouse_id': 'WH_0075', 'warehouse_level': 'district_store', 'commodity_category': 'PPE_IPC_supplies', 'facilities_affected_by_stockout': 2}, {'uid': 'district_store:WH_0080', 'warehouse_id': 'WH_0080', 'warehouse_level': 'district_store', 'commodity_category': 'IV_fluids', 'facilities_affected_by_stockout': 2}, {'uid': 'district_store:WH_0024', 'warehouse_id': 'WH_0024', 'warehouse_level': 'district_store', 'commodity_category': 'nutrition_commodities', 'facilities_affected_by_stockout': 2}, {'uid': 'district_store:WH_0080', 'warehouse_id': 'WH_0080', 'warehouse_level': 'district_store', 'commodity_category': 'essential_medicines', 'facilities_affected_by_stockout': 2}, {'uid': 'district_store:WH_0054', 'warehouse_id': 'WH_0054', 'warehouse_level': 'district_store', 'commodity_category': 'surgical_supplies', 'facilities_affected_by_stockout': 2}, {'uid': 'district_store:WH_0078', 'warehouse_id': 'WH_0078', 'warehouse_level': 'district_store', 'commodity_category': 'contraceptives', 'facilities_affected_by_stockout': 2}, {'uid': 'district_store:WH_0045', 'warehouse_id': 'WH_0045', 'warehouse_level': 'district_store', 'commodity_category': 'nutrition_commodities', 'facilities_affected_by_stockout': 2}, {'uid': 'district_store:WH_0001', 'warehouse_id': 'WH_0001', 'warehouse_level': 'district_store', 'commodity_category': 'laboratory_reagents', 'facilities_affected_by_stockout': 2}, {'uid': 'district_store:WH_0094', 'warehouse_id': 'WH_0094', 'warehouse_level': 'district_store', 'commodity_category': 'vaccines', 'facilities_affected_by_stockout': 2}, {'uid': 'district_store:WH_0033', 'warehouse_id': 'WH_0033', 'warehouse_level': 'district_store', 'commodity_category': 'ARVs', 'facilities_affected_by_stockout': 1}, {'uid': 'district_store:WH_0028', 'warehouse_id': 'WH_0028', 'warehouse_level': 'district_store', 'commodity_category': 'vaccines', 'facilities_affected_by_stockout': 1}, {'uid': 'district_store:WH_0075', 'warehouse_id': 'WH_0075', 'warehouse_level': 'district_store', 'commodity_category': 'medical_devices_consumables', 'facilities_affected_by_stockout': 1}, {'uid': 'district_store:WH_0006', 'warehouse_id': 'WH_0006', 'warehouse_level': 'district_store', 'commodity_category': 'controlled_substances', 'facilities_affected_by_stockout': 1}, {'uid': 'district_store:WH_0033', 'warehouse_id': 'WH_0033', 'warehouse_level': 'district_store', 'commodity_category': 'malaria_commodities', 'facilities_affected_by_stockout': 1}, {'uid': 'district_store:WH_0094', 'warehouse_id': 'WH_0094', 'warehouse_level': 'district_store', 'commodity_category': 'PPE_IPC_supplies', 'facilities_affected_by_stockout': 1}, {'uid': 'district_store:WH_0099', 'warehouse_id': 'WH_0099', 'warehouse_level': 'district_store', 'commodity_category': 'controlled_substances', 'facilities_affected_by_stockout': 1}, {'uid': 'regional_warehouse:WH_0096', 'warehouse_id': 'WH_0096', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'surgical_supplies', 'facilities_affected_by_stockout': 1}, {'uid': 'regional_warehouse:WH_0007', 'warehouse_id': 'WH_0007', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'controlled_substances', 'facilities_affected_by_stockout': 1}, {'uid': 'district_store:WH_0009', 'warehouse_id': 'WH_0009', 'warehouse_level': 'district_store', 'commodity_category': 'essential_medicines', 'facilities_affected_by_stockout': 0}, {'uid': 'district_store:WH_0071', 'warehouse_id': 'WH_0071', 'warehouse_level': 'district_store', 'commodity_category': 'surgical_supplies', 'facilities_affected_by_stockout': 0}, {'uid': 'district_store:WH_0033', 'warehouse_id': 'WH_0033', 'warehouse_level': 'district_store', 'commodity_category': 'laboratory_reagents', 'facilities_affected_by_stockout': 0}, {'uid': 'district_store:WH_0098', 'warehouse_id': 'WH_0098', 'warehouse_level': 'district_store', 'commodity_category': 'essential_medicines', 'facilities_affected_by_stockout': 0}, {'uid': 'district_store:WH_0019', 'warehouse_id': 'WH_0019', 'warehouse_level': 'district_store', 'commodity_category': 'nutrition_commodities', 'facilities_affected_by_stockout': 0}, {'uid': 'district_store:WH_0069', 'warehouse_id': 'WH_0069', 'warehouse_level': 'district_store', 'commodity_category': 'medical_devices_consumables', 'facilities_affected_by_stockout': 0}, {'uid': 'district_store:WH_0010', 'warehouse_id': 'WH_0010', 'warehouse_level': 'district_store', 'commodity_category': 'malaria_commodities', 'facilities_affected_by_stockout': 0}, {'uid': 'district_store:WH_0018', 'warehouse_id': 'WH_0018', 'warehouse_level': 'district_store', 'commodity_category': 'nutrition_commodities', 'facilities_affected_by_stockout': 0}, {'uid': 'district_store:WH_0007', 'warehouse_id': 'WH_0007', 'warehouse_level': 'district_store', 'commodity_category': 'IV_fluids', 'facilities_affected_by_stockout': 0}, {'uid': 'district_store:WH_0019', 'warehouse_id': 'WH_0019', 'warehouse_level': 'district_store', 'commodity_category': 'controlled_substances', 'facilities_affected_by_stockout': 0}, {'uid': 'regional_warehouse:WH_0098', 'warehouse_id': 'WH_0098', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'malaria_commodities', 'facilities_affected_by_stockout': 0}], 'urban': [{'uid': 'regional_warehouse:WH_0075', 'warehouse_id': 'WH_0075', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'medical_devices_consumables', 'facilities_affected_by_stockout': 17}, {'uid': 'national_CMS:WH_0008', 'warehouse_id': 'WH_0008', 'warehouse_level': 'national_CMS', 'commodity_category': 'essential_medicines', 'facilities_affected_by_stockout': 14}, {'uid': 'national_CMS:WH_0015', 'warehouse_id': 'WH_0015', 'warehouse_level': 'national_CMS', 'commodity_category': 'essential_medicines', 'facilities_affected_by_stockout': 14}, {'uid': 'regional_warehouse:WH_0050', 'warehouse_id': 'WH_0050', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'medical_devices_consumables', 'facilities_affected_by_stockout': 8}, {'uid': 'national_CMS:WH_0003', 'warehouse_id': 'WH_0003', 'warehouse_level': 'national_CMS', 'commodity_category': 'medical_devices_consumables', 'facilities_affected_by_stockout': 7}, {'uid': 'national_CMS:WH_0002', 'warehouse_id': 'WH_0002', 'warehouse_level': 'national_CMS', 'commodity_category': 'ARVs', 'facilities_affected_by_stockout': 5}, {'uid': 'national_CMS:WH_0080', 'warehouse_id': 'WH_0080', 'warehouse_level': 'national_CMS', 'commodity_category': 'controlled_substances', 'facilities_affected_by_stockout': 5}, {'uid': 'national_CMS:WH_0099', 'warehouse_id': 'WH_0099', 'warehouse_level': 'national_CMS', 'commodity_category': 'controlled_substances', 'facilities_affected_by_stockout': 3}, {'uid': 'district_store:WH_0070', 'warehouse_id': 'WH_0070', 'warehouse_level': 'district_store', 'commodity_category': 'vaccines', 'facilities_affected_by_stockout': 2}, {'uid': 'district_store:WH_0068', 'warehouse_id': 'WH_0068', 'warehouse_level': 'district_store', 'commodity_category': 'essential_medicines', 'facilities_affected_by_stockout': 2}, {'uid': 'national_CMS:WH_0096', 'warehouse_id': 'WH_0096', 'warehouse_level': 'national_CMS', 'commodity_category': 'malaria_commodities', 'facilities_affected_by_stockout': 0}, {'uid': 'regional_warehouse:WH_0022', 'warehouse_id': 'WH_0022', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'contraceptives', 'facilities_affected_by_stockout': 0}]}}

Q: how do rural and urban compare on stockouts?
A:

Chosen response:
FACTS: stockouts by region_type: rural: 45 stockouts, worst WH_0074 (vaccines, 60 facilities); urban: 12 stockouts, worst WH_0075 (medical_devices_consumables, 17 facilities)
RECOMMENDATION: prioritize the rural group first - most facilities affected.

Rejected response:
FACTS: stockouts by region_type: rural: 45 stockouts, worst WH_0074 (vaccines, 60 facilities); urban: 12 stockouts, worst WH_0075 (medical_devices_consumables, 17 facilities)
RECOMMENDATION: Not sure. (Not enough information to determine)


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: stockouts({'uid': 'national_CMS:WH_0079'}) -> []

Q: does WH_0079 at the national_CMS currently have any active stockouts?
A:

Chosen response:
FACTS: no active stockouts (uid=national_CMS:WH_0079)
RECOMMENDATION: nothing urgent here.

Rejected response:
FACTS: no active stockouts (uid=national_CMS:WH_0079)
RECOMMENDATION: Not sure. To get more information, I would need to check further.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'uid': 'district_store:WH_0022'}) -> {'n_records': 2, 'avg_inventory_accuracy_pct': 29.3, 'avg_order_fulfilment_rate_pct': 21.6, 'months_with_stockout': 1, 'issue_counts': {'theft_pilferage': 1, 'dispatch_error': 1}, 'uid': 'district_store:WH_0022', 'warehouse_id': 'WH_0022', 'warehouse_level': 'district_store'}

Q: how is WH_0022 at the district_store doing overall?
A:

Chosen response:
FACTS: WH_0022 (district_store): avg inventory accuracy 29.3%, avg fulfilment 21.6%, 1 months w/ stockout (based on 2 records), issues on record: {'theft_pilferage': 1, 'dispatch_error': 1}
RECOMMENDATION: worth a review.

Rejected response:
FACTS: WH_0022 (district_store): avg inventory accuracy 29.3%, avg fulfilment 21.6%, 1 months w/ stockout (based on 2 records), issues on record: {'theft_pilferage': 1, 'dispatch_error': 1}
RECOMMENDATION: Not sure about that - would need to check the system for more detail.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: shortage_risk({'uid': 'national_CMS:WH_0016'}) -> [{'uid': 'national_CMS:WH_0016', 'warehouse_id': 'WH_0016', 'warehouse_level': 'national_CMS', 'commodity_category': 'IV_fluids', 'risk_score': 6.5, 'risk_factors': ['high_backorder_rate', 'low_fulfilment', 'high_wastage', 'criticality_high']}]

Q: is WH_0016 at the national_CMS at risk of running short on anything?
A:

Chosen response:
FACTS: top shortage risk (uid=national_CMS:WH_0016) is WH_0016 (national_CMS, IV_fluids), score=6.5, factors=['high_backorder_rate', 'low_fulfilment', 'high_wastage', 'criticality_high']
RECOMMENDATION: focus replenishment planning on WH_0016 (national_CMS).

Rejected response: not sure, you'd have to check the system yourself


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'uid': 'national_CMS:WH_0024'}) -> {'n_records': 1, 'avg_inventory_accuracy_pct': 76.5, 'avg_order_fulfilment_rate_pct': 80.6, 'months_with_stockout': 0, 'issue_counts': {'damaged_goods': 1}, 'uid': 'national_CMS:WH_0024', 'warehouse_id': 'WH_0024', 'warehouse_level': 'national_CMS'}

Q: how is WH_0024 at the national_CMS doing overall?
A:

Chosen response:
FACTS: WH_0024 (national_CMS): avg inventory accuracy 76.5%, avg fulfilment 80.6%, 0 months w/ stockout (based on 1 records), issues on record: {'damaged_goods': 1}
RECOMMENDATION: looks fine.

Rejected response:
FACTS: WH_0024 (national_CMS): avg inventory accuracy 97.5%, avg fulfilment 80.6%, 0 months w/ stockout (based on 1 records), issues on record: {'damaged_goods': 1}
RECOMMENDATION: looks fine.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: shortage_risk({'uid': 'district_store:WH_0063'}) -> [{'uid': 'district_store:WH_0063', 'warehouse_id': 'WH_0063', 'warehouse_level': 'district_store', 'commodity_category': 'surgical_supplies', 'risk_score': 7.0, 'risk_factors': ['high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_medium']}]

Q: is WH_0063 at the district_store at risk of running short on anything?
A:

Chosen response:
FACTS: top shortage risk (uid=district_store:WH_0063) is WH_0063 (district_store, surgical_supplies), score=7.0, factors=['high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_medium']
RECOMMENDATION: focus replenishment planning on WH_0063 (district_store).

Rejected response:
FACTS: top shortage risk (uid=district_store:WH_0063) is WH_0063 (district_store, surgical_supplies), score=7.0, factors=['high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_medium'] Not entirely sure if this is complete.
RECOMMENDATION: focus replenishment planning on WH_0063 (district_store).


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: explain_issue({'uid': 'regional_warehouse:WH_0037', 'commodity_category': 'ARVs', 'year': 2024, 'month': 12}) -> {'status': 'ok', 'uid': 'regional_warehouse:WH_0037', 'warehouse_id': 'WH_0037', 'warehouse_level': 'regional_warehouse', 'year': 2024, 'month': 12, 'reported_issue': 'pest_infestation', 'has_issue': True, 'signals': ['FEFO compliance failed', 'low inventory accuracy (47.0%)', 'high wastage (21.4%)']}

Q: why is WH_0037 at the regional_warehouse failing fulfillment for ARVs?
A:

Chosen response:
FACTS: WH_0037 (regional_warehouse, 12/2024): reported issue = pest_infestation. other signals: FEFO compliance failed; low inventory accuracy (47.0%); high wastage (21.4%)
RECOMMENDATION: address the reported issue (pest_infestation).

Rejected response: not sure, you'd have to check the system yourself

FEFO compliance failed
low inventory accuracy (47.0%)
high wastage (21.4%)


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'uid': 'regional_warehouse:WH_0028'}) -> {'n_records': 2, 'avg_inventory_accuracy_pct': 39.2, 'avg_order_fulfilment_rate_pct': 52.5, 'months_with_stockout': 0, 'issue_counts': {'receiving_error': 1, 'dispatch_error': 1}, 'uid': 'regional_warehouse:WH_0028', 'warehouse_id': 'WH_0028', 'warehouse_level': 'regional_warehouse'}

Q: how is WH_0028 at the regional_warehouse doing overall?
A:

Chosen response:
FACTS: WH_0028 (regional_warehouse): avg inventory accuracy 39.2%, avg fulfilment 52.5%, 0 months w/ stockout (based on 2 records), issues on record: {'receiving_error': 1, 'dispatch_error': 1}
RECOMMENDATION: looks fine.

Rejected response:
FACTS: WH_0455 (regional_warehouse): avg inventory accuracy 39.2%, avg fulfilment 52.5%, 0 months w/ stockout (based on 2 records), issues on record: {'receiving_error': 1, 'dispatch_error': 1}
RECOMMENDATION: looks fine.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: shortage_risk({'uid': 'district_store:WH_0026'}) -> [{'uid': 'district_store:WH_0026', 'warehouse_id': 'WH_0026', 'warehouse_level': 'district_store', 'commodity_category': 'laboratory_reagents', 'risk_score': 10.0, 'risk_factors': ['stockout', 'high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_medium']}]

Q: is WH_0026 at the district_store at risk of running short on anything?
A:

Chosen response:
FACTS: top shortage risk (uid=district_store:WH_0026) is WH_0026 (district_store, laboratory_reagents), score=10.0, factors=['stockout', 'high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_medium']
RECOMMENDATION: focus replenishment planning on WH_0026 (district_store).

Rejected response:
FACTS: top shortage risk (uid=district_store:WH_0026) is WH_0026 (district_store, unclassified_stock), score=10.0, factors=['stockout', 'high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_medium']
RECOMMENDATION: focus replenishment planning on WH_0026 (district_store).


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: shortage_risk({'uid': 'regional_warehouse:WH_0042'}) -> [{'uid': 'regional_warehouse:WH_0042', 'warehouse_id': 'WH_0042', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'laboratory_reagents', 'risk_score': 7.0, 'risk_factors': ['high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_medium']}]

Q: is WH_0042 at the regional_warehouse at risk of running short on anything?
A:

Chosen response:
FACTS: top shortage risk (uid=regional_warehouse:WH_0042) is WH_0042 (regional_warehouse, laboratory_reagents), score=7.0, factors=['high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_medium']
RECOMMENDATION: focus replenishment planning on WH_0042 (regional_warehouse).

Rejected response: not sure, you'd have to check the system yourself


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: explain_issue({'uid': 'district_store:WH_0087', 'commodity_category': 'vaccines', 'year': 2022, 'month': 7}) -> {'status': 'ok', 'uid': 'district_store:WH_0087', 'warehouse_id': 'WH_0087', 'warehouse_level': 'district_store', 'year': 2022, 'month': 7, 'reported_issue': 'overstocking', 'has_issue': True, 'signals': ['storage conditions not adequate', 'FEFO compliance failed', 'low inventory accuracy (24.5%)', 'high wastage (30.1%)', 'active stockout'], 'uncertain': True}

Q: why is WH_0087 at the district_store failing fulfillment for vaccines?
A:

Chosen response:
FACTS: WH_0087 (district_store, 7/2022): reported issue = overstocking. other signals: storage conditions not adequate; FEFO compliance failed; low inventory accuracy (24.5%); high wastage (30.1%); active stockout (note: report not submitted, numbers may be provisional)
RECOMMENDATION: address the reported issue (overstocking).

Rejected response:
FACTS: WH_0188 (district_store, 7/2022): reported issue = overstocking. other signals: storage conditions not adequate; FEFO compliance failed; low inventory accuracy (24.5%); high wastage (30.1%); active stockout (note: report not submitted, numbers may be provisional)
RECOMMENDATION: address the reported issue (overstocking).

storage conditions not adequate
FEFO compliance failed
low inventory accuracy (24.5%)
high wastage (30.1%)
active stockout


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: stockouts({'uid': 'regional_warehouse:WH_0041'}) -> []

Q: does WH_0041 at the regional_warehouse currently have any active stockouts?
A:

Chosen response:
FACTS: no active stockouts (uid=regional_warehouse:WH_0041)
RECOMMENDATION: nothing urgent here.

Rejected response:
FACTS: no active stockouts (uid=regional_warehouse:WH_0041)
RECOMMENDATION: Not sure about that - would need to check the system for more detail.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: explain_issue({'uid': 'regional_warehouse:WH_0090', 'commodity_category': 'laboratory_reagents', 'year': 2021, 'month': 3}) -> {'status': 'ok', 'uid': 'regional_warehouse:WH_0090', 'warehouse_id': 'WH_0090', 'warehouse_level': 'regional_warehouse', 'year': 2021, 'month': 3, 'reported_issue': 'damaged_goods', 'has_issue': True, 'signals': ['storage conditions not adequate', 'FEFO compliance failed', 'low inventory accuracy (61.7%)', 'high wastage (21.7%)']}

Q: why is WH_0090 at the regional_warehouse failing fulfillment for laboratory reagents?
A:

Chosen response:
FACTS: WH_0090 (regional_warehouse, 3/2021): reported issue = damaged_goods. other signals: storage conditions not adequate; FEFO compliance failed; low inventory accuracy (61.7%); high wastage (21.7%)
RECOMMENDATION: address the reported issue (damaged_goods).

Rejected response:
FACTS: WH_0090 (regional_warehouse, 3/2021): reported issue = damaged_goods. other signals: storage conditions not adequate; FEFO compliance failed; low inventory accuracy (61.7%); high wastage (21.7%)
RECOMMENDATION: Not sure about that - would need to check the system for more detail.
FACTS: to repeat, the figure is 3. Again, 3 is the number.

storage conditions not adequate
FEFO compliance failed
low inventory accuracy (61.7%)
high wastage (21.7%)


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'uid': 'district_store:WH_0018'}) -> {'n_records': 2, 'avg_inventory_accuracy_pct': 29.3, 'avg_order_fulfilment_rate_pct': 53.1, 'months_with_stockout': 1, 'issue_counts': {'overstocking': 1, 'receiving_error': 1}, 'uid': 'district_store:WH_0018', 'warehouse_id': 'WH_0018', 'warehouse_level': 'district_store'}

Q: how is WH_0018 at the district_store doing overall?
A:

Chosen response:
FACTS: WH_0018 (district_store): avg inventory accuracy 29.3%, avg fulfilment 53.1%, 1 months w/ stockout (based on 2 records), issues on record: {'overstocking': 1, 'receiving_error': 1}
RECOMMENDATION: worth a review.

Rejected response:
FACTS: WH_0018 (district_store): avg inventory accuracy 29.3%, avg fulfilment 53.1%, 1 months w/ stockout (based on 2 records), issues on record: {'overstocking': 1, 'receiving_error': 1} Not sure if there's more to report here.
RECOMMENDATION: worth a review.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: backorders({'uid': 'national_CMS:WH_0018'}) -> [{'uid': 'national_CMS:WH_0018', 'warehouse_id': 'WH_0018', 'warehouse_level': 'national_CMS', 'commodity_category': 'vaccines', 'orders_backordered': 15, 'backorder_rate_pct': 30.6}]

Q: which category has the most backorders at WH_0018 at the national_CMS?
A:

Chosen response:
FACTS: 1 backordered records (uid=national_CMS:WH_0018). worst: WH_0018 (national_CMS, vaccines) at 30.6% backorder rate
RECOMMENDATION: expedite WH_0018 (national_CMS).

Rejected response:
FACTS: 1 backordered records (uid=national_CMS:WH_0761). worst: WH_0761 (national_CMS, vaccines) at 30.6% backorder rate
RECOMMENDATION: expedite WH_0761 (national_CMS).


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: backorders({'region_type': 'urban'}) -> [{'uid': 'district_store:WH_0068', 'warehouse_id': 'WH_0068', 'warehouse_level': 'district_store', 'commodity_category': 'essential_medicines', 'orders_backordered': 7, 'backorder_rate_pct': 87.5}, {'uid': 'regional_warehouse:WH_0050', 'warehouse_id': 'WH_0050', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'medical_devices_consumables', 'orders_backordered': 10, 'backorder_rate_pct': 76.9}, {'uid': 'regional_warehouse:WH_0022', 'warehouse_id': 'WH_0022', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'contraceptives', 'orders_backordered': 9, 'backorder_rate_pct': 75.0}, {'uid': 'regional_warehouse:WH_0030', 'warehouse_id': 'WH_0030', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'contraceptives', 'orders_backordered': 6, 'backorder_rate_pct': 66.7}, {'uid': 'regional_warehouse:WH_0079', 'warehouse_id': 'WH_0079', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'essential_medicines', 'orders_backordered': 6, 'backorder_rate_pct': 60.0}, '... and 47 more']

Q: which items are backordered in urban areas?
A:

Chosen response:
FACTS: 52 backordered records (region_type=urban). worst: WH_0068 (district_store, essential_medicines) at 87.5% backorder rate
RECOMMENDATION: expedite WH_0068 (district_store).

Rejected response: not sure, you'd have to check the system yourself


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: backorders({'uid': 'regional_warehouse:WH_0074'}) -> [{'uid': 'regional_warehouse:WH_0074', 'warehouse_id': 'WH_0074', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'ARVs', 'orders_backordered': 8, 'backorder_rate_pct': 38.1}]

Q: which category has the most backorders at WH_0074 at the regional_warehouse?
A:

Chosen response:
FACTS: 1 backordered records (uid=regional_warehouse:WH_0074). worst: WH_0074 (regional_warehouse, ARVs) at 38.1% backorder rate
RECOMMENDATION: expedite WH_0074 (regional_warehouse).

Rejected response:
FACTS: 1 backordered records (uid=regional_warehouse:WH_0074). worst: WH_0074 (regional_warehouse, ARVs) at 38.1% backorder rate
RECOMMENDATION: Not sure. To get more information, I would need to check further.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: explain_issue({'uid': 'regional_warehouse:WH_0027', 'commodity_category': 'surgical_supplies', 'year': 2023, 'month': 12}) -> {'status': 'ok', 'uid': 'regional_warehouse:WH_0027', 'warehouse_id': 'WH_0027', 'warehouse_level': 'regional_warehouse', 'year': 2023, 'month': 12, 'reported_issue': 'receiving_error', 'has_issue': True, 'signals': ['FEFO compliance failed', 'low inventory accuracy (27.0%)', 'high wastage (14.3%)', 'active stockout'], 'uncertain': True}

Q: why is WH_0027 at the regional_warehouse failing fulfillment for surgical supplies?
A:

Chosen response:
FACTS: WH_0027 (regional_warehouse, 12/2023): reported issue = receiving_error. other signals: FEFO compliance failed; low inventory accuracy (27.0%); high wastage (14.3%); active stockout (note: report not submitted, numbers may be provisional)
RECOMMENDATION: address the reported issue (receiving_error).

Rejected response:
FACTS: WH_0336 (regional_warehouse, 12/2023): reported issue = receiving_error. other signals: FEFO compliance failed; low inventory accuracy (27.0%); high wastage (14.3%); active stockout (note: report not submitted, numbers may be provisional)
RECOMMENDATION: address the reported issue (receiving_error).
FACTS: WH_0336 (regional_warehouse, 12/2023): reported issue = receiving_error. other signals: FEFO compliance failed; low inventory accuracy (27.0%); high wastage (14.3%); active stockout (note: report not submitted, numbers may be provisional)
RECOMMENDATION: address the reported issue (receiving_error).

FEFO compliance failed
low inventory accuracy (27.0%)
high wastage (14.3%)
active stockout


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: stockouts({'uid': 'district_store:WH_0092'}) -> []

Q: does WH_0092 at the district_store currently have any active stockouts?
A:

Chosen response:
FACTS: no active stockouts (uid=district_store:WH_0092)
RECOMMENDATION: nothing urgent here.

Rejected response:
FACTS: no active stockouts (uid=district_store:WH_0092)
RECOMMENDATION: Not sure. (Not enough information)


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: backorders({'uid': 'national_CMS:WH_0082'}) -> [{'uid': 'national_CMS:WH_0082', 'warehouse_id': 'WH_0082', 'warehouse_level': 'national_CMS', 'commodity_category': 'nutrition_commodities', 'orders_backordered': 16, 'backorder_rate_pct': 39.0}, {'uid': 'national_CMS:WH_0082', 'warehouse_id': 'WH_0082', 'warehouse_level': 'national_CMS', 'commodity_category': 'surgical_supplies', 'orders_backordered': 15, 'backorder_rate_pct': 32.6}]

Q: which category has the most backorders at WH_0082 at the national_CMS?
A:

Chosen response:
FACTS: 2 backordered records (uid=national_CMS:WH_0082). worst: WH_0082 (national_CMS, nutrition_commodities) at 39.0% backorder rate
RECOMMENDATION: expedite WH_0082 (national_CMS).

Rejected response:
FACTS: 2 backordered records (uid=national_CMS:WH_0082). worst: WH_0082 (national_CMS, nutrition_commodities) at 39.0% backorder rate
RECOMMENDATION: Not sure. To get more information, I would need to check further.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: stockouts({'uid': 'district_store:WH_0078'}) -> [{'uid': 'district_store:WH_0078', 'warehouse_id': 'WH_0078', 'warehouse_level': 'district_store', 'commodity_category': 'contraceptives', 'facilities_affected_by_stockout': 2}]

Q: does WH_0078 at the district_store currently have any active stockouts?
A:

Chosen response:
FACTS: 1 active stockouts (uid=district_store:WH_0078). worst: WH_0078 (district_store, contraceptives), 2 facilities hit
RECOMMENDATION: prioritize WH_0078 (district_store) first.

Rejected response: FACTS: prioritize WH_0078 (district_store) first.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: shortage_risk({'uid': 'regional_warehouse:WH_0029'}) -> [{'uid': 'regional_warehouse:WH_0029', 'warehouse_id': 'WH_0029', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'vaccines', 'risk_score': 8.5, 'risk_factors': ['high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_critical']}, {'uid': 'regional_warehouse:WH_0029', 'warehouse_id': 'WH_0029', 'warehouse_level': 'regional_warehouse', 'commodity_category': 'essential_medicines', 'risk_score': 6.5, 'risk_factors': ['high_backorder_rate', 'low_fulfilment', 'high_wastage', 'criticality_high']}]

Q: is WH_0029 at the regional_warehouse at risk of running short on anything?
A:

Chosen response:
FACTS: top shortage risk (uid=regional_warehouse:WH_0029) is WH_0029 (regional_warehouse, vaccines), score=8.5, factors=['high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_critical']
RECOMMENDATION: focus replenishment planning on WH_0029 (regional_warehouse).

Rejected response: not sure, you'd have to check the system yourself


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: backorders({'uid': 'district_store:WH_0026'}) -> [{'uid': 'district_store:WH_0026', 'warehouse_id': 'WH_0026', 'warehouse_level': 'district_store', 'commodity_category': 'laboratory_reagents', 'orders_backordered': 3, 'backorder_rate_pct': 75.0}]

Q: which category has the most backorders at WH_0026 at the district_store?
A:

Chosen response:
FACTS: 1 backordered records (uid=district_store:WH_0026). worst: WH_0026 (district_store, laboratory_reagents) at 75.0% backorder rate
RECOMMENDATION: expedite WH_0026 (district_store).

Rejected response:
FACTS: 1 backordered records (uid=district_store:WH_0026). worst: WH_0026 (district_store, laboratory_reagents) at 75.0% backorder rate Not sure about the rest of the details.
RECOMMENDATION: expedite WH_0026 (district_store).


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: shortage_risk({'uid': 'national_CMS:WH_0024'}) -> [{'uid': 'national_CMS:WH_0024', 'warehouse_id': 'WH_0024', 'warehouse_level': 'national_CMS', 'commodity_category': 'PPE_IPC_supplies', 'risk_score': 1.5, 'risk_factors': ['high_wastage', 'criticality_medium']}]

Q: is WH_0024 at the national_CMS at risk of running short on anything?
A:

Chosen response:
FACTS: top shortage risk (uid=national_CMS:WH_0024) is WH_0024 (national_CMS, PPE_IPC_supplies), score=1.5, factors=['high_wastage', 'criticality_medium']
RECOMMENDATION: focus replenishment planning on WH_0024 (national_CMS).

Rejected response: not sure, you'd have to check the system yourself


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({}) -> {'n_records': 210, 'avg_inventory_accuracy_pct': 52.7, 'avg_order_fulfilment_rate_pct': 53.4, 'months_with_stockout': 77, 'issue_counts': {'theft_pilferage': 18, 'expired_stock': 18, 'stock_record_discrepancy': 18, 'temperature_excursion': 18, 'FEFO_not_followed': 18, 'damaged_goods': 18, 'overstocking': 18, 'receiving_error': 18, 'understocking': 18, 'dispatch_error': 18, 'pest_infestation': 18}}

Q: what are the overall kpis?
A:

Chosen response:
FACTS: avg inventory accuracy 52.7%, avg fulfilment 53.4%, 77 months w/ stockout (based on 210 records), issues on record: {'theft_pilferage': 18, 'expired_stock': 18, 'stock_record_discrepancy': 18, 'temperature_excursion': 18, 'FEFO_not_followed': 18, 'damaged_goods': 18, 'overstocking': 18, 'receiving_error': 18, 'understocking': 18, 'dispatch_error': 18, 'pest_infestation': 18}
RECOMMENDATION: worth a review.

Rejected response: not sure, you'd have to check the system yourself


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: explain_issue({'uid': 'district_store:WH_0018', 'commodity_category': 'contraceptives', 'year': 2022, 'month': 1}) -> {'status': 'ok', 'uid': 'district_store:WH_0018', 'warehouse_id': 'WH_0018', 'warehouse_level': 'district_store', 'year': 2022, 'month': 1, 'reported_issue': 'overstocking', 'has_issue': True, 'signals': ['storage conditions not adequate', 'low inventory accuracy (35.9%)', 'high wastage (33.4%)'], 'uncertain': True}

Q: why is WH_0018 at the district_store failing fulfillment for contraceptives?
A:

Chosen response:
FACTS: WH_0018 (district_store, 1/2022): reported issue = overstocking. other signals: storage conditions not adequate; low inventory accuracy (35.9%); high wastage (33.4%) (note: report not submitted, numbers may be provisional)
RECOMMENDATION: address the reported issue (overstocking).

Rejected response:
FACTS: WH_0561 (district_store, 1/2022): reported issue = overstocking. other signals: storage conditions not adequate; low inventory accuracy (35.9%); high wastage (33.4%) (note: report not submitted, numbers may be provisional)
RECOMMENDATION: address the reported issue (overstocking).

storage conditions not adequate
low inventory accuracy (35.9%)
high wastage (33.4%)


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: backorders({'uid': 'district_store:WH_0063'}) -> [{'uid': 'district_store:WH_0063', 'warehouse_id': 'WH_0063', 'warehouse_level': 'district_store', 'commodity_category': 'surgical_supplies', 'orders_backordered': 3, 'backorder_rate_pct': 75.0}]

Q: which category has the most backorders at WH_0063 at the district_store?
A:

Chosen response:
FACTS: 1 backordered records (uid=district_store:WH_0063). worst: WH_0063 (district_store, surgical_supplies) at 75.0% backorder rate
RECOMMENDATION: expedite WH_0063 (district_store).

Rejected response:
FACTS: 1 backordered records (uid=district_store:WH_0063). worst: WH_0063 (district_store, surgical_supplies) at 75.0% backorder rate
RECOMMENDATION: Not sure about that - would need to check the system for more detail.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'compare_by': 'region_type', 'compare_values': ['peri_urban', 'urban']}) -> {'_grouped_by': 'region_type', 'groups': {'peri_urban': {'n_records': 68, 'avg_inventory_accuracy_pct': 53.2, 'avg_order_fulfilment_rate_pct': 55.1, 'months_with_stockout': 20, 'issue_counts': {'theft_pilferage': 7, 'expired_stock': 8, 'FEFO_not_followed': 7, 'overstocking': 6, 'dispatch_error': 5, 'pest_infestation': 7, 'damaged_goods': 5, 'understocking': 5, 'receiving_error': 7, 'temperature_excursion': 4, 'stock_record_discrepancy': 3}}, 'urban': {'n_records': 55, 'avg_inventory_accuracy_pct': 68.8, 'avg_order_fulfilment_rate_pct': 68.5, 'months_with_stockout': 12, 'issue_counts': {'stock_record_discrepancy': 6, 'pest_infestation': 5, 'theft_pilferage': 6, 'damaged_goods': 5, 'overstocking': 3, 'understocking': 4, 'expired_stock': 5, 'FEFO_not_followed': 1, 'receiving_error': 2, 'dispatch_error': 7, 'temperature_excursion': 6}}}}

Q: how do peri_urban and urban compare on kpis?
A:

Chosen response:
FACTS: kpis by region_type: peri_urban: avg inventory accuracy 53.2%, avg fulfilment 55.1%, 20 months w/ stockout; urban: avg inventory accuracy 68.8%, avg fulfilment 68.5%, 12 months w/ stockout
RECOMMENDATION: review the peri_urban group first - most months with a stockout.

Rejected response:
FACTS: kpis by warehouse_level: district_store: avg inventory accuracy 53.2%, avg fulfilment 55.1%, 20 months w/ stockout; national_CMS: avg inventory accuracy 68.8%, avg fulfilment 68.5%, 12 months w/ stockout
RECOMMENDATION: review the peri_urban group first - most months with a stockout.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: shortage_risk({'uid': 'national_CMS:WH_0034'}) -> [{'uid': 'national_CMS:WH_0034', 'warehouse_id': 'WH_0034', 'warehouse_level': 'national_CMS', 'commodity_category': 'IV_fluids', 'risk_score': 2.5, 'risk_factors': ['high_wastage', 'criticality_high']}, {'uid': 'national_CMS:WH_0034', 'warehouse_id': 'WH_0034', 'warehouse_level': 'national_CMS', 'commodity_category': 'surgical_supplies', 'risk_score': 1.5, 'risk_factors': ['high_wastage', 'criticality_medium']}, {'uid': 'national_CMS:WH_0034', 'warehouse_id': 'WH_0034', 'warehouse_level': 'national_CMS', 'commodity_category': 'medical_devices_consumables', 'risk_score': 1, 'risk_factors': ['high_wastage']}, {'uid': 'national_CMS:WH_0034', 'warehouse_id': 'WH_0034', 'warehouse_level': 'national_CMS', 'commodity_category': 'surgical_supplies', 'risk_score': 0.5, 'risk_factors': ['criticality_medium']}]

Q: is WH_0034 at the national_CMS at risk of running short on anything?
A:

Chosen response:
FACTS: top shortage risk (uid=national_CMS:WH_0034) is WH_0034 (national_CMS, IV_fluids), score=2.5, factors=['high_wastage', 'criticality_high']
RECOMMENDATION: focus replenishment planning on WH_0034 (national_CMS).

Rejected response:
FACTS: top shortage risk (uid=national_CMS:WH_0034) is WH_0034 (national_CMS, IV_fluids), score=2.5, factors=['high_wastage', 'criticality_high']
RECOMMENDATION: Not sure about that - would need to check the system for more detail.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: shortage_risk({'uid': 'district_store:WH_0075'}) -> [{'uid': 'district_store:WH_0075', 'warehouse_id': 'WH_0075', 'warehouse_level': 'district_store', 'commodity_category': 'PPE_IPC_supplies', 'risk_score': 10.0, 'risk_factors': ['stockout', 'high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_medium']}, {'uid': 'district_store:WH_0075', 'warehouse_id': 'WH_0075', 'warehouse_level': 'district_store', 'commodity_category': 'medical_devices_consumables', 'risk_score': 8, 'risk_factors': ['stockout', 'high_backorder_rate', 'low_fulfilment', 'high_wastage']}]

Q: is WH_0075 at the district_store at risk of running short on anything?
A:

Chosen response:
FACTS: top shortage risk (uid=district_store:WH_0075) is WH_0075 (district_store, PPE_IPC_supplies), score=10.0, factors=['stockout', 'high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_medium']
RECOMMENDATION: focus replenishment planning on WH_0075 (district_store).

Rejected response:
FACTS: top shortage risk (uid=district_store:WH_0075) is WH_0075 (district_store, PPE_IPC_supplies), score=10.0, factors=['stockout', 'high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_medium']
RECOMMENDATION: Not sure about that - would need to check the system for more detail.
FACTS: top shortage risk (uid=district_store:WH_0075) is WH_0075 (district_store, PPE_IPC_supplies), score=10.0, factors=['stockout', 'high_backorder_rate', 'low_fulfilment', 'high_wastage', 'storage_inadequate', 'criticality_medium']
RECOMMENDATION: Not sure about that - would need to check the system for more detail.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: backorders({'uid': 'district_store:WH_0075'}) -> [{'uid': 'district_store:WH_0075', 'warehouse_id': 'WH_0075', 'warehouse_level': 'district_store', 'commodity_category': 'PPE_IPC_supplies', 'orders_backordered': 3, 'backorder_rate_pct': 100.0}, {'uid': 'district_store:WH_0075', 'warehouse_id': 'WH_0075', 'warehouse_level': 'district_store', 'commodity_category': 'medical_devices_consumables', 'orders_backordered': 2, 'backorder_rate_pct': 100.0}]

Q: which category has the most backorders at WH_0075 at the district_store?
A:

Chosen response:
FACTS: 2 backordered records (uid=district_store:WH_0075). worst: WH_0075 (district_store, PPE_IPC_supplies) at 100.0% backorder rate
RECOMMENDATION: expedite WH_0075 (district_store).

Rejected response:
FACTS: 18.8 backordered records (uid=district_store:WH_0075). worst: WH_0075 (district_store, PPE_IPC_supplies) at 100.0% backorder rate
RECOMMENDATION: expedite WH_0075 (district_store).
FACTS: to repeat, the figure is 18.8. Again, 18.8 is the number.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: stockouts({'uid': 'regional_warehouse:WH_0091'}) -> []

Q: does WH_0091 at the regional_warehouse currently have any active stockouts?
A:

Chosen response:
FACTS: no active stockouts (uid=regional_warehouse:WH_0091)
RECOMMENDATION: nothing urgent here.

Rejected response:
FACTS: no active stockouts (uid=regional_warehouse:WH_0548)
RECOMMENDATION: nothing urgent here.
FACTS: no active stockouts (uid=regional_warehouse:WH_0548)
RECOMMENDATION: nothing urgent here.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'uid': 'national_CMS:WH_0007'}) -> {'n_records': 1, 'avg_inventory_accuracy_pct': 100.0, 'avg_order_fulfilment_rate_pct': 65.8, 'months_with_stockout': 0, 'issue_counts': {}, 'uid': 'national_CMS:WH_0007', 'warehouse_id': 'WH_0007', 'warehouse_level': 'national_CMS'}

Q: how is WH_0007 at the national_CMS doing overall?
A:

Chosen response:
FACTS: WH_0007 (national_CMS): avg inventory accuracy 100.0%, avg fulfilment 65.8%, 0 months w/ stockout (based on 1 records)
RECOMMENDATION: looks fine.

Rejected response: not sure, you'd have to check the system yourself


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: stockouts({'uid': 'national_CMS:WH_0082'}) -> []

Q: does WH_0082 at the national_CMS currently have any active stockouts?
A:

Chosen response:
FACTS: no active stockouts (uid=national_CMS:WH_0082)
RECOMMENDATION: nothing urgent here.

Rejected response:
FACTS: no active stockouts (uid=national_CMS:WH_0193)
RECOMMENDATION: nothing urgent here.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: stockouts({'uid': 'regional_warehouse:WH_0030'}) -> []

Q: does WH_0030 at the regional_warehouse currently have any active stockouts?
A:

Chosen response:
FACTS: no active stockouts (uid=regional_warehouse:WH_0030)
RECOMMENDATION: nothing urgent here.

Rejected response:
FACTS: no active stockouts (uid=regional_warehouse:WH_0030)
RECOMMENDATION: Not sure. (Not enough information to determine)


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'uid': 'regional_warehouse:WH_0025'}) -> {'n_records': 3, 'avg_inventory_accuracy_pct': 57.2, 'avg_order_fulfilment_rate_pct': 49.5, 'months_with_stockout': 2, 'issue_counts': {'pest_infestation': 1, 'understocking': 1, 'FEFO_not_followed': 1}, 'uid': 'regional_warehouse:WH_0025', 'warehouse_id': 'WH_0025', 'warehouse_level': 'regional_warehouse'}

Q: how is WH_0025 at the regional_warehouse doing overall?
A:

Chosen response:
FACTS: WH_0025 (regional_warehouse): avg inventory accuracy 57.2%, avg fulfilment 49.5%, 2 months w/ stockout (based on 3 records), issues on record: {'pest_infestation': 1, 'understocking': 1, 'FEFO_not_followed': 1}
RECOMMENDATION: worth a review.

Rejected response:
FACTS: WH_0025 (regional_warehouse): avg inventory accuracy 57.2%, avg fulfilment 49.5%, 2 months w/ stockout (based on 3 records), issues on record: {'pest_infestation': 1, 'understocking': 1, 'FEFO_not_followed': 1}
RECOMMENDATION: Not sure. To get more information, I would need to check further.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'compare_by': 'warehouse_level', 'compare_values': ['national_CMS', 'regional_warehouse']}) -> {'_grouped_by': 'warehouse_level', 'groups': {'national_CMS': {'n_records': 72, 'avg_inventory_accuracy_pct': 72.2, 'avg_order_fulfilment_rate_pct': 74.5, 'months_with_stockout': 10, 'issue_counts': {'theft_pilferage': 6, 'stock_record_discrepancy': 6, 'damaged_goods': 6, 'overstocking': 6, 'understocking': 6, 'expired_stock': 6, 'FEFO_not_followed': 6, 'receiving_error': 6, 'dispatch_error': 6, 'pest_infestation': 6, 'temperature_excursion': 6}}, 'regional_warehouse': {'n_records': 72, 'avg_inventory_accuracy_pct': 57.1, 'avg_order_fulfilment_rate_pct': 53.5, 'months_with_stockout': 29, 'issue_counts': {'stock_record_discrepancy': 6, 'pest_infestation': 6, 'theft_pilferage': 6, 'understocking': 6, 'expired_stock': 6, 'overstocking': 6, 'receiving_error': 6, 'FEFO_not_followed': 6, 'temperature_excursion': 6, 'damaged_goods': 6, 'dispatch_error': 6}}}}

Q: how do national_CMS and regional_warehouse compare on kpis?
A:

Chosen response:
FACTS: kpis by warehouse_level: national_CMS: avg inventory accuracy 72.2%, avg fulfilment 74.5%, 10 months w/ stockout; regional_warehouse: avg inventory accuracy 57.1%, avg fulfilment 53.5%, 29 months w/ stockout
RECOMMENDATION: review the regional_warehouse group first - most months with a stockout.

Rejected response:
FACTS: kpis by warehouse_level: national_CMS: avg inventory accuracy 72.2%, avg fulfilment 74.5%, 10 months w/ stockout; regional_warehouse: avg inventory accuracy 57.1%, avg fulfilment 53.5%, 29 months w/ stockout
RECOMMENDATION: Not sure. (Not enough information to determine)


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: backorders({'uid': 'district_store:WH_0006'}) -> [{'uid': 'district_store:WH_0006', 'warehouse_id': 'WH_0006', 'warehouse_level': 'district_store', 'commodity_category': 'controlled_substances', 'orders_backordered': 5, 'backorder_rate_pct': 55.6}]

Q: which category has the most backorders at WH_0006 at the district_store?
A:

Chosen response:
FACTS: 1 backordered records (uid=district_store:WH_0006). worst: WH_0006 (district_store, controlled_substances) at 55.6% backorder rate
RECOMMENDATION: expedite WH_0006 (district_store).

Rejected response:
FACTS: 1 backordered records (uid=district_store:WH_0006). worst: WH_0006 (district_store, controlled_substances) at 55.6% backorder rate
RECOMMENDATION: Not sure about that - would need to check the system for more detail.


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: kpis({'uid': 'district_store:WH_0069'}) -> {'n_records': 1, 'avg_inventory_accuracy_pct': 35.6, 'avg_order_fulfilment_rate_pct': 35.1, 'months_with_stockout': 1, 'issue_counts': {'overstocking': 1}, 'uid': 'district_store:WH_0069', 'warehouse_id': 'WH_0069', 'warehouse_level': 'district_store'}

Q: how is WH_0069 at the district_store doing overall?
A:

Chosen response:
FACTS: WH_0069 (district_store): avg inventory accuracy 35.6%, avg fulfilment 35.1%, 1 months w/ stockout (based on 1 records), issues on record: {'overstocking': 1}
RECOMMENDATION: worth a review.

Rejected response: not sure, you'd have to check the system yourself


Prompt:
You're a warehouse assistant. Answer using only the data given. Separate FACTS from RECOMMENDATION. Say if you're not sure. Don't make stuff up.

tool call: explain_issue({'uid': 'district_store:WH_0036', 'commodity_category': 'essential_medicines', 'year': 2024, 'month': 12}) -> {'status': 'ok', 'uid': 'district_store:WH_0036', 'warehouse_id': 'WH_0036', 'warehouse_level': 'district_store', 'year': 2024, 'month': 12, 'reported_issue': 'overstocking', 'has_issue': True, 'signals': ['storage conditions not adequate', 'FEFO compliance failed', 'low inventory accuracy (17.3%)', 'high wastage (29.5%)'], 'uncertain': True}

Q: why is WH_0036 at the district_store failing fulfillment for essential medicines?
A:

Chosen response:
FACTS: WH_0036 (district_store, 12/2024): reported issue = overstocking. other signals: storage conditions not adequate; FEFO compliance failed; low inventory accuracy (17.3%); high wastage (29.5%) (note: report not submitted, numbers may be provisional)
RECOMMENDATION: address the reported issue (overstocking).

Rejected response: FACTS: address the reported issue (overstocking).

storage conditions not adequate
FEFO compliance failed
low inventory accuracy (17.3%)
high wastage (29.5%)