-
Notifications
You must be signed in to change notification settings - Fork 6.3k
Expand file tree
/
Copy pathEnrich Property Inventory Survey with Image Recognition and AI Agent.json
More file actions
960 lines (960 loc) · 21.1 KB
/
Copy pathEnrich Property Inventory Survey with Image Recognition and AI Agent.json
File metadata and controls
960 lines (960 loc) · 21.1 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
{
"meta": {
"instanceId": "26ba763460b97c249b82942b23b6384876dfeb9327513332e743c5f6219c2b8e"
},
"nodes": [
{
"id": "192d3e4f-6bb0-4b87-a1fa-e32c9efb49cc",
"name": "When clicking \"Test workflow\"",
"type": "n8n-nodes-base.manualTrigger",
"position": [
336,
34
],
"parameters": {},
"typeVersion": 1
},
{
"id": "32a7a772-76a6-4614-a6ab-d2b152a5811f",
"name": "OpenAI Chat Model1",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
1220,
180
],
"parameters": {
"model": "gpt-4o",
"options": {
"temperature": 0
}
},
"credentials": {
"openAiApi": {
"id": "8gccIjcuf3gvaoEr",
"name": "OpenAi account"
}
},
"typeVersion": 1
},
{
"id": "8c444314-ed7d-4ca0-b0fa-b6d1e964c698",
"name": "Get Applicable Rows",
"type": "n8n-nodes-base.airtable",
"position": [
516,
34
],
"parameters": {
"base": {
"__rl": true,
"mode": "list",
"value": "appbgxPBurOmQK3E7",
"cachedResultUrl": "https://airtable.com/appbgxPBurOmQK3E7",
"cachedResultName": "Building Inventory Survey Example"
},
"table": {
"__rl": true,
"mode": "id",
"value": "tblEHkoTvKpa4Aa0Q"
},
"options": {},
"operation": "search",
"returnAll": false,
"filterByFormula": "AND(Image!=\"\", AI_status=FALSE())"
},
"credentials": {
"airtableTokenApi": {
"id": "Und0frCQ6SNVX3VV",
"name": "Airtable Personal Access Token account"
}
},
"typeVersion": 2
},
{
"id": "f90578fa-b886-4653-8ff7-0c91884dc517",
"name": "Execute Workflow Trigger",
"type": "n8n-nodes-base.executeWorkflowTrigger",
"position": [
1257,
733
],
"parameters": {},
"typeVersion": 1
},
{
"id": "8f5959eb-45bd-4185-a959-10268827e41d",
"name": "Edit Fields",
"type": "n8n-nodes-base.set",
"position": [
1417,
733
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "7263764b-8409-4cea-8db3-3278dd7ef9d8",
"name": "=route",
"type": "string",
"value": "={{ $json.route }}"
},
{
"id": "55c3b207-2e98-4137-8413-f72cbff17986",
"name": "query",
"type": "string",
"value": "={{ $json.query }}"
},
{
"id": "6eb873de-3c3a-4135-9dc0-1d441c63647c",
"name": "",
"type": "string",
"value": ""
}
]
}
},
"typeVersion": 3.3
},
{
"id": "2c7f7274-12e9-4dd3-8ee4-679b408d5430",
"name": "Fallback Response",
"type": "n8n-nodes-base.set",
"position": [
1580,
875
],
"parameters": {
"mode": "raw",
"options": {},
"jsonOutput": "{\n \"response\": {\n \"ok\": false,\n \"error\": \"The requested tool was not found or the service may be unavailable. Do not retry.\"\n }\n}\n"
},
"typeVersion": 3.3
},
{
"id": "09f36f4d-eb88-4d93-a8b3-e9ba66b46b54",
"name": "SERP Google Reverse Image API",
"type": "n8n-nodes-base.httpRequest",
"position": [
1860,
549
],
"parameters": {
"url": "https://serpapi.com/search.json",
"options": {},
"sendQuery": true,
"authentication": "predefinedCredentialType",
"queryParameters": {
"parameters": [
{
"name": "engine",
"value": "google_reverse_image"
},
{
"name": "image_url",
"value": "={{ $json.query }}"
}
]
},
"nodeCredentialType": "serpApi"
},
"credentials": {
"serpApi": {
"id": "aJCKjxx6U3K7ydDe",
"name": "SerpAPI account"
}
},
"typeVersion": 4.2
},
{
"id": "8e3a0f38-8663-4f5c-837f-4b9aa21f14fb",
"name": "Reverse Image Search Response",
"type": "n8n-nodes-base.set",
"position": [
2037,
547
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "de99a504-713f-4c78-8679-08139b2def31",
"name": "response",
"type": "string",
"value": "={{ JSON.stringify($json.image_results.map(x => ({ position: x.position, title: x.title, link: x.link, description: x.snippet }))) }}"
}
]
}
},
"typeVersion": 3.3
},
{
"id": "0cd2269a-5b1f-4f10-b180-7f9cff9b1102",
"name": "Reverse Image Search Tool",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
1300,
340
],
"parameters": {
"name": "reverse_image_search",
"fields": {
"values": [
{
"name": "route",
"stringValue": "serp.google_reverse_image"
}
]
},
"workflowId": "={{ $workflow.id }}",
"description": "Call this tool to perform a reverse image search. Reverse image searches return urls where similar looking products exists. Fetch the returned urls to gather more information. This tool requires the following object request body.\n```\n{\n \"type\": \"object\",\n \"properties\": {\n \"image_url\": { \"type\": \"string\" },\n }\n}\n```\nimage_url should be an absolute URL to the image."
},
"typeVersion": 1.1
},
{
"id": "9825651e-b382-4e0a-97ef-37764cb5be9e",
"name": "Firecrawl Scrape API",
"type": "n8n-nodes-base.httpRequest",
"position": [
1860,
889
],
"parameters": {
"url": "https://api.firecrawl.dev/v0/scrape",
"method": "POST",
"options": {},
"sendBody": true,
"sendHeaders": true,
"authentication": "genericCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "url",
"value": "={{ $json.query }}"
}
]
},
"genericAuthType": "httpHeaderAuth",
"headerParameters": {
"parameters": [
{
"name": "Content-Type",
"value": "application/json"
}
]
}
},
"credentials": {
"httpHeaderAuth": {
"id": "OUOnyTkL9vHZNorB",
"name": "Firecrawl API"
}
},
"typeVersion": 4.2
},
{
"id": "7f61d60b-b052-4b7c-abfd-9eb8e05a45a2",
"name": "Scrape Success?",
"type": "n8n-nodes-base.if",
"position": [
2020,
889
],
"parameters": {
"options": {},
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "a15a164f-d0c5-478f-8b27-f3d51746c214",
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
},
"leftValue": "={{ $json.success }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2
},
{
"id": "29c65ef4-6350-490a-b8e3-a5c869e656b2",
"name": "Firecrawl Scrape Success Response",
"type": "n8n-nodes-base.set",
"position": [
2180,
889
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "7db5c81f-de90-40e1-8086-3f13d40451c7",
"name": "response",
"type": "string",
"value": "={{ $json.data.markdown.substring(0, 3000) }}"
}
]
}
},
"typeVersion": 3.3
},
{
"id": "229b4008-d8a8-4609-854a-fc244a4ed630",
"name": "Firecrawl scrape Error Response",
"type": "n8n-nodes-base.set",
"position": [
2180,
1049
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "e691d86a-d366-44a2-baa6-3dba42527f6e",
"name": "response",
"type": "string",
"value": "{ error: \"Unable to scrape website due to unknown error. Do not retry.\" }"
}
]
}
},
"typeVersion": 3.3
},
{
"id": "f080069b-e849-45e0-88cf-03707d22c704",
"name": "Firecrawl Web Scaper Tool",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
1440,
340
],
"parameters": {
"name": "webpage_url_scraper_tool",
"fields": {
"values": [
{
"name": "route",
"stringValue": "firecrawl.scrape"
}
]
},
"workflowId": "={{ $workflow.id }}",
"description": "Call this tool to retrieve page contents of a url.\n```\n{\n \"type\": \"object\",\n \"properties\": {\n \"url\": { \"type\": \"string\" },\n }\n}\n```\nurl should be an absolute URL."
},
"typeVersion": 1.1
},
{
"id": "4eff88bb-bd5e-4d6a-b5e1-8521632c461f",
"name": "Structured Output Parser",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
1500,
180
],
"parameters": {
"jsonSchema": "{\n \"type\": \"object\",\n \"properties\": {\n \"title\": { \"type\": \"string\" },\n \"description\": { \"type\": \"string\" },\n \"model\": { \"type\": \"string\" },\n \"material\": { \"type\": \"string\" },\n \"color\": { \"type\": \"string\" },\n \"condition\": { \"type\": \"string\" }\n }\n}"
},
"typeVersion": 1.1
},
{
"id": "328d106b-a473-4f54-82fd-55c30d813da9",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
280,
-260
],
"parameters": {
"color": 7,
"width": 402.5984702109446,
"height": 495.4071184783251,
"content": "## 1. Use Airtable to Capture Survey Photos\n[Read more about AirTable](https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-base.airtable)\n\nTo enable this workflow, we need a database where we can retreive the title and photo to analyse and write the generate values back to. Airtable is perfect for this since it has a robust API we can work with.\n\nFor this demo, we'll manually trigger but this can be changed for forms or other triggers."
},
"typeVersion": 1
},
{
"id": "e358775d-ff83-411d-9364-b43c87d98134",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
716.3106363781314,
-160
],
"parameters": {
"color": 7,
"width": 359.40869874940336,
"height": 428.4787925736586,
"content": "## 2. Use AI Vision Model to Analyse the Photo.\n[Read more about OpenAI Vision](https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-langchain.openai)\n\nWe'll use OpenAi vision model to create a detailed description of the product in the photo. We split this step from the agent because it uses an image model rather than the usual text-based one."
},
"typeVersion": 1
},
{
"id": "51b4a70c-9583-4e8a-8e8d-896a80ad53c3",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
1111.3914848823072,
-293.9250474768817
],
"parameters": {
"color": 7,
"width": 593.0683948010671,
"height": 803.956942672397,
"content": "## 3. Build an AI Agent who Searches the Internet\n[Read more about OpenAI Agents](https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-langchain.openai)\n\nThis AI Agent has the ability to perform reverse image searches using our captured photos as well visit external webpages in order to obtain accurate product names and attributes. The Agent along with the tools might mimic what the average human user would carry out the same task.\n\n* For reverse image search, we're using SERP API service however we won't use the built-in SERP node as we need to specify custom parameters. \n* For scraping, we'll use [Firecrawl](https://www.firecrawl.dev/) as this service also helps to parse and return the page as markdown which is more efficient."
},
"typeVersion": 1
},
{
"id": "adfb519b-a5c7-432c-be32-5acfcc388b49",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
1740,
-149.28190375244515
],
"parameters": {
"color": 7,
"width": 373.3601237414979,
"height": 397.7168664109706,
"content": "## 4. Overwrite our Rows with Enriched Results\n\nAnd Viola! Our AI agent has potentially saved hours of manual data entry work for our surveyor. This technique can be used for many other usecases."
},
"typeVersion": 1
},
{
"id": "6444e217-b944-450e-892a-5822d4d390ce",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
1200,
549
],
"parameters": {
"color": 7,
"width": 554.6092633638649,
"height": 490.7010880746526,
"content": "## 5. Using the Custom Workflow Tool\n[Read more about Workflow Tools](https://docs.n8n.io/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.toolworkflow)\n\nAI Agents rely on Tools to make decisions and become exponentially more powerful the more tools they have. A common pattern to manage multiple tools is to create a routing system for tools using the API pattern."
},
"typeVersion": 1
},
{
"id": "bf2459cf-a931-4232-9504-b36b15721194",
"name": "Enrich Product Rows",
"type": "n8n-nodes-base.airtable",
"position": [
1880,
60
],
"parameters": {
"base": {
"__rl": true,
"mode": "list",
"value": "appbgxPBurOmQK3E7",
"cachedResultUrl": "https://airtable.com/appbgxPBurOmQK3E7",
"cachedResultName": "Building Inventory Survey Example"
},
"table": {
"__rl": true,
"mode": "id",
"value": "tblEHkoTvKpa4Aa0Q"
},
"columns": {
"value": {
"id": "={{ $('Get Applicable Rows').item.json.id }}",
"Color": "={{ $json.output.output.color }}",
"Model": "={{ $json.output.output.model }}",
"Title": "={{ $json.output.output.title }}",
"Material": "={{ $json.output.output.material }}",
"AI_status": true,
"Condition": "={{ $json.output.output.condition }}",
"Description": "={{ $json.output.output.description }}"
},
"schema": [
{
"id": "id",
"type": "string",
"display": true,
"removed": false,
"readOnly": true,
"required": false,
"displayName": "id",
"defaultMatch": true
},
{
"id": "Title",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Title",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Image",
"type": "array",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Image",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Description",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Description",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Model",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Model",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Material",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Material",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Color",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Color",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Condition",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Condition",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "AI_status",
"type": "boolean",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "AI_status",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"id"
]
},
"options": {},
"operation": "update"
},
"credentials": {
"airtableTokenApi": {
"id": "Und0frCQ6SNVX3VV",
"name": "Airtable Personal Access Token account"
}
},
"typeVersion": 2
},
{
"id": "19d736bf-c29d-46a2-93bc-b536ff28c4b5",
"name": "Sticky Note6",
"type": "n8n-nodes-base.stickyNote",
"position": [
-100,
-260
],
"parameters": {
"width": 359.6648027457353,
"height": 381.0536322713287,
"content": "## Try It Out!\n### This workflow does the following:\n* Scans an Airtable spreadsheet for rows with product photo images.\n* Uses an AI vision model to attempt to identify the product.\n* Uses an AI Agent to research the product on the internet to enrich the product data.\n* Overwrites our Airtable spreadsheet with the enriched data.\n\n### Need Help?\nJoin the [Discord](https://discord.com/invite/XPKeKXeB7d) or ask in the [Forum](https://community.n8n.io/)!\n\nHappy Hacking!"
},
"typeVersion": 1
},
{
"id": "25f15c48-16bf-4f92-942d-c224ed88d208",
"name": "Analyse Image",
"type": "@n8n/n8n-nodes-langchain.openAi",
"position": [
840,
80
],
"parameters": {
"text": "=Focus on the {{ $json.Title }} in the image - we'll refer to this as the \"object\". Identify the following attributes of the object. If you cannot determine confidently, then leave blank and move to next attribute.\n* Decription of the object.\n* The model/make of the object.\n* The material(s) used in the construction of the object.\n* The color(s) of the object\n* The condition of the object. Use one of poor, good, excellent.\n",
"options": {},
"resource": "image",
"imageUrls": "={{ $json.Image[0].thumbnails.large.url }}",
"operation": "analyze"
},
"credentials": {
"openAiApi": {
"id": "8gccIjcuf3gvaoEr",
"name": "OpenAi account"
}
},
"typeVersion": 1.3
},
{
"id": "e6c99f71-ccc9-426e-b916-cc38864e3224",
"name": "Object Identifier Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
1260,
20
],
"parameters": {
"text": "=system: Your role is to help an building surveyor perform a object classification and data collection task whereby the surveyor will take photos of various objects and your job is to try and identify accurately certain product attributes of the objects as detailed below.\n\nThe surveyor has given you the following:\n1) photo url ```{{ $('Get Applicable Rows').item.json.Image[0].thumbnails.large.url }}```.\n2) photo description ```{{ $json.content }}```.\n\nFor each product attribute the surveyor is unable to determine, you may:\n1) use the reverse image search tool to search the product on the internet via the provided image url.\n2) use the web scraper tool to read webpages on the internet which may be relevant to the product.\n3) If after using these tools, you are still unable to determine the required product attributes then leave the data blank.\n\nUse all the information provided and gathered, to extract the following product attributes: title, description, model, material, color and condition.",
"agent": "openAiFunctionsAgent",
"options": {},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 1.5
},
{
"id": "661b14bd-6511-4f20-981c-2e68a7c34ec5",
"name": "Actions Router",
"type": "n8n-nodes-base.switch",
"position": [
1577,
733
],
"parameters": {
"rules": {
"values": [
{
"outputKey": "serp.google_reverse_image",
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.route }}",
"rightValue": "serp.google_reverse_image"
}
]
},
"renameOutput": true
},
{
"outputKey": "firecrawl.scrape",
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "0a1f54ae-39f1-468d-ba6e-1376d13e4ee8",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.route }}",
"rightValue": "firecrawl.scrape"
}
]
},
"renameOutput": true
}
]
},
"options": {
"fallbackOutput": "extra"
}
},
"typeVersion": 3
},
{
"id": "c5078221-9239-4ec0-b25e-7cd880b58216",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
480,
20
],
"parameters": {
"width": 181.2788838920522,
"height": 297.0159375852115,
"content": "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n🚨**Required**\n* Set Airtable Base and Table IDs here."
},
"typeVersion": 1
},
{
"id": "c58c0db4-9b99-4a77-90ae-66fa3981b684",
"name": "Sticky Note7",
"type": "n8n-nodes-base.stickyNote",
"position": [
1840,
40
],
"parameters": {
"width": 181.2788838920522,
"height": 297.0159375852115,
"content": "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n🚨**Required**\n* Set Airtable Base and Table IDs here."
},
"typeVersion": 1
},
{
"id": "e3a666d7-d7a5-43f5-8f04-7972332f8916",
"name": "Sticky Note8",
"type": "n8n-nodes-base.stickyNote",
"position": [
1780,
440
],
"parameters": {
"color": 7,
"width": 460.3301604548244,
"height": 298.81538450684064,
"content": "## 5.1 Google Reverse Image Tool\nThis tool uses Google's reverse image API to return websites where similar images are found."
},
"typeVersion": 1
},
{
"id": "d7407cdb-16bb-4bd9-a28e-7a72a5289354",
"name": "Sticky Note9",
"type": "n8n-nodes-base.stickyNote",
"position": [
1780,
769.9385328672522
],
"parameters": {
"color": 7,
"width": 575.3216480295998,
"height": 463.34699288922565,
"content": "## 5.2 Webscraper Tool\nThis tool uses Firecrawl.dev API to crawl webpages and returns those pages in markdown format."
},
"typeVersion": 1
}
],
"pinData": {},
"connections": {
"Edit Fields": {
"main": [
[
{
"node": "Actions Router",
"type": "main",
"index": 0
}
]
]
},
"Analyse Image": {
"main": [
[
{
"node": "Object Identifier Agent",
"type": "main",
"index": 0
}
]
]
},
"Actions Router": {
"main": [
[
{
"node": "SERP Google Reverse Image API",
"type": "main",
"index": 0
}
],
[
{
"node": "Firecrawl Scrape API",
"type": "main",
"index": 0
}
],
[
{
"node": "Fallback Response",
"type": "main",
"index": 0
}
]
]
},
"Scrape Success?": {
"main": [
[
{
"node": "Firecrawl Scrape Success Response",
"type": "main",
"index": 0
}
],
[
{
"node": "Firecrawl scrape Error Response",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model1": {
"ai_languageModel": [
[
{
"node": "Object Identifier Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Get Applicable Rows": {
"main": [
[
{
"node": "Analyse Image",
"type": "main",
"index": 0
}
]
]
},
"Firecrawl Scrape API": {
"main": [
[
{
"node": "Scrape Success?",
"type": "main",
"index": 0
}
]
]
},
"Object Identifier Agent": {
"main": [
[
{
"node": "Enrich Product Rows",
"type": "main",
"index": 0
}
]
]
},
"Execute Workflow Trigger": {
"main": [
[
{
"node": "Edit Fields",
"type": "main",
"index": 0
}
]
]
},
"Structured Output Parser": {
"ai_outputParser": [
[
{
"node": "Object Identifier Agent",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Firecrawl Web Scaper Tool": {
"ai_tool": [
[
{
"node": "Object Identifier Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Reverse Image Search Tool": {
"ai_tool": [
[
{
"node": "Object Identifier Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"SERP Google Reverse Image API": {
"main": [
[
{
"node": "Reverse Image Search Response",
"type": "main",
"index": 0
}
]
]
},
"When clicking \"Test workflow\"": {
"main": [
[
{
"node": "Get Applicable Rows",
"type": "main",
"index": 0
}
]
]
}
}
}