Spaces:
Running
Running
Merge remote-tracking branch 'origin/main' into darabos-crdt-updated
Browse files- data/LynxScribe demo +960 -0
- requirements.txt +1 -0
- server/executors/one_by_one.py +20 -10
- server/lynxscribe_ops.py +203 -52
- server/main.py +10 -1
- server/ops.py +1 -1
- web/package-lock.json +85 -820
- web/package.json +1 -0
- web/src/NodeParameter.svelte +21 -8
data/LynxScribe demo
ADDED
@@ -0,0 +1,960 @@
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1 |
+
{
|
2 |
+
"env": "LynxScribe",
|
3 |
+
"nodes": [
|
4 |
+
{
|
5 |
+
"id": "Input chat 1",
|
6 |
+
"type": "basic",
|
7 |
+
"data": {
|
8 |
+
"title": "Input chat",
|
9 |
+
"params": {
|
10 |
+
"chat": "who is the CIO of Lynx?"
|
11 |
+
},
|
12 |
+
"display": null,
|
13 |
+
"error": null,
|
14 |
+
"meta": {
|
15 |
+
"name": "Input chat",
|
16 |
+
"params": {
|
17 |
+
"chat": {
|
18 |
+
"name": "chat",
|
19 |
+
"default": null,
|
20 |
+
"type": {
|
21 |
+
"type": "<class 'str'>"
|
22 |
+
}
|
23 |
+
}
|
24 |
+
},
|
25 |
+
"inputs": {},
|
26 |
+
"outputs": {
|
27 |
+
"output": {
|
28 |
+
"name": "output",
|
29 |
+
"type": {
|
30 |
+
"type": "None"
|
31 |
+
},
|
32 |
+
"position": "right"
|
33 |
+
}
|
34 |
+
},
|
35 |
+
"type": "basic",
|
36 |
+
"sub_nodes": null
|
37 |
+
}
|
38 |
+
},
|
39 |
+
"position": {
|
40 |
+
"x": -383.5496596237119,
|
41 |
+
"y": 27.567899191800223
|
42 |
+
},
|
43 |
+
"parentId": null
|
44 |
+
},
|
45 |
+
{
|
46 |
+
"id": "View 1",
|
47 |
+
"type": "table_view",
|
48 |
+
"data": {
|
49 |
+
"title": "View",
|
50 |
+
"params": {},
|
51 |
+
"display": {
|
52 |
+
"dataframes": {
|
53 |
+
"df": {
|
54 |
+
"columns": [
|
55 |
+
"answer"
|
56 |
+
],
|
57 |
+
"data": [
|
58 |
+
[
|
59 |
+
"The Chief Innovation Officer (CIO) of Lynx Analytics is Gabor Benedek. He is responsible for defining the methodological roadmap for the company's predictive analytics consulting and product development departments. If you need more specific information about his role, feel free to ask!\n\nPlease visit <a href='https://www.lynxanalytics.com/team-leadership' target='_blank'>https://www.lynxanalytics.com/team-leadership</a> for further information."
|
60 |
+
]
|
61 |
+
]
|
62 |
+
}
|
63 |
+
}
|
64 |
+
},
|
65 |
+
"error": null,
|
66 |
+
"meta": {
|
67 |
+
"name": "View",
|
68 |
+
"params": {},
|
69 |
+
"inputs": {
|
70 |
+
"input": {
|
71 |
+
"name": "input",
|
72 |
+
"type": {
|
73 |
+
"type": "<class 'inspect._empty'>"
|
74 |
+
},
|
75 |
+
"position": "left"
|
76 |
+
}
|
77 |
+
},
|
78 |
+
"outputs": {},
|
79 |
+
"type": "table_view",
|
80 |
+
"sub_nodes": null
|
81 |
+
}
|
82 |
+
},
|
83 |
+
"position": {
|
84 |
+
"x": 722.1450069267316,
|
85 |
+
"y": -785.6076562320527
|
86 |
+
},
|
87 |
+
"parentId": null
|
88 |
+
},
|
89 |
+
{
|
90 |
+
"id": "LLM 1",
|
91 |
+
"type": "basic",
|
92 |
+
"data": {
|
93 |
+
"title": "LLM",
|
94 |
+
"params": {
|
95 |
+
"name": "openai"
|
96 |
+
},
|
97 |
+
"display": null,
|
98 |
+
"error": null,
|
99 |
+
"meta": {
|
100 |
+
"name": "LLM",
|
101 |
+
"params": {
|
102 |
+
"name": {
|
103 |
+
"name": "name",
|
104 |
+
"default": "openai",
|
105 |
+
"type": {
|
106 |
+
"type": "<class 'str'>"
|
107 |
+
}
|
108 |
+
}
|
109 |
+
},
|
110 |
+
"inputs": {},
|
111 |
+
"outputs": {
|
112 |
+
"output": {
|
113 |
+
"name": "output",
|
114 |
+
"type": {
|
115 |
+
"type": "None"
|
116 |
+
},
|
117 |
+
"position": "top"
|
118 |
+
}
|
119 |
+
},
|
120 |
+
"type": "basic",
|
121 |
+
"sub_nodes": null
|
122 |
+
}
|
123 |
+
},
|
124 |
+
"position": {
|
125 |
+
"x": -312.5774211084781,
|
126 |
+
"y": 1093.4019527511366
|
127 |
+
},
|
128 |
+
"parentId": null
|
129 |
+
},
|
130 |
+
{
|
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"inputs": {},
|
607 |
+
"outputs": {
|
608 |
+
"output": {
|
609 |
+
"name": "output",
|
610 |
+
"type": {
|
611 |
+
"type": "None"
|
612 |
+
},
|
613 |
+
"position": "top"
|
614 |
+
}
|
615 |
+
},
|
616 |
+
"type": "basic",
|
617 |
+
"sub_nodes": null
|
618 |
+
}
|
619 |
+
},
|
620 |
+
"position": {
|
621 |
+
"x": 0.08889822620079713,
|
622 |
+
"y": 1044.7639853229612
|
623 |
+
},
|
624 |
+
"parentId": null
|
625 |
+
},
|
626 |
+
{
|
627 |
+
"id": "Chat processor 1",
|
628 |
+
"type": "basic",
|
629 |
+
"data": {
|
630 |
+
"title": "Chat processor",
|
631 |
+
"params": {},
|
632 |
+
"display": null,
|
633 |
+
"error": null,
|
634 |
+
"meta": {
|
635 |
+
"name": "Chat processor",
|
636 |
+
"params": {},
|
637 |
+
"inputs": {
|
638 |
+
"processor": {
|
639 |
+
"name": "processor",
|
640 |
+
"type": {
|
641 |
+
"type": "<class 'inspect._empty'>"
|
642 |
+
},
|
643 |
+
"position": "bottom"
|
644 |
+
}
|
645 |
+
},
|
646 |
+
"outputs": {
|
647 |
+
"output": {
|
648 |
+
"name": "output",
|
649 |
+
"type": {
|
650 |
+
"type": "None"
|
651 |
+
},
|
652 |
+
"position": "top"
|
653 |
+
}
|
654 |
+
},
|
655 |
+
"type": "basic",
|
656 |
+
"sub_nodes": null
|
657 |
+
}
|
658 |
+
},
|
659 |
+
"position": {
|
660 |
+
"x": 266.23062579739207,
|
661 |
+
"y": 931.8796075565143
|
662 |
+
},
|
663 |
+
"parentId": null
|
664 |
+
},
|
665 |
+
{
|
666 |
+
"id": "Mask 1",
|
667 |
+
"type": "basic",
|
668 |
+
"data": {
|
669 |
+
"title": "Mask",
|
670 |
+
"params": {
|
671 |
+
"name": "email",
|
672 |
+
"regex": "([a-z0-9!#$%&'*+\\/=?^_`{|.}~-]+@(?:[a-z0-9](?:[a-z0-9-]*[a-z0-9])?\\.)+[a-z0-9](?:[a-z0-9-]*[a-z0-9])?)",
|
673 |
+
"exceptions": "[email protected],[email protected],[email protected],[email protected]",
|
674 |
+
"mask_pattern": "masked_email_address_{}"
|
675 |
+
},
|
676 |
+
"display": null,
|
677 |
+
"error": null,
|
678 |
+
"meta": {
|
679 |
+
"name": "Mask",
|
680 |
+
"params": {
|
681 |
+
"name": {
|
682 |
+
"name": "name",
|
683 |
+
"default": "",
|
684 |
+
"type": {
|
685 |
+
"type": "<class 'str'>"
|
686 |
+
}
|
687 |
+
},
|
688 |
+
"regex": {
|
689 |
+
"name": "regex",
|
690 |
+
"default": "",
|
691 |
+
"type": {
|
692 |
+
"type": "<class 'str'>"
|
693 |
+
}
|
694 |
+
},
|
695 |
+
"exceptions": {
|
696 |
+
"name": "exceptions",
|
697 |
+
"default": "",
|
698 |
+
"type": {
|
699 |
+
"type": "<class 'str'>"
|
700 |
+
}
|
701 |
+
},
|
702 |
+
"mask_pattern": {
|
703 |
+
"name": "mask_pattern",
|
704 |
+
"default": "",
|
705 |
+
"type": {
|
706 |
+
"type": "<class 'str'>"
|
707 |
+
}
|
708 |
+
}
|
709 |
+
},
|
710 |
+
"inputs": {},
|
711 |
+
"outputs": {
|
712 |
+
"output": {
|
713 |
+
"name": "output",
|
714 |
+
"type": {
|
715 |
+
"type": "None"
|
716 |
+
},
|
717 |
+
"position": "top"
|
718 |
+
}
|
719 |
+
},
|
720 |
+
"type": "basic",
|
721 |
+
"sub_nodes": null
|
722 |
+
}
|
723 |
+
},
|
724 |
+
"position": {
|
725 |
+
"x": 233.69759202223884,
|
726 |
+
"y": 1041.6145468043276
|
727 |
+
},
|
728 |
+
"parentId": null
|
729 |
+
},
|
730 |
+
{
|
731 |
+
"id": "Mask 2",
|
732 |
+
"type": "basic",
|
733 |
+
"data": {
|
734 |
+
"title": "Mask",
|
735 |
+
"params": {
|
736 |
+
"name": "credit_card",
|
737 |
+
"regex": "((?:(?:\\\\d{4}[- ]?){3}\\\\d{4}|\\\\d{15,16}))(?![\\\\d])",
|
738 |
+
"exceptions": "",
|
739 |
+
"mask_pattern": "masked_credit_card_number_{}"
|
740 |
+
},
|
741 |
+
"display": null,
|
742 |
+
"error": null,
|
743 |
+
"meta": {
|
744 |
+
"name": "Mask",
|
745 |
+
"params": {
|
746 |
+
"name": {
|
747 |
+
"name": "name",
|
748 |
+
"default": "",
|
749 |
+
"type": {
|
750 |
+
"type": "<class 'str'>"
|
751 |
+
}
|
752 |
+
},
|
753 |
+
"regex": {
|
754 |
+
"name": "regex",
|
755 |
+
"default": "",
|
756 |
+
"type": {
|
757 |
+
"type": "<class 'str'>"
|
758 |
+
}
|
759 |
+
},
|
760 |
+
"exceptions": {
|
761 |
+
"name": "exceptions",
|
762 |
+
"default": "",
|
763 |
+
"type": {
|
764 |
+
"type": "<class 'str'>"
|
765 |
+
}
|
766 |
+
},
|
767 |
+
"mask_pattern": {
|
768 |
+
"name": "mask_pattern",
|
769 |
+
"default": "",
|
770 |
+
"type": {
|
771 |
+
"type": "<class 'str'>"
|
772 |
+
}
|
773 |
+
}
|
774 |
+
},
|
775 |
+
"inputs": {},
|
776 |
+
"outputs": {
|
777 |
+
"output": {
|
778 |
+
"name": "output",
|
779 |
+
"type": {
|
780 |
+
"type": "None"
|
781 |
+
},
|
782 |
+
"position": "top"
|
783 |
+
}
|
784 |
+
},
|
785 |
+
"type": "basic",
|
786 |
+
"sub_nodes": null
|
787 |
+
}
|
788 |
+
},
|
789 |
+
"position": {
|
790 |
+
"x": 513.2761671440603,
|
791 |
+
"y": 1034.8547191984255
|
792 |
+
},
|
793 |
+
"parentId": null
|
794 |
+
},
|
795 |
+
{
|
796 |
+
"id": "Test Chat API 2",
|
797 |
+
"type": "basic",
|
798 |
+
"data": {
|
799 |
+
"title": "Test Chat API",
|
800 |
+
"params": {
|
801 |
+
"show_details": false
|
802 |
+
},
|
803 |
+
"display": null,
|
804 |
+
"error": null,
|
805 |
+
"meta": {
|
806 |
+
"name": "Test Chat API",
|
807 |
+
"params": {
|
808 |
+
"show_details": {
|
809 |
+
"name": "show_details",
|
810 |
+
"default": false,
|
811 |
+
"type": {
|
812 |
+
"type": "<class 'bool'>"
|
813 |
+
}
|
814 |
+
}
|
815 |
+
},
|
816 |
+
"inputs": {
|
817 |
+
"message": {
|
818 |
+
"name": "message",
|
819 |
+
"type": {
|
820 |
+
"type": "<class 'inspect._empty'>"
|
821 |
+
},
|
822 |
+
"position": "left"
|
823 |
+
},
|
824 |
+
"chat_api": {
|
825 |
+
"name": "chat_api",
|
826 |
+
"type": {
|
827 |
+
"type": "<class 'inspect._empty'>"
|
828 |
+
},
|
829 |
+
"position": "bottom"
|
830 |
+
}
|
831 |
+
},
|
832 |
+
"outputs": {
|
833 |
+
"output": {
|
834 |
+
"name": "output",
|
835 |
+
"type": {
|
836 |
+
"type": "None"
|
837 |
+
},
|
838 |
+
"position": "right"
|
839 |
+
}
|
840 |
+
},
|
841 |
+
"type": "basic",
|
842 |
+
"sub_nodes": null
|
843 |
+
},
|
844 |
+
"collapsed": false
|
845 |
+
},
|
846 |
+
"position": {
|
847 |
+
"x": -11.653333595036415,
|
848 |
+
"y": -0.9210389517918429
|
849 |
+
},
|
850 |
+
"parentId": null
|
851 |
+
}
|
852 |
+
],
|
853 |
+
"edges": [
|
854 |
+
{
|
855 |
+
"id": "xy-edge__Knowledge base 1output-Chat API 1knowledge_base",
|
856 |
+
"source": "Knowledge base 1",
|
857 |
+
"target": "Chat API 1",
|
858 |
+
"sourceHandle": "output",
|
859 |
+
"targetHandle": "knowledge_base"
|
860 |
+
},
|
861 |
+
{
|
862 |
+
"id": "xy-edge__RAG chatbot 1output-Chat API 1chatbot",
|
863 |
+
"source": "RAG chatbot 1",
|
864 |
+
"target": "Chat API 1",
|
865 |
+
"sourceHandle": "output",
|
866 |
+
"targetHandle": "chatbot"
|
867 |
+
},
|
868 |
+
{
|
869 |
+
"id": "xy-edge__LLM 1output-RAG chatbot 1llm",
|
870 |
+
"source": "LLM 1",
|
871 |
+
"target": "RAG chatbot 1",
|
872 |
+
"sourceHandle": "output",
|
873 |
+
"targetHandle": "llm"
|
874 |
+
},
|
875 |
+
{
|
876 |
+
"id": "xy-edge__Scenario selector 1output-RAG chatbot 1scenario_selector",
|
877 |
+
"source": "Scenario selector 1",
|
878 |
+
"target": "RAG chatbot 1",
|
879 |
+
"sourceHandle": "output",
|
880 |
+
"targetHandle": "scenario_selector"
|
881 |
+
},
|
882 |
+
{
|
883 |
+
"id": "xy-edge__RAG graph 1output-RAG chatbot 1rag_graph",
|
884 |
+
"source": "RAG graph 1",
|
885 |
+
"target": "RAG chatbot 1",
|
886 |
+
"sourceHandle": "output",
|
887 |
+
"targetHandle": "rag_graph"
|
888 |
+
},
|
889 |
+
{
|
890 |
+
"id": "xy-edge__Vector store 1output-RAG graph 1vector_store",
|
891 |
+
"source": "Vector store 1",
|
892 |
+
"target": "RAG graph 1",
|
893 |
+
"sourceHandle": "output",
|
894 |
+
"targetHandle": "vector_store"
|
895 |
+
},
|
896 |
+
{
|
897 |
+
"id": "xy-edge__Text embedder 2output-RAG graph 1text_embedder",
|
898 |
+
"source": "Text embedder 2",
|
899 |
+
"target": "RAG graph 1",
|
900 |
+
"sourceHandle": "output",
|
901 |
+
"targetHandle": "text_embedder"
|
902 |
+
},
|
903 |
+
{
|
904 |
+
"id": "xy-edge__LLM 2output-Text embedder 2llm",
|
905 |
+
"source": "LLM 2",
|
906 |
+
"target": "Text embedder 2",
|
907 |
+
"sourceHandle": "output",
|
908 |
+
"targetHandle": "llm"
|
909 |
+
},
|
910 |
+
{
|
911 |
+
"id": "xy-edge__Truncate history 1output-Chat processor 1processor",
|
912 |
+
"source": "Truncate history 1",
|
913 |
+
"target": "Chat processor 1",
|
914 |
+
"sourceHandle": "output",
|
915 |
+
"targetHandle": "processor"
|
916 |
+
},
|
917 |
+
{
|
918 |
+
"id": "xy-edge__Chat processor 1output-Chat API 1chat_processor",
|
919 |
+
"source": "Chat processor 1",
|
920 |
+
"target": "Chat API 1",
|
921 |
+
"sourceHandle": "output",
|
922 |
+
"targetHandle": "chat_processor"
|
923 |
+
},
|
924 |
+
{
|
925 |
+
"id": "xy-edge__Mask 1output-Chat processor 1processor",
|
926 |
+
"source": "Mask 1",
|
927 |
+
"target": "Chat processor 1",
|
928 |
+
"sourceHandle": "output",
|
929 |
+
"targetHandle": "processor"
|
930 |
+
},
|
931 |
+
{
|
932 |
+
"id": "xy-edge__Mask 2output-Chat processor 1processor",
|
933 |
+
"source": "Mask 2",
|
934 |
+
"target": "Chat processor 1",
|
935 |
+
"sourceHandle": "output",
|
936 |
+
"targetHandle": "processor"
|
937 |
+
},
|
938 |
+
{
|
939 |
+
"id": "xy-edge__Input chat 1output-Test Chat API 2message",
|
940 |
+
"source": "Input chat 1",
|
941 |
+
"target": "Test Chat API 2",
|
942 |
+
"sourceHandle": "output",
|
943 |
+
"targetHandle": "message"
|
944 |
+
},
|
945 |
+
{
|
946 |
+
"id": "xy-edge__Test Chat API 2output-View 1input",
|
947 |
+
"source": "Test Chat API 2",
|
948 |
+
"target": "View 1",
|
949 |
+
"sourceHandle": "output",
|
950 |
+
"targetHandle": "input"
|
951 |
+
},
|
952 |
+
{
|
953 |
+
"id": "xy-edge__Chat API 1output-Test Chat API 2chat_api",
|
954 |
+
"source": "Chat API 1",
|
955 |
+
"target": "Test Chat API 2",
|
956 |
+
"sourceHandle": "output",
|
957 |
+
"targetHandle": "chat_api"
|
958 |
+
}
|
959 |
+
]
|
960 |
+
}
|
requirements.txt
CHANGED
@@ -2,6 +2,7 @@ fastapi
|
|
2 |
matplotlib
|
3 |
networkx
|
4 |
numpy
|
|
|
5 |
pandas
|
6 |
scipy
|
7 |
uvicorn[standard]
|
|
|
2 |
matplotlib
|
3 |
networkx
|
4 |
numpy
|
5 |
+
orjson
|
6 |
pandas
|
7 |
scipy
|
8 |
uvicorn[standard]
|
server/executors/one_by_one.py
CHANGED
@@ -1,8 +1,8 @@
|
|
1 |
from .. import ops
|
2 |
from .. import workspace
|
3 |
-
import
|
4 |
-
import json
|
5 |
import pandas as pd
|
|
|
6 |
import traceback
|
7 |
import inspect
|
8 |
import typing
|
@@ -37,7 +37,7 @@ def register(env: str, cache: bool = True):
|
|
37 |
ops.EXECUTORS[env] = lambda ws: execute(ws, ops.CATALOGS[env], cache=cache)
|
38 |
|
39 |
def get_stages(ws, catalog):
|
40 |
-
'''Inputs on top are batch inputs. We decompose the graph into a DAG of components along these edges.'''
|
41 |
nodes = {n.id: n for n in ws.nodes}
|
42 |
batch_inputs = {}
|
43 |
inputs = {}
|
@@ -46,7 +46,7 @@ def get_stages(ws, catalog):
|
|
46 |
node = nodes[edge.target]
|
47 |
op = catalog[node.data.title]
|
48 |
i = op.inputs[edge.targetHandle]
|
49 |
-
if i.position
|
50 |
batch_inputs.setdefault(edge.target, []).append(edge.source)
|
51 |
stages = []
|
52 |
for bt, bss in batch_inputs.items():
|
@@ -63,6 +63,15 @@ def get_stages(ws, catalog):
|
|
63 |
stages.append(set(nodes))
|
64 |
return stages
|
65 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
66 |
EXECUTOR_OUTPUT_CACHE = {}
|
67 |
|
68 |
def execute(ws, catalog, cache=None):
|
@@ -77,7 +86,7 @@ def execute(ws, catalog, cache=None):
|
|
77 |
node.data.error = None
|
78 |
op = catalog[node.data.title]
|
79 |
# Start tasks for nodes that have no non-batch inputs.
|
80 |
-
if all([i.position
|
81 |
tasks[node.id] = [NO_INPUT]
|
82 |
batch_inputs = {}
|
83 |
# Run the rest until we run out of tasks.
|
@@ -99,12 +108,12 @@ def execute(ws, catalog, cache=None):
|
|
99 |
for task in ts:
|
100 |
try:
|
101 |
inputs = [
|
102 |
-
batch_inputs[(n, i.name)] if i.position
|
103 |
for i in op.inputs.values()]
|
104 |
-
if cache:
|
105 |
-
key =
|
106 |
if key not in cache:
|
107 |
-
cache[key] = op
|
108 |
result = cache[key]
|
109 |
else:
|
110 |
result = op(*inputs, **params)
|
@@ -126,8 +135,9 @@ def execute(ws, catalog, cache=None):
|
|
126 |
t = nodes[edge.target]
|
127 |
op = catalog[t.data.title]
|
128 |
i = op.inputs[edge.targetHandle]
|
129 |
-
if i.position
|
130 |
batch_inputs.setdefault((edge.target, edge.targetHandle), []).extend(results)
|
131 |
else:
|
132 |
tasks.setdefault(edge.target, []).extend(results)
|
133 |
tasks = next_stage
|
|
|
|
1 |
from .. import ops
|
2 |
from .. import workspace
|
3 |
+
import orjson
|
|
|
4 |
import pandas as pd
|
5 |
+
import pydantic
|
6 |
import traceback
|
7 |
import inspect
|
8 |
import typing
|
|
|
37 |
ops.EXECUTORS[env] = lambda ws: execute(ws, ops.CATALOGS[env], cache=cache)
|
38 |
|
39 |
def get_stages(ws, catalog):
|
40 |
+
'''Inputs on top/bottom are batch inputs. We decompose the graph into a DAG of components along these edges.'''
|
41 |
nodes = {n.id: n for n in ws.nodes}
|
42 |
batch_inputs = {}
|
43 |
inputs = {}
|
|
|
46 |
node = nodes[edge.target]
|
47 |
op = catalog[node.data.title]
|
48 |
i = op.inputs[edge.targetHandle]
|
49 |
+
if i.position in 'top or bottom':
|
50 |
batch_inputs.setdefault(edge.target, []).append(edge.source)
|
51 |
stages = []
|
52 |
for bt, bss in batch_inputs.items():
|
|
|
63 |
stages.append(set(nodes))
|
64 |
return stages
|
65 |
|
66 |
+
|
67 |
+
def _default_serializer(obj):
|
68 |
+
if isinstance(obj, pydantic.BaseModel):
|
69 |
+
return obj.dict()
|
70 |
+
return {"__nonserializable__": id(obj)}
|
71 |
+
|
72 |
+
def make_cache_key(obj):
|
73 |
+
return orjson.dumps(obj, default=_default_serializer)
|
74 |
+
|
75 |
EXECUTOR_OUTPUT_CACHE = {}
|
76 |
|
77 |
def execute(ws, catalog, cache=None):
|
|
|
86 |
node.data.error = None
|
87 |
op = catalog[node.data.title]
|
88 |
# Start tasks for nodes that have no non-batch inputs.
|
89 |
+
if all([i.position in 'top or bottom' for i in op.inputs.values()]):
|
90 |
tasks[node.id] = [NO_INPUT]
|
91 |
batch_inputs = {}
|
92 |
# Run the rest until we run out of tasks.
|
|
|
108 |
for task in ts:
|
109 |
try:
|
110 |
inputs = [
|
111 |
+
batch_inputs[(n, i.name)] if i.position in 'top or bottom' else task
|
112 |
for i in op.inputs.values()]
|
113 |
+
if cache is not None:
|
114 |
+
key = make_cache_key((inputs, params))
|
115 |
if key not in cache:
|
116 |
+
cache[key] = op(*inputs, **params)
|
117 |
result = cache[key]
|
118 |
else:
|
119 |
result = op(*inputs, **params)
|
|
|
135 |
t = nodes[edge.target]
|
136 |
op = catalog[t.data.title]
|
137 |
i = op.inputs[edge.targetHandle]
|
138 |
+
if i.position in 'top or bottom':
|
139 |
batch_inputs.setdefault((edge.target, edge.targetHandle), []).extend(results)
|
140 |
else:
|
141 |
tasks.setdefault(edge.target, []).extend(results)
|
142 |
tasks = next_stage
|
143 |
+
return contexts
|
server/lynxscribe_ops.py
CHANGED
@@ -1,52 +1,203 @@
|
|
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 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
"""
|
2 |
+
LynxScribe configuration and testing in LynxKite.
|
3 |
+
"""
|
4 |
+
from lynxscribe.core.llm.base import get_llm_engine
|
5 |
+
from lynxscribe.core.vector_store.base import get_vector_store
|
6 |
+
from lynxscribe.common.config import load_config
|
7 |
+
from lynxscribe.components.text_embedder import TextEmbedder
|
8 |
+
from lynxscribe.components.rag.rag_graph import RAGGraph
|
9 |
+
from lynxscribe.components.rag.knowledge_base_graph import PandasKnowledgeBaseGraph
|
10 |
+
from lynxscribe.components.rag.rag_chatbot import Scenario, ScenarioSelector, RAGChatbot
|
11 |
+
from lynxscribe.components.chat_processor.base import ChatProcessor
|
12 |
+
from lynxscribe.components.chat_processor.processors import MaskTemplate, TruncateHistory
|
13 |
+
from lynxscribe.components.chat_api import ChatAPI, ChatAPIRequest, ChatAPIResponse
|
14 |
+
|
15 |
+
from . import ops
|
16 |
+
import asyncio
|
17 |
+
import json
|
18 |
+
from .executors import one_by_one
|
19 |
+
|
20 |
+
ENV = 'LynxScribe'
|
21 |
+
one_by_one.register(ENV)
|
22 |
+
op = ops.op_registration(ENV)
|
23 |
+
output_on_top = ops.output_position(output="top")
|
24 |
+
|
25 |
+
@output_on_top
|
26 |
+
@op("Vector store")
|
27 |
+
def vector_store(*, name='chromadb', collection_name='lynx'):
|
28 |
+
vector_store = get_vector_store(name=name, collection_name=collection_name)
|
29 |
+
return {'vector_store': vector_store}
|
30 |
+
|
31 |
+
@output_on_top
|
32 |
+
@op("LLM")
|
33 |
+
def llm(*, name='openai'):
|
34 |
+
llm = get_llm_engine(name=name)
|
35 |
+
return {'llm': llm}
|
36 |
+
|
37 |
+
@output_on_top
|
38 |
+
@ops.input_position(llm="bottom")
|
39 |
+
@op("Text embedder")
|
40 |
+
def text_embedder(llm, *, model='text-embedding-ada-002'):
|
41 |
+
llm = llm[0]['llm']
|
42 |
+
text_embedder = TextEmbedder(llm=llm, model=model)
|
43 |
+
return {'text_embedder': text_embedder}
|
44 |
+
|
45 |
+
@output_on_top
|
46 |
+
@ops.input_position(vector_store="bottom", text_embedder="bottom")
|
47 |
+
@op("RAG graph")
|
48 |
+
def rag_graph(vector_store, text_embedder):
|
49 |
+
vector_store = vector_store[0]['vector_store']
|
50 |
+
text_embedder = text_embedder[0]['text_embedder']
|
51 |
+
rag_graph = RAGGraph(
|
52 |
+
PandasKnowledgeBaseGraph(vector_store=vector_store, text_embedder=text_embedder)
|
53 |
+
)
|
54 |
+
return {'rag_graph': rag_graph}
|
55 |
+
|
56 |
+
@output_on_top
|
57 |
+
@op("Scenario selector")
|
58 |
+
def scenario_selector(*, scenario_file: str, node_types='intent_cluster'):
|
59 |
+
scenarios = load_config(scenario_file)
|
60 |
+
node_types = [t.strip() for t in node_types.split(',')]
|
61 |
+
scenario_selector = ScenarioSelector(
|
62 |
+
scenarios=[Scenario(**scenario) for scenario in scenarios],
|
63 |
+
node_types=node_types,
|
64 |
+
)
|
65 |
+
return {'scenario_selector': scenario_selector}
|
66 |
+
|
67 |
+
DEFAULT_NEGATIVE_ANSWER = "I'm sorry, but the data I've been trained on does not contain any information related to your question."
|
68 |
+
|
69 |
+
@output_on_top
|
70 |
+
@ops.input_position(rag_graph="bottom", scenario_selector="bottom", llm="bottom")
|
71 |
+
@op("RAG chatbot")
|
72 |
+
def rag_chatbot(
|
73 |
+
rag_graph, scenario_selector, llm, *,
|
74 |
+
negative_answer=DEFAULT_NEGATIVE_ANSWER,
|
75 |
+
limits_by_type='{}',
|
76 |
+
strict_limits=True, max_results=5):
|
77 |
+
rag_graph = rag_graph[0]['rag_graph']
|
78 |
+
scenario_selector = scenario_selector[0]['scenario_selector']
|
79 |
+
llm = llm[0]['llm']
|
80 |
+
limits_by_type = json.loads(limits_by_type)
|
81 |
+
rag_chatbot = RAGChatbot(
|
82 |
+
rag_graph=rag_graph,
|
83 |
+
scenario_selector=scenario_selector,
|
84 |
+
llm=llm,
|
85 |
+
negative_answer=negative_answer,
|
86 |
+
limits_by_type=limits_by_type,
|
87 |
+
strict_limits=strict_limits,
|
88 |
+
max_results=max_results,
|
89 |
+
)
|
90 |
+
return {'chatbot': rag_chatbot}
|
91 |
+
|
92 |
+
@output_on_top
|
93 |
+
@ops.input_position(processor="bottom")
|
94 |
+
@op("Chat processor")
|
95 |
+
def chat_processor(processor, *, _ctx: one_by_one.Context):
|
96 |
+
cfg = _ctx.last_result or {'question_processors': [], 'answer_processors': [], 'masks': []}
|
97 |
+
for f in ['question_processor', 'answer_processor', 'mask']:
|
98 |
+
if f in processor:
|
99 |
+
cfg[f + 's'].append(processor[f])
|
100 |
+
question_processors = cfg['question_processors'][:]
|
101 |
+
answer_processors = cfg['answer_processors'][:]
|
102 |
+
masking_templates = {}
|
103 |
+
for mask in cfg['masks']:
|
104 |
+
masking_templates[mask['name']] = mask
|
105 |
+
if masking_templates:
|
106 |
+
question_processors.append(MaskTemplate(masking_templates=masking_templates))
|
107 |
+
answer_processors.append(MaskTemplate(masking_templates=masking_templates))
|
108 |
+
chat_processor = ChatProcessor(question_processors=question_processors, answer_processors=answer_processors)
|
109 |
+
return {'chat_processor': chat_processor, **cfg}
|
110 |
+
|
111 |
+
@output_on_top
|
112 |
+
@op("Truncate history")
|
113 |
+
def truncate_history(*, max_tokens=10000, language='English'):
|
114 |
+
return {'question_processor': TruncateHistory(max_tokens=max_tokens, language=language.lower())}
|
115 |
+
|
116 |
+
@output_on_top
|
117 |
+
@op("Mask")
|
118 |
+
def mask(*, name='', regex='', exceptions='', mask_pattern=''):
|
119 |
+
exceptions = [e.strip() for e in exceptions.split(',') if e.strip()]
|
120 |
+
return {'mask': {'name': name, 'regex': regex, 'exceptions': exceptions, 'mask_pattern': mask_pattern}}
|
121 |
+
|
122 |
+
@ops.input_position(chat_api="bottom")
|
123 |
+
@op("Test Chat API")
|
124 |
+
def test_chat_api(message, chat_api, *, show_details=False):
|
125 |
+
chat_api = chat_api[0]['chat_api']
|
126 |
+
request = ChatAPIRequest(session_id="b43215a0-428f-11ef-9454-0242ac120002", question=message['text'], history=[])
|
127 |
+
response = asyncio.run(chat_api.answer(request))
|
128 |
+
if show_details:
|
129 |
+
return {**response.__dict__}
|
130 |
+
else:
|
131 |
+
return {'answer': response.answer}
|
132 |
+
|
133 |
+
@op("Input chat")
|
134 |
+
def input_chat(*, chat: str):
|
135 |
+
return {'text': chat}
|
136 |
+
|
137 |
+
@output_on_top
|
138 |
+
@ops.input_position(chatbot="bottom", chat_processor="bottom", knowledge_base="bottom")
|
139 |
+
@op("Chat API")
|
140 |
+
def chat_api(chatbot, chat_processor, knowledge_base, *, model='gpt-4o-mini'):
|
141 |
+
chatbot = chatbot[0]['chatbot']
|
142 |
+
chat_processor = chat_processor[0]['chat_processor']
|
143 |
+
knowledge_base = knowledge_base[0]
|
144 |
+
c = ChatAPI(
|
145 |
+
chatbot=chatbot,
|
146 |
+
chat_processor=chat_processor,
|
147 |
+
model=model,
|
148 |
+
)
|
149 |
+
if knowledge_base:
|
150 |
+
c.chatbot.rag_graph.kg_base.load_v1_knowledge_base(**knowledge_base)
|
151 |
+
c.chatbot.scenario_selector.check_compatibility(c.chatbot.rag_graph)
|
152 |
+
return {'chat_api': c}
|
153 |
+
|
154 |
+
@output_on_top
|
155 |
+
@op("Knowledge base")
|
156 |
+
def knowledge_base(*, nodes_path='nodes.pickle', edges_path='edges.pickle', template_cluster_path='tempclusters.pickle'):
|
157 |
+
return {'nodes_path': nodes_path, 'edges_path': edges_path, 'template_cluster_path': template_cluster_path}
|
158 |
+
|
159 |
+
@op("View", view="table_view")
|
160 |
+
def view(input):
|
161 |
+
columns = [str(c) for c in input.keys() if not str(c).startswith('_')]
|
162 |
+
v = {
|
163 |
+
'dataframes': { 'df': {
|
164 |
+
'columns': columns,
|
165 |
+
'data': [[input[c] for c in columns]],
|
166 |
+
}}
|
167 |
+
}
|
168 |
+
return v
|
169 |
+
|
170 |
+
async def api_service(request):
|
171 |
+
'''
|
172 |
+
Serves a chat endpoint that matches LynxScribe's interface.
|
173 |
+
To access it you need to add the "module" and "workspace"
|
174 |
+
parameters.
|
175 |
+
The workspace must contain exactly one "Chat API" node.
|
176 |
+
|
177 |
+
curl -X POST ${LYNXKITE_URL}/api/service \
|
178 |
+
-H "Content-Type: application/json" \
|
179 |
+
-d '{
|
180 |
+
"module": "server.lynxscribe_ops",
|
181 |
+
"workspace": "LynxScribe demo",
|
182 |
+
"session_id": "b43215a0-428f-11ef-9454-0242ac120002",
|
183 |
+
"question": "what does the fox say",
|
184 |
+
"history": [],
|
185 |
+
"user_id": "x",
|
186 |
+
"meta_inputs": {}
|
187 |
+
}'
|
188 |
+
'''
|
189 |
+
import pathlib
|
190 |
+
from . import workspace
|
191 |
+
DATA_PATH = pathlib.Path.cwd() / 'data'
|
192 |
+
path = DATA_PATH / request['workspace']
|
193 |
+
assert path.is_relative_to(DATA_PATH)
|
194 |
+
assert path.exists(), f'Workspace {path} does not exist'
|
195 |
+
ws = workspace.load(path)
|
196 |
+
contexts = ops.EXECUTORS[ENV](ws)
|
197 |
+
nodes = [op for op in ws.nodes if op.data.title == 'Chat API']
|
198 |
+
[node] = nodes
|
199 |
+
context = contexts[node.id]
|
200 |
+
chat_api = context.last_result['chat_api']
|
201 |
+
request = ChatAPIRequest(session_id=request['session_id'], question=request['question'], history=request['history'])
|
202 |
+
response = await chat_api.answer(request)
|
203 |
+
return response
|
server/main.py
CHANGED
@@ -1,5 +1,6 @@
|
|
1 |
import dataclasses
|
2 |
import fastapi
|
|
|
3 |
import pathlib
|
4 |
import pkgutil
|
5 |
from . import crdt
|
@@ -7,10 +8,12 @@ from . import ops
|
|
7 |
from . import workspace
|
8 |
|
9 |
here = pathlib.Path(__file__).parent
|
|
|
10 |
for _, name, _ in pkgutil.iter_modules([str(here)]):
|
11 |
if name.endswith('_ops') and not name.startswith('test_'):
|
12 |
print(f'Importing {name}')
|
13 |
-
|
|
|
14 |
|
15 |
app = fastapi.FastAPI(lifespan=crdt.lifespan)
|
16 |
app.include_router(crdt.router)
|
@@ -68,3 +71,9 @@ def make_dir(req: dict):
|
|
68 |
assert not path.exists()
|
69 |
path.mkdir()
|
70 |
return list_dir(path.parent)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
import dataclasses
|
2 |
import fastapi
|
3 |
+
import importlib
|
4 |
import pathlib
|
5 |
import pkgutil
|
6 |
from . import crdt
|
|
|
8 |
from . import workspace
|
9 |
|
10 |
here = pathlib.Path(__file__).parent
|
11 |
+
lynxkite_modules = {}
|
12 |
for _, name, _ in pkgutil.iter_modules([str(here)]):
|
13 |
if name.endswith('_ops') and not name.startswith('test_'):
|
14 |
print(f'Importing {name}')
|
15 |
+
name = f'server.{name}'
|
16 |
+
lynxkite_modules[name] = importlib.import_module(name)
|
17 |
|
18 |
app = fastapi.FastAPI(lifespan=crdt.lifespan)
|
19 |
app.include_router(crdt.router)
|
|
|
71 |
assert not path.exists()
|
72 |
path.mkdir()
|
73 |
return list_dir(path.parent)
|
74 |
+
|
75 |
+
@app.post("/api/service")
|
76 |
+
async def service(req: dict):
|
77 |
+
'''Executors can provide extra HTTP APIs through the /api/service endpoint.'''
|
78 |
+
module = lynxkite_modules[req['module']]
|
79 |
+
return await module.api_service(req)
|
server/ops.py
CHANGED
@@ -61,7 +61,7 @@ class Parameter(BaseConfig):
|
|
61 |
if default is inspect._empty:
|
62 |
default = None
|
63 |
if type is None or type is inspect._empty:
|
64 |
-
type = typeof(default) if default else None
|
65 |
return Parameter(name=name, default=default, type=type)
|
66 |
|
67 |
class Input(BaseConfig):
|
|
|
61 |
if default is inspect._empty:
|
62 |
default = None
|
63 |
if type is None or type is inspect._empty:
|
64 |
+
type = typeof(default) if default is not None else None
|
65 |
return Parameter(name=name, default=default, type=type)
|
66 |
|
67 |
class Input(BaseConfig):
|
web/package-lock.json
CHANGED
@@ -25,6 +25,7 @@
|
|
25 |
"sass": "1.79.5",
|
26 |
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@@ -1933,6 +1173,18 @@
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},
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"funding": {
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"type": "opencollective",
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"url": "https://opencollective.com/parcel"
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+
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|
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],
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|
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"os": [
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+
"darwin"
|
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|
225 |
"node_modules/@rollup/rollup-darwin-arm64": {
|
226 |
"version": "4.24.0",
|
227 |
"resolved": "https://registry.npmjs.org/@rollup/rollup-darwin-arm64/-/rollup-darwin-arm64-4.24.0.tgz",
|
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|
235 |
"darwin"
|
236 |
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|
237 |
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238 |
"node_modules/@svelte-put/shortcut": {
|
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"version": "3.1.1",
|
240 |
"resolved": "https://registry.npmjs.org/@svelte-put/shortcut/-/shortcut-3.1.1.tgz",
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|
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"resolved": "https://registry.npmjs.org/@xyflow/svelte/-/svelte-0.1.21.tgz",
|
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1173 |
"@jridgewell/sourcemap-codec": "^1.5.0"
|
1174 |
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|
1175 |
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|
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|
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|
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|
1190 |
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|
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|
1587 |
"svelte": "^3.19.0 || ^4.0.0"
|
1588 |
}
|
1589 |
},
|
1590 |
+
"node_modules/svelte-markdown": {
|
1591 |
+
"version": "0.4.1",
|
1592 |
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"resolved": "https://registry.npmjs.org/svelte-markdown/-/svelte-markdown-0.4.1.tgz",
|
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"dependencies": {
|
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|
1597 |
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"marked": "^5.1.2"
|
1598 |
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|
1599 |
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|
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"svelte": "^4.0.0"
|
1601 |
+
}
|
1602 |
+
},
|
1603 |
"node_modules/tinyexec": {
|
1604 |
"version": "0.3.0",
|
1605 |
"resolved": "https://registry.npmjs.org/tinyexec/-/tinyexec-0.3.0.tgz",
|
web/package.json
CHANGED
@@ -17,6 +17,7 @@
|
|
17 |
"sass": "1.79.5",
|
18 |
"svelte": "4.2.19",
|
19 |
"svelte-check": "4.0.5",
|
|
|
20 |
"tslib": "2.7.0",
|
21 |
"typescript": "5.6.3",
|
22 |
"unplugin-icons": "0.19.3",
|
|
|
17 |
"sass": "1.79.5",
|
18 |
"svelte": "4.2.19",
|
19 |
"svelte-check": "4.0.5",
|
20 |
+
"svelte-markdown": "^0.4.1",
|
21 |
"tslib": "2.7.0",
|
22 |
"typescript": "5.6.3",
|
23 |
"unplugin-icons": "0.19.3",
|
web/src/NodeParameter.svelte
CHANGED
@@ -3,21 +3,24 @@
|
|
3 |
export let value;
|
4 |
export let meta;
|
5 |
export let onChange;
|
|
|
6 |
</script>
|
7 |
|
8 |
<label class="param">
|
9 |
-
<span class="param-name">{name.replace(/_/g, ' ')}</span>
|
10 |
{#if meta?.type?.format === 'collapsed'}
|
|
|
11 |
<button class="collapsed-param form-control form-control-sm">
|
12 |
⋯
|
13 |
</button>
|
14 |
{:else if meta?.type?.format === 'textarea'}
|
|
|
15 |
<textarea class="form-control form-control-sm"
|
16 |
-
|
17 |
-
|
18 |
-
|
19 |
-
|
20 |
{:else if meta?.type?.enum}
|
|
|
21 |
<select class="form-select form-select-sm"
|
22 |
value={value || meta.type.enum[0]}
|
23 |
on:change={(evt) => onChange(evt.currentTarget.value)}
|
@@ -26,11 +29,21 @@
|
|
26 |
<option value={option}>{option}</option>
|
27 |
{/each}
|
28 |
</select>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
29 |
{:else}
|
|
|
30 |
<input class="form-control form-control-sm"
|
31 |
-
|
32 |
-
|
33 |
-
|
34 |
{/if}
|
35 |
</label>
|
36 |
|
|
|
3 |
export let value;
|
4 |
export let meta;
|
5 |
export let onChange;
|
6 |
+
const BOOLEAN = "<class 'bool'>";
|
7 |
</script>
|
8 |
|
9 |
<label class="param">
|
|
|
10 |
{#if meta?.type?.format === 'collapsed'}
|
11 |
+
<span class="param-name">{name.replace(/_/g, ' ')}</span>
|
12 |
<button class="collapsed-param form-control form-control-sm">
|
13 |
⋯
|
14 |
</button>
|
15 |
{:else if meta?.type?.format === 'textarea'}
|
16 |
+
<span class="param-name">{name.replace(/_/g, ' ')}</span>
|
17 |
<textarea class="form-control form-control-sm"
|
18 |
+
rows="6"
|
19 |
+
value={value}
|
20 |
+
on:change={(evt) => onChange(evt.currentTarget.value)}
|
21 |
+
/>
|
22 |
{:else if meta?.type?.enum}
|
23 |
+
<span class="param-name">{name.replace(/_/g, ' ')}</span>
|
24 |
<select class="form-select form-select-sm"
|
25 |
value={value || meta.type.enum[0]}
|
26 |
on:change={(evt) => onChange(evt.currentTarget.value)}
|
|
|
29 |
<option value={option}>{option}</option>
|
30 |
{/each}
|
31 |
</select>
|
32 |
+
{:else if meta?.type?.type === BOOLEAN}
|
33 |
+
<label class="form-check-label">
|
34 |
+
<input class="form-check-input"
|
35 |
+
type="checkbox"
|
36 |
+
checked={value}
|
37 |
+
on:change={(evt) => onChange(evt.currentTarget.checked)}
|
38 |
+
/>
|
39 |
+
{name.replace(/_/g, ' ')}
|
40 |
+
</label>
|
41 |
{:else}
|
42 |
+
<span class="param-name">{name.replace(/_/g, ' ')}</span>
|
43 |
<input class="form-control form-control-sm"
|
44 |
+
value={value}
|
45 |
+
on:change={(evt) => onChange(evt.currentTarget.value)}
|
46 |
+
/>
|
47 |
{/if}
|
48 |
</label>
|
49 |
|