diff options
| -rw-r--r-- | src/client/apis/gpt/GPT.ts | 35 | ||||
| -rw-r--r-- | src/client/views/collections/collectionFreeForm/ImageLabelBox.tsx | 2 | ||||
| -rw-r--r-- | src/client/views/nodes/ImageBox.tsx | 48 | ||||
| -rw-r--r-- | src/client/views/nodes/formattedText/FormattedTextBox.tsx | 18 | ||||
| -rw-r--r-- | src/client/views/nodes/scrapbook/ScrapbookBox.tsx | 50 | ||||
| -rw-r--r-- | src/client/views/search/FaceRecognitionHandler.tsx | 4 |
6 files changed, 137 insertions, 20 deletions
diff --git a/src/client/apis/gpt/GPT.ts b/src/client/apis/gpt/GPT.ts index 9cb47995c..1956fef0c 100644 --- a/src/client/apis/gpt/GPT.ts +++ b/src/client/apis/gpt/GPT.ts @@ -11,6 +11,10 @@ export enum GPTDocCommand { export const DescriptionSeperator = '======'; export const DocSeperator = '------'; +export enum TextClassifications { + Title = 'title', //a few words + Caption = 'caption', //few sentences + LengthyDescription = 'lengthy description' } enum GPTCallType { SUMMARY = 'summary', @@ -36,6 +40,7 @@ enum GPTCallType { SUBSETDOCS = 'subset_docs', // select a subset of documents based on their descriptions DOCINFO = 'doc_info', // provide information about a document SORTDOCS = 'sort_docs', + CLASSIFYTEXT = 'classify_text', // classify text into one of the three categories: title, caption, lengthy description } type GPTCallOpts = { @@ -48,6 +53,23 @@ type GPTCallOpts = { const callTypeMap: { [type in GPTCallType]: GPTCallOpts } = { // newest model: gpt-4 summary: { model: 'gpt-4-turbo', maxTokens: 256, temp: 0.5, prompt: 'Summarize the text given in simpler terms.' }, + + + sort_docs: { + model: 'gpt-4o', + maxTokens: 2048, + temp: 0.25, + prompt: + `The user is going to give you a list of descriptions. + Each one is separated by '${DescriptionSeperator}' on either side. + Descriptions will vary in length, so make sure to only separate when you see '${DescriptionSeperator}'. + Sort them by the user's specifications. + Make sure each description is only in the list once. Each item should be separated by '${DescriptionSeperator}'. + Immediately afterward, surrounded by '${DocSeperator}' on BOTH SIDES, provide some insight into your reasoning for the way you sorted (and mention nothing about the formatting details given in this description). + It is VERY important that you format it exactly as described, ensuring the proper number of '${DescriptionSeperator[0]}' and '${DocSeperator[0]}' (${DescriptionSeperator.length} of each) and NO commas`, + }, + + edit: { model: 'gpt-4-turbo', maxTokens: 256, temp: 0.5, prompt: 'Reword the text.' }, stack: { model: 'gpt-4o', @@ -69,17 +91,14 @@ const callTypeMap: { [type in GPTCallType]: GPTCallOpts } = { temp: 0.5, prompt: "You are a helpful resarch assistant. Analyze the user's data to find meaningful patterns and/or correlation. Please only return a JSON with a correlation column 1 propert, a correlation column 2 property, and an analysis property. ", }, - sort_docs: { + //new + classify_text: { model: 'gpt-4o', maxTokens: 2048, temp: 0.25, - prompt: `The user is going to give you a list of descriptions. - Each one is separated by '${DescriptionSeperator}' on either side. - Descriptions will vary in length, so make sure to only separate when you see '${DescriptionSeperator}'. - Sort them by the user's specifications. - Make sure each description is only in the list once. Each item should be separated by '${DescriptionSeperator}'. - Immediately afterward, surrounded by '${DocSeperator}' on BOTH SIDES, provide some insight into your reasoning for the way you sorted (and mention nothing about the formatting details given in this description). - It is VERY important that you format it exactly as described, ensuring the proper number of '${DescriptionSeperator[0]}' and '${DocSeperator[0]}' (${DescriptionSeperator.length} of each) and NO commas`, + prompt: `Based on the content of the the text, classify it into the + most appropriate category: '${TextClassifications.Title}', '${TextClassifications.Caption}', or '${TextClassifications.LengthyDescription}'. Output exclusively the classification in your response. + ` }, describe: { model: 'gpt-4-vision-preview', maxTokens: 2048, temp: 0, prompt: 'Describe these images in 3-5 words' }, flashcard: { diff --git a/src/client/views/collections/collectionFreeForm/ImageLabelBox.tsx b/src/client/views/collections/collectionFreeForm/ImageLabelBox.tsx index bf674c025..038b1c6f9 100644 --- a/src/client/views/collections/collectionFreeForm/ImageLabelBox.tsx +++ b/src/client/views/collections/collectionFreeForm/ImageLabelBox.tsx @@ -160,7 +160,7 @@ export class ImageLabelBox extends ViewBoxBaseComponent<FieldViewProps>() { classifyImagesInBox = async (selectedImages? : Doc[], prompt? : string) => { this.startLoading(); - + alert('Classifying images...'); selectedImages ??= this._selectedImages; // Converts the images into a Base64 format, afterwhich the information is sent to GPT to label them. diff --git a/src/client/views/nodes/ImageBox.tsx b/src/client/views/nodes/ImageBox.tsx index 6e6ca3f73..0b6814c01 100644 --- a/src/client/views/nodes/ImageBox.tsx +++ b/src/client/views/nodes/ImageBox.tsx @@ -7,8 +7,9 @@ import { observer } from 'mobx-react'; import { extname } from 'path'; import * as React from 'react'; import { AiOutlineSend } from 'react-icons/ai'; +import { ImageLabelBoxData } from '../collections/collectionFreeForm/ImageLabelBox'; import ReactLoading from 'react-loading'; -import { ClientUtils, DashColor, returnEmptyString, returnFalse, returnOne, returnZero, setupMoveUpEvents, UpdateIcon } from '../../../ClientUtils'; +import { ClientUtils, imageUrlToBase64, DashColor, returnEmptyString, returnFalse, returnOne, returnZero, setupMoveUpEvents, UpdateIcon } from '../../../ClientUtils'; import { Doc, DocListCast, Opt } from '../../../fields/Doc'; import { DocData } from '../../../fields/DocSymbols'; import { Id } from '../../../fields/FieldSymbols'; @@ -16,7 +17,7 @@ import { InkTool } from '../../../fields/InkField'; import { List } from '../../../fields/List'; import { ObjectField } from '../../../fields/ObjectField'; import { ComputedField } from '../../../fields/ScriptField'; -import { Cast, DocCast, ImageCast, NumCast, RTFCast, StrCast } from '../../../fields/Types'; +import { Cast, DocCast, ImageCast, NumCast, RTFCast, StrCast, ImageCastWithSuffix } from '../../../fields/Types'; import { ImageField } from '../../../fields/URLField'; import { TraceMobx } from '../../../fields/util'; import { emptyFunction } from '../../../Utils'; @@ -46,6 +47,7 @@ import { FieldView, FieldViewProps } from './FieldView'; import { FocusViewOptions } from './FocusViewOptions'; import './ImageBox.scss'; import { OpenWhere } from './OpenWhere'; +import { gptImageLabel } from '../../apis/gpt/GPT'; import { ImageLabelBox } from '../collections/collectionFreeForm/ImageLabelBox'; const DefaultPath = '/assets/unknown-file-icon-hi.png'; @@ -122,11 +124,47 @@ export class ImageBox extends ViewBoxAnnotatableComponent<FieldViewProps>() { }; autoTag = async () => { - ImageLabelBox.Instance.classifyImagesInBox([this.Document], "Classify this image as a PERSON or LANDSCAPE. You may only respond with one of these two options"); - - //Doc.getDescription(this.Document).then(desc => this.desc = desc) + try { + // 1) grab the full-size URL + const layoutKey = Doc.LayoutDataKey(this.Document); + const url = ImageCastWithSuffix(this.Document[layoutKey], '_o') ?? ''; + if (!url) throw new Error('No image URL found'); + + // 2) convert to base64 + const base64 = await imageUrlToBase64(url); + if (!base64) throw new Error('Failed to load image data'); + + // 3) ask GPT for exactly one label: PERSON or LANDSCAPE + const raw = await gptImageLabel( + base64, + 'Classify this image as PERSON or LANDSCAPE. You may only respond with one of these two options.' + ); + + // 4) normalize and prefix + const label = raw + .trim() + .toUpperCase() + + // 5) stash it on the Doc + // overwrite any old tags so re-runs still work + this.Document.$tags_chat = new List<string>(); + (this.Document.$tags_chat as List<string>).push(label); + + // 6) flip on “show tags” in the layout + // (same flag that ImageLabelBox.toggleDisplayInformation uses) + //note to self: What if i used my own field (ex: Document.$auto_description or something + //Would i still have to toggle it on for it to show in the metadata? + this.Document._layout_showTags = true; + + } catch (err) { + console.error('autoTag failed:', err); + } finally { } + }; + + //Doc.getDescription(this.Document).then(desc => this.desc = desc) + diff --git a/src/client/views/nodes/formattedText/FormattedTextBox.tsx b/src/client/views/nodes/formattedText/FormattedTextBox.tsx index 98e461a52..f4cbbcc9e 100644 --- a/src/client/views/nodes/formattedText/FormattedTextBox.tsx +++ b/src/client/views/nodes/formattedText/FormattedTextBox.tsx @@ -64,6 +64,7 @@ import { removeMarkWithAttrs } from './prosemirrorPatches'; import { RichTextMenu, RichTextMenuPlugin } from './RichTextMenu'; import { RichTextRules } from './RichTextRules'; import { schema } from './schema_rts'; +import { tickStep } from 'd3'; // import * as applyDevTools from 'prosemirror-dev-tools'; export interface FormattedTextBoxProps extends FieldViewProps { @@ -304,6 +305,14 @@ export class FormattedTextBox extends ViewBoxAnnotatableComponent<FormattedTextB } }; + autoTag = async () => { + this.Document.$tags_chat = new List<string>(); + gptAPICall(RTFCast(this.Document[Doc.LayoutDataKey(this.Document)])?.Text ?? StrCast(this.Document[Doc.LayoutDataKey(this.Document)]), + GPTCallType.CLASSIFYTEXT).then(desc => (this.Document.$tags_chat as List<string>).push(desc)); + this.Document._layout_showTags = true; + //or... then(desc => this.Document.$tags_chat = desc); + } + leafText = (node: Node) => { if (node.type === this.EditorView?.state.schema.nodes.dashField) { const refDoc = !node.attrs.docId ? this.rootDoc : (DocServer.GetCachedRefField(node.attrs.docId as string) as Doc); @@ -1236,6 +1245,7 @@ export class FormattedTextBox extends ViewBoxAnnotatableComponent<FormattedTextB }, { fireImmediately: true } ); + this._disposers.search = reaction( () => Doc.IsSearchMatch(this.Document), @@ -1269,6 +1279,14 @@ export class FormattedTextBox extends ViewBoxAnnotatableComponent<FormattedTextB { fireImmediately: true } ); + this._disposers.tagger = reaction( + () => ({ title: this.Document.title, sel: this.props.isSelected() }), + action(() => { + this.autoTag(); + }), + { fireImmediately: true } + ); + if (!this._props.dontRegisterView) { this._disposers.record = reaction( () => this.recordingDictation, diff --git a/src/client/views/nodes/scrapbook/ScrapbookBox.tsx b/src/client/views/nodes/scrapbook/ScrapbookBox.tsx index 55d0df585..39729a1c5 100644 --- a/src/client/views/nodes/scrapbook/ScrapbookBox.tsx +++ b/src/client/views/nodes/scrapbook/ScrapbookBox.tsx @@ -1,6 +1,6 @@ import { action, makeObservable, observable } from 'mobx'; import * as React from 'react'; -import { Doc, DocListCast } from '../../../../fields/Doc'; +import { Doc, DocListCast, StrListCast } from '../../../../fields/Doc'; import { List } from '../../../../fields/List'; import { emptyFunction } from '../../../../Utils'; import { Docs } from '../../../documents/Documents'; @@ -100,20 +100,62 @@ export class ScrapbookBox extends ViewBoxAnnotatableComponent<FieldViewProps>() }; filterAddDocument = (docIn: Doc | Doc[]) => { - const docs = toList(docIn); + const docs = toList(docIn); //The docs being added to the scrapbook + + // 1) Grab all template slots: + const slots = DocListCast(this.dataDoc[this.fieldKey]); + + // 2) recursive unwrap: + const unwrap = (items: Doc[]): Doc[] => + items.flatMap(d => + d.$type === DocumentType.COL + ? unwrap(DocListCast(d[Doc.LayoutDataKey(d)])) + : [d] + ); + + // 3) produce a flat list of every doc, unwrapping any number of nested COLs + const allDocs: Doc[] = unwrap(slots); + + if (docs?.length === 1) { - const placeholder = DocListCast(this.dataDoc[this.fieldKey]).find(d => + const placeholder = allDocs.filter(d => + (d.accepts_docType === docs[0].$type || // match fields based on type, or by analyzing content .. simple example of matching text in placeholder to dropped doc's type RTFCast(d[Doc.LayoutDataKey(d)])?.Text.includes(StrCast(docs[0].$type))) ); // prettier-ignore + //DocListCast(this.Document.items).map(doc => DocListCast(doc[Doc.LayoutDataKey(doc)]) + if (placeholder) { + /**Look at the autotags and see what matches*RTFCast(d[Doc.LayoutDataKey(d)])?.Text*/ // ugh. we have to tell the underlying view not to add the Doc so that we can add it where we want it. // However, returning 'false' triggers an undo. so this settimeout is needed to make the assignment happen after the undo. setTimeout( undoable(() => { + + const slotTagsList: Set<string>[] = placeholder.map(doc => + new Set<string>(StrListCast(doc.$tags_chat)) + ); + // turn docs[0].$tags_chat into a Set + const targetTags = new Set(StrListCast(docs[0].$tags_chat)); + //StrListCast(placeholder.overrideFields).map(field => (docs[0][field] = placeholder[field])); // // shouldn't need to do this for layout fields since the placeholder already overrides its protos - placeholder.proto = docs[0]; + + // find the first placeholder that shares *any* tag + const match = placeholder.find(ph => + StrListCast(ph.$tags_chat).some(tag => targetTags.has(tag)) + ); + if (match) { + match.proto = docs[0]; + } + + /*const chosenPlaceholder = placeholder.find(d => + pl = new Set<string>(StrListCast(d.$tags_chat) + + d.$tags_chat && d.$tags_chat[0].equals(docs[0].$tags_chat)); //why [0] + if (chosenPlaceholder){ + chosenPlaceholder.proto = docs[0];}*/ + //excess if statement?? }, 'Scrapbook add') ); return false; diff --git a/src/client/views/search/FaceRecognitionHandler.tsx b/src/client/views/search/FaceRecognitionHandler.tsx index 60744588f..256e68afd 100644 --- a/src/client/views/search/FaceRecognitionHandler.tsx +++ b/src/client/views/search/FaceRecognitionHandler.tsx @@ -210,8 +210,8 @@ export class FaceRecognitionHandler { } else if (imgDoc.type === DocumentType.LOADING && !imgDoc.loadingError) { setTimeout(() => this.classifyFacesInImage(imgDocView), 1000); } else { - reaction(() => ({sel:imgDocView.isSelected()}), ({sel}) => !sel && imgDoc.type == 'text' - && imgDocView.ComponentView?.autoTag?.(), {fireImmediately: true} + reaction(() => ({sel:imgDocView.isSelected()}), ({sel}) => !sel && + imgDocView.ComponentView?.autoTag?.(), {fireImmediately: true} ) const imgUrl = ImageCast(imgDoc[Doc.LayoutDataKey(imgDoc)]); if (imgUrl && !DocListCast(Doc.MyFaceCollection?.examinedFaceDocs).includes(imgDoc[DocData])) { |