diff options
Diffstat (limited to 'src/client/views/nodes/chatbot')
3 files changed, 27 insertions, 22 deletions
diff --git a/src/client/views/nodes/chatbot/chatboxcomponents/ChatBox.tsx b/src/client/views/nodes/chatbot/chatboxcomponents/ChatBox.tsx index 6e9307d37..6c3da8977 100644 --- a/src/client/views/nodes/chatbot/chatboxcomponents/ChatBox.tsx +++ b/src/client/views/nodes/chatbot/chatboxcomponents/ChatBox.tsx @@ -196,7 +196,7 @@ export class ChatBox extends ViewBoxAnnotatableComponent<FieldViewProps>() { // Add CSV details to linked files this._linked_csv_files.push({ - filename: CsvCast(newLinkedDoc.data).url.pathname, + filename: CsvCast(newLinkedDoc.data)?.url.pathname ?? '', id: csvId, text: csvData, }); @@ -634,6 +634,7 @@ export class ChatBox extends ViewBoxAnnotatableComponent<FieldViewProps>() { }; getDirectMatchingSegmentStart = (doc: Doc, citationText: string, indexesOfSegments: string[]): number => { + // eslint-disable-next-line @typescript-eslint/no-explicit-any const originalSegments = JSON.parse(StrCast(doc.original_segments!)).map((segment: any, index: number) => ({ index: index.toString(), text: segment.text, @@ -733,9 +734,9 @@ export class ChatBox extends ViewBoxAnnotatableComponent<FieldViewProps>() { const x2 = parseFloat(values[2]) * Doc.NativeWidth(doc); const y2 = parseFloat(values[3]) * Doc.NativeHeight(doc) + foundChunk.startPage * Doc.NativeHeight(doc); - const annotationKey = Doc.LayoutFieldKey(doc) + '_annotations'; + const annotationKey = '$' + Doc.LayoutDataKey(doc) + '_annotations'; - const existingDoc = DocListCast(doc[DocData][annotationKey]).find(d => d.citation_id === citation.citation_id); + const existingDoc = DocListCast(doc[annotationKey]).find(d => d.citation_id === citation.citation_id); const highlightDoc = existingDoc ?? this.createImageCitationHighlight(x1, y1, x2, y2, citation, annotationKey, doc); DocumentManager.Instance.showDocument(highlightDoc, { willZoomCentered: true }, () => {}); @@ -779,7 +780,7 @@ export class ChatBox extends ViewBoxAnnotatableComponent<FieldViewProps>() { _height: y2 - y1, backgroundColor: 'rgba(255, 255, 0, 0.5)', }); - highlight_doc[DocData].citation_id = citation.citation_id; + highlight_doc.$citation_id = citation.citation_id; Doc.AddDocToList(pdfDoc[DocData], annotationKey, highlight_doc); highlight_doc.annotationOn = pdfDoc; Doc.SetContainer(highlight_doc, pdfDoc); @@ -877,7 +878,8 @@ export class ChatBox extends ViewBoxAnnotatableComponent<FieldViewProps>() { return LinkManager.Instance.getAllRelatedLinks(this.Document) .map(d => DocCast(LinkManager.getOppositeAnchor(d, this.Document))) .map(d => DocCast(d?.annotationOn, d)) - .filter(d => d); + .filter(d => d) + .map(d => d!); } /** @@ -889,6 +891,7 @@ export class ChatBox extends ViewBoxAnnotatableComponent<FieldViewProps>() { .map(d => DocCast(LinkManager.getOppositeAnchor(d, this.Document))) .map(d => DocCast(d?.annotationOn, d)) .filter(d => d) + .map(d => d!) .filter(d => { console.log(d.ai_doc_id); return d.ai_doc_id; @@ -905,15 +908,14 @@ export class ChatBox extends ViewBoxAnnotatableComponent<FieldViewProps>() { LinkManager.Instance.getAllRelatedLinks(this.Document) .map(d => DocCast(LinkManager.getOppositeAnchor(d, this.Document))) .map(d => DocCast(d?.annotationOn, d)) - .filter(d => d) - .filter(d => d.summary) + .filter(d => d?.summary) .map((doc, index) => { - if (PDFCast(doc.data)) { - return `<summary file_name="${PDFCast(doc.data).url.pathname}" applicable_tools=["rag"]>${doc.summary}</summary>`; - } else if (CsvCast(doc.data)) { - return `<summary file_name="${CsvCast(doc.data).url.pathname}" applicable_tools=["dataAnalysis"]>${doc.summary}</summary>`; + if (PDFCast(doc?.data)) { + return `<summary file_name="${PDFCast(doc!.data)!.url.pathname}" applicable_tools=["rag"]>${doc!.summary}</summary>`; + } else if (CsvCast(doc?.data)) { + return `<summary file_name="${CsvCast(doc!.data)!.url.pathname}" applicable_tools=["dataAnalysis"]>${doc!.summary}</summary>`; } else { - return `${index + 1}) ${doc.summary}`; + return `${index + 1}) ${doc?.summary}`; } }) .join('\n') + '\n' diff --git a/src/client/views/nodes/chatbot/tools/GetDocsTool.ts b/src/client/views/nodes/chatbot/tools/GetDocsTool.ts index 05482a66e..42a7747d3 100644 --- a/src/client/views/nodes/chatbot/tools/GetDocsTool.ts +++ b/src/client/views/nodes/chatbot/tools/GetDocsTool.ts @@ -40,7 +40,10 @@ export class GetDocsTool extends BaseTool<GetDocsToolParamsType> { } async execute(args: ParametersType<GetDocsToolParamsType>): Promise<Observation[]> { - const docs = args.document_ids.map(doc_id => DocCast(DocServer.GetCachedRefField(doc_id))); + const docs = args.document_ids + .map(doc_id => DocCast(DocServer.GetCachedRefField(doc_id))) + .filter(d => d) + .map(d => d!); const collection = Docs.Create.FreeformDocument(docs, { title: args.title }); this._docView._props.addDocTab(collection, OpenWhere.addRight); return [{ type: 'text', text: `Collection created in Dash called ${args.title}` }]; diff --git a/src/client/views/nodes/chatbot/vectorstore/Vectorstore.ts b/src/client/views/nodes/chatbot/vectorstore/Vectorstore.ts index afd34f28d..6d524e40f 100644 --- a/src/client/views/nodes/chatbot/vectorstore/Vectorstore.ts +++ b/src/client/views/nodes/chatbot/vectorstore/Vectorstore.ts @@ -15,7 +15,6 @@ import { Networking } from '../../../../Network'; import { AI_Document, CHUNK_TYPE, RAGChunk } from '../types/types'; import OpenAI from 'openai'; import { Embedding } from 'openai/resources'; -import { PineconeEnvironmentVarsNotSupportedError } from '@pinecone-database/pinecone/dist/errors'; dotenv.config(); @@ -42,7 +41,8 @@ export class Vectorstore { constructor(id: string, doc_ids: () => string[]) { const pineconeApiKey = process.env.PINECONE_API_KEY; if (!pineconeApiKey) { - throw new Error('PINECONE_API_KEY is not defined.'); + console.log('PINECONE_API_KEY is not defined - Vectorstore will be unavailable'); + return; } // Initialize Pinecone and OpenAI clients with API keys from the environment. @@ -100,7 +100,7 @@ export class Vectorstore { } else { // Start processing the document. doc.ai_document_status = 'PROGRESS'; - const local_file_path: string = CsvCast(doc.data)?.url?.pathname ?? PDFCast(doc.data)?.url?.pathname ?? VideoCast(doc.data)?.url?.pathname ?? AudioCast(doc.data)?.url?.pathname; + const local_file_path = CsvCast(doc.data)?.url?.pathname ?? PDFCast(doc.data)?.url?.pathname ?? VideoCast(doc.data)?.url?.pathname ?? AudioCast(doc.data)?.url?.pathname; if (!local_file_path) { console.log('Invalid file path.'); @@ -111,13 +111,13 @@ export class Vectorstore { let result: AI_Document & { doc_id: string }; if (isAudioOrVideo) { console.log('Processing media file...'); - const response = await Networking.PostToServer('/processMediaFile', { fileName: path.basename(local_file_path) }); + const response = (await Networking.PostToServer('/processMediaFile', { fileName: path.basename(local_file_path) })) as { [key: string]: unknown }; const segmentedTranscript = response.condensed; console.log(segmentedTranscript); - const summary = response.summary; + const summary = response.summary as string; doc.summary = summary; // Generate embeddings for each chunk - const texts = segmentedTranscript.map((chunk: any) => chunk.text); + const texts = (segmentedTranscript as { text: string }[])?.map(chunk => chunk.text); try { const embeddingsResponse = await this.openai.embeddings.create({ @@ -137,7 +137,7 @@ export class Vectorstore { file_name: local_file_path, num_pages: 0, summary: '', - chunks: segmentedTranscript.map((chunk: any, index: number) => ({ + chunks: (segmentedTranscript as { text: string; start: number; end: number; indexes: string[] }[]).map((chunk, index) => ({ id: uuidv4(), values: (embeddingsResponse.data as Embedding[])[index].embedding, // Assign embedding metadata: { @@ -172,7 +172,7 @@ export class Vectorstore { } else { // Existing document processing logic remains unchanged console.log('Processing regular document...'); - const { jobId } = await Networking.PostToServer('/createDocument', { file_path: local_file_path }); + const { jobId } = (await Networking.PostToServer('/createDocument', { file_path: local_file_path })) as { jobId: string }; while (true) { await new Promise(resolve => setTimeout(resolve, 2000)); @@ -296,7 +296,7 @@ export class Vectorstore { encoding_format: 'float', }); - let queryEmbedding = queryEmbeddingResponse.data[0].embedding; + const queryEmbedding = queryEmbeddingResponse.data[0].embedding; // Extract the embedding from the response. |