Merge branch 'master' into aarav_edit

3 files changed, 22 insertions, 18 deletions

diff --git a/src/client/views/nodes/chatbot/chatboxcomponents/ChatBox.tsx b/src/client/views/nodes/chatbot/chatboxcomponents/ChatBox.tsx
index 528bcd05a..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,
@@ -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 c1915a398..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();
 
@@ -101,7 +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.');
@@ -112,13 +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({
@@ -138,7 +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: {
@@ -173,7 +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));
@@ -297,7 +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.