completely restructured, added comments, and significantly reduced the length of the prompt (~72% shorter and cheaper)

1 files changed, 0 insertions, 125 deletions

diff --git a/src/client/views/nodes/ChatBox/response_parsers/AnswerParser.ts b/src/client/views/nodes/ChatBox/response_parsers/AnswerParser.ts
deleted file mode 100644
index 79b53b0a3..000000000
--- a/src/client/views/nodes/ChatBox/response_parsers/AnswerParser.ts
+++ /dev/null
@@ -1,125 +0,0 @@
-import { ASSISTANT_ROLE, AssistantMessage, Citation, CHUNK_TYPE, TEXT_TYPE, getChunkType, ProcessingInfo } from '../types';
-import { v4 as uuid } from 'uuid';
-
-export class AnswerParser {
-    static parse(xml: string, processingInfo: ProcessingInfo[]): AssistantMessage {
-        const answerRegex = /<answer>([\s\S]*?)<\/answer>/;
-        const citationsRegex = /<citations>([\s\S]*?)<\/citations>/;
-        const citationRegex = /<citation index="([^"]+)" chunk_id="([^"]+)" type="([^"]+)">([\s\S]*?)<\/citation>/g;
-        const followUpQuestionsRegex = /<follow_up_questions>([\s\S]*?)<\/follow_up_questions>/;
-        const questionRegex = /<question>(.*?)<\/question>/g;
-        const groundedTextRegex = /<grounded_text citation_index="([^"]+)">([\s\S]*?)<\/grounded_text>/g;
-        const normalTextRegex = /<normal_text>([\s\S]*?)<\/normal_text>/g;
-        const loopSummaryRegex = /<loop_summary>([\s\S]*?)<\/loop_summary>/;
-
-        const answerMatch = answerRegex.exec(xml);
-        const citationsMatch = citationsRegex.exec(xml);
-        const followUpQuestionsMatch = followUpQuestionsRegex.exec(xml);
-        const loopSummaryMatch = loopSummaryRegex.exec(xml);
-
-        if (!answerMatch) {
-            throw new Error('Invalid XML: Missing <answer> tag.');
-        }
-
-        let rawTextContent = answerMatch[1].trim();
-        let content: AssistantMessage['content'] = [];
-        let citations: Citation[] = [];
-        let contentIndex = 0;
-
-        // Remove citations and follow-up questions from rawTextContent
-        if (citationsMatch) {
-            rawTextContent = rawTextContent.replace(citationsMatch[0], '').trim();
-        }
-        if (followUpQuestionsMatch) {
-            rawTextContent = rawTextContent.replace(followUpQuestionsMatch[0], '').trim();
-        }
-        if (loopSummaryMatch) {
-            rawTextContent = rawTextContent.replace(loopSummaryMatch[0], '').trim();
-        }
-
-        // Parse citations
-        let citationMatch;
-        const citationMap = new Map<string, string>();
-        if (citationsMatch) {
-            const citationsContent = citationsMatch[1];
-            while ((citationMatch = citationRegex.exec(citationsContent)) !== null) {
-                const [_, index, chunk_id, type, direct_text] = citationMatch;
-                const citation_id = uuid();
-                citationMap.set(index, citation_id);
-                citations.push({
-                    direct_text: direct_text.trim(),
-                    type: getChunkType(type),
-                    chunk_id,
-                    citation_id,
-                });
-            }
-        }
-
-        rawTextContent = rawTextContent.replace(normalTextRegex, '$1');
-
-        // Parse text content (normal and grounded)
-        let lastIndex = 0;
-        let match;
-
-        while ((match = groundedTextRegex.exec(rawTextContent)) !== null) {
-            const [fullMatch, citationIndex, groundedText] = match;
-
-            // Add normal text that is before the grounded text
-            if (match.index > lastIndex) {
-                const normalText = rawTextContent.slice(lastIndex, match.index).trim();
-                if (normalText) {
-                    content.push({
-                        index: contentIndex++,
-                        type: TEXT_TYPE.NORMAL,
-                        text: normalText,
-                        citation_ids: null,
-                    });
-                }
-            }
-
-            // Add grounded text
-            const citation_ids = citationIndex.split(',').map(index => citationMap.get(index) || '');
-            content.push({
-                index: contentIndex++,
-                type: TEXT_TYPE.GROUNDED,
-                text: groundedText.trim(),
-                citation_ids,
-            });
-
-            lastIndex = match.index + fullMatch.length;
-        }
-
-        // Add any remaining normal text after the last grounded text
-        if (lastIndex < rawTextContent.length) {
-            const remainingText = rawTextContent.slice(lastIndex).trim();
-            if (remainingText) {
-                content.push({
-                    index: contentIndex++,
-                    type: TEXT_TYPE.NORMAL,
-                    text: remainingText,
-                    citation_ids: null,
-                });
-            }
-        }
-
-        let followUpQuestions: string[] = [];
-        if (followUpQuestionsMatch) {
-            const questionsText = followUpQuestionsMatch[1];
-            let questionMatch;
-            while ((questionMatch = questionRegex.exec(questionsText)) !== null) {
-                followUpQuestions.push(questionMatch[1].trim());
-            }
-        }
-
-        const assistantResponse: AssistantMessage = {
-            role: ASSISTANT_ROLE.ASSISTANT,
-            content,
-            follow_up_questions: followUpQuestions,
-            citations,
-            processing_info: processingInfo,
-            loop_summary: loopSummaryMatch ? loopSummaryMatch[1].trim() : undefined,
-        };
-
-        return assistantResponse;
-    }
-}