@jss-rule-engine/chat/dist/src/ruleEngine/actions/ragSearchAction.js

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import { cleanId } from '../../lib/helper';
var RAGSearchAction = /** @class */ (function () {
    function RAGSearchAction() {
    }
    RAGSearchAction.prototype.execute = function (action, context) {
        var _a, _b, _c, _d;
        return __awaiter(this, void 0, void 0, function () {
            var fields, chatContext, message, indexId, cleanedIndexId, thresold, topN, results, aiRagContent, minDistance, err_1;
            return __generator(this, function (_e) {
                switch (_e.label) {
                    case 0:
                        fields = action.fields;
                        console.log('Running RAGSearchAction', fields);
                        chatContext = (_b = (_a = context.ruleEngineContext) === null || _a === void 0 ? void 0 : _a.sessionContext) === null || _b === void 0 ? void 0 : _b.get("chatContext");
                        if (!chatContext) {
                            (_c = context.ruleEngine) === null || _c === void 0 ? void 0 : _c.debugMessage('Chat context is not provided.');
                            throw new Error("Chat context is not provided.");
                        }
                        message = chatContext.userInput;
                        indexId = fields["RAG Index"] || '';
                        cleanedIndexId = cleanId(indexId);
                        thresold = Number(fields["Thresold"]) || 1;
                        topN = Number(fields["TopN"]) || 5;
                        _e.label = 1;
                    case 1:
                        _e.trys.push([1, 3, , 4]);
                        console.log('RAG search for - ', message, topN, thresold, cleanedIndexId);
                        return [4 /*yield*/, ((_d = context.workflowService) === null || _d === void 0 ? void 0 : _d.findRelevantEmbeddings(message, cleanedIndexId, topN, thresold))];
                    case 2:
                        results = _e.sent();
                        aiRagContent = '';
                        if (Array.isArray(results)) {
                            aiRagContent = results.map(function (r) { return JSON.stringify(r); }).join('\n\n');
                        }
                        else if (results) {
                            aiRagContent = JSON.stringify(results);
                        }
                        minDistance = 1;
                        if (Array.isArray(results) && results.length > 0) {
                            minDistance = Math.min.apply(Math, results.map(function (r) { return typeof r.distance === 'number' ? r.distance : 1; }));
                        }
                        console.log('RAG Results:');
                        results === null || results === void 0 ? void 0 : results.forEach(function (x) { return console.log("path: ".concat(x.path, " distance: ").concat(x.distance)); });
                        chatContext.variables.set("aiRagContent", aiRagContent);
                        chatContext.variables.set("aiRagResults", results);
                        chatContext.variables.set("aiRagMinDistance", minDistance);
                        return [3 /*break*/, 4];
                    case 3:
                        err_1 = _e.sent();
                        console.error("Error searching RAG table with findRelevantEmbeddings:", err_1);
                        throw err_1;
                    case 4: return [2 /*return*/];
                }
            });
        });
    };
    return RAGSearchAction;
}());
export { RAGSearchAction };