import { z } from "zod";
import {
DevelopTextToolSchema,
DevelopTextToolSchemaBase,
} from "../schemas/index.js";
import { makeInfraNodusRequest } from "../api/client.js";
import { fetchUrlContentAsText } from "../utils/urlContent.js";
import {
generateResearchQuestions,
extractLatentTopicsIdeas,
generateGaps,
extractLatentConceptsIdeas,
} from "../utils/transformers.js";
function errorContent(message: string) {
return {
content: [
{ type: "text" as const, text: JSON.stringify({ error: message }) },
],
isError: true,
};
}
export const developTextTool = {
name: "develop_text_tool",
definition: {
title: "Develop a Text Based on Content Gaps and Latent Topics",
description:
"Analyze text or an existing graph to extract research questions, develop latent topics, and identify content gaps in a single workflow with progress tracking. Provide either text, url, or graphName.",
inputSchema: DevelopTextToolSchemaBase.shape,
annotations: {
readOnlyHint: true,
idempotentHint: true,
destructiveHint: false,
},
},
handler: async (
params: z.infer<typeof DevelopTextToolSchema>,
context?: {
progressToken?: string;
sendNotification?: (notification: any) => void;
}
) => {
try {
const useGraph = params.graphName?.trim();
let contentText: string | undefined;
if (!useGraph) {
if (params.url) {
const result = await fetchUrlContentAsText(params.url);
if (!result.ok) return errorContent(result.error);
contentText = result.contentText;
if (!contentText?.trim())
return errorContent("URL did not return any text content");
} else if (params.text?.trim()) {
contentText = params.text;
} else {
return errorContent(
"Provide either text, url, or graphName for analysis"
);
}
}
// Create progress helper
const progress = {
report: async (percentage: number, message: string) => {
if (context?.progressToken && context?.sendNotification) {
await context.sendNotification({
method: "notifications/progress",
params: {
progressToken: context.progressToken,
progress: percentage,
total: 100,
message,
},
});
}
},
};
// Step 1: Generate Research Questions
await progress.report(
10,
"🔍 Generating research questions and topical gaps from text based on its structure..."
);
const queryParamsResearch = new URLSearchParams({
doNotSave: "true",
addStats: "true",
optimize: "optimize",
includeStatements: "false",
includeGraphSummary: "false",
extendedGraphSummary: "true",
includeGraph: "false",
aiTopics: "true",
extendedAdvice: params.useSeveralGaps ? "true" : "false",
gapDepth: params.gapDepth ? params.gapDepth.toString() : "0",
});
const endpointResearch = `/graphAndAdvice?${queryParamsResearch.toString()}`;
const requestBodyResearch: any = useGraph
? {
name: params.graphName,
aiTopics: "true",
requestMode: params.transcendDiscourse ? "transcend" : "question",
modelToUse: params.modelToUse ?? "gpt-4o",
}
: {
text: contentText,
aiTopics: "true",
requestMode: params.transcendDiscourse ? "transcend" : "question",
modelToUse: params.modelToUse ?? "gpt-4o",
};
const researchResponse = await makeInfraNodusRequest(
endpointResearch,
requestBodyResearch
);
// Extract content gaps and AI advice from research questions response
const researchQuestions = generateResearchQuestions(researchResponse);
const contentGaps = generateGaps(researchResponse);
await progress.report(
40,
`✅ Generated ${
researchQuestions.questions?.length || 0
} research questions`
);
// Step 2: Develop Latent Topics
await progress.report(40, "🎯 Analyzing text for latent topics...");
const queryParamsLatent = new URLSearchParams({
doNotSave: "true",
addStats: "true",
optimize: "latent",
includeStatements: "false",
includeGraphSummary: "false",
extendedGraphSummary: "true",
includeGraph: "false",
aiTopics: "true",
});
const endpointLatent = `/graphAndAdvice?${queryParamsLatent.toString()}`;
const requestBodyLatent: any = useGraph
? {
name: params.graphName,
aiTopics: "true",
requestMode: params.transcendDiscourse ? "transcend" : "question",
modelToUse: params.modelToUse ?? "gpt-4o",
}
: {
text: contentText,
aiTopics: "true",
requestMode: params.transcendDiscourse ? "transcend" : "question",
modelToUse: params.modelToUse ?? "gpt-4o",
};
const latentResponse = await makeInfraNodusRequest(
endpointLatent,
requestBodyLatent
);
const latentTopics = extractLatentTopicsIdeas(latentResponse);
await progress.report(
60,
`✅ Identified ${
latentTopics.latentTopicsToDevelop?.length || 0
} latent topics to develop`
);
// Step 3: Generate Content Gaps
await progress.report(
70,
"🔎 Identifying conceptual bridges in the text..."
);
const queryParamsBridges = new URLSearchParams({
doNotSave: "true",
addStats: "true",
optimize: "imagine",
includeStatements: "false",
includeGraphSummary: "false",
extendedGraphSummary: "true",
includeGraph: "false",
aiTopics: "true",
});
const endpointBridges = `/graphAndAdvice?${queryParamsBridges.toString()}`;
const requestBodyBridges: any = useGraph
? {
name: params.graphName,
aiTopics: "true",
requestMode: params.transcendDiscourse ? "transcend" : "question",
modelToUse: params.modelToUse ?? "gpt-4o",
}
: {
text: contentText,
aiTopics: "true",
requestMode: params.transcendDiscourse ? "transcend" : "question",
modelToUse: params.modelToUse ?? "gpt-4o",
};
const conceptualBridgesResponse = await makeInfraNodusRequest(
endpointBridges,
requestBodyBridges
);
const conceptualBridges = extractLatentConceptsIdeas(
conceptualBridgesResponse
);
await progress.report(
90,
`✅ Identified ${
conceptualBridges.latentConceptsToDevelop?.length || 0
} conceptual bridges to develop`
);
// Compile final results
const results = {
contentGapIdeas: researchQuestions.questions || [],
latentTopicsIdeas: latentTopics.ideas || [],
conceptualBridgesIdeas: conceptualBridges.ideas || [],
contentGaps: contentGaps.contentGaps || [],
conceptualBridges: conceptualBridges.latentConceptsToDevelop || [],
latentTopics: latentTopics.latentTopicsToDevelop || [],
mainTopics: latentTopics.mainTopics || [],
};
await progress.report(100, "🎉 Analysis complete!");
// Handle errors from any of the responses
if (
researchResponse.error ||
latentResponse.error ||
conceptualBridgesResponse.error
) {
const errors = [
researchResponse.error &&
`Research Questions: ${researchResponse.error}`,
latentResponse.error && `Latent Topics: ${latentResponse.error}`,
conceptualBridgesResponse.error &&
`Conceptual Gaps: ${conceptualBridgesResponse.error}`,
]
.filter(Boolean)
.join("\n");
return {
content: [
{
type: "text" as const,
text: `Errors encountered:\n${errors}`,
},
],
isError: true,
};
}
return {
content: [
{
type: "text" as const,
text: JSON.stringify(results, null, 2),
},
],
};
} catch (error) {
return {
content: [
{
type: "text" as const,
text: JSON.stringify({
error: error instanceof Error ? error.message : String(error),
}),
},
],
isError: true,
};
}
},
};
