import { z } from "zod";
import {
GenerateResponsesFromGraphSchema,
GenerateResponsesFromGraphSchemaBase,
} from "../schemas/index.js";
import { makeInfraNodusRequest } from "../api/client.js";
import { fetchUrlContentAsText } from "../utils/urlContent.js";
import { generateResponses } from "../utils/transformers.js";
function errorContent(message: string) {
return {
content: [
{ type: "text" as const, text: JSON.stringify({ error: message }) },
],
isError: true,
};
}
export const generateResponsesFromGraphTool = {
name: "generate_responses_from_graph",
definition: {
title: "Generate Responses and Expert Advice from Text or Graph",
description:
"Use text, URL, or an existing InfraNodus knowledge graph and generate responses and expert advice based on a prompt provided.",
inputSchema: GenerateResponsesFromGraphSchemaBase.shape,
annotations: {
readOnlyHint: true,
idempotentHint: true,
destructiveHint: false,
},
},
handler: async (params: z.infer<typeof GenerateResponsesFromGraphSchema>) => {
try {
// Build query parameters
const queryParams = new URLSearchParams({
doNotSave: "true",
addStats: "true",
optimize: "gap",
includeStatements: "false",
includeGraphSummary: "false",
extendedGraphSummary: "false",
includeGraph: "false",
aiTopics: "true",
});
const endpoint = `/graphAndAdvice?${queryParams.toString()}`;
let requestBody: {
name?: string;
text?: string;
aiTopics: string;
requestMode: string;
prompt: string;
modelToUse: string;
};
if (params.graphName?.trim()) {
requestBody = {
name: params.graphName,
aiTopics: "true",
requestMode: "response",
prompt: params.prompt ?? "",
modelToUse: params.modelToUse ?? "gpt-4o",
};
} else {
let contentText: string;
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"
);
}
requestBody = {
text: contentText,
aiTopics: "true",
requestMode: "response",
prompt: params.prompt ?? "",
modelToUse: params.modelToUse ?? "gpt-4o",
};
}
const response = await makeInfraNodusRequest(endpoint, requestBody);
const responses = generateResponses(response);
if (response.error) {
return {
content: [
{
type: "text" as const,
text: `Error: ${response.error}`,
},
],
isError: true,
};
}
return {
content: [
{
type: "text" as const,
text: JSON.stringify(responses, null, 2),
},
],
};
} catch (error) {
return {
content: [
{
type: "text" as const,
text: JSON.stringify({
error: error instanceof Error ? error.message : String(error),
}),
},
],
isError: true,
};
}
},
};
