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web_data_linkedin_posts

Extract structured LinkedIn post data from URLs using reliable cached data instead of direct scraping, enabling access to post content and metadata.

Instructions

Quickly read structured linkedin posts data This can be a cache lookup, so it can be more reliable than scraping

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes

Implementation Reference

  • Dataset configuration for linkedin_posts, which defines the input schema (url), description, and specific dataset_id used by the web_data_linkedin_posts tool.
    id: 'linkedin_posts', dataset_id: 'gd_lyy3tktm25m4avu764', description: [ 'Quickly read structured linkedin posts data', 'This can be a cache lookup, so it can be more reliable than scraping', ].join('\n'), inputs: ['url'], }, {
  • server.js:674-745 (registration)
    Loop that registers all web_data_* tools, including web_data_linkedin_posts, by generating name, parameters from inputs, and execute handler.
    for (let {dataset_id, id, description, inputs, defaults = {}} of datasets) { let parameters = {}; for (let input of inputs) { let param_schema = input=='url' ? z.string().url() : z.string(); parameters[input] = defaults[input] !== undefined ? param_schema.default(defaults[input]) : param_schema; } addTool({ name: `web_data_${id}`, description, parameters: z.object(parameters), execute: tool_fn(`web_data_${id}`, async(data, ctx)=>{ let trigger_response = await axios({ url: 'https://api.brightdata.com/datasets/v3/trigger', params: {dataset_id, include_errors: true}, method: 'POST', data: [data], headers: api_headers(), }); if (!trigger_response.data?.snapshot_id) throw new Error('No snapshot ID returned from request'); let snapshot_id = trigger_response.data.snapshot_id; console.error(`[web_data_${id}] triggered collection with ` +`snapshot ID: ${snapshot_id}`); let max_attempts = 600; let attempts = 0; while (attempts < max_attempts) { try { if (ctx && ctx.reportProgress) { await ctx.reportProgress({ progress: attempts, total: max_attempts, message: `Polling for data (attempt ` +`${attempts + 1}/${max_attempts})`, }); } let snapshot_response = await axios({ url: `https://api.brightdata.com/datasets/v3` +`/snapshot/${snapshot_id}`, params: {format: 'json'}, method: 'GET', headers: api_headers(), }); if (['running', 'building'].includes(snapshot_response.data?.status)) { console.error(`[web_data_${id}] snapshot not ready, ` +`polling again (attempt ` +`${attempts + 1}/${max_attempts})`); attempts++; await new Promise(resolve=>setTimeout(resolve, 1000)); continue; } console.error(`[web_data_${id}] snapshot data received ` +`after ${attempts + 1} attempts`); let result_data = JSON.stringify(snapshot_response.data); return result_data; } catch(e){ console.error(`[web_data_${id}] polling error: ` +`${e.message}`); attempts++; await new Promise(resolve=>setTimeout(resolve, 1000)); } } throw new Error(`Timeout after ${max_attempts} seconds waiting ` +`for data`); }), }); }
  • Handler function for web_data_linkedin_posts: triggers dataset collection via BrightData API using the specific dataset_id, polls for snapshot completion up to 600 attempts, and returns the JSON data.
    execute: tool_fn(`web_data_${id}`, async(data, ctx)=>{ let trigger_response = await axios({ url: 'https://api.brightdata.com/datasets/v3/trigger', params: {dataset_id, include_errors: true}, method: 'POST', data: [data], headers: api_headers(), }); if (!trigger_response.data?.snapshot_id) throw new Error('No snapshot ID returned from request'); let snapshot_id = trigger_response.data.snapshot_id; console.error(`[web_data_${id}] triggered collection with ` +`snapshot ID: ${snapshot_id}`); let max_attempts = 600; let attempts = 0; while (attempts < max_attempts) { try { if (ctx && ctx.reportProgress) { await ctx.reportProgress({ progress: attempts, total: max_attempts, message: `Polling for data (attempt ` +`${attempts + 1}/${max_attempts})`, }); } let snapshot_response = await axios({ url: `https://api.brightdata.com/datasets/v3` +`/snapshot/${snapshot_id}`, params: {format: 'json'}, method: 'GET', headers: api_headers(), }); if (['running', 'building'].includes(snapshot_response.data?.status)) { console.error(`[web_data_${id}] snapshot not ready, ` +`polling again (attempt ` +`${attempts + 1}/${max_attempts})`); attempts++; await new Promise(resolve=>setTimeout(resolve, 1000)); continue; } console.error(`[web_data_${id}] snapshot data received ` +`after ${attempts + 1} attempts`); let result_data = JSON.stringify(snapshot_response.data); return result_data; } catch(e){ console.error(`[web_data_${id}] polling error: ` +`${e.message}`); attempts++; await new Promise(resolve=>setTimeout(resolve, 1000)); } } throw new Error(`Timeout after ${max_attempts} seconds waiting ` +`for data`); }),
  • Helper function tool_fn that wraps the specific handler with rate limiting, stats tracking, logging, error handling, and timing.
    function tool_fn(name, fn){ return async(data, ctx)=>{ check_rate_limit(); debug_stats.tool_calls[name] = debug_stats.tool_calls[name]||0; debug_stats.tool_calls[name]++; debug_stats.session_calls++; let ts = Date.now(); console.error(`[%s] executing %s`, name, JSON.stringify(data)); try { return await fn(data, ctx); } catch(e){ if (e.response) { console.error(`[%s] error %s %s: %s`, name, e.response.status, e.response.statusText, e.response.data); let message = e.response.data; if (message?.length) throw new Error(`HTTP ${e.response.status}: ${message}`); } else console.error(`[%s] error %s`, name, e.stack); throw e; } finally { let dur = Date.now()-ts; console.error(`[%s] tool finished in %sms`, name, dur); } }; }

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