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feat(integrations): add DataForB2B block and tools
Add a native DataForB2B integration: search and enrich B2B companies and LinkedIn profiles. Six tools (search people, search companies, reasoning search, typeahead, enrich profile, enrich company) wired into a single multi-operation block, with icon, registries, generated docs and catalog metadata. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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‎apps/docs/components/icons.tsx‎

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</svg>
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)
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}
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export function DataForB2BIcon(props: SVGProps<SVGSVGElement>) {
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return (
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<svg {...props} viewBox='0 0 36 36' fill='none' xmlns='http://www.w3.org/2000/svg'>
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<image
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href='https://api.dataforb2b.ai/DataForB2B_logo.png'
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x='0'
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y='0'
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width='36'
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height='36'
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preserveAspectRatio='xMidYMid meet'
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/>
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</svg>
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)
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}

‎apps/docs/components/ui/icon-mapping.ts‎

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DagsterIcon,
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DatabricksIcon,
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DatadogIcon,
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DataForB2BIcon,
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DatagmaIcon,
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DaytonaIcon,
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DevinIcon,
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dagster: DagsterIcon,
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databricks: DatabricksIcon,
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datadog: DatadogIcon,
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dataforb2b: DataForB2BIcon,
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datagma: DatagmaIcon,
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daytona: DaytonaIcon,
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devin: DevinIcon,

‎apps/docs/content/docs/en/integrations/dataforb2b.mdx‎

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---
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title: DataForB2B
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description: Search LinkedIn profiles & companies and find B2B emails
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---
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import { BlockInfoCard } from "@/components/ui/block-info-card"
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<BlockInfoCard
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type="dataforb2b"
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color="#0B0F1A"
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/>
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## Usage Instructions
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Integrates DataForB2B into the workflow — a B2B data, LinkedIn enrichment and email-finder source for lead generation, sales prospecting, recruitment / candidate sourcing and CRM enrichment. Search people and companies on LinkedIn with structured filters (job title, company, industry, location, headcount, funding, skills, school, degree, years of experience), run a natural-language (reasoning) search from an ICP or candidate persona, resolve filter values with typeahead, and enrich a LinkedIn profile or company URL to get the full profile plus verified work email, personal email, phone and GitHub.
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## Actions
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### `dataforb2b_search_people`
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Search people and B2B leads by structured filters (job title, current company, location, industry, seniority, skills, school, funding and LinkedIn data) with DataForB2B. Find employees at a company, decision-makers and key contacts for sales prospecting.
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#### Input
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| Parameter | Type | Required | Description |
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| --------- | ---- | -------- | ----------- |
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| `apiKey` | string | Yes | DataForB2B API key \(https://app.dataforb2b.ai\) |
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| `filters` | json | Yes | Structured filters as JSON: \{"op":"and"\|"or","conditions":\[\{"column","type","value","value2"?\}\]\}. Columns: first_name, last_name, profile_location, profile_country, profile_industry, follower_count, keyword, current_company, current_title, current_job_location, current_company_industry, current_company_category, current_company_size, current_company_id, current_employment_type, years_in_current_position, years_at_current_company, current_company_has_funding, current_company_funding_stage, current_company_investor, past_company, past_title, past_job_location, past_company_industry, past_company_size, past_company_id, past_employment_type, years_at_past_company, skill, school, degree, degree_level, field_of_study, language, language_iso, language_proficiency, certification, certification_authority, years_of_experience, num_total_jobs, is_currently_employed. Operators \(type\): =, !=, like, not_like, in, not_in, &gt;, &gt;=, &lt;, &lt;=, between. Use an array value for "in"/"not_in"; for "between" set value \(min\) and value2 \(max\). Example: \{"op":"and","conditions":\[\{"column":"current_title","type":"like","value":"Head of Growth"\},\{"column":"current_company_size","type":"in","value":\["51-200","201-500"\]\}\]\} |
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| `count` | number | No | Max results to return \(default 25, max 100\) |
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| `offset` | number | No | Pagination offset, e.g. 25, 50 \(default 0\) |
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#### Output
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| Parameter | Type | Description |
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| --------- | ---- | ----------- |
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| `results` | json | Array of matching people: each with profile, current role/company, location, industry, skills and LinkedIn URL |
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| `total` | number | Total number of people matching the filters |
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| `count` | number | Number of people returned in this page |
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### `dataforb2b_search_companies`
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Search companies and accounts by structured filters (industry, headcount/size, location, founded year, funding stage/amount, growth, keywords and LinkedIn data) with DataForB2B. Build target account lists for B2B sales and account-based marketing.
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#### Input
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| Parameter | Type | Required | Description |
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| --------- | ---- | -------- | ----------- |
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| `apiKey` | string | Yes | DataForB2B API key \(https://app.dataforb2b.ai\) |
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| `filters` | json | Yes | Structured filters as JSON: \{"op":"and"\|"or","conditions":\[\{"column","type","value","value2"?\}\]\}. Columns: name, tagline, description, domain, universal_name, keyword, industry, employee_count, country_iso_code, city, region, office_country, office_city, office_region, employee_growth_1m, employee_growth_6m, employee_growth_12m, recent_hires_count, founded_year, company_type, follower_count, page_verified, category, last_funding_amount_usd, last_funding_date, funding_stage_normalized, has_funding. Operators \(type\): =, !=, like, not_like, in, not_in, &gt;, &gt;=, &lt;, &lt;=, between. Use an array value for "in"/"not_in"; for "between" set value \(min\) and value2 \(max\). Example: \{"op":"and","conditions":\[\{"column":"industry","type":"like","value":"software development"\},\{"column":"employee_count","type":"between","value":51,"value2":500\},\{"column":"funding_stage_normalized","type":"in","value":\["series_a","series_b"\]\}\]\} |
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| `count` | number | No | Max results to return \(default 25, max 100\) |
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| `offset` | number | No | Pagination offset, e.g. 25, 50 \(default 0\) |
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#### Output
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| Parameter | Type | Description |
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| --------- | ---- | ----------- |
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| `results` | json | Array of matching companies: each with name, domain, industry, headcount, location, funding and LinkedIn data |
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| `total` | number | Total number of companies matching the filters |
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| `count` | number | Number of companies returned in this page |
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### `dataforb2b_reasoning_search`
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Natural-language search for people, leads or companies with DataForB2B. Describe your ideal lead or ICP in plain English (e.g. \
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#### Input
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| Parameter | Type | Required | Description |
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| --------- | ---- | -------- | ----------- |
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| `apiKey` | string | Yes | DataForB2B API key \(https://app.dataforb2b.ai\) |
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| `query` | string | No | Natural-language description of the ideal lead/company \(ICP\). Required on the first call. |
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| `category` | string | No | Search "people" or "companies" \(default people\) |
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| `max_results` | number | No | Max results, 1-100 \(default 25\) |
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| `session_id` | string | No | Session id from a previous "needs_input" response, to refine the search. |
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| `answers` | json | No | Answers to clarifying questions as a \{question_id: answer\} object, for a needs_input turn. |
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#### Output
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| Parameter | Type | Description |
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| --------- | ---- | ----------- |
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| `status` | string | "needs_input" when clarification is required, otherwise the search status |
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| `results` | json | Array of matching people or companies |
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| `total` | number | Total number of matches |
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| `count` | number | Number of results returned |
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| `session_id` | string | Session id to pass back with answers when status is needs_input |
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| `questions` | json | Clarifying questions \[\{id, text, suggestions\}\] when status is needs_input |
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| `applied_filters` | json | Structured filters the agent applied; reuse with search/people\|companies for paging |
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### `dataforb2b_typeahead`
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Resolve the exact stored value for a free-text filter (company, industry, job title, skill, school, location, investor, category) before a people or company search on DataForB2B. Use it to normalize free text, or when a search returns few or no results.
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#### Input
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| Parameter | Type | Required | Description |
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| --------- | ---- | -------- | ----------- |
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| `apiKey` | string | Yes | DataForB2B API key \(https://app.dataforb2b.ai\) |
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| `type` | string | Yes | Which kind of value to resolve. One of: company, people_industry, company_industry, category, location, city, region, school, title, skill, investor |
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| `q` | string | Yes | Free-text query \(1-100 chars\) to resolve to a stored value |
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| `limit` | number | No | Max suggestions, 1-20 \(default 20\) |
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#### Output
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| Parameter | Type | Description |
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| --------- | ---- | ----------- |
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| `results` | json | Suggestions ordered by popularity; each has the exact stored value to use in a search filter |
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### `dataforb2b_enrich_profile`
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Look up and enrich a professional profile from a LinkedIn URL with DataForB2B. Returns the full profile (current role, experience, skills) plus work email, personal email, phone and GitHub. An email finder for lead enrichment. At least one enrich_* flag is used (defaults to the full profile).
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#### Input
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| Parameter | Type | Required | Description |
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| --------- | ---- | -------- | ----------- |
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| `apiKey` | string | Yes | DataForB2B API key \(https://app.dataforb2b.ai\) |
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| `profile_identifier` | string | Yes | LinkedIn profile URL, public id \(e.g. john-doe\) or encoded id \(prof_...\). Encoded id recommended. |
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| `enrich_profile` | boolean | No | Return the full profile \(role, experience, skills\) |
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| `enrich_work_email` | boolean | No | Find the professional/work email |
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| `enrich_personal_email` | boolean | No | Find the personal email |
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| `enrich_phone` | boolean | No | Find the phone number |
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| `enrich_github` | boolean | No | Find the GitHub profile |
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#### Output
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| Parameter | Type | Description |
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| --------- | ---- | ----------- |
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| `profile` | json | Enriched profile: identity, current role, experience, skills, education |
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| `work_email` | json | Professional/work email \(when requested\) |
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| `personal_email` | json | Personal email \(when requested\) |
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| `phone` | json | Phone number \(when requested\) |
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| `git_profile` | json | GitHub profile \(when requested\) |
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### `dataforb2b_enrich_company`
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Look up and enrich a company with DataForB2B from a company domain, name, slug or LinkedIn URL. Returns firmographics, headcount/size, industry, domain and social profiles. Account enrichment for B2B sales and CRM.
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#### Input
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| Parameter | Type | Required | Description |
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| --------- | ---- | -------- | ----------- |
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| `apiKey` | string | Yes | DataForB2B API key \(https://app.dataforb2b.ai\) |
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| `company_identifier` | string | Yes | Company slug \(e.g. google\), domain \(e.g. google.com\), name or LinkedIn company URL. Slugs resolve most reliably. |
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#### Output
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| Parameter | Type | Description |
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| --------- | ---- | ----------- |
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| `company` | json | Enriched company: name, domain, industry, headcount/size, location, founded year, funding and social profiles |
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‎apps/docs/content/docs/en/integrations/meta.json‎

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"dagster",
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"databricks",
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"datadog",
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"dataforb2b",
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"datagma",
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"daytona",
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"deployments",

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