Gen
The Gen class is a high-level layer to simplify AI integration and content generation with one line call. It abstracts the prompt, the provider call and the output parsing, so a complete task is a single function: build a component, write the SQL, review the code, produce the SEO tags.
Every function takes the same arguments and works with every chat provider:
const { Gen } = require('intellinode');
const result = await Gen.<function>(input, apiKey, provider, options);
- input: the description, code or data the function works on.
- apiKey: the provider key (
nullfor a local Ollama or LM Studio). - provider:
openai(default),anthropic,gemini,mistral,cohere,nvidia,vllm, or an OpenAI-compatible service:openrouter,groq,deepseek,xai,together,ollama,lmstudio,openai_compatible. - options: the function's own options plus the common ones below.
Common options:
| Option | Purpose |
|---|---|
model | Model name at the provider (defaults to the intellinode default of the provider). |
maxTokens, temperature | Tune the generation. |
system | Override the system message. |
baseUrl, headers | For openai_compatible and the presets. |
timeout, retries, retryDelay, signal | The retries & timeouts. |
customProxyHelper | Azure OpenAI or a proxy. |
Code functions return the code as a string (no markdown fences); structured functions return parsed objects. The output parser removes the reasoning of models that return it inline and repairs common JSON slips.
Categories
| Page | What you get |
|---|---|
| Ask Any Model | Text or ready-to-use JSON from any provider: generate_text, generate_json, instructUpdate |
| Build Web UI | Components, forms, CSS, icons, design tokens and full pages: generate_component, generate_form, generate_page_section, generate_css, improve_accessibility, generate_email_template, generate_svg_icon, generate_color_palette, generate_design_tokens, generate_html_page, save_html_page, generate_dashboard |
| Build APIs & SQL | Endpoints, SQL, schemas, mock data, regex and OpenAPI specs: generate_api_endpoint, generate_sql, generate_json_schema, generate_mock_data, generate_regex, generate_openapi_spec |
| Review & Fix Code | Code reviews, bug fixes, unit tests, commits and release notes: generate_unit_tests, review_code, fix_code, explain_code, convert_code, generate_commit_message, generate_readme, generate_release_notes |
| Write Marketing Copy | Landing copy, SEO tags, FAQs, translations, images and speech: get_marketing_desc, get_blog_post, generate_landing_copy, generate_faq, generate_seo_meta, translate_ui_strings, generate_image_from_desc, generate_speech_synthesis |
Example
const { Gen } = require('intellinode');
// UI code with OpenAI (gpt-5.5 is default)
const code = await Gen.generate_component('a pricing card with a plan name, price and a CTA button', openaiKey, 'openai',
{ framework: 'react', language: 'typescript', styling: 'tailwind' });
// the same function with Claude
const form = await Gen.generate_form('a contact form with name, email and message', anthropicKey, 'anthropic');
// structured results
const review = await Gen.review_code(code, openaiKey); // { summary, score, issues }
const regex = await Gen.generate_regex('a US phone number', openaiKey); // { pattern, flags, regex, matches, nonMatches, verified }
// a local model, no key
const sql = await Gen.generate_sql('top 10 customers by order total', null, 'ollama', { model: 'qwen3' });
The same functions are exposed as MCP tools by npx intellinode mcp, so a coding assistant can call them on any provider. See the MCP server page.