{ "info": { "_postman_id": "6b6447b2-dfc4-4b5c-92a6-c103b52803e8", "name": "Generate Code Service", "description": "Chat GPT Api", "schema": "https://schema.getpostman.com/json/collection/v2.1.0/collection.json", "_exporter_id": "15881084" }, "item": [ { "name": "Generate Custom API Service", "request": { "method": "POST", "header": [ { "key": "Content-Type", "value": "application/json" } ], "body": { "mode": "raw", "raw": "{\n \"type\": \"microservice\",\n \"language\": \"typescript\",\n \"framework\": \"nestjs\",\n \"specifications\": {\n \"include\": [\n \"Authentication service\",\n \"User management\",\n \"Role-based access control\"\n ],\n \"requirements\": {\n \"database\": \"PostgreSQL with TypeORM\",\n \"caching\": \"Redis\",\n \"security\": \"JWT with refresh tokens\",\n \"validation\": \"class-validator\"\n },\n \"features\": [\n \"Email verification\",\n \"Password reset\",\n \"2FA support\",\n \"Session management\"\n ],\n \"architecture\": {\n \"pattern\": \"Clean Architecture\",\n \"layers\": [\n \"Controllers\",\n \"Use Cases\",\n \"Repositories\",\n \"Entities\"\n ]\n }\n }\n}", "options": { "raw": { "language": "json" } } }, "url": { "raw": "{{host}}/generate?noqueue=1", "host": [ "{{host}}" ], "path": [ "generate" ], "query": [ { "key": "noqueue", "value": "1" } ] } }, "response": [ { "name": "Generate Custom API Service", "originalRequest": { "method": "POST", "header": [ { "key": "Content-Type", "value": "application/json" } ], "body": { "mode": "raw", "raw": "{\n \"type\": \"microservice\",\n \"language\": \"typescript\",\n \"framework\": \"nestjs\",\n \"specifications\": {\n \"include\": [\n \"Authentication service\",\n \"User management\",\n \"Role-based access control\"\n ],\n \"requirements\": {\n \"database\": \"PostgreSQL with TypeORM\",\n \"caching\": \"Redis\",\n \"security\": \"JWT with refresh tokens\",\n \"validation\": \"class-validator\"\n },\n \"features\": [\n \"Email verification\",\n \"Password reset\",\n \"2FA support\",\n \"Session management\"\n ],\n \"architecture\": {\n \"pattern\": \"Clean Architecture\",\n \"layers\": [\n \"Controllers\",\n \"Use Cases\",\n \"Repositories\",\n \"Entities\"\n ]\n }\n }\n}", "options": { "raw": { "language": "json" } } }, "url": { "raw": "{{host}}/generate?noqueue=1", "host": [ "{{host}}" ], "path": [ "generate" ], "query": [ { "key": "noqueue", "value": "1" } ] } }, "_postman_previewlanguage": "json", "header": [ { "key": "Content-Type", "value": "application/json", "name": "Content-Type", "description": "", "type": "text" } ], "cookie": [], "body": "{\r\n \"status\": \"success\",\r\n \"message\": \"Code generated successfully\",\r\n \"result\": {\r\n \"code\": {\r\n \"content\": \"import { Module } from '@nestjs/common';\\nimport { TypeOrmModule } from '@nestjs/typeorm';\\nimport { JwtModule } from '@nestjs/jwt';\\nimport { RedisModule } from 'nestjs-redis';\\nimport { AuthController } from './controllers/auth.controller';\\nimport { UserController } from './controllers/user.controller';\\nimport { AuthService } from './services/auth.service';\\nimport { UserService } from './services/user.service';\\nimport { User } from './entities/user.entity';\\nimport { Role } from './entities/role.entity';\\n\\n@Module({\\n imports: [\\n TypeOrmModule.forRoot({\\n type: 'postgres',\\n host: 'localhost',\\n port: 5432,\\n username: 'test',\\n password: 'test',\\n database: 'test',\\n entities: [User, Role],\\n synchronize: true,\\n }),\\n TypeOrmModule.forFeature([User, Role]),\\n JwtModule.register({\\n secret: 'secretKey',\\n signOptions: { expiresIn: '60s' },\\n }),\\n RedisModule.forRoot({\\n url: 'redis://localhost:6379',\\n }),\\n ],\\n controllers: [AuthController, UserController],\\n providers: [AuthService, UserService],\\n})\\nexport class AppModule {}\",\r\n \"language\": \"typescript\",\r\n \"framework\": \"nestjs\",\r\n \"type\": \"microservice\"\r\n },\r\n \"explanation\": {\r\n \"overview\": \"This code sets up a NestJS microservice for user authentication and management, implementing role-based access control, email verification, password reset, and 2FA support, using PostgreSQL with TypeORM for the database and Redis for caching.\",\r\n \"keyComponents\": [\r\n \"Controllers for handling HTTP requests (AuthController, UserController)\",\r\n \"Services for business logic (AuthService, UserService)\",\r\n \"Entities representing database models (User, Role)\",\r\n \"Modules for organizing application structure (AppModule)\"\r\n ],\r\n \"bestPractices\": [\r\n \"Use DTOs for data transfer and validation with class-validator.\",\r\n \"Implement error handling in services and controllers.\",\r\n \"Use environment variables for sensitive information like database credentials and JWT secret.\"\r\n ],\r\n \"considerations\": [\r\n \"Ensure that the database connection is properly managed and closed.\",\r\n \"Consider implementing rate limiting and logging for security.\",\r\n \"Optimize Redis usage for session management and caching.\"\r\n ]\r\n },\r\n \"implementation\": {\r\n \"steps\": [\r\n \"Install necessary packages: @nestjs/common, @nestjs/core, @nestjs/typeorm, @nestjs/jwt, nestjs-redis, class-validator, typeorm, pg.\",\r\n \"Create entities for User and Role with appropriate fields and decorators.\",\r\n \"Implement services for authentication and user management, including methods for registration, login, email verification, password reset, and 2FA.\",\r\n \"Create controllers to handle incoming requests and route them to the appropriate service methods.\",\r\n \"Set up JWT authentication and refresh tokens in the AuthService.\",\r\n \"Configure Redis for caching and session management.\"\r\n ],\r\n \"dependencies\": [\r\n \"@nestjs/common\",\r\n \"@nestjs/core\",\r\n \"@nestjs/typeorm\",\r\n \"@nestjs/jwt\",\r\n \"nestjs-redis\",\r\n \"class-validator\",\r\n \"typeorm\",\r\n \"pg\"\r\n ],\r\n \"configuration\": {\r\n \"database\": {\r\n \"type\": \"postgres\",\r\n \"host\": \"localhost\",\r\n \"port\": 5432,\r\n \"username\": \"test\",\r\n \"password\": \"test\",\r\n \"database\": \"test\"\r\n },\r\n \"jwt\": {\r\n \"secret\": \"secretKey\",\r\n \"expiresIn\": \"60s\"\r\n },\r\n \"redis\": {\r\n \"url\": \"redis://localhost:6379\"\r\n }\r\n }\r\n },\r\n \"testing\": {\r\n \"testCases\": [\r\n \"Test user registration with valid and invalid data.\",\r\n \"Test login functionality with correct and incorrect credentials.\",\r\n \"Test email verification process.\",\r\n \"Test password reset functionality.\"\r\n ],\r\n \"validationPoints\": [\r\n \"Ensure that all endpoints return appropriate HTTP status codes.\",\r\n \"Validate that JWT tokens are correctly issued and verified.\",\r\n \"Check that role-based access control is enforced on protected routes.\"\r\n ]\r\n },\r\n \"documentation\": {\r\n \"usage\": \"This microservice provides authentication and user management functionalities, including role-based access control, email verification, and password reset.\",\r\n \"parameters\": [\r\n {\r\n \"name\": \"username\",\r\n \"type\": \"string\",\r\n \"description\": \"The username of the user.\",\r\n \"required\": true\r\n },\r\n {\r\n \"name\": \"password\",\r\n \"type\": \"string\",\r\n \"description\": \"The password of the user.\",\r\n \"required\": true\r\n },\r\n {\r\n \"name\": \"email\",\r\n \"type\": \"string\",\r\n \"description\": \"The email address of the user.\",\r\n \"required\": true\r\n }\r\n ],\r\n \"returns\": {\r\n \"type\": \"object\",\r\n \"description\": \"Returns user details and JWT token upon successful authentication.\"\r\n },\r\n \"examples\": [\r\n \"POST /auth/register with body {\\\"username\\\": \\\"testuser\\\", \\\"password\\\": \\\"password123\\\", \\\"email\\\": \\\"test@example.com\\\"}\",\r\n \"POST /auth/login with body {\\\"username\\\": \\\"testuser\\\", \\\"password\\\": \\\"password123\\\"}\"\r\n ]\r\n }\r\n },\r\n \"cacheTime\": 1736283012060,\r\n \"time\": 1736283012318\r\n}" } ] }, { "name": "Generate AI Integration", "request": { "method": "POST", "header": [ { "key": "Content-Type", "value": "application/json" } ], "body": { "mode": "raw", "raw": "{\n \"type\": \"ai-integration\",\n \"language\": \"python\",\n \"framework\": \"fastapi\",\n \"specifications\": {\n \"include\": [\n \"OpenAI integration\",\n \"Vector database connection\",\n \"Caching layer\",\n \"Rate limiting\"\n ],\n \"requirements\": {\n \"modelType\": \"GPT-4\",\n \"vectorDB\": \"PostgreSQL with pgvector\",\n \"performance\": \"High throughput\",\n \"scalability\": \"Horizontal scaling\"\n },\n \"features\": [\n \"Async processing\",\n \"Batch requests\",\n \"Error recovery\",\n \"Request logging\"\n ]\n },\n \"customPrompt\": \"Create a production-ready AI service that handles multiple LLM requests efficiently with proper error handling and monitoring.\"\n}", "options": { "raw": { "language": "json" } } }, "url": { "raw": "{{host}}/generate?noqueue=1", "host": [ "{{host}}" ], "path": [ "generate" ], "query": [ { "key": "noqueue", "value": "1" } ] } }, "response": [ { "name": "Generate AI Integration", "originalRequest": { "method": "POST", "header": [ { "key": "Content-Type", "value": "application/json" } ], "body": { "mode": "raw", "raw": "{\n \"type\": \"ai-integration\",\n \"language\": \"python\",\n \"framework\": \"fastapi\",\n \"specifications\": {\n \"include\": [\n \"OpenAI integration\",\n \"Vector database connection\",\n \"Caching layer\",\n \"Rate limiting\"\n ],\n \"requirements\": {\n \"modelType\": \"GPT-4\",\n \"vectorDB\": \"PostgreSQL with pgvector\",\n \"performance\": \"High throughput\",\n \"scalability\": \"Horizontal scaling\"\n },\n \"features\": [\n \"Async processing\",\n \"Batch requests\",\n \"Error recovery\",\n \"Request logging\"\n ]\n },\n \"customPrompt\": \"Create a production-ready AI service that handles multiple LLM requests efficiently with proper error handling and monitoring.\"\n}", "options": { "raw": { "language": "json" } } }, "url": { "raw": "{{host}}/generate?noqueue=1", "host": [ "{{host}}" ], "path": [ "generate" ], "query": [ { "key": "noqueue", "value": "1" } ] } }, "_postman_previewlanguage": "json", "header": [ { "key": "Content-Type", "value": "application/json", "name": "Content-Type", "description": "", "type": "text" } ], "cookie": [], "body": "{\r\n \"status\": \"success\",\r\n \"message\": \"Code generated successfully\",\r\n \"result\": {\r\n \"code\": {\r\n \"content\": \"from fastapi import FastAPI, HTTPException, Request\\nfrom pydantic import BaseModel\\nimport logging\\nimport asyncio\\n\\napp = FastAPI()\\n\\n# Configure logging\\nlogging.basicConfig(level=logging.INFO)\\nlogger = logging.getLogger(__name__)\\n\\nclass LLMRequest(BaseModel):\\n prompt: str\\n model: str\\n\\nclass LLMResponse(BaseModel):\\n response: str\\n\\nasync def call_llm_service(prompt: str, model: str) -> str:\\n # Simulate an LLM service call\\n await asyncio.sleep(1) # Simulate network delay\\n return f\\\"Response from {model}: {prompt}\\\"\\n\\n@app.post('/llm', response_model=LLMResponse)\\nasync def handle_llm_request(request: LLMRequest):\\n try:\\n logger.info(f'Received request: {request}')\\n response = await call_llm_service(request.prompt, request.model)\\n return LLMResponse(response=response)\\n except Exception as e:\\n logger.error(f'Error processing request: {e}')\\n raise HTTPException(status_code=500, detail='Internal Server Error')\\n\\n@app.get('/health')\\nasync def health_check():\\n return {'status': 'healthy'}\",\r\n \"language\": \"python\",\r\n \"framework\": \"fastapi\",\r\n \"type\": \"service\"\r\n },\r\n \"explanation\": {\r\n \"overview\": \"This FastAPI service handles requests to a large language model (LLM) efficiently, with error handling and logging for monitoring purposes.\",\r\n \"keyComponents\": [\r\n \"FastAPI for creating the web service\",\r\n \"Pydantic for request validation\",\r\n \"Asynchronous programming for handling multiple requests efficiently\",\r\n \"Logging for monitoring and debugging\"\r\n ],\r\n \"bestPractices\": [\r\n \"Use asynchronous functions to handle I/O-bound operations.\",\r\n \"Implement proper error handling to return meaningful HTTP responses.\",\r\n \"Log important events and errors for monitoring.\"\r\n ],\r\n \"considerations\": [\r\n \"Ensure the LLM service can handle concurrent requests without bottlenecks.\",\r\n \"Monitor the service for performance and error rates.\",\r\n \"Consider rate limiting to prevent abuse of the LLM service.\"\r\n ]\r\n },\r\n \"implementation\": {\r\n \"steps\": [\r\n \"Install FastAPI and an ASGI server like uvicorn.\",\r\n \"Define request and response models using Pydantic.\",\r\n \"Create an asynchronous function to simulate LLM service calls.\",\r\n \"Implement a POST endpoint to handle LLM requests.\",\r\n \"Add logging for incoming requests and errors.\",\r\n \"Implement a health check endpoint.\"\r\n ],\r\n \"dependencies\": [\r\n \"fastapi\",\r\n \"uvicorn\",\r\n \"pydantic\"\r\n ],\r\n \"configuration\": {\r\n \"host\": \"0.0.0.0\",\r\n \"port\": 8000,\r\n \"log_level\": \"info\"\r\n }\r\n },\r\n \"testing\": {\r\n \"testCases\": [\r\n \"Test valid LLM requests to ensure proper responses.\",\r\n \"Test invalid requests to verify error handling.\",\r\n \"Test the health check endpoint to ensure service availability.\"\r\n ],\r\n \"validationPoints\": [\r\n \"Check that the response matches the expected format.\",\r\n \"Verify that error responses have the correct status codes.\",\r\n \"Monitor logs for any unexpected errors.\"\r\n ]\r\n },\r\n \"documentation\": {\r\n \"usage\": \"This service provides an endpoint to send prompts to a specified LLM and receive responses.\",\r\n \"parameters\": [\r\n {\r\n \"name\": \"prompt\",\r\n \"type\": \"string\",\r\n \"description\": \"The input prompt for the LLM.\",\r\n \"required\": true\r\n },\r\n {\r\n \"name\": \"model\",\r\n \"type\": \"string\",\r\n \"description\": \"The model to use for generating the response.\",\r\n \"required\": true\r\n }\r\n ],\r\n \"returns\": {\r\n \"type\": \"LLMResponse\",\r\n \"description\": \"A response object containing the generated text from the LLM.\"\r\n },\r\n \"examples\": [\r\n \"{ 'prompt': 'What is the capital of France?', 'model': 'gpt-3.5' }\"\r\n ]\r\n }\r\n },\r\n \"cacheTime\": 1736283183378,\r\n \"time\": 1736283183476\r\n}" } ] }, { "name": "Generate Custom UI Component", "request": { "method": "POST", "header": [ { "key": "Content-Type", "value": "application/json" } ], "body": { "mode": "raw", "raw": "{\n \"type\": \"ui-component\",\n \"language\": \"typescript\",\n \"framework\": \"react\",\n \"specifications\": {\n \"include\": [\n \"Advanced data grid\",\n \"Custom hooks\",\n \"Styling system\"\n ],\n \"requirements\": {\n \"accessibility\": \"WCAG 2.1 AA\",\n \"performance\": \"Virtual scrolling\",\n \"styling\": \"Styled-components with theme\",\n \"stateManagement\": \"React Query + Zustand\"\n },\n \"features\": [\n \"Sorting\",\n \"Filtering\",\n \"Column resizing\",\n \"Row selection\",\n \"Custom cell rendering\"\n ]\n },\n \"responseFormat\": {\n \"component\": {\n \"main\": \"string\",\n \"types\": \"string\",\n \"hooks\": \"string\",\n \"styles\": \"string\"\n },\n \"documentation\": {\n \"setup\": \"string\",\n \"api\": \"object\",\n \"examples\": [\"string\"]\n },\n \"tests\": {\n \"unit\": \"string\",\n \"integration\": \"string\"\n }\n }\n}", "options": { "raw": { "language": "json" } } }, "url": { "raw": "{{host}}/generate?noqueue=1", "host": [ "{{host}}" ], "path": [ "generate" ], "query": [ { "key": "noqueue", "value": "1" } ] } }, "response": [ { "name": "Generate Custom UI Component", "originalRequest": { "method": "POST", "header": [ { "key": "Content-Type", "value": "application/json", "type": "text" } ], "body": { "mode": "raw", "raw": "{\n \"type\": \"ui-component\",\n \"language\": \"typescript\",\n \"framework\": \"react\",\n \"specifications\": {\n \"include\": [\n \"Advanced data grid\",\n \"Custom hooks\",\n \"Styling system\"\n ],\n \"requirements\": {\n \"accessibility\": \"WCAG 2.1 AA\",\n \"performance\": \"Virtual scrolling\",\n \"styling\": \"Styled-components with theme\",\n \"stateManagement\": \"React Query + Zustand\"\n },\n \"features\": [\n \"Sorting\",\n \"Filtering\",\n \"Column resizing\",\n \"Row selection\",\n \"Custom cell rendering\"\n ]\n },\n \"responseFormat\": {\n \"component\": {\n \"main\": \"string\",\n \"types\": \"string\",\n \"hooks\": \"string\",\n \"styles\": \"string\"\n },\n \"documentation\": {\n \"setup\": \"string\",\n \"api\": \"object\",\n \"examples\": [\"string\"]\n },\n \"tests\": {\n \"unit\": \"string\",\n \"integration\": \"string\"\n }\n }\n}", "options": { "raw": { "language": "json" } } }, "url": { "raw": "{{host}}/generate?noqueue=1", "host": [ "{{host}}" ], "path": [ "generate" ], "query": [ { "key": "noqueue", "value": "1" } ] } }, "_postman_previewlanguage": "json", "header": [ { "key": "Content-Type", "value": "application/json", "name": "Content-Type", "description": "", "type": "text" } ], "cookie": [], "body": "{\r\n \"status\": \"success\",\r\n \"message\": \"Code generated successfully\",\r\n \"result\": {\r\n \"component\": {\r\n \"main\": \"import React, { useEffect } from 'react';\\nimport styled, { ThemeProvider } from 'styled-components';\\nimport { useQuery } from 'react-query';\\nimport create from 'zustand';\\n\\nconst GridContainer = styled.div`\\n display: flex;\\n flex-direction: column;\\n overflow: auto;\\n`;\\n\\nconst Header = styled.div`\\n display: flex;\\n background: ${(props) => props.theme.headerBackground};\\n`;\\n\\nconst Cell = styled.div`\\n padding: 10px;\\n border: 1px solid ${(props) => props.theme.borderColor};\\n`;\\n\\nconst useStore = create((set) => ({\\n selectedRows: [],\\n setSelectedRows: (rows) => set({ selectedRows: rows }),\\n}));\\n\\nconst DataGrid = ({ columns, data }) => {\\n const { selectedRows, setSelectedRows } = useStore();\\n\\n const { data: gridData, error } = useQuery('fetchData', () => fetchDataFunction());\\n\\n useEffect(() => {\\n if (error) {\\n console.error('Error fetching data:', error);\\n }\\n }, [error]);\\n\\n const handleRowSelect = (row) => {\\n setSelectedRows((prev) => [...prev, row]);\\n };\\n\\n return (\\n \\n

\\n {columns.map((col) => (\\n {col.Header}\\n ))}\\n

\\n {gridData && gridData.map((row) => (\\n

handleRowSelect(row)}>\\n {columns.map((col) => (\\n {row[col.accessor]}\\n ))}\\n

\\n ))}\\n \\n );\\n};\\n\\nconst DataGridWrapper = ({ theme }) => (\\n \\n \\n \\n);\\n\\nexport default DataGridWrapper;\",\r\n \"types\": \"interface Column {\\n Header: string;\\n accessor: string;\\n}\\n\\ninterface DataGridProps {\\n columns: Column[];\\n data: any[];\\n}\",\r\n \"hooks\": \"const useFetchData = () => {\\n return useQuery('fetchData', fetchDataFunction);\\n};\",\r\n \"styles\": \"const theme = {\\n headerBackground: '#f0f0f0',\\n borderColor: '#ccc',\\n};\"\r\n },\r\n \"documentation\": {\r\n \"setup\": \"To use the DataGrid component, ensure you have styled-components, react-query, and zustand installed. Import the DataGridWrapper and pass the required props.\",\r\n \"api\": {\r\n \"DataGrid\": {\r\n \"props\": {\r\n \"columns\": \"Array of column definitions\",\r\n \"data\": \"Array of data objects\"\r\n }\r\n }\r\n },\r\n \"examples\": [\r\n \"const columns = [{ Header: 'Name', accessor: 'name' }, { Header: 'Age', accessor: 'age' }];\\nconst data = [{ id: 1, name: 'John', age: 30 }, { id: 2, name: 'Jane', age: 25 }];\\n\"\r\n ]\r\n },\r\n \"tests\": {\r\n \"unit\": \"describe('DataGrid Component', () => {\\n it('renders without crashing', () => {\\n const { getByText } = render();\\n expect(getByText('Name')).toBeInTheDocument();\\n });\\n});\",\r\n \"integration\": \"describe('DataGrid Integration', () => {\\n it('fetches data and displays it', async () => {\\n const { findByText } = render();\\n expect(await findByText('John')).toBeInTheDocument();\\n });\\n});\"\r\n }\r\n },\r\n \"cacheTime\": 1736283233834,\r\n \"time\": 1736283233979\r\n}" } ] }, { "name": "Generate Database Schema Copy", "request": { "method": "POST", "header": [ { "key": "Content-Type", "value": "application/json" } ], "body": { "mode": "raw", "raw": "{\n \"type\": \"database-schema\",\n \"language\": \"sql\",\n \"specifications\": {\n \"include\": [\n \"Table definitions\",\n \"Indexes\",\n \"Stored procedures\",\n \"Triggers\"\n ],\n \"requirements\": {\n \"database\": \"PostgreSQL 15\",\n \"schema\": \"E-commerce system\",\n \"performance\": \"Optimized for read-heavy workload\",\n \"security\": \"Row-level security\"\n },\n \"features\": [\n \"Full-text search\",\n \"Audit logging\",\n \"Versioning\",\n \"Partitioning\"\n ],\n \"entities\": [\n {\n \"name\": \"products\",\n \"fields\": [\n {\"name\": \"id\", \"type\": \"uuid\", \"primary\": true},\n {\"name\": \"name\", \"type\": \"text\", \"index\": true},\n {\"name\": \"description\", \"type\": \"text\", \"searchable\": true},\n {\"name\": \"price\", \"type\": \"decimal(10,2)\"},\n {\"name\": \"metadata\", \"type\": \"jsonb\"}\n ]\n }\n ]\n }\n}", "options": { "raw": { "language": "json" } } }, "url": { "raw": "{{host}}/generate?noqueue=1", "host": [ "{{host}}" ], "path": [ "generate" ], "query": [ { "key": "noqueue", "value": "1" } ] } }, "response": [ { "name": "Generate Database Schema Copy", "originalRequest": { "method": "POST", "header": [ { "key": "Content-Type", "value": "application/json" } ], "body": { "mode": "raw", "raw": "{\n \"type\": \"database-schema\",\n \"language\": \"sql\",\n \"specifications\": {\n \"include\": [\n \"Table definitions\",\n \"Indexes\",\n \"Stored procedures\",\n \"Triggers\"\n ],\n \"requirements\": {\n \"database\": \"PostgreSQL 15\",\n \"schema\": \"E-commerce system\",\n \"performance\": \"Optimized for read-heavy workload\",\n \"security\": \"Row-level security\"\n },\n \"features\": [\n \"Full-text search\",\n \"Audit logging\",\n \"Versioning\",\n \"Partitioning\"\n ],\n \"entities\": [\n {\n \"name\": \"products\",\n \"fields\": [\n {\"name\": \"id\", \"type\": \"uuid\", \"primary\": true},\n {\"name\": \"name\", \"type\": \"text\", \"index\": true},\n {\"name\": \"description\", \"type\": \"text\", \"searchable\": true},\n {\"name\": \"price\", \"type\": \"decimal(10,2)\"},\n {\"name\": \"metadata\", \"type\": \"jsonb\"}\n ]\n }\n ]\n }\n}", "options": { "raw": { "language": "json" } } }, "url": { "raw": "{{host}}/generate?noqueue=1", "host": [ "{{host}}" ], "path": [ "generate" ], "query": [ { "key": "noqueue", "value": "1" } ] } }, "_postman_previewlanguage": "json", "header": [ { "key": "Content-Type", "value": "application/json", "name": "Content-Type", "description": "", "type": "text" } ], "cookie": [], "body": "{\r\n \"status\": \"success\",\r\n \"message\": \"Code generated successfully\",\r\n \"result\": {\r\n \"code\": {\r\n \"content\": \"-- Create schema for E-commerce system\\nCREATE SCHEMA ecommerce;\\n\\n-- Create products table\\nCREATE TABLE ecommerce.products (\\n id UUID PRIMARY KEY DEFAULT gen_random_uuid(),\\n name TEXT NOT NULL,\\n description TEXT,\\n price DECIMAL(10,2) NOT NULL,\\n metadata JSONB,\\n created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,\\n updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP\\n);\\n\\n-- Create index for full-text search on description\\nCREATE INDEX idx_products_description ON ecommerce.products USING gin(to_tsvector('english', description));\\n\\n-- Create index for optimized read on name\\nCREATE INDEX idx_products_name ON ecommerce.products(name);\\n\\n-- Create trigger function for audit logging\\nCREATE OR REPLACE FUNCTION log_product_changes() RETURNS TRIGGER AS $$\\nBEGIN\\n INSERT INTO ecommerce.audit_log (product_id, operation, changed_at)\\n VALUES (NEW.id, TG_OP, CURRENT_TIMESTAMP);\\n RETURN NEW;\\nEND;\\n$$ LANGUAGE plpgsql;\\n\\n-- Create trigger for insert/update/delete operations\\nCREATE TRIGGER trg_product_changes\\nAFTER INSERT OR UPDATE OR DELETE ON ecommerce.products\\nFOR EACH ROW EXECUTE FUNCTION log_product_changes();\\n\\n-- Create audit log table\\nCREATE TABLE ecommerce.audit_log (\\n id SERIAL PRIMARY KEY,\\n product_id UUID NOT NULL,\\n operation TEXT NOT NULL,\\n changed_at TIMESTAMP NOT NULL\\n);\\n\\n-- Create stored procedure for versioning\\nCREATE OR REPLACE FUNCTION version_product(p_id UUID) RETURNS VOID AS $$\\nBEGIN\\n INSERT INTO ecommerce.products (id, name, description, price, metadata, created_at, updated_at)\\n SELECT id, name, description, price, metadata, created_at, updated_at\\n FROM ecommerce.products\\n WHERE id = p_id;\\nEND;\\n$$ LANGUAGE plpgsql;\\n\\n-- Enable row-level security\\nALTER TABLE ecommerce.products ENABLE ROW LEVEL SECURITY;\\n\\n-- Create policy for row-level security\\nCREATE POLICY select_policy ON ecommerce.products\\n FOR SELECT\\n USING (true);\",\r\n \"language\": \"sql\",\r\n \"framework\": null,\r\n \"type\": \"database-schema\"\r\n },\r\n \"explanation\": {\r\n \"overview\": \"This SQL code defines a schema for an E-commerce system in PostgreSQL 15, focusing on performance optimization for read-heavy workloads and implementing security measures such as row-level security. It includes table definitions, indexes, stored procedures, and triggers to support features like full-text search, audit logging, versioning, and partitioning.\",\r\n \"keyComponents\": [\r\n \"Table definitions for products and audit log\",\r\n \"Indexes for performance optimization\",\r\n \"Triggers for audit logging\",\r\n \"Stored procedures for versioning\"\r\n ],\r\n \"bestPractices\": [\r\n \"Use UUIDs for primary keys for better scalability\",\r\n \"Implement full-text search for searchable fields\",\r\n \"Enable row-level security to protect sensitive data\",\r\n \"Use JSONB for flexible metadata storage\"\r\n ],\r\n \"considerations\": [\r\n \"Ensure that the database is properly indexed to optimize read operations\",\r\n \"Monitor the performance of the full-text search to adjust configurations if necessary\",\r\n \"Regularly review and update security policies as needed\"\r\n ]\r\n },\r\n \"implementation\": {\r\n \"steps\": [\r\n \"Create the schema for the E-commerce system.\",\r\n \"Define the products table with appropriate fields and types.\",\r\n \"Create indexes for optimizing read-heavy workloads.\",\r\n \"Implement triggers for audit logging on product changes.\",\r\n \"Define stored procedures for versioning products.\",\r\n \"Enable row-level security on the products table.\"\r\n ],\r\n \"dependencies\": [\r\n \"PostgreSQL 15\"\r\n ],\r\n \"configuration\": {}\r\n },\r\n \"testing\": {\r\n \"testCases\": [\r\n \"Insert a new product and verify it appears in the products table.\",\r\n \"Update a product and check if the audit log captures the change.\",\r\n \"Delete a product and ensure the audit log reflects the deletion.\",\r\n \"Test full-text search functionality on product descriptions.\"\r\n ],\r\n \"validationPoints\": [\r\n \"Ensure all indexes are created and functioning as expected.\",\r\n \"Validate that row-level security policies are applied correctly.\",\r\n \"Check that the stored procedures execute without errors.\"\r\n ]\r\n },\r\n \"documentation\": {\r\n \"usage\": \"This schema is used to manage products in an E-commerce system, providing features for full-text search, audit logging, versioning, and row-level security.\",\r\n \"parameters\": [\r\n {\r\n \"name\": \"id\",\r\n \"type\": \"UUID\",\r\n \"description\": \"Unique identifier for the product.\",\r\n \"required\": true\r\n },\r\n {\r\n \"name\": \"name\",\r\n \"type\": \"TEXT\",\r\n \"description\": \"Name of the product.\",\r\n \"required\": true\r\n },\r\n {\r\n \"name\": \"description\",\r\n \"type\": \"TEXT\",\r\n \"description\": \"Detailed description of the product.\",\r\n \"required\": false\r\n },\r\n {\r\n \"name\": \"price\",\r\n \"type\": \"DECIMAL(10,2)\",\r\n \"description\": \"Price of the product.\",\r\n \"required\": true\r\n },\r\n {\r\n \"name\": \"metadata\",\r\n \"type\": \"JSONB\",\r\n \"description\": \"Additional metadata about the product.\",\r\n \"required\": false\r\n }\r\n ],\r\n \"returns\": {\r\n \"type\": \"void\",\r\n \"description\": \"No return value, but the operation modifies the database.\"\r\n },\r\n \"examples\": [\r\n \"INSERT INTO ecommerce.products (name, description, price, metadata) VALUES ('Sample Product', 'This is a sample product.', 19.99, '{\\\"color\\\": \\\"red\\\", \\\"size\\\": \\\"M\\\"}');\"\r\n ]\r\n }\r\n },\r\n \"cacheTime\": 1736283292163,\r\n \"time\": 1736283292360\r\n}" } ] }, { "name": "Generate Custom Testing Suite", "request": { "method": "POST", "header": [ { "key": "Content-Type", "value": "application/json" } ], "body": { "mode": "raw", "raw": "{\n \"type\": \"test-suite\",\n \"language\": \"javascript\",\n \"framework\": \"jest\",\n \"specifications\": {\n \"include\": [\n \"Unit tests\",\n \"Integration tests\",\n \"E2E tests\",\n \"Performance tests\"\n ],\n \"requirements\": {\n \"coverage\": \"100%\",\n \"ci\": \"GitHub Actions\",\n \"reporting\": \"HTML and JSON reports\",\n \"mocking\": \"MSW for API mocking\"\n },\n \"features\": [\n 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apiLogin('test@example.com', 'password'); expect(response.data).toHaveProperty('user'); });\",\r\n \"test('Database should store user session on login', async () => { await loginUser('test@example.com', 'password'); const session = await getSessionFromDatabase('test@example.com'); expect(session).toBeDefined(); });\"\r\n ],\r\n \"e2e\": [\r\n \"it('should allow user to login, perform actions and logout', () => { cy.visit('/login'); cy.get('input[name=email]').type('test@example.com'); cy.get('input[name=password]').type('password'); cy.get('button[type=submit]').click(); cy.url().should('include', '/dashboard'); cy.get('button.logout').click(); cy.url().should('include', '/login'); });\"\r\n ]\r\n },\r\n \"configuration\": {\r\n \"jest\": \"{\\\"collectCoverage\\\": true, \\\"coverageDirectory\\\": \\\"coverage\\\", \\\"coverageReporters\\\": [\\\"json\\\", \\\"html\\\"], \\\"setupFilesAfterEnv\\\": [\\\"/setupTests.js\\\"]}\",\r\n \"msw\": \"{\\\"handlers\\\": [ { \\\"method\\\": 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"method": "POST", "header": [ { "key": "Content-Type", "value": "application/json" } ], "body": { "mode": "raw", "raw": "{\n \"type\": \"sql\",\n \"language\": \"sql\",\n \"specifications\": {\n \"description\": \"Get all active users who registered in the last 30 days and have made at least one purchase\",\n \"tables\": {\n \"users\": {\n \"columns\": [\"id\", \"name\", \"email\", \"created_at\", \"status\"],\n \"primaryKey\": \"id\"\n },\n \"orders\": {\n \"columns\": [\"id\", \"user_id\", \"total\", \"created_at\"],\n \"foreignKey\": {\n \"user_id\": \"users.id\"\n }\n }\n },\n \"requirements\": {\n \"conditions\": [\n \"users must be active\",\n \"registration within last 30 days\",\n \"minimum 1 order\"\n ],\n \"orderBy\": \"users.created_at DESC\"\n }\n }\n}", "options": { "raw": { "language": "json" } } }, "url": { "raw": "{{host}}/generate?noqueue=1", "host": [ "{{host}}" ], "path": [ "generate" ], "query": [ { "key": "noqueue", "value": "1" } ] } }, "response": [ { "name": "Generate SQL Generator", "originalRequest": { "method": "POST", "header": [ { "key": "Content-Type", "value": "application/json" } ], "body": { "mode": "raw", "raw": "{\n \"type\": \"sql\",\n \"language\": \"sql\",\n \"specifications\": {\n \"description\": \"Get all active users who registered in the last 30 days and have made at least one purchase\",\n \"tables\": {\n \"users\": {\n \"columns\": [\"id\", \"name\", \"email\", \"created_at\", \"status\"],\n \"primaryKey\": \"id\"\n },\n \"orders\": {\n \"columns\": [\"id\", \"user_id\", \"total\", \"created_at\"],\n \"foreignKey\": {\n \"user_id\": \"users.id\"\n }\n }\n },\n \"requirements\": {\n \"conditions\": [\n \"users must be active\",\n \"registration within last 30 days\",\n \"minimum 1 order\"\n ],\n \"orderBy\": \"users.created_at DESC\"\n }\n }\n}", "options": { "raw": { "language": "json" } } }, "url": { "raw": "{{host}}/generate?noqueue=1", "host": [ "{{host}}" ], "path": [ "generate" ], "query": [ { "key": "noqueue", "value": "1" } ] } }, "_postman_previewlanguage": "json", "header": [ { "key": "Content-Type", "value": "application/json", "name": "Content-Type", "description": "", "type": "text" } ], "cookie": [], "body": "{\r\n \"status\": \"success\",\r\n \"message\": \"Code generated successfully\",\r\n \"result\": {\r\n \"code\": {\r\n \"content\": \"SELECT u.id, u.name, u.email, u.created_at\\nFROM users u\\nJOIN orders o ON u.id = o.user_id\\nWHERE u.status = 'active'\\n AND u.created_at >= NOW() - INTERVAL '30 days'\\nGROUP BY u.id\\nHAVING COUNT(o.id) >= 1\\nORDER BY u.created_at DESC;\",\r\n \"language\": \"sql\",\r\n \"framework\": null,\r\n \"type\": \"query\"\r\n },\r\n \"explanation\": {\r\n \"overview\": \"This SQL query retrieves all active users who registered within the last 30 days and have made at least one purchase. It joins the 'users' and 'orders' tables to filter the results based on the specified conditions.\",\r\n \"keyComponents\": [\r\n \"SELECT statement to retrieve user details\",\r\n \"JOIN clause to combine users and orders\",\r\n \"WHERE clause for filtering active users and registration date\",\r\n \"GROUP BY clause to aggregate orders per user\",\r\n \"HAVING clause to ensure at least one order exists\",\r\n \"ORDER BY clause to sort results by registration date\"\r\n ],\r\n \"bestPractices\": [\r\n \"Use meaningful aliases for tables to improve readability.\",\r\n \"Always specify the columns you need instead of using SELECT *.\",\r\n \"Utilize JOINs appropriately to avoid Cartesian products.\",\r\n \"Implement error handling by checking for NULL values or unexpected results.\"\r\n ],\r\n \"considerations\": [\r\n \"Ensure that the 'status' field is indexed for better performance.\",\r\n \"Consider the impact of large datasets on query performance and use pagination if necessary.\",\r\n \"Be cautious of SQL injection; use parameterized queries in application code.\"\r\n ]\r\n },\r\n \"implementation\": {\r\n \"steps\": [\r\n \"Define the SQL query to join the users and orders tables.\",\r\n \"Apply the necessary filters in the WHERE clause.\",\r\n \"Group the results by user ID to count the orders.\",\r\n \"Sort the results by the registration date in descending order.\",\r\n \"Test the query for performance and accuracy.\"\r\n ],\r\n \"dependencies\": [\r\n \"Database management system (e.g., PostgreSQL, MySQL)\"\r\n ],\r\n \"configuration\": {}\r\n },\r\n \"testing\": {\r\n \"testCases\": [\r\n \"Test with users who registered in the last 30 days and made purchases.\",\r\n \"Test with users who registered more than 30 days ago.\",\r\n \"Test with inactive users.\",\r\n \"Test with users who have not made any purchases.\"\r\n ],\r\n \"validationPoints\": [\r\n \"Ensure that the output only includes active users.\",\r\n \"Verify that all users in the result set registered within the last 30 days.\",\r\n \"Check that each user in the result set has at least one associated order.\"\r\n ]\r\n },\r\n \"documentation\": {\r\n \"usage\": \"This query is used to retrieve active users who registered recently and have made at least one purchase.\",\r\n \"parameters\": [\r\n {\r\n \"name\": \"status\",\r\n \"type\": \"string\",\r\n \"description\": \"The status of the user (e.g., 'active').\",\r\n \"required\": true\r\n },\r\n {\r\n \"name\": \"registration_period\",\r\n \"type\": \"integer\",\r\n \"description\": \"The number of days to look back for user registration.\",\r\n \"required\": true\r\n }\r\n ],\r\n \"returns\": {\r\n \"type\": \"array\",\r\n \"description\": \"An array of user objects containing id, name, email, and registration date.\"\r\n },\r\n \"examples\": [\r\n \"SELECT * FROM users WHERE status = 'active' AND created_at >= NOW() - INTERVAL '30 days';\"\r\n ]\r\n }\r\n },\r\n \"cacheTime\": 1736283914142,\r\n \"time\": 1736283914373\r\n}" } ] } ], "event": [ { "listen": "prerequest", "script": { "type": "text/javascript", "packages": {}, "exec": [ "" ] } }, { "listen": "test", "script": { "type": "text/javascript", "packages": {}, "exec": [ "" ] } } ], "variable": [ { "key": "host", "value": "https://codegenerator.service1.api.bilgisam.com", "type": "string" } ] }