@simpleapps-com/augur-api/dist/esm/services/gregorovich/resources/ollama-generate.js

TypeScript client library for Augur microservices API endpoints

import { OllamaGenerateRequestParamsSchema, OllamaGenerateResponseSchema, } from '../schemas/ollamaGenerate';
/**
 * Creates the ollama.generate resource methods
 * OpenAPI Path: /ollama/generate → ollama.generate.*
 * @description Ollama local AI model generation functionality
 */
export function createOllamaGenerateResource(executeRequest) {
    return {
        /**
         * Generate content using local Ollama AI models
         *
         * @fullPath api.gregorovich.ollama.generate.create
         * @service gregorovich
         * @domain ai-generation
         * @dataMethod ollamaData.generate.create
         * @discoverable true
         * @searchTerms ["ollama", "generate", "ai", "local", "llm", "model", "text", "completion", "generation"]
         * @relatedEndpoints ["api.gregorovich.chatGpt.ask.get", "api.p21Pim.ai.suggestions.get", "api.agrSite.ai.transcripts.create", "api.gregorovich.documents.list"]
         * @commonPatterns ["Generate AI content", "Local AI processing", "Text completion", "AI writing assistant", "Custom model inference", "Private AI generation"]
         * @workflow ["content-generation", "ai-assistance", "text-processing", "creative-writing", "code-generation", "document-analysis"]
         * @prerequisites ["Public bearer token", "x-site-id header", "Model name", "Generation prompt", "Ollama service availability"]
         * @nextSteps ["Process generated content", "Refine generation parameters", "Chain multiple generations", "Store generation results"]
         * @businessRules ["Requires model and prompt parameters", "Supports local model execution", "Configurable generation parameters", "Token and context management", "Performance monitoring"]
         * @functionalArea "ai-and-automation"
         * @crossSite "Multi-site AI generation support"
         * @caching "Cache responses for 30 minutes for identical prompts and parameters"
         * @performance "Local processing, faster than external APIs but depends on model size and complexity"
         *
         * @param params Ollama generation parameters including model, prompt, and generation configuration
         * @returns Promise<OllamaGenerateResponse> Complete AI generation result with content, metadata, and performance metrics
         *
         * @example
         * ```typescript
         * // Simple text generation
         * const generation = await client.ollama.generate.create({
         *   model: 'llama2',
         *   prompt: 'Write a short story about a robot learning to paint'
         * });
         * console.log(generation.data.response); // Generated story
         * console.log(generation.data.total_duration); // Generation time
         *
         * // Get just the generated content
         * const story = await client.ollamaData.generate.create({
         *   model: 'codellama',
         *   prompt: 'Create a Python function to calculate fibonacci numbers'
         * });
         * console.log(story.response); // Direct access to generated code
         *
         * // Advanced generation with parameters
         * const technicalDoc = await client.ollamaData.generate.create({
         *   model: 'mistral',
         *   prompt: 'Explain machine learning algorithms for beginners',
         *   temperature: 0.3,
         *   max_tokens: 1500,
         *   system: 'You are a patient teacher who explains complex topics simply',
         *   format: 'json',
         *   top_p: 0.9,
         *   seed: 42
         * });
         *
         * // Creative writing with higher randomness
         * const creativeContent = await client.ollamaData.generate.create({
         *   model: 'neural-chat',
         *   prompt: 'Write a product description for a smart home device',
         *   temperature: 0.8,
         *   top_k: 40,
         *   repeat_penalty: 1.1,
         *   stop: ['\\n\\n', 'END'],
         *   sessionId: 'creative-session-1'
         * });
         *
         * // Conversation with context
         * const conversational = await client.ollamaData.generate.create({
         *   model: 'llama2-chat',
         *   prompt: 'What are the benefits of renewable energy?',
         *   context: previousContext, // Array of context tokens
         *   conversationId: 'energy-discussion',
         *   num_predict: 200
         * });
         * ```
         */
        create: async (params) => {
            return executeRequest({
                method: 'POST',
                path: '/ollama/generate',
                paramsSchema: OllamaGenerateRequestParamsSchema,
                responseSchema: OllamaGenerateResponseSchema,
            }, params);
        },
    };
}
/**
 * Creates the ollamaData.generate resource methods (data-only versions)
 */
export function createOllamaGenerateDataResource(ollamaGenerate) {
    return {
        /**
         * Generate content with Ollama and return generation result data only
         * @param params Ollama generation parameters
         * @returns Promise<OllamaGenerateResult> Generated content with metadata and performance metrics
         */
        create: async (params) => {
            const response = await ollamaGenerate.create(params);
            return response.data;
        },
    };
}
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