@simpleapps-com/augur-api/dist/cjs/services/gregorovich/resources/ollama-generate.d.ts

TypeScript client library for Augur microservices API endpoints

import type { OllamaGenerateRequestParams, OllamaGenerateResult } from '../schemas';
import type { EndpointConfig } from '../../../core/base-client';
type BoundExecuteRequest = <TParams, TResponse>(config: EndpointConfig<TParams, TResponse>, params?: TParams, pathParams?: Record<string, string>) => Promise<TResponse>;
/**
 * Creates the ollama.generate resource methods
 * OpenAPI Path: /ollama/generate → ollama.generate.*
 * @description Ollama local AI model generation functionality
 */
export declare function createOllamaGenerateResource(executeRequest: BoundExecuteRequest): {
    /**
     * 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: (params: OllamaGenerateRequestParams) => Promise<{
        params: Record<string, unknown> | unknown[];
        data: {} & {
            [k: string]: unknown;
        };
        options: Record<string, unknown> | unknown[];
        status: number;
        message: string;
        count: number;
        total: number;
        totalResults: number;
    }>;
};
/**
 * Creates the ollamaData.generate resource methods (data-only versions)
 */
export declare function createOllamaGenerateDataResource(ollamaGenerate: ReturnType<typeof createOllamaGenerateResource>): {
    /**
     * 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: (params: OllamaGenerateRequestParams) => Promise<OllamaGenerateResult>;
};
export type OllamaGenerateResource = ReturnType<typeof createOllamaGenerateResource>;
export type OllamaGenerateDataResource = ReturnType<typeof createOllamaGenerateDataResource>;
export {};
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