Trainkore
Trainkore is an automated prompt engineering platform that enables model switching, evaluation, and optimization across multiple LLM providers while reducing costs by up to 85%.
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https://trainkore.com/
Product Information
Updated:25/10/2024
What is Trainkore
Trainkore is a unified platform for managing and optimizing large language model (LLM) interactions. It serves as a comprehensive solution that helps organizations work with multiple AI models through automated prompt generation, model routing, and performance monitoring. The platform is designed to make AI implementation more efficient and cost-effective by providing tools for prompt engineering, version control, and integration with popular AI frameworks.
Key Features of Trainkore
Trainkore is a unified AI platform that provides auto prompt generation, model switching, and evaluation capabilities across multiple LLM providers. It offers features like prompt versioning, observability suite, and performance optimization while claiming to reduce costs by up to 85% compared to using single LLMs.
Auto Prompt Generation: Dynamically generates optimized prompts for various use cases and different AI models
Model Router & Switching: Intelligently routes requests across multiple LLM providers including OpenAI, Gemini, Coherence, and Anthropic for better performance and cost efficiency
Comprehensive Observability: Provides detailed logs, metrics, and performance analysis tools for monitoring and debugging AI interactions
Prompt Versioning: Maintains version control for prompts and allows iterative improvements based on performance data
Use Cases of Trainkore
AI Development Integration: Seamlessly integrates with existing AI frameworks like Langchain and LlamaIndex for enhanced development workflows
Cost Optimization: Helps organizations reduce AI operational costs through intelligent model routing and optimization
Performance Monitoring: Enables teams to track and analyze AI model performance through comprehensive logging and analytics
Pros
Significant cost savings through optimization
Easy integration with multiple AI providers
Comprehensive monitoring and analytics capabilities
Cons
Experimental features may not be fully stable
Learning curve for utilizing all features effectively
How to Use Trainkore
Install Trainkore: Import and initialize Trainkore in your project using: import Trainkore from 'trainkore'
Create Instance: Initialize a new Trainkore instance with: const trainkore = new Trainkore()
Configure Chat Prompt: Set up your chat prompt by creating an object with messages and model parameters using trainkore.chatPrompt.create()
Select Model: Choose from available models including OpenAI, Anthropic, Llama2 or custom models in the model parameter
Generate Prompts: Use the auto prompt generation feature to dynamically create prompts for different use cases
Monitor Performance: Access the observability suite to view metrics, debug logs, and analyze input/output performance
Version Control: Use the prompt versioning system to manage and iterate on prompts across your organization
Evaluate Results: Review logs containing input, output, ratings, prompts, and metadata to evaluate performance
Trainkore FAQs
Trainkore is a prompting and RAG platform that offers auto prompt generation, model switching, and evaluation capabilities. It provides higher performance and lower cost than using any single LLM.
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