ReliableGPT

Use Case 1: Handling API Rate Limits

Problem: Production applications frequently hit OpenAI rate limits, leading to service interruptions and poor user experience.
Solution: ReliableGPT implements automated error handling to manage rate limits, ensuring that no requests are dropped.
Example: A high-traffic chatbot remains operational during peak usage by managing request flows and retries without manual intervention.

Use Case 2: Implementing Model Fallbacks

Problem: A specific LLM model might experience high latency or temporary downtime, causing application lag.
Solution: The tool allows developers to define fallback models to ensure requests are fulfilled by an alternative endpoint if the primary fails.
Example: If GPT-4 returns a timeout error, the system automatically reroutes the prompt to GPT-3.5-Turbo to maintain service availability.

Use Case 3: Managing Multiple API Keys

Problem: Relying on a single API key is risky; if it expires or hits a hard limit, the entire application stops working.
Solution: ReliableGPT handles API key errors and can rotate through multiple keys to maximize uptime.
Example: An AI content platform switches to a secondary developer key instantly if the primary key is flagged for billing issues.