Integrations
Humanloop integration
Humanloop helps teams build better LLM applications through prompt management, evaluation frameworks, and human feedback integration.
Humanloop helps teams build better LLM applications through prompt management, evaluation frameworks, and human feedback integration.
Link your Humanloop account to CodeWords by entering your API key from your workspace settings. This connection enables access to your prompts, models, and evaluation data.
Select managed prompts from your Humanloop project to use in workflows. Reference versioned prompts by name or ID to ensure consistent AI behavior across your applications.
Map inputs from your trigger sources to prompt variables. Pass user messages, context, or structured data to Humanloop prompts for LLM processing and response generation.
Extract generated text, completions, or structured outputs from Humanloop responses. Transform AI-generated content into formats suitable for your applications and business processes.
Record all prompt executions, user inputs, and model outputs to Humanloop for monitoring. Build comprehensive logs of AI interactions for quality assurance and model improvement.
Trigger feedback collection workflows when AI responses are generated. Send outputs to reviewers, capture ratings or corrections, and route feedback back to Humanloop for model refinement.
Track completion quality, latency, token usage, and costs across your AI workflows. Set up alerts when performance metrics fall outside acceptable ranges.
Deploy new prompt versions without code changes by updating them in Humanloop. Automatically test prompt variations, measure performance differences, and roll out improvements systematically.
Process support tickets using Humanloop-managed prompts for consistent response quality. Generate draft responses, classify ticket urgency, extract key information, and log all interactions for quality monitoring and continuous prompt improvement.
Create marketing copy, product descriptions, or social media posts using versioned prompts. A/B test different prompt approaches, collect team feedback on outputs, and refine prompts based on performance data to improve content quality over time.
Route AI-generated outputs to human reviewers for validation before publication. Collect structured feedback on accuracy, tone, and relevance, feed corrections back to Humanloop for model fine-tuning, and maintain quality standards across all AI interactions.
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