Prompt Versioning for LLMs with Opik

Problem: Lack of prompt versioning hinders debugging, collaboration, and systematic improvement in LLM-based applications, treating prompts as disposable strings.
Solution: The post introduces a method for prompt versioning using Opik (by Comet), treating prompts like code. This involves a `Prompt` class that encapsulates the prompt text and associates a name for tracking in Opik.
Implementation Details: The `Prompt` class, found in the `PhiloAgents API`, includes a private attribute `__prompt` (an `Opik` prompt class instance) and a `prompt` property to convert the `Opik` prompt into a usable string. Prompts are versioned by instantiating the `Prompt` class with a name and the prompt text.
Workflow: Changes to prompts trigger a new version in Opik's Prompt Library. The demonstration involves modifying a prompt (evaluation data set generation prompt) and redeploying the application, resulting in an incremented version in the library.
Benefits Demonstrated: Versioning allows tracking prompt evolution (e.g., Philosopher character card prompt had 18 versions due to iterative tweaking).
Additional Insights (from additional source): Opik's `OpikTracer` can be used as a callback with LangGraph to monitor agent behavior, providing detailed traces of node calls, execution time, inputs, and outputs. Opik also supports evaluation dataset creation and tracks metrics like hallucination, answer relevance, moderation, context precision, and context recall.