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LLM Evaluation Multi Model

ProBack

Ship AI agents with confidence.
ProBack helps teams test, compare, and evaluate LLM-powered agents before they reach production. Write prompts, chat with models side-by-side, and run automated evaluations — all in one place.


The Problem

Building AI agents means writing prompts, testing across models, iterating on behavior, and proving quality before launch. Most teams do this in notebooks, chat windows, and spreadsheets — slow, unstructured, and impossible to scale.

The Solution

ProBack gives you a structured workspace for every stage of the agent development lifecycle:

Playground

  • Compare models side-by-side — Open GPT-4o, Claude 3.5 Sonnet, and other models in parallel prompt cards. See different responses for the same input instantly.
  • Tune parameters — Adjust temperature, max tokens, and system prompts with a visual settings panel.
  • Chat in real-time — Stream responses token-by-token as you iterate.

Agent Management

  • Save and version agents — Store prompt configurations as reusable agents. Create named variants (e.g., "friendly tone" vs "professional tone") for systematic A/B testing.
  • Template variables — Use {variable} placeholders in prompts. ProBack auto-generates input fields and links them to your test data.

Evaluation

  • LLM-as-a-Judge — Automatically score agent outputs against custom rubrics. No manual review needed for hundreds of test cases.
  • Build test datasets — Create datasets of inputs and expected outputs linked to your agent's variables.
  • Objective + Subjective testing — Validate factual correctness with input/output pairs, and assess conversational quality with subjective scoring.

Built With

Python · Flask · MongoDB · OpenAI · Anthropic · Firebase Auth

License

MIT

About

LLM Evaluation, Testing and Analytics Framework: Making AI Agents production ready.

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