Merge pull request #59 from meta-llama/frontend

Add Web Frontend for prompt-ops

Author: heyjustinai

.coveragerc

@@ -0,0 +1,15 @@
+[run]
+source = src/prompt_ops
+omit =
+    */tests/*
+    */site-packages/*
+    setup.py
+
+[report]
+exclude_lines =
+    pragma: no cover
+    def __repr__
+    raise NotImplementedError
+    if __name__ == .__main__.:
+    pass
+    raise ImportError

.github/workflows/publish.yml

@@ -40,7 +40,7 @@ jobs:
         echo "Package version: $VERSION"
 
         # Check if this version already exists on PyPI
-        if pip index versions llama-prompt-ops 2>/dev/null | grep -q "$VERSION"; then
+        if pip index versions prompt-ops 2>/dev/null | grep -q "$VERSION"; then
           echo "Error: Version $VERSION already exists on PyPI"
           exit 1
         fi

README.md

@@ -130,7 +130,8 @@ Add your API key to the `.env` file:
 ```bash
 OPENROUTER_API_KEY=your_key_here
 ```
-You can get an OpenRouter API key by creating an account at [OpenRouter](https://openrouter.ai/). For more inference provider options, see [Inference Providers](./docs/inference_providers.md).
+
+prompt-ops uses LiteLLM as a unified API client. LiteLLM automatically detects the provider from your model name (e.g., `openrouter/model`, `groq/model`) and looks for the corresponding provider-specific environment variable (`OPENROUTER_API_KEY`, `GROQ_API_KEY`, etc.). For more inference provider options, see [Inference Providers](./docs/inference_providers.md).
 
 ### Step 4: Run Optimization
 The optimization will take about 5 minutes.

configs/facility-simple.yaml

@@ -10,6 +10,7 @@ dataset:
   golden_output_field: "answer"
 
 # Model configuration (minimal required settings)
+# LiteLLM auto-detects API keys from provider-specific env vars (e.g., OPENROUTER_API_KEY)
 model:
   name: "openrouter/meta-llama/llama-3.3-70b-instruct"
   task_model: "openrouter/meta-llama/llama-3.3-70b-instruct"

configs/facility.yaml

@@ -1,12 +1,9 @@
 # Facility dataset configuration for prompt optimization
 
-#TODO: think if there are any way to abstract this
-# provider: openrouter/hosted_vllm/togethercomputer
-# model: meta-llama/llama-3.3-70b-instruct
-# litellm
+# Model configuration - uses LiteLLM with provider prefix
+# LiteLLM auto-detects API key from provider-specific env vars (e.g., OPENROUTER_API_KEY, GROQ_API_KEY)
 model:
   name: "openrouter/meta-llama/llama-3.3-70b-instruct"
-  api_base: "https://openrouter.ai/api/v1" # rename base_url:
   temperature: 0.0
   # max_tokens: 2048       # Maximum number of tokens to generate
   # top_p: 0.9             # Nucleus sampling parameter

configs/hotpotqa.yaml

@@ -1,6 +1,5 @@
 model:
   name: "openrouter/meta-llama/llama-3.1-8b-instruct"
-  api_base: "https://openrouter.ai/api/v1"
   temperature: 0.0
   max_tokens: 40960
 

docs/README.md

@@ -1,3 +1,11 @@
+---
+title: Getting Started
+category: Basics
+description: Learn the fundamentals of prompt-ops and choose your optimization path
+order: 1
+icon: book
+---
+
 # prompt-ops Getting Started Guide
 
 Welcome to prompt-ops! This guide will help you understand what's supported out of the box and how to get started quickly.

docs/advanced/logging.md

@@ -1,3 +1,11 @@
+---
+title: Logging & Telemetry
+category: Advanced
+description: Configure logging levels and export optimization telemetry for analysis
+order: 32
+icon: settings
+---
+
 # Logging and Telemetry
 
 The `prompt-ops` library includes a flexible logging framework to provide insights into the optimization process. You can control the verbosity of the output and export detailed telemetry for analysis.

docs/advanced/readme.md

@@ -1,3 +1,11 @@
+---
+title: Custom Adapters & Metrics
+category: Advanced
+description: Create custom dataset adapters and evaluation metrics for your use case
+order: 31
+icon: code
+---
+
 # Using prompt-ops for your use case (with Examples)
 
 > **Note:** This guide explains how to add new use cases to prompt-ops by either configuring existing components or creating custom components.

docs/basic/readme.md

@@ -1,3 +1,11 @@
+---
+title: Quick Start Guide
+category: Basics
+description: Optimize your first prompt in 5 minutes with a guided walkthrough
+order: 2
+icon: zap
+---
+
 # Quick Start Guide: Optimizing Prompts in 5 Minutes
 
 ## What You'll Build