chore: import upstream snapshot with attribution

examples/provider-nscale/README.md

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+# provider-nscale (Nscale Example (Cost-Effective AI Inference))
+
+This example demonstrates how to use the Nscale provider with promptfoo to evaluate Nscale Serverless Inference API models, which offer cost-effective, high-performance AI inference with zero rate limits.
+
+You can run this example with:
+
+```bash
+npx promptfoo@latest init --example provider-nscale
+cd provider-nscale
+```
+
+## Prerequisites
+
+### Authentication Setup
+
+1. Sign up for an account at [Nscale](https://nscale.com/)
+2. Navigate to your account settings
+3. Go to "Service Tokens" section
+4. Generate a service token and set it as an environment variable:
+
+```bash
+export NSCALE_SERVICE_TOKEN="your-service-token-here"
+```
+
+Alternatively, you can add it to your `.env` file:
+
+```env
+NSCALE_SERVICE_TOKEN=your-service-token-here
+```
+
+## Example Configuration
+
+This repository contains an example configuration demonstrating Nscale's capabilities:
+
+### Basic Model Evaluation (`promptfooconfig.yaml`)
+
+This configuration evaluates two popular Nscale models on their ability to solve reasoning problems and generate creative content.
+
+```bash
+promptfoo eval
+```
+
+**Expected output:** You'll see a comparison of how each model handles different types of tasks, with metrics on accuracy, creativity, and response quality.
+
+### Image Generation Evaluation (`image-promptfooconfig.yaml`)
+
+This configuration compares Nscale's image generation models on various prompts to evaluate their quality and consistency.
+
+```bash
+promptfoo eval -c image-promptfooconfig.yaml
+```
+
+**Expected output:** You'll see generated images from different models (Flux.1 Schnell, SDXL Lightning, Stable Diffusion XL) for comparison across various image types including landscapes, futuristic scenes, portraits, and abstract art.
+
+## Model Capabilities
+
+Nscale supports many popular models with competitive pricing:
+
+**Text Generation Models:**
+
+- `openai/gpt-oss-120b` - OpenAI's 120B open-weight model
+- `openai/gpt-oss-20b` - OpenAI's 20B model
+- `qwen/qwen-3-235b-a22b-instruct` - Qwen 3 235B model
+- `qwen/qwen-3-235b-a22b-instruct-2507` - Qwen 3 235B Instruct 2507
+- `qwen/qwen-3-4b-thinking-2507` - Qwen 3 4B Thinking 2507
+- `qwen/qwen-3-8b` - Qwen 3 8B model
+- `qwen/qwen-3-14b` - Qwen 3 14B model
+- `qwen/qwen-3-32b` - Qwen 3 32B model
+- `qwen/qwen-2.5-coder-3b-instruct` - Qwen 2.5 Coder 3B Instruct
+- `qwen/qwen-2.5-coder-7b-instruct` - Qwen 2.5 Coder 7B Instruct
+- `qwen/qwen-2.5-coder-32b-instruct` - Qwen 2.5 Coder 32B Instruct
+- `qwen/qwq-32b` - Qwen QwQ 32B model
+- `meta/llama-3.3-70b-instruct` - Meta's Llama 3.3 70B model
+- `meta/llama-3.1-8b-instruct` - Meta's Llama 3.1 8B model
+- `meta/llama-4-scout-17b-16e-instruct` - Llama 4 Scout 17B model (Image-Text-to-Text)
+- `deepseek/deepseek-r1-distill-llama-70b` - DeepSeek R1 Distill Llama 70B
+- `deepseek/deepseek-r1-distill-llama-8b` - DeepSeek R1 Distill Llama 8B
+- `deepseek/deepseek-r1-distill-qwen-1.5b` - DeepSeek R1 Distill Qwen 1.5B
+- `deepseek/deepseek-r1-distill-qwen-7b` - DeepSeek R1 Distill Qwen 7B
+- `deepseek/deepseek-r1-distill-qwen-14b` - DeepSeek R1 Distill Qwen 14B
+- `deepseek/deepseek-r1-distill-qwen-32b` - DeepSeek R1 Distill Qwen 32B
+- `mistral/devstral-small-2505` - Mistral's Devstral Small model
+- `mistral/mixtral-8x22b-instruct-v0.1` - Mixtral 8x22B Instruct
+
+**Embedding Models:**
+
+- `Qwen/Qwen3-Embedding-8B` - Qwen 3 8B Embedding model
+
+**Text-to-Image Models:**
+
+- `BlackForestLabs/FLUX.1-schnell` - Flux.1 Schnell image generation model
+- `stabilityai/stable-diffusion-xl-base-1.0` - Stable Diffusion XL 1.0
+- `ByteDance/SDXL-Lightning-4step` - SDXL Lightning 4-step
+- `ByteDance/SDXL-Lightning-8step` - SDXL Lightning 8-step
+
+## Pricing & Usage
+
+Nscale offers highly competitive pricing with up to 80% cost savings compared to other providers:
+
+- **Text Generation:** Starting from $0.01 input / $0.03 output per 1M tokens
+- **Image Generation:** Starting from $0.0008 per mega-pixel
+- **Zero rate limits** and **no cold starts**
+
+Check the [official pricing page](https://docs.nscale.com/pricing) for the most current rates.
+
+## Learn More
+
+- [Nscale Provider Documentation](https://promptfoo.dev/docs/providers/nscale)
+- [Nscale API Reference](https://docs.nscale.com/)
+- [Nscale Serverless Inference](https://nscale.com/serverless)
+- [Nscale Model Marketplace](https://nscale.com/models)

examples/provider-nscale/image-promptfooconfig.yaml

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+description: 'Nscale Image Generation Example - comparing different image models'
+
+providers:
+  - id: nscale:image:BlackForestLabs/FLUX.1-schnell
+    config:
+      size: '1024x1024'
+      n: 1
+  - id: nscale:image:ByteDance/SDXL-Lightning-4step
+    config:
+      size: '1024x1024'
+      n: 1
+  - id: nscale:image:stabilityai/stable-diffusion-xl-base-1.0
+    config:
+      size: '1024x1024'
+      n: 1
+
+prompts:
+  - 'A serene landscape with mountains and a lake at sunset'
+  - 'A futuristic cityscape with flying cars and neon lights'
+  - 'A close-up portrait of a wise old wizard with a long beard'
+  - 'An abstract geometric pattern in vibrant colors'
+
+tests:
+  - description: 'Nature scene generation'
+    vars:
+      prompt: 'A serene landscape with mountains and a lake at sunset'
+    assert:
+      - type: not-empty
+        value: 'Image should be generated'
+
+  - description: 'Futuristic scene generation'
+    vars:
+      prompt: 'A futuristic cityscape with flying cars and neon lights'
+    assert:
+      - type: not-empty
+        value: 'Image should be generated'
+
+  - description: 'Portrait generation'
+    vars:
+      prompt: 'A close-up portrait of a wise old wizard with a long beard'
+    assert:
+      - type: not-empty
+        value: 'Image should be generated'
+
+  - description: 'Abstract art generation'
+    vars:
+      prompt: 'An abstract geometric pattern in vibrant colors'
+    assert:
+      - type: not-empty
+        value: 'Image should be generated'

examples/provider-nscale/promptfooconfig.yaml

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+# yaml-language-server: $schema=https://promptfoo.dev/config-schema.json
+description: Evaluating Nscale models for reasoning and creative tasks
+prompts:
+  - file://prompts.txt
+providers:
+  - id: nscale:openai/gpt-oss-120b
+    config:
+      temperature: 0.7
+      max_tokens: 1024
+  - id: nscale:meta/llama-3.3-70b-instruct
+    config:
+      temperature: 0.5
+      max_tokens: 1024
+tests:
+  - vars:
+      task_type: mathematical reasoning
+      task_description: 'Solve this problem step by step: A train leaves Station A at 2:00 PM traveling at 60 mph toward Station B, which is 180 miles away. Another train leaves Station B at 2:30 PM traveling at 80 mph toward Station A. At what time will the two trains meet?'
+    assert:
+      - type: contains-any
+        value: ['3:48', '3:48 PM', 'distance', 'relative speed', 'combined speed']
+      - type: llm-rubric
+        value: 'The response should show clear step-by-step mathematical reasoning and arrive at the correct answer of 3:48 PM.'
+  - vars:
+      task_type: creative writing
+      task_description: 'Write a short story (2-3 paragraphs) about a librarian who discovers that books in their library are portals to different worlds. Include vivid descriptions and an intriguing plot twist.'
+    assert:
+      - type: contains-any
+        value: ['portal', 'world', 'librarian', 'books', 'discovery']
+      - type: llm-rubric
+        value: 'The story should be creative, well-structured, include vivid descriptions, and have an interesting plot twist.'
+  - vars:
+      task_type: logical reasoning
+      task_description: "Three friends - Alice, Bob, and Charlie - each have a different favorite color (red, blue, green) and a different pet (cat, dog, bird). Given the clues: 1) Alice doesn't like red, 2) The person who likes blue has a cat, 3) Charlie has a bird, 4) Bob doesn't like green. Determine who has which pet and favorite color."
+    assert:
+      - type: contains-any
+        value: ['Alice', 'Bob', 'Charlie', 'blue', 'cat', 'bird']
+      - type: llm-rubric
+        value: 'The response should systematically work through the logical constraints and arrive at the correct solution.'
+  - vars:
+      task_type: scientific explanation
+      task_description: "Explain the concept of photosynthesis in a way that a 12-year-old could understand, including why it's important for life on Earth."
+    assert:
+      - type: contains-any
+        value: ['sunlight', 'carbon dioxide', 'oxygen', 'glucose', 'chlorophyll', 'plants']
+      - type: llm-rubric
+        value: 'The explanation should be age-appropriate, scientifically accurate, and clearly explain the importance of photosynthesis.'
+outputs:
+  - type: csv

examples/provider-nscale/prompts.txt

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+You are an expert assistant that provides clear, accurate, and helpful responses.
+
+Please analyze the following {{task_type}} task and provide a comprehensive response:
+
+{{task_description}}
+
+Consider the following aspects:
+1. Key concepts and principles involved
+2. Step-by-step reasoning or approach
+3. Practical implications or applications
+4. Any potential challenges or considerations
+
+Provide your response in a clear, structured format.