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111 lines
4.6 KiB
Markdown
111 lines
4.6 KiB
Markdown
# mistral (Mistral AI Chat Models)
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This example demonstrates Mistral AI's chat models, including Magistral reasoning models, current multimodal models, and shows how to use Mistral models for evaluation grading and embeddings.
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You can run this example with:
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```bash
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npx promptfoo@latest init --example mistral
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cd mistral
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```
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## Environment Variables
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This example requires:
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- `MISTRAL_API_KEY` - Your Mistral API key (get it from [console.mistral.ai](https://console.mistral.ai))
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## What This Example Shows
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- **Mathematical Reasoning**: AIME2024 competition problems with Magistral Medium
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- **Model Comparison**: Compare Mistral's different model capabilities
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- **Reasoning Models**: Showcase Magistral Medium (native reasoning) vs. Mistral Small 4
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- **Chat Capabilities**: General conversation and task completion
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- **Mistral-powered Evaluation**: Use Mistral models for grading instead of OpenAI
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- **Mistral Embeddings**: Use Mistral's embedding model for similarity checks
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## Models Demonstrated
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### Reasoning Models
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- **Magistral Medium** (`magistral-medium-latest` → `magistral-medium-2509`): Native reasoning model ($2/$5 per 1M tokens, 128k context) — the reasoning showcase in these examples.
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> Mistral folded Magistral Small into **Mistral Small 4**: the `magistral-small-latest` alias now resolves to `mistral-small-2603` (a hybrid model, $0.15/$0.60 per 1M), so these examples use the canonical `mistral-small-latest` id. Enable Small 4's reasoning mode with `reasoning_effort: high`. The standalone `magistral-small-2509` snapshot is deprecated (retires 2026-07-31).
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### Chat Models
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- **Mistral Medium 3.5** (`mistral-medium-latest` → `mistral-medium-2604`): Frontier agentic/coding multimodal model ($1.50/$7.50 per 1M, 256k context)
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- **Mistral Large 3** (`mistral-large-latest` → `mistral-large-2512`): General-purpose multimodal model ($0.50/$1.50 per 1M, 256k context)
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- **Mistral Small 4** (`mistral-small-latest` → `mistral-small-2603`): Hybrid instruct/reasoning/coding model ($0.15/$0.60 per 1M, 256k context)
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### Evaluation Models
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- **Grading**: Uses `mistral-large-latest` for LLM-as-a-judge evaluation
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- **Embeddings**: Uses `mistral-embed` for semantic similarity checks
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## Key Features Demonstrated
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- **Multi-model comparison**: Compare performance across different Mistral models
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- **Reasoning capabilities**: Step-by-step problem solving with Magistral models
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- **Cost optimization**: Balance performance vs. cost across model tiers
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- **Self-evaluation**: Use Mistral models to grade their own outputs
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- **Semantic similarity**: Mistral embeddings for content comparison
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## Running the Example
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```bash
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# Set your API key
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export MISTRAL_API_KEY=your_api_key_here
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# Run the evaluation
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promptfoo eval
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# View results in the web UI
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promptfoo view
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```
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## Configuration Highlights
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This example showcases several advanced promptfoo features:
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- **Provider overrides** for grading and embeddings
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- **Multiple assertion types** including llm-rubric and similarity
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- **Cost tracking** across different model tiers
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- **Mixed scenarios** from simple chat to complex reasoning
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The evaluation uses Mistral models end-to-end, providing a comprehensive view of their ecosystem capabilities.
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## Available Configurations
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This example includes multiple configuration files for different use cases:
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### Mathematical Reasoning
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- **`promptfooconfig.aime2024.yaml`** - Advanced mathematical competition problems (AIME2024 dataset)
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- **`promptfooconfig.reasoning.yaml`** - Step-by-step logical problem solving
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### Model Capabilities
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- **`promptfooconfig.comparison.yaml`** - Compare reasoning across all Mistral models
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- **`promptfooconfig.code-generation.yaml`** - Multi-language programming with Codestral
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- **`promptfooconfig.multimodal.yaml`** - Vision and text processing with current Mistral multimodal models
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### Advanced Features
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- **`promptfooconfig.tool-use.yaml`** - Function calling and tool integration
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- **`promptfooconfig.tool-routing.yaml`** - End-to-end QA for tool-only, mixed content+tool_calls, file-based tools, and plain chat output
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- **`promptfooconfig.json-mode.yaml`** - Structured JSON output generation
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- **`promptfooconfig.yaml`** - Main example with evaluation using Mistral models
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Run any specific configuration:
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```bash
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npx promptfoo@latest eval -c promptfooconfig.aime2024.yaml # Mathematical reasoning
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npx promptfoo@latest eval -c promptfooconfig.comparison.yaml # Model comparison
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```
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## Additional Resources
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- **[Mistral Provider Documentation](/docs/providers/mistral)** - Complete API reference and configuration options
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- **[Mistral Magistral Announcement](https://mistral.ai/news/magistral/)** - Official announcement and technical details
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