Explore the examples
Use cases
| Code example | Related docs guide |
|---|---|
| Code Generation Evals: Programmatically test the quality of LLM-generated code. | Code generation evals use case guide |
| Data analysis: Analyze data and generate charts using Riza and an LLM. | Data analysis use case guide |
| Data extraction: Prompt an LLM to generate code to scrape data from HTML, and run the code safely with Riza. | Data extraction use case guide |
| Data transformation: Run LLM-generated code to transform data to another format. | Data transformation use case guide |
LLM platforms
The following examples show how to enable different LLM models to execute code using Riza.
| Code example | Related docs guide |
|---|---|
| Anthropic | Anthropic platform guide |
| Anthropic and LangChain: Similar to the Anthropic example, but uses LangChain libraries. | |
| Gemini | Gemini platform guide |
| Groq | Groq platform guide |
| OpenAI | OpenAI platform guide |
| Mistral | Mistral platform guide |
Demos
| Code example | Related guide |
|---|---|
| MCP + PydanticAI: Build an agent with PydanticAI, with 3 MCP servers: 1. the fetch MCP server (web browsing) 2. the Postgres MCP server (database querying) 3. Riza's remote MCP server (code interpreter) | video walkthrough |
Provide feedback
You're welcome to:
- Open a discussion about an idea.
- Open an issue to report a bug.
- Submit a PR with suggestions.