> ## Documentation Index > Fetch the complete documentation index at: https://docs.mellea.ai/llms.txt > Use this file to discover all available pages before exploring further. # Examples > Complete working programs demonstrating Mellea patterns in production-like scenarios. Each example in this section is a complete, runnable Python program. The pages walk through the code section by section so you can see how the pieces fit together. Copy any example as a starting point for your own project. ## Examples in this section | Example | What it shows | | ------------------------------------------------------- | ------------------------------------------------------------------------------------ | | [Data extraction pipeline](./data-extraction-pipeline) | Use `@generative` with a typed return to pull structured data from unstructured text | | [Legacy code integration](./legacy-code-integration) | Apply `@mify` to existing Python classes so the model can act on them | | [Resilient RAG with fallback](./resilient-rag-fallback) | Build a FAISS retrieval pipeline with an LLM relevance filter before generation | | [Traced generation loop](./traced-generation-loop) | Enable OpenTelemetry application and backend traces with two environment variables | ## All example categories The repository contains many more runnable examples than the four documented above. Every category has its own `README.md` and one or more `.py` files ready to run. ### Core concepts | Category | What it shows | | --------------------------- | --------------------------------------------------------------------------------------------------------------------------- | | `instruct_validate_repair/` | The IVR loop end-to-end: basic generation, adding requirements, automatic repair on failure, custom validators | | `generative_stubs/` | `@generative` functions with typed returns, pipeline composition, `ChatContext` persona injection, pre/postcondition checks | | `context/` | Context inspection, sampling with context trees, parallel context branches | | `sessions/` | Custom session types and backend selection | | `async/` | How to utilize basic async capabilities | | `streaming/` | `stream_with_chunking()` with per-chunk validation, typed event vocabulary, early-exit on fail | ### Data and documents | Category | What it shows | | ------------------------- | ----------------------------------------------------------------------------------------------------- | | `information_extraction/` | Named entity recognition and type-safe structured extraction with Pydantic | | `mobject/` | Table queries and transformations using `MObject` structured data types | | `mify/` | `@mify` on existing classes — custom string representations, field filtering, `funcs_include` | | `rag/` | FAISS vector search, `@generative bool` relevance filter, `grounding_context` for grounded generation | ### Agents and tools | Category | What it shows | | ------------------ | -------------------------------------------------------------------------------------------------------------------- | | `agents/` | ReACT reasoning-and-acting loop, multi-turn tool workflows | | `tools/` | `@tool` definition, code interpreter integration, tool argument validation, safe `eval` patterns | | `mini_researcher/` | Complete research assistant: multi-model architecture, document retrieval, safety checks, custom validation pipeline | ### Extensibility | Category | What it shows | | ---------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `plugins/` | Plugin system end-to-end: function hooks, class-based plugins, payload modification, scoped and session-scoped plugins, `PluginSet` composition, execution modes, tool hooks, and testing patterns | ### Safety and validation | Category | What it shows | | --------- | --------------------------------------------------------------------------------------------------------------- | | `safety/` | `GuardianCheck` for harm, jailbreak, profanity, social bias, violence, and groundedness; shared backend pattern | ### Integration and deployment | Category | What it shows | | ------------------ | ---------------------------------------------------------------------------------- | | `m_serve/` | Deploying Mellea programs as REST APIs with production deployment patterns | | `m_decompose/` | Decomposing complex prompts into sub-tasks via the CLI and Python API | | `library_interop/` | LangChain message conversion, OpenAI format compatibility, cross-library workflows | | `mcp/` | MCP tool creation, Claude Desktop integration, Langflow integration | | `bedrock/` | Amazon Bedrock backend configuration and usage | ### Performance and advanced sampling | Category | What it shows | | ----------------- | --------------------------------------------------------------------------------------------------------------------- | | `aLora/` | Training aLoRA adapters for fast constraint checking; performance optimisation | | `intrinsics/` | Answer relevance, hallucination detection, citation validation, context relevance — specialised adapter-backed checks | | `granite-switch/` | Running intrinsics via OpenAI backend with Granite Switch embedded adapters | | `sofai/` | Two-tier sampling: fast-model iteration with escalation to a slow model; cost optimisation | ### Multimodal | Category | What it shows | | -------------------- | ---------------------------------------------------------------------------------- | | `image_text_models/` | Vision-language models, `ImageBlock`, multimodal prompting, backend support matrix | ### Observability | Category | What it shows | | ------------ | ----------------------------------------------------------------------- | | `telemetry/` | OpenTelemetry application and backend traces; span export configuration | ### Experimental | Category | What it shows | | -------- | ----------------------------------------------------------------------------------- | | `melp/` | ⚠️ Experimental lazy evaluation — thunks, deferred execution, advanced control flow | ### Getting started and tutorials | Category | What it shows | | ---------------- | ----------------------------------------------------------------------------------------------------------------------------- | | `hello_world.py` | Minimal single-file starting point | | `tutorial/` | Python script versions of the tutorials: email generation, IVR, generative stubs, contexts, MObjects, model options, and more | | `notebooks/` | Jupyter notebook versions of the same tutorials for interactive, cell-by-cell exploration | *** ## Running the examples All examples are in the `docs/examples/` directory of the repository. Unless otherwise noted, run them with: ```bash theme={null} python docs/examples//.py ``` Some examples declare inline script dependencies using the [PEP 723](https://peps.python.org/pep-0723/) `/// script` block and can be run with `uv run` instead: ```bash theme={null} uv run docs/examples//.py ``` **Default backend:** `start_session()` with no arguments connects to a local [Ollama](https://ollama.ai) instance running **IBM Granite 4 Micro** (`granite4.1:3b`). Make sure Ollama is running before you execute any example.