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simplify readme
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README.md

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@@ -337,9 +337,6 @@ Marvin includes high-level functions for the most common tasks, like summarizing
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- 🔍 **`marvin.extract`**: Extract structured information from a text
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- 🪄 **`marvin.cast`**: Transform data into a different type
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-**`marvin.generate`**: Create structured data from a description
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- 💬 **`marvin.say`**: Converse with an LLM
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- 🧠 **`marvin.plan`**: Break down complex objectives into tasks
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- 🦾 **`@marvin.fn`**: Write custom AI functions without source code
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All Marvin functions have thread management built-in, meaning they can be composed into chains of tasks that share context and history.
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@@ -364,27 +361,6 @@ Marvin 3.0 combines the DX of Marvin 2.0 with the powerful agentic engine of [Co
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- **Database Changes**: Thread/message history is now stored in SQLite. During development:
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- No database migrations are currently available; expect to reset data during updates
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### New Features
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- **Swarms**: Use `marvin.Swarm` for OpenAI-style agent swarms:
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```python
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import marvin
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swarm = marvin.Swarm(
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[
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marvin.Agent('Agent A'),
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marvin.Agent('Agent B'),
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marvin.Agent('Agent C'),
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]
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)
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swarm.run('Everybody say hi!')
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```
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- **Teams**: A `Team` lets you control how multiple agents (or even nested teams!) work together and delegate to each other. A `Swarm` is actually a type of team in which all agents are allowed to delegate to each other at any time.
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- **Marvin Functions**: Marvin's user-friendly functions have been rewritten to use the ControlFlow engine, which means they can be seamlessly integrated into your workflows. A few new functions have been added, including `summarize` and `say`.
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### Missing Features
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- Marvin does not support streaming responses from LLMs yet, which will change once this is fully supported by Pydantic AI.
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## Workflow Example
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