feat: add Python SDK facade and per-session isolation
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# Python SDK
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Use nanobot programmatically — load config, run the agent, get results.
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## Quick Start
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```python
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import asyncio
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from nanobot import Nanobot
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async def main():
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bot = Nanobot.from_config()
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result = await bot.run("What time is it in Tokyo?")
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print(result.content)
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asyncio.run(main())
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```
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## API
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### `Nanobot.from_config(config_path?, *, workspace?)`
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Create a `Nanobot` from a config file.
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| Param | Type | Default | Description |
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|-------|------|---------|-------------|
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| `config_path` | `str \| Path \| None` | `None` | Path to `config.json`. Defaults to `~/.nanobot/config.json`. |
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| `workspace` | `str \| Path \| None` | `None` | Override workspace directory from config. |
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Raises `FileNotFoundError` if an explicit path doesn't exist.
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### `await bot.run(message, *, session_key?, hooks?)`
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Run the agent once. Returns a `RunResult`.
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| Param | Type | Default | Description |
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|-------|------|---------|-------------|
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| `message` | `str` | *(required)* | The user message to process. |
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| `session_key` | `str` | `"sdk:default"` | Session identifier for conversation isolation. Different keys get independent history. |
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| `hooks` | `list[AgentHook] \| None` | `None` | Lifecycle hooks for this run only. |
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```python
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# Isolated sessions — each user gets independent conversation history
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await bot.run("hi", session_key="user-alice")
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await bot.run("hi", session_key="user-bob")
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```
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### `RunResult`
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| Field | Type | Description |
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|-------|------|-------------|
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| `content` | `str` | The agent's final text response. |
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| `tools_used` | `list[str]` | Tool names invoked during the run. |
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| `messages` | `list[dict]` | Raw message history (for debugging). |
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## Hooks
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Hooks let you observe or modify the agent loop without touching internals.
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Subclass `AgentHook` and override any method:
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| Method | When |
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|--------|------|
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| `before_iteration(ctx)` | Before each LLM call |
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| `on_stream(ctx, delta)` | On each streamed token |
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| `on_stream_end(ctx)` | When streaming finishes |
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| `before_execute_tools(ctx)` | Before tool execution (inspect `ctx.tool_calls`) |
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| `after_iteration(ctx, response)` | After each LLM response |
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| `finalize_content(ctx, content)` | Transform final output text |
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### Example: Audit Hook
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```python
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from nanobot.agent import AgentHook, AgentHookContext
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class AuditHook(AgentHook):
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def __init__(self):
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self.calls = []
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async def before_execute_tools(self, ctx: AgentHookContext) -> None:
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for tc in ctx.tool_calls:
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self.calls.append(tc.name)
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print(f"[audit] {tc.name}({tc.arguments})")
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hook = AuditHook()
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result = await bot.run("List files in /tmp", hooks=[hook])
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print(f"Tools used: {hook.calls}")
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```
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### Composing Hooks
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Pass multiple hooks — they run in order, errors in one don't block others:
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```python
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result = await bot.run("hi", hooks=[AuditHook(), MetricsHook()])
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```
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Under the hood this uses `CompositeHook` for fan-out with error isolation.
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### `finalize_content` Pipeline
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Unlike the async methods (fan-out), `finalize_content` is a pipeline — each hook's output feeds the next:
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```python
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class Censor(AgentHook):
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def finalize_content(self, ctx, content):
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return content.replace("secret", "***") if content else content
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```
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## Full Example
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```python
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import asyncio
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from nanobot import Nanobot
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from nanobot.agent import AgentHook, AgentHookContext
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class TimingHook(AgentHook):
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async def before_iteration(self, ctx: AgentHookContext) -> None:
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import time
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ctx.metadata["_t0"] = time.time()
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async def after_iteration(self, ctx, response) -> None:
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import time
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elapsed = time.time() - ctx.metadata.get("_t0", 0)
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print(f"[timing] iteration took {elapsed:.2f}s")
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async def main():
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bot = Nanobot.from_config(workspace="/my/project")
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result = await bot.run(
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"Explain the main function",
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hooks=[TimingHook()],
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)
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print(result.content)
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asyncio.run(main())
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```
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