| 1 | """High-level programmatic interface to nanobot.""" |
| 2 | |
| 3 | from __future__ import annotations |
| 4 | |
| 5 | from dataclasses import dataclass |
| 6 | from pathlib import Path |
| 7 | from typing import Any |
| 8 | |
| 9 | from nanobot.agent.hook import AgentHook |
| 10 | from nanobot.agent.loop import AgentLoop |
| 11 | from nanobot.bus.queue import MessageBus |
| 12 | |
| 13 | |
| 14 | @dataclass(slots=True) |
| 15 | class RunResult: |
| 16 | """Result of a single agent run.""" |
| 17 | |
| 18 | content: str |
| 19 | tools_used: list[str] |
| 20 | messages: list[dict[str, Any]] |
| 21 | |
| 22 | |
| 23 | class Nanobot: |
| 24 | """Programmatic facade for running the nanobot agent. |
| 25 | |
| 26 | Usage:: |
| 27 | |
| 28 | bot = Nanobot.from_config() |
| 29 | result = await bot.run("Summarize this repo", hooks=[MyHook()]) |
| 30 | print(result.content) |
| 31 | """ |
| 32 | |
| 33 | def __init__(self, loop: AgentLoop) -> None: |
| 34 | self._loop = loop |
| 35 | |
| 36 | @classmethod |
| 37 | def from_config( |
| 38 | cls, |
| 39 | config_path: str | Path | None = None, |
| 40 | *, |
| 41 | workspace: str | Path | None = None, |
| 42 | ) -> Nanobot: |
| 43 | """Create a Nanobot instance from a config file. |
| 44 | |
| 45 | Args: |
| 46 | config_path: Path to ``config.json``. Defaults to |
| 47 | ``~/.nanobot/config.json``. |
| 48 | workspace: Override the workspace directory from config. |
| 49 | """ |
| 50 | from nanobot.config.loader import load_config, resolve_config_env_vars |
| 51 | from nanobot.config.schema import Config |
| 52 | |
| 53 | resolved: Path | None = None |
| 54 | if config_path is not None: |
| 55 | resolved = Path(config_path).expanduser().resolve() |
| 56 | if not resolved.exists(): |
| 57 | raise FileNotFoundError(f"Config not found: {resolved}") |
| 58 | |
| 59 | config: Config = resolve_config_env_vars(load_config(resolved)) |
| 60 | if workspace is not None: |
| 61 | config.agents.defaults.workspace = str( |
| 62 | Path(workspace).expanduser().resolve() |
| 63 | ) |
| 64 | |
| 65 | provider = _make_provider(config) |
| 66 | bus = MessageBus() |
| 67 | defaults = config.agents.defaults |
| 68 | |
| 69 | loop = AgentLoop( |
| 70 | bus=bus, |
| 71 | provider=provider, |
| 72 | workspace=config.workspace_path, |
| 73 | model=defaults.model, |
| 74 | max_iterations=defaults.max_tool_iterations, |
| 75 | context_window_tokens=defaults.context_window_tokens, |
| 76 | context_block_limit=defaults.context_block_limit, |
| 77 | max_tool_result_chars=defaults.max_tool_result_chars, |
| 78 | provider_retry_mode=defaults.provider_retry_mode, |
| 79 | web_config=config.tools.web, |
| 80 | exec_config=config.tools.exec, |
| 81 | restrict_to_workspace=config.tools.restrict_to_workspace, |
| 82 | mcp_servers=config.tools.mcp_servers, |
| 83 | timezone=defaults.timezone, |
| 84 | unified_session=defaults.unified_session, |
| 85 | disabled_skills=defaults.disabled_skills, |
| 86 | session_ttl_minutes=defaults.session_ttl_minutes, |
| 87 | tools_config=config.tools, |
| 88 | config=config, |
| 89 | prompt_stacker_enabled=config.prompt_stacker.enabled, |
| 90 | prompt_stacker_max_traces=config.prompt_stacker.max_traces, |
| 91 | ) |
| 92 | return cls(loop) |
| 93 | |
| 94 | async def run( |
| 95 | self, |
| 96 | message: str, |
| 97 | *, |
| 98 | session_key: str = "sdk:default", |
| 99 | hooks: list[AgentHook] | None = None, |
| 100 | ) -> RunResult: |
| 101 | """Run the agent once and return the result. |
| 102 | |
| 103 | Args: |
| 104 | message: The user message to process. |
| 105 | session_key: Session identifier for conversation isolation. |
| 106 | Different keys get independent history. |
| 107 | hooks: Optional lifecycle hooks for this run. |
| 108 | """ |
| 109 | prev = self._loop._extra_hooks |
| 110 | if hooks is not None: |
| 111 | self._loop._extra_hooks = list(hooks) |
| 112 | try: |
| 113 | response = await self._loop.process_direct( |
| 114 | message, session_key=session_key, |
| 115 | ) |
| 116 | finally: |
| 117 | self._loop._extra_hooks = prev |
| 118 | |
| 119 | content = (response.content if response else None) or "" |
| 120 | return RunResult(content=content, tools_used=[], messages=[]) |
| 121 | |
| 122 | |
| 123 | def _make_provider(config: Any) -> Any: |
| 124 | """Create the LLM provider from config (extracted from CLI).""" |
| 125 | from nanobot.providers.base import GenerationSettings |
| 126 | from nanobot.providers.registry import find_by_name |
| 127 | |
| 128 | model = config.agents.defaults.model |
| 129 | provider_name = config.get_provider_name(model) |
| 130 | p = config.get_provider(model) |
| 131 | spec = find_by_name(provider_name) if provider_name else None |
| 132 | backend = spec.backend if spec else "openai_compat" |
| 133 | |
| 134 | if backend == "azure_openai": |
| 135 | if not p or not p.api_key or not p.api_base: |
| 136 | raise ValueError("Azure OpenAI requires api_key and api_base in config.") |
| 137 | elif backend == "openai_compat" and not model.startswith("bedrock/"): |
| 138 | needs_key = not (p and p.api_key) |
| 139 | exempt = spec and (spec.is_oauth or spec.is_local or spec.is_direct) |
| 140 | if needs_key and not exempt: |
| 141 | raise ValueError(f"No API key configured for provider '{provider_name}'.") |
| 142 | |
| 143 | if backend == "openai_codex": |
| 144 | from nanobot.providers.openai_codex_provider import OpenAICodexProvider |
| 145 | |
| 146 | provider = OpenAICodexProvider(default_model=model) |
| 147 | elif backend == "github_copilot": |
| 148 | from nanobot.providers.github_copilot_provider import GitHubCopilotProvider |
| 149 | |
| 150 | provider = GitHubCopilotProvider(default_model=model) |
| 151 | elif backend == "azure_openai": |
| 152 | from nanobot.providers.azure_openai_provider import AzureOpenAIProvider |
| 153 | |
| 154 | provider = AzureOpenAIProvider( |
| 155 | api_key=p.api_key, api_base=p.api_base, default_model=model |
| 156 | ) |
| 157 | elif backend == "anthropic": |
| 158 | from nanobot.providers.anthropic_provider import AnthropicProvider |
| 159 | |
| 160 | provider = AnthropicProvider( |
| 161 | api_key=p.api_key if p else None, |
| 162 | api_base=config.get_api_base(model), |
| 163 | default_model=model, |
| 164 | extra_headers=p.extra_headers if p else None, |
| 165 | ) |
| 166 | else: |
| 167 | from nanobot.providers.openai_compat_provider import OpenAICompatProvider |
| 168 | |
| 169 | provider = OpenAICompatProvider( |
| 170 | api_key=p.api_key if p else None, |
| 171 | api_base=config.get_api_base(model), |
| 172 | default_model=model, |
| 173 | extra_headers=p.extra_headers if p else None, |
| 174 | spec=spec, |
| 175 | ) |
| 176 | |
| 177 | defaults = config.agents.defaults |
| 178 | provider.generation = GenerationSettings( |
| 179 | temperature=defaults.temperature, |
| 180 | max_tokens=defaults.max_tokens, |
| 181 | reasoning_effort=defaults.reasoning_effort, |
| 182 | ) |
| 183 | return provider |
| 184 |