b3608b35fa
- Enable Discord channel, respond to all messages from allowed users - Switch all agents to NVIDIA NIM (Kimi K2.5, DeepSeek V3.1) - Auto-approve all tools for non-interactive Docker deployment - Fix tool call arguments serialization (dict → JSON string) - Fix Dockerfile to copy source before uv sync Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
110 lines
3.9 KiB
Python
110 lines
3.9 KiB
Python
"""Single agent engine — one LLM loop per agent."""
|
|
|
|
from __future__ import annotations
|
|
|
|
from typing import Any
|
|
|
|
from loguru import logger
|
|
|
|
from xtrm_agent.config import AgentFileConfig
|
|
import json
|
|
|
|
from xtrm_agent.llm.provider import LLMProvider, LLMResponse
|
|
from xtrm_agent.tools.approval import ApprovalEngine
|
|
from xtrm_agent.tools.registry import ToolRegistry
|
|
|
|
|
|
class Engine:
|
|
"""Runs one agent's LLM loop: messages → LLM → tool calls → loop → response."""
|
|
|
|
def __init__(
|
|
self,
|
|
agent_config: AgentFileConfig,
|
|
provider: LLMProvider,
|
|
tools: ToolRegistry,
|
|
approval: ApprovalEngine,
|
|
) -> None:
|
|
self.config = agent_config
|
|
self.provider = provider
|
|
self.tools = tools
|
|
self.approval = approval
|
|
|
|
async def run(self, user_message: str) -> str:
|
|
"""Process a single user message through the agent loop."""
|
|
messages = self._build_initial_messages(user_message)
|
|
return await self._agent_loop(messages)
|
|
|
|
async def run_delegation(self, task: str) -> str:
|
|
"""Process a delegation task (no system prompt changes)."""
|
|
messages = self._build_initial_messages(task)
|
|
return await self._agent_loop(messages)
|
|
|
|
def _build_initial_messages(self, user_message: str) -> list[dict[str, Any]]:
|
|
messages: list[dict[str, Any]] = []
|
|
if self.config.instructions:
|
|
messages.append({"role": "system", "content": self.config.instructions})
|
|
messages.append({"role": "user", "content": user_message})
|
|
return messages
|
|
|
|
async def _agent_loop(self, messages: list[dict[str, Any]]) -> str:
|
|
"""Core agent iteration loop."""
|
|
for iteration in range(self.config.max_iterations):
|
|
model = self.config.model or self.provider.get_default_model()
|
|
tool_defs = self.tools.get_definitions() if self.tools.names() else None
|
|
|
|
response = await self.provider.complete(
|
|
messages=messages,
|
|
tools=tool_defs,
|
|
model=model,
|
|
max_tokens=8192,
|
|
temperature=self.config.temperature,
|
|
)
|
|
|
|
if not response.has_tool_calls:
|
|
return response.content or "(no response)"
|
|
|
|
# Add assistant message with tool calls
|
|
messages.append(self._assistant_message(response))
|
|
|
|
# Execute each tool call
|
|
for tc in response.tool_calls:
|
|
result = await self._execute_tool(tc.name, tc.arguments)
|
|
messages.append(
|
|
{
|
|
"role": "tool",
|
|
"tool_call_id": tc.id,
|
|
"name": tc.name,
|
|
"content": result,
|
|
}
|
|
)
|
|
|
|
logger.debug(
|
|
f"[{self.config.name}] Iteration {iteration + 1}: "
|
|
f"{len(response.tool_calls)} tool call(s)"
|
|
)
|
|
|
|
return "(max iterations reached)"
|
|
|
|
async def _execute_tool(self, name: str, arguments: dict[str, Any]) -> str:
|
|
"""Execute a tool with approval check."""
|
|
approved = await self.approval.check(name, arguments)
|
|
if not approved:
|
|
return f"Tool '{name}' was denied by approval policy."
|
|
return await self.tools.execute(name, arguments)
|
|
|
|
def _assistant_message(self, response: LLMResponse) -> dict[str, Any]:
|
|
"""Build assistant message dict from LLMResponse."""
|
|
msg: dict[str, Any] = {"role": "assistant"}
|
|
if response.content:
|
|
msg["content"] = response.content
|
|
if response.tool_calls:
|
|
msg["tool_calls"] = [
|
|
{
|
|
"id": tc.id,
|
|
"type": "function",
|
|
"function": {"name": tc.name, "arguments": json.dumps(tc.arguments)},
|
|
}
|
|
for tc in response.tool_calls
|
|
]
|
|
return msg
|