mrhavens
e151cee69f
- Add .env to .gitignore (API keys stay local) - Add LLM client with MiniMax and OpenAI support - Update config to load from environment variables - Wire up Architect agent to actually call the LLM - Add MiniMax API key to local .env file
160 lines
4.5 KiB
Python
160 lines
4.5 KiB
Python
"""LLM client for Opus Orchestrator.
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Supports MiniMax and OpenAI providers.
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"""
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import os
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from typing import Any, Optional
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import httpx
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class LLMClient:
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"""Simple LLM client for making API calls."""
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def __init__(
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self,
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api_key: Optional[str] = None,
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provider: str = "minimax",
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model: str = "MiniMax/MiniMax-M2.1",
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base_url: Optional[str] = None,
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):
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"""Initialize LLM client.
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Args:
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api_key: API key for the provider
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provider: Provider name (minimax, openai, anthropic)
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model: Model identifier
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base_url: Optional custom base URL
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"""
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self.api_key = api_key or os.environ.get("MINIMAX_API_KEY") or os.environ.get("OPENAI_API_KEY")
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self.provider = provider
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self.model = model
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# Set base URL based on provider
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if base_url:
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self.base_url = base_url
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elif provider == "minimax":
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self.base_url = "https://api.minimax.chat/v1"
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elif provider == "openai":
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self.base_url = "https://api.openai.com/v1"
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else:
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self.base_url = "https://api.openai.com/v1"
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self.client = httpx.AsyncClient(timeout=120.0)
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async def complete(
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self,
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system_prompt: str,
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user_prompt: str,
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temperature: float = 0.7,
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max_tokens: Optional[int] = None,
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) -> str:
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"""Make a completion request.
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Args:
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system_prompt: System prompt
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user_prompt: User prompt
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temperature: Sampling temperature
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max_tokens: Maximum tokens to generate
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Returns:
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Generated text
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"""
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headers = {
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"Authorization": f"Bearer {self.api_key}",
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"Content-Type": "application/json",
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}
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if self.provider == "minimax":
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return await self._complete_minimax(
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system_prompt, user_prompt, temperature, max_tokens, headers
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)
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elif self.provider == "openai":
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return await self._complete_openai(
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system_prompt, user_prompt, temperature, max_tokens, headers
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)
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else:
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raise ValueError(f"Unsupported provider: {self.provider}")
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async def _complete_minimax(
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self,
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system_prompt: str,
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user_prompt: str,
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temperature: float,
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max_tokens: Optional[int],
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headers: dict,
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) -> str:
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"""Call MiniMax API."""
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# MiniMax uses chat/completions format
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payload = {
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"model": self.model,
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"messages": [
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": user_prompt},
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],
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"temperature": temperature,
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}
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if max_tokens:
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payload["max_tokens"] = max_tokens
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response = await self.client.post(
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f"{self.base_url}/text/chatcompletion_v2",
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headers=headers,
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json=payload,
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)
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response.raise_for_status()
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data = response.json()
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return data["choices"][0]["message"]["content"]
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async def _complete_openai(
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self,
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system_prompt: str,
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user_prompt: str,
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temperature: float,
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max_tokens: Optional[int],
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headers: dict,
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) -> str:
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"""Call OpenAI API."""
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payload = {
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"model": self.model,
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"messages": [
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": user_prompt},
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],
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"temperature": temperature,
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}
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if max_tokens:
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payload["max_tokens"] = max_tokens
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response = await self.client.post(
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f"{self.base_url}/chat/completions",
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headers=headers,
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json=payload,
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)
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response.raise_for_status()
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data = response.json()
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return data["choices"][0]["message"]["content"]
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async def close(self):
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"""Close the HTTP client."""
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await self.client.aclose()
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# Convenience function
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def get_llm_client(config: Optional[Any] = None) -> LLMClient:
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"""Get an LLM client from config."""
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from opus_orchestrator.config import get_config
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cfg = config or get_config()
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return LLMClient(
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api_key=cfg.agent.api_key,
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provider=cfg.agent.provider,
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model=cfg.agent.model,
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)
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