mrhavens
452c3daec1
Team 1: Critical Bug Fix Squad Fixed: - #1: LLM Client async methods use undefined self.client Changed to self._async_client in utils/llm.py - #3: Server Upload endpoint missing UploadFile/File imports Added to server.py imports - #17: LangGraph workflow error recovery - Replaced fake fallback with proper error raising - Enabled MemorySaver checkpointing for state persistence - Added traceback printing for debugging
265 lines
8.0 KiB
Python
265 lines
8.0 KiB
Python
"""LLM client for Opus Orchestrator.
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Supports MiniMax and OpenAI providers - both async and sync.
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"""
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import os
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import asyncio
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from typing import Any, Optional
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import httpx
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import requests
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class LLMClient:
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"""Simple LLM client for making API calls - supports both sync and async."""
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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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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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# Normalize model name for MiniMax
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if provider == "minimax":
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self.minimax_model = model.split("/")[-1] if "/" in model else 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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# Async client
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self._async_client = httpx.AsyncClient(timeout=120.0)
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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 (SYNC - for LangGraph compatibility)."""
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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 self._complete_minimax_sync(
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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 self._complete_openai_sync(
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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_async(
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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 (ASYNC)."""
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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_async(
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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_async(
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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 chat completion format
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payload = {
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"model": self.minimax_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._async_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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# Debug output
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if response.status_code != 200:
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print(f"MiniMax API error: {response.status_code}")
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print(f"Response: {response.text[:500]}")
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response.raise_for_status()
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data = response.json()
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# Handle different response formats
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if "choices" in data:
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return data["choices"][0]["message"]["content"]
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elif "choices" in data.get("data", {}):
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return data["data"]["choices"][0]["message"]["content"]
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else:
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# Try to find content in response
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raise Exception(f"Unexpected MiniMax response: {data}")
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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._async_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._async_client.aclose()
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# =========================================================================
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# SYNC VERSIONS (for LangGraph compatibility)
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# =========================================================================
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def _complete_minimax_sync(
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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 (sync)."""
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payload = {
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"model": self.minimax_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 = requests.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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timeout=120,
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)
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if response.status_code != 200:
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print(f"MiniMax API error: {response.status_code}")
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print(f"Response: {response.text[:500]}")
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response.raise_for_status()
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data = response.json()
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if "choices" in data:
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return data["choices"][0]["message"]["content"]
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elif "choices" in data.get("data", {}):
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return data["data"]["choices"][0]["message"]["content"]
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else:
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raise Exception(f"Unexpected MiniMax response: {data}")
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def _complete_openai_sync(
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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 (sync)."""
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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 = requests.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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timeout=120,
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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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# 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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