Final cleanup: Merge LLM, add Dockerfile

- Merge llm.py + llm_sync.py into single unified client - Remove llm_sync.py (now just llm.py with both sync/async) - Add requests to dependencies - Add Dockerfile for containerized deployment - Add .dockerignore All issues resolved!
2026-03-13 04:47:01 +00:00
parent 8e92e99205
commit 6766e93c3d
5 changed files with 93 additions and 143 deletions
@@ -1,142 +0,0 @@
-"""LLM client for Opus Orchestrator - Synchronous version.
-
-Uses synchronous httpx to avoid event loop issues with LangGraph.
-"""
-
-import os
-from typing import Any, Optional
-
-import requests
-
-
-class LLMClient:
-    """Synchronous LLM client for making API calls."""
-
-    def __init__(
-        self,
-        api_key: Optional[str] = None,
-        provider: str = "openai",
-        model: str = "gpt-4o",
-        base_url: Optional[str] = None,
-    ):
-        """Initialize LLM client."""
-        self.api_key = api_key or os.environ.get("MINIMAX_API_KEY") or os.environ.get("OPENAI_API_KEY")
-        self.provider = provider
-        self.model = model
-        
-        if base_url:
-            self.base_url = base_url
-        elif provider == "minimax":
-            self.base_url = "https://api.minimax.chat/v1"
-        elif provider == "openai":
-            self.base_url = "https://api.openai.com/v1"
-        else:
-            self.base_url = "https://api.openai.com/v1"
-
-    def complete(
-        self,
-        system_prompt: str,
-        user_prompt: str,
-        temperature: float = 0.7,
-        max_tokens: Optional[int] = None,
-    ) -> str:
-        """Make a completion request (synchronous)."""
-        headers = {
-            "Authorization": f"Bearer {self.api_key}",
-            "Content-Type": "application/json",
-        }
-        
-        if self.provider == "minimax":
-            return self._complete_minimax(
-                system_prompt, user_prompt, temperature, max_tokens, headers
-            )
-        elif self.provider == "openai":
-            return self._complete_openai(
-                system_prompt, user_prompt, temperature, max_tokens, headers
-            )
-        else:
-            raise ValueError(f"Unsupported provider: {self.provider}")
-
-    def _complete_minimax(
-        self,
-        system_prompt: str,
-        user_prompt: str,
-        temperature: float,
-        max_tokens: Optional[int],
-        headers: dict,
-    ) -> str:
-        """Call MiniMax API (synchronous)."""
-        minimax_model = self.model.split("/")[-1] if "/" in self.model else self.model
-        
-        payload = {
-            "model": minimax_model,
-            "messages": [
-                {"role": "system", "content": system_prompt},
-                {"role": "user", "content": user_prompt},
-            ],
-            "temperature": temperature,
-        }
-        
-        if max_tokens:
-            payload["max_tokens"] = max_tokens
-        
-        response = requests.post(
-            f"{self.base_url}/text/chatcompletion_v2",
-            headers=headers,
-            json=payload,
-            timeout=120,
-        )
-        response.raise_for_status()
-        
-        data = response.json()
-        
-        if "choices" in data:
-            return data["choices"][0]["message"]["content"]
-        else:
-            raise Exception(f"Unexpected MiniMax response: {data}")
-
-    def _complete_openai(
-        self,
-        system_prompt: str,
-        user_prompt: str,
-        temperature: float,
-        max_tokens: Optional[int],
-        headers: dict,
-    ) -> str:
-        """Call OpenAI API (synchronous)."""
-        payload = {
-            "model": self.model,
-            "messages": [
-                {"role": "system", "content": system_prompt},
-                {"role": "user", "content": user_prompt},
-            ],
-            "temperature": temperature,
-        }
-        
-        if max_tokens:
-            payload["max_tokens"] = max_tokens
-        
-        response = requests.post(
-            f"{self.base_url}/chat/completions",
-            headers=headers,
-            json=payload,
-            timeout=120,
-        )
-        response.raise_for_status()
-        
-        data = response.json()
-        return data["choices"][0]["message"]["content"]
-
-
-# Convenience function
-def get_llm_client(config: Optional[Any] = None) -> LLMClient:
-    """Get an LLM client from config."""
-    from opus_orchestrator.config import get_config
-    
-    cfg = config or get_config()
-    
-    return LLMClient(
-        api_key=cfg.agent.api_key,
-        provider=cfg.agent.provider,
-        model=cfg.agent.model,
-    )