Initial working translator implementation

backend/llm_client.py

@@ -0,0 +1,88 @@
+"""OpenAI-compatible LLM client for multi-server support."""
+
+import os
+from pathlib import Path
+
+from openai import AsyncOpenAI
+
+from backend.models import LLMConfig
+
+
+# ── Server Config Loading ─────────────────────────────
+
+def _load_llm_configs() -> list[LLMConfig]:
+    config_path = os.getenv(
+        "LLMS_CONFIG_PATH", str(Path(__file__).parent.parent / "config" / "llms.json")
+    )
+    import json
+    with open(config_path, encoding="utf-8") as f:
+        data = json.load(f)
+    return [LLMConfig(**item) for item in data]
+
+
+_llm_configs: list[LLMConfig] = []
+_clients: dict[str, AsyncOpenAI] = {}  # alias -> client instance
+
+
+def get_llm_configs() -> list[LLMConfig]:
+    """Return all LLM configurations."""
+    return _llm_configs
+
+
+def get_client_for_alias(alias: str) -> tuple[AsyncOpenAI, LLMConfig]:
+    """Get the AsyncOpenAI client and config for a given alias.
+    
+    Creates a lazily cached client per alias.
+    """
+    if alias not in _clients:
+        cfg = None
+        for c in _llm_configs:
+            if c.alias == alias:
+                cfg = c
+                break
+        if cfg is None:
+            raise ValueError(f"Unknown LLM alias: {alias}")
+
+        client = AsyncOpenAI(
+            api_key=cfg.api_key,
+            base_url=cfg.base_url,
+            timeout=120.0,
+        )
+        _clients[alias] = client
+
+    return _clients[alias], next(c for c in _llm_configs if c.alias == alias)
+
+
+async def chat_complete(
+    alias: str,
+    system_prompt: str,
+    user_content: str,
+    temperature: float = 0.3,
+) -> str:
+    """Send a single-turn chat completion and return the assistant message."""
+    client, cfg = get_client_for_alias(alias)
+
+    response = await client.chat.completions.create(
+        model=cfg.model,
+        messages=[
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": user_content},
+        ],
+        temperature=temperature,
+    )
+
+    content = response.choices[0].message.content or ""
+    return content.strip()
+
+
+def get_context_size(alias: str) -> int | None:
+    """Get the context window size for a given alias."""
+    for c in _llm_configs:
+        if c.alias == alias:
+            return c.context_size
+    return None
+
+
+# ── Initialize on import ──────────────────────────────
+
+_llm_configs = _load_llm_configs()