Create inference.py

inference.py

@@ -0,0 +1,53 @@
+# inference.py
+
+from typing import List, Dict, Generator, Optional
+from hf_client import get_inference_client
+
+def chat_completion(
+    model_id: str,
+    messages: List[Dict[str, str]],
+    provider: Optional[str] = None,
+    max_tokens: int = 4096
+) -> str:
+    """
+    Send a chat completion request to the appropriate inference provider.
+
+    Args:
+        model_id: The model identifier to use.
+        messages: A list of OpenAI‑style {'role':'...', 'content':'...'} messages.
+        provider: Optional override for provider; uses model default if None.
+        max_tokens: Maximum tokens to generate.
+
+    Returns:
+        The assistant's response content.
+    """
+    client = get_inference_client(model_id, provider or "auto")
+    response = client.chat.completions.create(
+        model=model_id,
+        messages=messages,
+        max_tokens=max_tokens
+    )
+    return response.choices[0].message.content
+
+
+def stream_chat_completion(
+    model_id: str,
+    messages: List[Dict[str, str]],
+    provider: Optional[str] = None,
+    max_tokens: int = 4096
+) -> Generator[str, None, None]:
+    """
+    Generator for streaming chat completions.
+    Yields partial message chunks as strings.
+    """
+    client = get_inference_client(model_id, provider or "auto")
+    stream = client.chat.completions.create(
+        model=model_id,
+        messages=messages,
+        max_tokens=max_tokens,
+        stream=True
+    )
+    for chunk in stream:
+        delta = getattr(chunk.choices[0].delta, "content", None)
+        if delta:
+            yield delta