Update hf_client.py

hf_client.py

@@ -1,61 +1,28 @@
-import os
-from huggingface_hub import InferenceClient
-from tavily import TavilyClient
-
-# === API Keys ===
-HF_TOKEN = os.getenv('HF_TOKEN')
-GROQ_API_KEY = os.getenv('GROQ_API_KEY')
-TAVILY_API_KEY = os.getenv('TAVILY_API_KEY')
 
-if not HF_TOKEN:
-    raise RuntimeError("HF_TOKEN environment variable is not set. Please set it to your Hugging Face API token.")
 
-# === GROQ-Compatible Wrapper ===
-class GroqChatClient:
-    def __init__(self, api_key: str):
-        import openai
-        openai.api_key = api_key
-        openai.api_base = "https://api.groq.com/openai/v1"
-        self.client = openai
-        self.chat = self.Chat(openai)
 
-    class Chat:
-        def __init__(self, openai_client):
-            self.completions = self.Completions(openai_client)
+### hf_client.py
 
-        class Completions:
-            def __init__(self, openai_client):
-                self.client = openai_client
+from huggingface_hub import InferenceClient, HfApi
+from tavily import TavilyClient
 
-            def create(self, model, messages, temperature=0.7, max_tokens=1024, **kwargs):
-                return self.client.ChatCompletion.create(
-                    model=model,
-                    messages=messages,
-                    temperature=temperature,
-                    max_tokens=max_tokens,
-                    **kwargs
-                )
+# HF Inference Client
+HF_TOKEN = os.getenv('HF_TOKEN')
+if not HF_TOKEN:
+    raise RuntimeError("HF_TOKEN environment variable is not set. Please set it to your Hugging Face API token.")
 
-# === Inference Client Selector ===
-def get_inference_client(model_id: str, provider: str = "auto"):
-    """
-    Returns a unified interface:
-    - For 'moonshotai/Kimi-K2-Instruct', uses Groq with OpenAI-compatible API
-    - For others, uses Hugging Face InferenceClient
-    """
+def get_inference_client(model_id, provider="auto"):
+    """Return an InferenceClient with provider based on model_id and user selection."""
     if model_id == "moonshotai/Kimi-K2-Instruct":
-        if not GROQ_API_KEY:
-            raise RuntimeError("GROQ_API_KEY is required for Groq-hosted models.")
-        return GroqChatClient(api_key=GROQ_API_KEY)
-
+        provider = "groq"
     return InferenceClient(
-        model=model_id,
         provider=provider,
         api_key=HF_TOKEN,
         bill_to="huggingface"
     )
 
-# === Tavily Search Client ===
+# Tavily Search Client
+TAVILY_API_KEY = os.getenv('TAVILY_API_KEY')
 tavily_client = None
 if TAVILY_API_KEY:
     try: