Update models.py

models.py

@@ -1,4 +1,5 @@
 # models.py
+
 from dataclasses import dataclass
 from typing import List, Optional
 
@@ -8,148 +9,105 @@ class ModelInfo:
     Represents metadata for an inference model.
 
     Attributes:
-        name: Human-readable name of the model.
-        id: Unique model identifier (HF/externally routed).
+        name: Human‑readable name of the model.
+        id: Unique model identifier (HF or routed provider).
         description: Short description of the model's capabilities.
-        default_provider: Preferred inference provider ("auto", "groq", "openai", "gemini", "fireworks").
+        default_provider: Preferred inference provider
+                          ("auto", "groq", "openai", "gemini", "fireworks").
     """
     name: str
     id: str
     description: str
     default_provider: str = "auto"
 
+
 # Registry of supported models
 AVAILABLE_MODELS: List[ModelInfo] = [
     ModelInfo(
-        name="Moonshot Kimi-K2",
-        id="moonshotai/Kimi-K2-Instruct",
-        description="Moonshot AI Kimi-K2-Instruct model for code generation and general tasks",
+        name="Moonshot Kimi‑K2",
+        id="moonshotai/Kimi‑K2‑Instruct",
+        description="Moonshot AI Kimi‑K2‑Instruct model for code generation and general tasks",
         default_provider="groq"
     ),
     ModelInfo(
         name="DeepSeek V3",
-        id="deepseek-ai/DeepSeek-V3-0324",
-        description="DeepSeek V3 model for code generation",
+        id="deepseek‑ai/DeepSeek‑V3‑0324",
+        description="DeepSeek V3 model for code generation"
     ),
     ModelInfo(
         name="DeepSeek R1",
-        id="deepseek-ai/DeepSeek-R1-0528",
-        description="DeepSeek R1 model for code generation",
+        id="deepseek‑ai/DeepSeek‑R1‑0528",
+        description="DeepSeek R1 model for code generation"
     ),
     ModelInfo(
-        name="ERNIE-4.5-VL",
-        id="baidu/ERNIE-4.5-VL-424B-A47B-Base-PT",
-        description="ERNIE-4.5-VL model for multimodal code generation with image support",
+        name="ERNIE‑4.5‑VL",
+        id="baidu/ERNIE‑4.5‑VL‑424B‑A47B‑Base‑PT",
+        description="ERNIE‑4.5‑VL model for multimodal code generation with image support"
     ),
     ModelInfo(
         name="MiniMax M1",
-        id="MiniMaxAI/MiniMax-M1-80k",
-        description="MiniMax M1 model for code generation and general tasks",
+        id="MiniMaxAI/MiniMax‑M1‑80k",
+        description="MiniMax M1 model for code generation and general tasks"
+    ),
+    ModelInfo(
+        name="Qwen3‑235B‑A22B",
+        id="Qwen/Qwen3‑235B‑A22B",
+        description="Qwen3‑235B‑A22B model for code generation and general tasks"
+    ),
+    ModelInfo(
+        name="Qwen3‑235B‑A22B‑Instruct‑2507",
+        id="Qwen/Qwen3‑235B‑A22B‑Instruct‑2507",
+        description="Qwen3‑235B‑A22B‑Instruct‑2507 model for code generation and general tasks"
     ),
     ModelInfo(
-        name="Qwen3-235B-A22B",
-        id="Qwen/Qwen3-235B-A22B",
-        description="Qwen3-235B-A22B model for code generation and general tasks",
+        name="Qwen3‑Coder‑480B‑A35B",
+        id="Qwen/Qwen3‑Coder‑480B‑A35B‑Instruct",
+        description="Qwen3‑Coder‑480B‑A35B‑Instruct model for advanced code generation"
     ),
     ModelInfo(
-        name="SmolLM3-3B",
-        id="HuggingFaceTB/SmolLM3-3B",
-        description="SmolLM3-3B model for code generation and general tasks",
+        name="Qwen3‑32B",
+        id="Qwen/Qwen3‑32B",
+        description="Qwen3‑32B model for large‑scale code and general tasks"
     ),
     ModelInfo(
-        name="GLM-4.1V-9B-Thinking",
-        id="THUDM/GLM-4.1V-9B-Thinking",
-        description="GLM-4.1V-9B-Thinking model for multimodal code generation with image support",
+        name="SmolLM3‑3B",
+        id="HuggingFaceTB/SmolLM3‑3B",
+        description="SmolLM3‑3B model for code generation and general tasks"
     ),
     ModelInfo(
-        name="OpenAI GPT-4",
-        id="openai/gpt-4",
-        description="OpenAI GPT-4 model via HF Inference Providers",
+        name="GLM‑4.1V‑9B‑Thinking",
+        id="THUDM/GLM‑4.1V‑9B‑Thinking",
+        description="GLM‑4.1V‑9B‑Thinking model for multimodal code generation with image support"
+    ),
+    ModelInfo(
+        name="OpenAI GPT‑4",
+        id="openai/gpt‑4",
+        description="OpenAI GPT‑4 via HF Inference Providers",
         default_provider="openai"
     ),
     ModelInfo(
         name="Gemini Pro",
         id="gemini/pro",
-        description="Google Gemini Pro model via HF Inference Providers",
+        description="Google Gemini Pro via HF Inference Providers",
         default_provider="gemini"
     ),
     ModelInfo(
         name="Fireworks AI",
-        id="fireworks-ai/fireworks-v1",
-        description="Fireworks AI model via HF Inference Providers",
+        id="fireworks‑ai/fireworks‑v1",
+        description="Fireworks AI via HF Inference Providers",
         default_provider="fireworks"
     ),
 ]
 
-
 def find_model(identifier: str) -> Optional[ModelInfo]:
     """
-    Lookup a model by its human name or identifier.
+    Lookup a model by its human name (case‑insensitive) or identifier.
 
-    Args:
-        identifier: ModelInfo.name (case-insensitive) or ModelInfo.id
     Returns:
         The matching ModelInfo or None if not found.
     """
     identifier_lower = identifier.lower()
-    for model in AVAILABLE_MODELS:
-        if model.id == identifier or model.name.lower() == identifier_lower:
-            return model
+    for m in AVAILABLE_MODELS:
+        if m.id == identifier or m.name.lower() == identifier_lower:
+            return m
     return None
-
-
-# inference.py
-from typing import List, Dict
-from hf_client import get_inference_client
-
-
-def chat_completion(
-    model_id: str,
-    messages: List[Dict[str, str]],
-    provider: 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.
-    """
-    # Initialize client (provider resolution inside)
-    client = get_inference_client(model_id, provider or "auto")
-    response = client.chat.completions.create(
-        model=model_id,
-        messages=messages,
-        max_tokens=max_tokens
-    )
-    # Extract and return first choice content
-    return response.choices[0].message.content
-
-
-def stream_chat_completion(
-    model_id: str,
-    messages: List[Dict[str, str]],
-    provider: str = None,
-    max_tokens: int = 4096
-):
-    """
-    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