Upload serve_ministral.py with huggingface_hub

serve_ministral.py

@@ -75,6 +75,11 @@ class ChatRequest(BaseModel):
     max_tokens: Optional[int] = 2048
     temperature: Optional[float] = 0.7
     top_p: Optional[float] = 0.9
+    top_k: Optional[int] = None
+    min_p: Optional[float] = None  # "bottom_p" - minimum probability threshold
+    typical_p: Optional[float] = None  # Typical decoding
+    repetition_penalty: Optional[float] = None  # 1.0 = no penalty, >1.0 = penalize repeats
+    no_repeat_ngram_size: Optional[int] = None  # Prevent n-gram repetition
     stream: Optional[bool] = False
 
 @app.on_event("startup")
@@ -145,6 +150,17 @@ async def chat_completions(request: ChatRequest):
                     "pad_token_id": processor.tokenizer.eos_token_id,
                     "streamer": streamer,
                 }
+                # Add optional parameters if provided
+                if request.top_k is not None:
+                    generation_kwargs["top_k"] = request.top_k
+                if request.min_p is not None:
+                    generation_kwargs["min_p"] = request.min_p
+                if request.typical_p is not None:
+                    generation_kwargs["typical_p"] = request.typical_p
+                if request.repetition_penalty is not None:
+                    generation_kwargs["repetition_penalty"] = request.repetition_penalty
+                if request.no_repeat_ngram_size is not None:
+                    generation_kwargs["no_repeat_ngram_size"] = request.no_repeat_ngram_size
 
                 thread = Thread(target=model.generate, kwargs=generation_kwargs)
                 thread.start()
@@ -197,15 +213,28 @@ async def chat_completions(request: ChatRequest):
             )
         else:
             # Non-streaming response
+            generation_kwargs = {
+                **inputs,
+                "max_new_tokens": request.max_tokens,
+                "temperature": request.temperature if request.temperature and request.temperature > 0 else 1.0,
+                "top_p": request.top_p if request.top_p else 0.9,
+                "do_sample": request.temperature is not None and request.temperature > 0,
+                "pad_token_id": processor.tokenizer.eos_token_id,
+            }
+            # Add optional parameters if provided
+            if request.top_k is not None:
+                generation_kwargs["top_k"] = request.top_k
+            if request.min_p is not None:
+                generation_kwargs["min_p"] = request.min_p
+            if request.typical_p is not None:
+                generation_kwargs["typical_p"] = request.typical_p
+            if request.repetition_penalty is not None:
+                generation_kwargs["repetition_penalty"] = request.repetition_penalty
+            if request.no_repeat_ngram_size is not None:
+                generation_kwargs["no_repeat_ngram_size"] = request.no_repeat_ngram_size
+
             with torch.no_grad():
-                outputs = model.generate(
-                    **inputs,
-                    max_new_tokens=request.max_tokens,
-                    temperature=request.temperature if request.temperature and request.temperature > 0 else 1.0,
-                    top_p=request.top_p if request.top_p else 0.9,
-                    do_sample=request.temperature is not None and request.temperature > 0,
-                    pad_token_id=processor.tokenizer.eos_token_id,
-                )
+                outputs = model.generate(**generation_kwargs)
 
             new_tokens = outputs[0][input_len:]
             response_text = processor.tokenizer.decode(