From 909955767b1fe051202f3a64d13d92cb4e160d28 Mon Sep 17 00:00:00 2001
From: Roland Tannous <rolandtannous@gravityq.ai>
Date: Mon, 16 Feb 2026 06:33:17 +0000
Subject: [PATCH] feat: add min_p sampling parameter to /chat/completions
 generation pipeline

---
 studio/backend/core/inference/inference.py | 12 +++++++++---
 studio/backend/models/inference.py         |  1 +
 studio/backend/routes/inference.py         |  1 +
 3 files changed, 11 insertions(+), 3 deletions(-)

diff --git a/studio/backend/core/inference/inference.py b/studio/backend/core/inference/inference.py
index 6be7e63306..38394f6f33 100644
--- a/studio/backend/core/inference/inference.py
+++ b/studio/backend/core/inference/inference.py
@@ -515,6 +515,7 @@ class InferenceBackend:
                           temperature: float = 0.7,
                           top_p: float = 0.9,
                           top_k: int = 40,
+                          min_p: float = 0.0,
                           max_new_tokens: int = 256,
                           repetition_penalty: float = 1.1,
                           cancel_event=None) -> Generator[str, None, None]:
@@ -531,6 +532,7 @@ class InferenceBackend:
                 temperature=temperature,
                 top_p=top_p,
                 top_k=top_k,
+                min_p=min_p,
                 max_new_tokens=max_new_tokens,
                 repetition_penalty=repetition_penalty,
                 cancel_event=cancel_event,
@@ -543,6 +545,7 @@ class InferenceBackend:
                           temperature: float = 0.7,
                           top_p: float = 0.9,
                           top_k: int = 40,
+                          min_p: float = 0.0,
                           max_new_tokens: int = 256,
                           repetition_penalty: float = 1.1,
                           cancel_event=None) -> Generator[str, None, None]:
@@ -562,7 +565,7 @@ class InferenceBackend:
             # Vision model generation
             yield from self._generate_vision_response(
                 messages, system_prompt, image,
-                temperature, top_p, top_k, max_new_tokens, repetition_penalty,
+                temperature, top_p, top_k, min_p, max_new_tokens, repetition_penalty,
                 cancel_event=cancel_event,
             )
         else:
@@ -605,12 +608,12 @@ class InferenceBackend:
 
             # Step 3: Generate
             yield from self.generate_stream(
-                formatted_prompt, temperature, top_p, top_k, max_new_tokens, repetition_penalty,
+                formatted_prompt, temperature, top_p, top_k, min_p, max_new_tokens, repetition_penalty,
                 cancel_event=cancel_event,
             )
 
     def _generate_vision_response(self, messages, system_prompt, image,
-                                  temperature, top_p, top_k, max_new_tokens,
+                                  temperature, top_p, top_k, min_p, max_new_tokens,
                                   repetition_penalty, cancel_event=None) -> Generator[str, None, None]:
         """Handle vision model generation with true token-by-token streaming."""
         model_info = self.models[self.active_model_name]
@@ -671,6 +674,7 @@ class InferenceBackend:
                 temperature=temperature,
                 top_p=top_p,
                 top_k=top_k,
+                min_p=min_p,
             )
 
             err: dict[str, str] = {}
@@ -728,6 +732,7 @@ class InferenceBackend:
                        temperature: float = 0.7,
                        top_p: float = 0.9,
                        top_k: int = 40,
+                       min_p: float = 0.0,
                        max_new_tokens: int = 256,
                        repetition_penalty: float = 1.1,
                        cancel_event=None) -> Generator[str, None, None]:
@@ -760,6 +765,7 @@ class InferenceBackend:
                 temperature=temperature,
                 top_p=top_p,
                 top_k=top_k,
+                min_p=min_p,
                 repetition_penalty=repetition_penalty,
                 do_sample=True,
                 eos_token_id=tokenizer.eos_token_id,
diff --git a/studio/backend/models/inference.py b/studio/backend/models/inference.py
index b3924c5569..1b661047ae 100644
--- a/studio/backend/models/inference.py
+++ b/studio/backend/models/inference.py
@@ -129,6 +129,7 @@ class ChatCompletionRequest(BaseModel):
 
     # ── Unsloth extensions (ignored by standard OpenAI clients) ──
     top_k: int = Field(40, ge=1, le=100, description="[x-unsloth] Top-k sampling")
+    min_p: float = Field(0.0, ge=0.0, le=1.0, description="[x-unsloth] Min-p sampling threshold")
     repetition_penalty: float = Field(1.1, ge=1.0, le=2.0, description="[x-unsloth] Repetition penalty")
     image_base64: Optional[str] = Field(None, description="[x-unsloth] Base64-encoded image for vision models")
     use_adapter: Optional[Union[bool, str]] = Field(
diff --git a/studio/backend/routes/inference.py b/studio/backend/routes/inference.py
index 3bb84d5c6b..c30a1638d4 100644
--- a/studio/backend/routes/inference.py
+++ b/studio/backend/routes/inference.py
@@ -371,6 +371,7 @@ async def openai_chat_completions(payload: ChatCompletionRequest, request: Reque
         temperature=payload.temperature,
         top_p=payload.top_p,
         top_k=payload.top_k,
+        min_p=payload.min_p,
         max_new_tokens=payload.max_tokens or 512,
         repetition_penalty=payload.repetition_penalty,
     )