Auto-sync from demo at Wed Jan 14 04:31:41 UTC 2026

graphgen/models/llm/local/vllm_wrapper.py

@@ -20,7 +20,7 @@ class VLLMWrapper(BaseLLMWrapper):
         temperature: float = 0.6,
         top_p: float = 1.0,
         top_k: int = 5,
-        timeout: float = 300,
+        timeout: float = 600,
         **kwargs: Any,
     ):
         super().__init__(temperature=temperature, top_p=top_p, top_k=top_k, **kwargs)
@@ -42,25 +42,24 @@ class VLLMWrapper(BaseLLMWrapper):
         )
         self.engine = AsyncLLMEngine.from_engine_args(engine_args)
         self.timeout = float(timeout)
+        self.tokenizer = self.engine.engine.tokenizer.tokenizer
 
-    @staticmethod
-    def _build_inputs(prompt: str, history: Optional[List[str]] = None) -> str:
-        msgs = history or []
-        lines = []
-        for m in msgs:
-            if isinstance(m, dict):
-                role = m.get("role", "")
-                content = m.get("content", "")
-                lines.append(f"{role}: {content}")
-            else:
-                lines.append(str(m))
-        lines.append(prompt)
-        return "\n".join(lines)
+    def _build_inputs(self, prompt: str, history: Optional[List[dict]] = None) -> Any:
+        messages = history or []
+        messages.append({"role": "user", "content": prompt})
+
+        return self.tokenizer.apply_chat_template(
+            messages,
+            tokenize=False,
+            add_generation_prompt=True
+        )
 
     async def _consume_generator(self, generator):
         final_output = None
         async for request_output in generator:
-            final_output = request_output
+            if request_output.finished:
+                final_output = request_output
+                break
         return final_output
 
     async def generate_answer(
@@ -70,14 +69,14 @@ class VLLMWrapper(BaseLLMWrapper):
         request_id = f"graphgen_req_{uuid.uuid4()}"
 
         sp = self.SamplingParams(
-            temperature=self.temperature if self.temperature > 0 else 1.0,
-            top_p=self.top_p if self.temperature > 0 else 1.0,
+            temperature=self.temperature if self.temperature >= 0 else 1.0,
+            top_p=self.top_p if self.top_p >= 0 else 1.0,
             max_tokens=extra.get("max_new_tokens", 2048),
+            repetition_penalty=extra.get("repetition_penalty", 1.05),
         )
 
-        result_generator = self.engine.generate(full_prompt, sp, request_id=request_id)
-
         try:
+            result_generator = self.engine.generate(full_prompt, sp, request_id=request_id)
             final_output = await asyncio.wait_for(
                 self._consume_generator(result_generator),
                 timeout=self.timeout
@@ -89,7 +88,7 @@ class VLLMWrapper(BaseLLMWrapper):
             result_text = final_output.outputs[0].text
             return result_text
 
-        except (Exception, asyncio.CancelledError):
+        except (Exception, asyncio.CancelledError, asyncio.TimeoutError):
             await self.engine.abort(request_id)
             raise
 
@@ -105,14 +104,14 @@ class VLLMWrapper(BaseLLMWrapper):
             logprobs=self.top_k,
         )
 
-        result_generator = self.engine.generate(full_prompt, sp, request_id=request_id)
-
         try:
+            result_generator = self.engine.generate(full_prompt, sp, request_id=request_id)
             final_output = await asyncio.wait_for(
                 self._consume_generator(result_generator),
                 timeout=self.timeout
             )
 
+
             if (
                 not final_output
                 or not final_output.outputs
@@ -141,7 +140,7 @@ class VLLMWrapper(BaseLLMWrapper):
                 return [main_token]
             return []
 
-        except (Exception, asyncio.CancelledError):
+        except (Exception, asyncio.CancelledError, asyncio.TimeoutError):
             await self.engine.abort(request_id)
             raise