Fixes in vLLM

`instruct_in_prompt` is a boolean option; when set, system instruction
will be prefixed to the user role, for models without a system role.
Default is `False`, which means system instruction will be inserted as
the system role.

ragfoundry/models/vllm.py

@@ -27,7 +27,7 @@ def __init__(
         self,
         model_name_or_path: str,
         instruction: Path,
-        instruct_in_prompt: False,
+        instruct_in_prompt: bool = False,
         template: Path = None,
         num_gpus: int = 1,
         llm_params: Dict = {},
@@ -39,28 +39,27 @@ def __init__(
         )
         from vllm import LLM, SamplingParams
 
-        logger.info(f"Using the following instruction: {self.instruction}")
-
+        self.model_name = model_name_or_path
         self.instruct_in_prompt = instruct_in_prompt
         self.template = open(template).read() if template else None
         self.instruction = open(instruction).read()
+        logger.info(f"Using the following instruction: {self.instruction}")
 
         self.sampling_params = SamplingParams(**generation)
-        self.llm = LLM(
-            model=model_name_or_path, tensor_parallel_size=num_gpus, **llm_params
-        )
-        if self.instruct_in_prompt:
-            self.tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)
-            self.config = AutoConfig.from_pretrained(self.model_name)
+        self.llm = LLM(model=self.model_name, tensor_parallel_size=num_gpus, **llm_params)
+
+        self.tokenizer = AutoTokenizer.from_pretrained(self.model_name)
+        self.config = AutoConfig.from_pretrained(self.model_name)
 
     def generate(self, prompt: str) -> str:
         """
         Generates text based on the given prompt.
         """
         if self.template:
             prompt = self.template.format(instruction=self.instruction, query=prompt)
-        elif self.instruct_in_prompt:
-            prompt = self.instruction + "\n" + prompt
+        else:
+            if self.instruct_in_prompt:
+                prompt = self.instruction + "\n" + prompt
             messages = [
                 {"role": "system", "content": self.instruction},
                 {"role": "user", "content": prompt},
@@ -72,7 +71,7 @@ def generate(self, prompt: str) -> str:
                 add_generation_prompt=True,
                 truncation=True,
                 max_length=(
-                    self.config.max_position_embeddings - self.sampling_param.max_tokens
+                    self.config.max_position_embeddings - self.sampling_params.max_tokens
                 ),
             )