Add support to images in requests

src/guidellm/backend/openai.py

@@ -1,4 +1,5 @@
 from typing import AsyncGenerator, Dict, List, Optional
+import io, base64
 
 from loguru import logger
 from openai import AsyncOpenAI, OpenAI
@@ -103,11 +104,11 @@ async def make_request(
 
         request_args.update(self._request_args)
 
+        messages = self._build_messages(request)
+
         stream = await self._async_client.chat.completions.create(
             model=self.model,
-            messages=[
-                {"role": "user", "content": request.prompt},
-            ],
+            messages=messages,
             stream=True,
             **request_args,
         )
@@ -167,3 +168,21 @@ def validate_connection(self):
         except Exception as error:
             logger.error("Failed to validate OpenAI connection: {}", error)
             raise error
+
+    def _build_messages(self, request: TextGenerationRequest) -> Dict:
+        if request.number_images == 0:
+            messages = [{"role": "user", "content": request.prompt}]
+        else:
+            content = []
+            for image in request.images:
+                stream = io.BytesIO()
+                im_format = image.image.format or "PNG"
+                image.image.save(stream, format=im_format)
+                im_b64 = base64.b64encode(stream.getvalue()).decode("ascii")
+                image_url = {"url": f"data:image/{im_format.lower()};base64,{im_b64}"}
+                content.append({"type": "image_url", "image_url": image_url})
+
+            content.append({"type": "text", "text": request.prompt})            
+            messages = [{"role": "user", "content": content}]
+
+        return messages

src/guidellm/core/request.py

@@ -1,9 +1,10 @@
 import uuid
-from typing import Any, Dict, Optional
+from typing import Any, Dict, Optional, List
 
 from pydantic import Field
 
 from guidellm.core.serializable import Serializable
+from guidellm.utils import ImageDescriptor
 
 
 class TextGenerationRequest(Serializable):
@@ -16,6 +17,10 @@ class TextGenerationRequest(Serializable):
         description="The unique identifier for the request.",
     )
     prompt: str = Field(description="The input prompt for the text generation.")
+    images: Optional[List[ImageDescriptor]] = Field(
+        default=None,
+        description="Input images.",
+    )
     prompt_token_count: Optional[int] = Field(
         default=None,
         description="The number of tokens in the input prompt.",
@@ -29,6 +34,13 @@ class TextGenerationRequest(Serializable):
         description="The parameters for the text generation request.",
     )
 
+    @property
+    def number_images(self) -> int:
+        if self.images is None:
+            return 0
+        else:
+            return len(self.images)
+
     def __str__(self) -> str:
         prompt_short = (
             self.prompt[:32] + "..."
@@ -41,4 +53,5 @@ def __str__(self) -> str:
             f"prompt={prompt_short}, prompt_token_count={self.prompt_token_count}, "
             f"output_token_count={self.output_token_count}, "
             f"params={self.params})"
+            f"images={self.number_images}"
         )

src/guidellm/request/emulated.py

@@ -11,7 +11,7 @@
 from guidellm.config import settings
 from guidellm.core.request import TextGenerationRequest
 from guidellm.request.base import GenerationMode, RequestGenerator
-from guidellm.utils import clean_text, filter_text, load_text, split_text
+from guidellm.utils import clean_text, filter_text, load_text, split_text, load_images
 
 __all__ = ["EmulatedConfig", "EmulatedRequestGenerator", "EndlessTokens"]
 
@@ -30,6 +30,7 @@ class EmulatedConfig:
         generated_tokens_variance (Optional[int]): Variance for generated tokens.
         generated_tokens_min (Optional[int]): Minimum number of generated tokens.
         generated_tokens_max (Optional[int]): Maximum number of generated tokens.
+        images (Optional[int]): Number of input images.
     """
 
     @staticmethod
@@ -47,7 +48,7 @@ def create_config(config: Optional[Union[str, Path, Dict]]) -> "EmulatedConfig":
         """
         if not config:
             logger.debug("Creating default configuration")
-            return EmulatedConfig(prompt_tokens=1024, generated_tokens=256)
+            return EmulatedConfig(prompt_tokens=1024, generated_tokens=256, images=0)
 
         if isinstance(config, dict):
             logger.debug("Loading configuration from dict: {}", config)
@@ -105,6 +106,8 @@ def create_config(config: Optional[Union[str, Path, Dict]]) -> "EmulatedConfig":
     generated_tokens_min: Optional[int] = None
     generated_tokens_max: Optional[int] = None
 
+    images: int = 0
+
     @property
     def prompt_tokens_range(self) -> Tuple[int, int]:
         """
@@ -327,6 +330,8 @@ def __init__(
             settings.emulated_data.filter_start,
             settings.emulated_data.filter_end,
         )
+        if self._config.images > 0:
+            self._images = load_images(settings.emulated_data.image_source)
         self._rng = np.random.default_rng(random_seed)
 
         # NOTE: Must be after all the parameters since the queue population
@@ -355,6 +360,7 @@ def create_item(self) -> TextGenerationRequest:
         logger.debug("Creating new text generation request")
         target_prompt_token_count = self._config.sample_prompt_tokens(self._rng)
         prompt = self.sample_prompt(target_prompt_token_count)
+        images = self.sample_images()
         prompt_token_count = len(self.tokenizer.tokenize(prompt))
         output_token_count = self._config.sample_output_tokens(self._rng)
         logger.debug("Generated prompt: {}", prompt)
@@ -363,6 +369,7 @@ def create_item(self) -> TextGenerationRequest:
             prompt=prompt,
             prompt_token_count=prompt_token_count,
             output_token_count=output_token_count,
+            images=images,
         )
 
     def sample_prompt(self, tokens: int) -> str:
@@ -395,3 +402,9 @@ def sample_prompt(self, tokens: int) -> str:
                 right = mid
 
         return self._tokens.create_text(start_line_index, left)
+
+
+    def sample_images(self):
+        image_indices = self._rng.choice(len(self._images), size=self._config.images, replace=False)
+
+        return [self._images[i] for i in image_indices]