diff --git a/endpoints/OAI/router.py b/endpoints/OAI/router.py
index acb35f9..8403a87 100644
--- a/endpoints/OAI/router.py
+++ b/endpoints/OAI/router.py
@@ -132,6 +132,7 @@ async def chat_completion_request(
     else:
         if model.container.use_vision:
             data.messages, embeddings = await preprocess_vision_request(data.messages)
+
         prompt = await format_prompt_with_template(data)
 
     # Set an empty JSON schema if the request wants a JSON response
diff --git a/endpoints/OAI/types/chat_completion.py b/endpoints/OAI/types/chat_completion.py
index 30ec769..86a2247 100644
--- a/endpoints/OAI/types/chat_completion.py
+++ b/endpoints/OAI/types/chat_completion.py
@@ -1,7 +1,7 @@
 from pydantic import BaseModel, Field
 from pydantic.json_schema import SkipJsonSchema
 from time import time
-from typing import Union, List, Optional, Dict
+from typing import Literal, Union, List, Optional, Dict
 from uuid import uuid4
 
 from endpoints.OAI.types.common import UsageStats, CommonCompletionRequest
@@ -18,10 +18,21 @@ class ChatCompletionLogprobs(BaseModel):
     content: List[ChatCompletionLogprob] = Field(default_factory=list)
 
 
+class ChatCompletionImageUrl(BaseModel):
+    url: str
+
+
+class ChatCompletionMessagePart(BaseModel):
+    type: Literal["text", "image_url"] = "text"
+    text: Optional[str] = None
+    image_url: Optional[ChatCompletionImageUrl] = None
+
+
 class ChatCompletionMessage(BaseModel):
-    role: Optional[str] = None
-    content: Optional[str] = None
+    role: str = "user"
+    content: Optional[Union[str, List[ChatCompletionMessagePart]]] = None
     tool_calls: Optional[List[ToolCall]] = None
+    tool_calls_json: SkipJsonSchema[Optional[str]] = None
 
 
 class ChatCompletionRespChoice(BaseModel):
@@ -51,7 +62,7 @@ class ChatCompletionRequest(CommonCompletionRequest):
 
     # WIP this can probably be tightened, or maybe match the OAI lib type
     # in openai\types\chat\chat_completion_message_param.py
-    messages: Union[str, List[Dict]]
+    messages: List[ChatCompletionMessage] = Field(default_factory=list)
     prompt_template: Optional[str] = None
     add_generation_prompt: Optional[bool] = True
     template_vars: Optional[dict] = {}
diff --git a/endpoints/OAI/utils/chat_completion.py b/endpoints/OAI/utils/chat_completion.py
index a59f425..c14a8dc 100644
--- a/endpoints/OAI/utils/chat_completion.py
+++ b/endpoints/OAI/utils/chat_completion.py
@@ -1,17 +1,16 @@
 """Chat completion utilities for OAI server."""
 
 import asyncio
+import json
 import pathlib
 from asyncio import CancelledError
-from typing import Dict, List, Optional
-import json
-
-from common.multimodal import MultimodalEmbeddingWrapper, add_image_embedding
+from typing import List, Optional
 from fastapi import HTTPException, Request
 from jinja2 import TemplateError
 from loguru import logger
 
 from common import model
+from common.multimodal import MultimodalEmbeddingWrapper, add_image_embedding
 from common.networking import (
     get_generator_error,
     handle_request_disconnect,
@@ -214,21 +213,21 @@ async def format_prompt_with_template(
             unwrap(data.ban_eos_token, False),
         )
 
-        # Deal with list in messages.content
-        # Just replace the content list with the very first text message
+        # Convert list to text-based content
+        # Use the first instance of text inside the part list
         for message in data.messages:
-            if isinstance(message["content"], list):
-                message["content"] = next(
+            if isinstance(message.content, list):
+                message.content = next(
                     (
-                        content["text"]
-                        for content in message["content"]
-                        if content["type"] == "text"
+                        content.text
+                        for content in message.content
+                        if content.type == "text"
                     ),
                     "",
                 )
 
-            if "tool_calls" in message:
-                message["tool_calls_json"] = json.dumps(message["tool_calls"], indent=2)
+            if message.tool_calls:
+                message.tool_calls_json = json.dumps(message.tool_calls, indent=2)
 
         # Overwrite any protected vars with their values
         data.template_vars.update(
@@ -474,20 +473,21 @@ def postprocess_tool_call(call_str: str) -> List[ToolCall]:
     return [ToolCall(**tool_call) for tool_call in tool_calls]
 
 
-async def preprocess_vision_request(messages: List[Dict]):
+# TODO: Combine this with the existing preprocessor in format_prompt_with_template
+async def preprocess_vision_request(messages: List[ChatCompletionMessage]):
     embeddings = MultimodalEmbeddingWrapper()
     for message in messages:
-        if isinstance(message["content"], list):
+        if isinstance(message.content, list):
             concatenated_content = ""
-            for content in message["content"]:
-                if content["type"] == "text":
-                    concatenated_content += content["text"]
-                elif content["type"] == "image_url":
+            for content in message.content:
+                if content.type == "text":
+                    concatenated_content += content.text
+                elif content.type == "image_url":
                     embeddings = await add_image_embedding(
-                        embeddings, content["image_url"]["url"]
+                        embeddings, content.image_url.url
                     )
                     concatenated_content += embeddings.text_alias[-1]
 
-            message["content"] = concatenated_content
+            message.content = concatenated_content
 
     return messages, embeddings