Naming conventions

omnitool/gradio/agent/llm_utils/oaiclient.py

@@ -0,0 +1,62 @@
+import os
+import logging
+import base64
+import requests
+from .utils import is_image_path, encode_image
+
+def run_oai_interleaved(messages: list, system: str, model_name: str, api_key: str, max_tokens=256, temperature=0, provider_base_url: str = "https://api.openai.com/v1"):    
+    headers = {"Content-Type": "application/json",
+               "Authorization": f"Bearer {api_key}"}
+    final_messages = [{"role": "system", "content": system}]
+
+    if type(messages) == list:
+        for item in messages:
+            contents = []
+            if isinstance(item, dict):
+                for cnt in item["content"]:
+                    if isinstance(cnt, str):
+                        if is_image_path(cnt) and 'o3-mini' not in model_name:
+                            # 03 mini does not support images
+                            base64_image = encode_image(cnt)
+                            content = {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"}}
+                        else:
+                            content = {"type": "text", "text": cnt}
+                    else:
+                        # in this case it is a text block from anthropic
+                        content = {"type": "text", "text": str(cnt)}
+                        
+                    contents.append(content)
+                    
+                message = {"role": 'user', "content": contents}
+            else:  # str
+                contents.append({"type": "text", "text": item})
+                message = {"role": "user", "content": contents}
+            
+            final_messages.append(message)
+
+    
+    elif isinstance(messages, str):
+        final_messages = [{"role": "user", "content": messages}]
+
+    payload = {
+        "model": model_name,
+        "messages": final_messages,
+    }
+    if 'o1' in model_name or 'o3-mini' in model_name:
+        payload['reasoning_effort'] = 'low'
+        payload['max_completion_tokens'] = max_tokens
+    else:
+        payload['max_tokens'] = max_tokens
+
+    response = requests.post(
+        f"{provider_base_url}/chat/completions", headers=headers, json=payload
+    )
+
+
+    try:
+        text = response.json()['choices'][0]['message']['content']
+        token_usage = int(response.json()['usage']['total_tokens'])
+        return text, token_usage
+    except Exception as e:
+        print(f"Error in interleaved openAI: {e}. This may due to your invalid API key. Please check the response: {response.json()} ")
+        return response.json()