Allow model and max tokens to be dynamic parameters in Standalone LLM Tool.

standalone_llm_tool.py

@@ -6,26 +6,24 @@ from openai import OpenAI
 class StandaloneLLMTool:
     def __init__(self):
         self.client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))
-        self.model = "llm-preview"
-        self.max_tokens = 16384
 
-    def get_detailed_instructions(self, user_prompt):
+    def get_detailed_instructions(self, user_prompt, model="llm-preview", max_tokens=16384):
         response = self.client.completions.create(
-            model=self.model,
+            model=model,
             prompt=user_prompt,
-            max_tokens=self.max_tokens
+            max_tokens=max_tokens
         )
         return response
 
-    def process_user_input(self, user_prompt):
+    def process_user_input(self, user_prompt, model="llm-preview", max_tokens=16384):
         logging.info(f"Received prompt: {user_prompt}")
-        response = self.get_detailed_instructions(user_prompt)
+        response = self.get_detailed_instructions(user_prompt, model, max_tokens)
         logging.info("Response generated")
         return response.choices[0].text
 
 
 # Utility function for programmatic access
 
-def get_llm_response(prompt):
+def get_llm_response(prompt, model="llm-preview", max_tokens=16384):
     tool = StandaloneLLMTool()
-    return tool.process_user_input(prompt)
+    return tool.process_user_input(prompt, model, max_tokens)