feat: add support for gpt5.

topicgpt_python/assignment.py

@@ -199,7 +199,7 @@ def assign_topics(api, model, data, prompt_file, out_file, topic_file, verbose):
     - verbose (bool): Whether to print out results
     """
     api_client = APIClient(api=api, model=model)
-    max_tokens, temperature, top_p = 1000, 0.0, 1.0
+    max_tokens, temperature, top_p = 1000, 1.0, 1.0
 
     if verbose:
         print("-------------------")

topicgpt_python/correction.py

@@ -198,7 +198,7 @@ def correct_topics(
     - verbose: Print verbose output
     """
     api_client = APIClient(api=api, model=model)
-    max_tokens, temperature, top_p = 1000, 0.6, 0.9
+    max_tokens, temperature, top_p = 1000, 1.0, 0.9
     context_len = (
         128000
         if model not in ["gpt-3.5-turbo", "gpt-4"]

topicgpt_python/generation_1.py

@@ -170,7 +170,7 @@ def generate_topic_lvl1(
     - topics_root (TopicTree): Root node of the topic tree
     """
     api_client = APIClient(api=api, model=model)
-    max_tokens, temperature, top_p = 1000, 0.0, 1.0
+    max_tokens, temperature, top_p = 1000, 1.0, 1.0
 
     if verbose:
         print("-------------------")

topicgpt_python/generation_2.py

@@ -254,7 +254,7 @@ def generate_topic_lvl2(
     Returns: Root node of the topic tree
     """
     api_client = APIClient(api=api, model=model)
-    max_tokens, temperature, top_p = 1000, 0.0, 1.0
+    max_tokens, temperature, top_p = 1000, 1.0, 1.0
 
     if verbose:
         print("-------------------")

topicgpt_python/refinement.py

@@ -261,7 +261,7 @@ def refine_topics(
     - None
     """
     api_client = APIClient(api=api, model=model)
-    max_tokens, temperature, top_p = 1000, 0.0, 1.0
+    max_tokens, temperature, top_p = 1000, 1.0, 1.0
     topics_root = TopicTree().from_topic_list(topic_file, from_file=True)
     if verbose:
         print("-------------------")

topicgpt_python/utils.py

@@ -159,7 +159,7 @@ def iterative_prompt(
                     completion = self.client.chat.completions.create(
                         model=self.model,
                         messages=message,
-                        max_tokens=max_tokens,
+                        max_completion_tokens=max_tokens,
                         temperature=temperature,
                         top_p=top_p,
                     )