docs: implement feedback

src/apis/gpt.py

@@ -69,7 +69,7 @@ class _GPTConversation:
             model_name=model,
             streaming=True,
             callback_manager=CallbackManager([AssistantStreamingStdOutCallbackHandler()]),
-            verbose=os.environ['VERBOSE'].lower() == 'true',
+            verbose=True,
             temperature=0,
         )
         self.messages: List[BaseMessage] = []

src/cli.py

@@ -65,10 +65,8 @@ def generate(
 
     from src.options.generate.generator import Generator
     generator = Generator(description, test, model=model)
-    with get_openai_callback() as cb:
-        generator.generate(path)
-        # print(f"Prompt/Completion/Total Tokens: {cb.prompt_tokens}/{cb.completion_tokens}/{cb.total_tokens}")
-        # print(f"Total Cost on OpenAI (USD): ${cb.total_cost}")
+    generator.generate(path)
+
 
 @main.command()
 @path_param

src/options/generate/generator.py

@@ -53,14 +53,14 @@ metas:
         return all_microservice_files_string.strip()
 
 
-    def generate_and_persist_file(self, section_title, template, destination_folder, file_name, **kwargs):
+    def generate_and_persist_file(self, section_title, template, destination_folder, file_name, **template_kwargs):
         print_colored('', f'\n############# {section_title} #############', 'blue')
         conversation = self.gpt_session.get_conversation()
-        kwargs = {k: v for k, v in kwargs.items() if k in template.input_variables}
+        template_kwargs = {k: v for k, v in template_kwargs.items() if k in template.input_variables}
         content_raw = conversation.chat(
             template.format(
                 file_name=file_name,
-                **kwargs
+                **template_kwargs
             )
         )
         content = self.extract_content_from_result(content_raw, file_name, match_single_block=True)