Format Python code with psf/black push

models/openai_model.py

@@ -808,7 +808,6 @@ class Model:
         text = re.sub(r"[^a-zA-Z0-9]", "_", text)
         return text
 
-
     @backoff.on_exception(
         backoff.expo,
         ValueError,
@@ -830,7 +829,6 @@ class Model:
         max_tokens_override=None,
         stop=None,
         custom_api_key=None,
-
     ) -> (
         Tuple[dict, bool]
     ):  # The response, and a boolean indicating whether or not the context limit was reached.
@@ -850,20 +848,30 @@ class Model:
         # Format the request body into the messages format that the API is expecting
         #   "messages": [{"role": "user", "content": "Hello!"}]
         messages = []
-        for number,message in enumerate(prompt_history):
+        for number, message in enumerate(prompt_history):
             if number == 0:
                 # If this is the first message, it is the context prompt.
-                messages.append({"role": "user", "name":"System_Instructor", "content": message.text})
+                messages.append(
+                    {
+                        "role": "user",
+                        "name": "System_Instructor",
+                        "content": message.text,
+                    }
+                )
                 continue
 
             if user_displayname in message.text:
-                text = message.text.replace(user_displayname+":", "")
+                text = message.text.replace(user_displayname + ":", "")
                 text = text.replace("<|endofstatement|>", "")
-                messages.append({"role": "user", "name":user_displayname_clean, "content": text})
+                messages.append(
+                    {"role": "user", "name": user_displayname_clean, "content": text}
+                )
             else:
                 text = message.text.replace(bot_name, "")
                 text = text.replace("<|endofstatement|>", "")
-                messages.append({"role": "assistant", "name":bot_name_clean, "content": text})
+                messages.append(
+                    {"role": "assistant", "name": bot_name_clean, "content": text}
+                )
 
         print(f"Messages -> {messages}")
         async with aiohttp.ClientSession(raise_for_status=False) as session:
@@ -884,7 +892,9 @@ class Model:
                 "Authorization": f"Bearer {self.openai_key if not custom_api_key else custom_api_key}"
             }
             async with session.post(
-                "https://api.openai.com/v1/chat/completions", json=payload, headers=headers
+                "https://api.openai.com/v1/chat/completions",
+                json=payload,
+                headers=headers,
             ) as resp:
                 response = await resp.json()
                 # print(f"Payload -> {payload}")

services/text_service.py

@@ -113,7 +113,6 @@ class TextService:
                 new_prompt = unidecode.unidecode(new_prompt)
                 prompt_less_author = f"{new_prompt} <|endofstatement|>\n"
 
-
                 new_prompt = f"\n{user_displayname}: {new_prompt} <|endofstatement|>\n"
 
                 # new_prompt = new_prompt.encode("ascii", "ignore").decode()
@@ -275,7 +274,9 @@ class TextService:
                     return
 
             if not converser_cog.pinecone_service:
-                _prompt_with_history = converser_cog.conversation_threads[ctx.channel.id].history
+                _prompt_with_history = converser_cog.conversation_threads[
+                    ctx.channel.id
+                ].history
             print("The prompt with history is ", _prompt_with_history)
 
             # Send the request to the model
@@ -291,7 +292,6 @@ class TextService:
                     presence_penalty_override=overrides.presence_penalty,
                     stop=stop if not from_ask_command else None,
                     custom_api_key=custom_api_key,
-
                 )
 
             elif from_edit_command:
@@ -317,9 +317,13 @@ class TextService:
                 )
 
             # Clean the request response
-            response_text = converser_cog.cleanse_response(
-                str(response["choices"][0]["text"])
-            ) if not chatgpt else converser_cog.cleanse_response(str(response["choices"][0]["message"]["content"]))
+            response_text = (
+                converser_cog.cleanse_response(str(response["choices"][0]["text"]))
+                if not chatgpt
+                else converser_cog.cleanse_response(
+                    str(response["choices"][0]["message"]["content"])
+                )
+            )
 
             if from_message_context:
                 response_text = f"{response_text}"