Update AI and librarian commands to use 'GENERAL' context"

ai_commands.py

@@ -294,7 +294,7 @@ class Events(commands.Cog):
                     bartender,
                     MESSAGE_TABLE,
                     username,
-                    "CONVERSATION",
+                    "GENERAL",
                 )
 
                 await discord_friendly_reply(message, result)
@@ -332,7 +332,7 @@ class Events(commands.Cog):
                         True,
                         MESSAGE_TABLE,
                         username,
-                        "RANDOM",
+                        "GENERAL",
                     )
                     await discord_friendly_reply(
                         message, f"Sorki, cenzura: {resp}. Jak chcesz to są kanały na nudle #sexy-foteczky i #kanal-do-fapania *Na ekranie pojawia się: {e}"

ai_functions.py

@@ -5,6 +5,7 @@ import random
 
 import openai
 import tiktoken
+import time
 from other_functions import discord_friendly_send
 from constants import (
     ASSISTANTS,
@@ -23,6 +24,36 @@ from constants import (
 #this do per user
 VECTOR_STORE_ID = -1
 
+
+async def _openai_call(messages, model, temperature=0.2):
+    """
+    Responses API dla 4o/4.1*, fallback Chat Completions dla gpt-3.5-turbo.
+    Zwraca czysty string odpowiedzi.
+    """
+
+    if model.startswith("gpt-3.5"):
+        # legacy path – bez zmian w Twoim kodzie wyżej/niżej
+        def _sync_call():
+            resp = OPENAICLIENT.chat.completions.create(
+                model=model,
+                messages=messages,
+                temperature=temperature,
+            )
+            return resp.choices[0].message.content.strip()
+        return await asyncio.to_thread(_sync_call)
+
+    # Responses API (zalecane dla 4o/4.1*)
+    def _sync_resp():
+        resp = OPENAICLIENT.responses.create(
+            model=model,
+            temperature=temperature,
+            input=messages,
+        )
+        # SDK zapewnia output_text dla zwykłych odpowiedzi
+        return (getattr(resp, "output_text", None) or "").strip() or str(resp)
+    return await asyncio.to_thread(_sync_resp)
+
+
 def create_vector_store():
     # Create a vector store caled "Financial Statements"
     return OPENAICLIENT.beta.vector_stores.create_and_poll(name="Hammer Stash")
@@ -99,7 +130,7 @@ def num_tokens_from_string(message, model):
 
 
 async def handle_response(
-    prompt, vykidailo, bartender, history, username, request_type
+    prompt, vykidailo, bartender, history, username, request_type, algorithm="gpt-4o"
 ):
     """
     Handle responses by appending them to a history, use OpenAI to
@@ -115,6 +146,10 @@ async def handle_response(
     :param music: The "music" parameter is a boolean value that indicates whether the conversation is
     related to music or not. If it is True, the conversation history will be stored in a different file
     and the response will be generated using a different model
+    :param request_type: The type of request being made, which can be "MUSIC", "RANDOM", "NONE" or "GENERAL"
+        GENERAL is for regular conversations, MUSIC is for music-related requests,
+        RANDOM is for random requests, and NONE is to not store the request in memory
+    :param algorithm: The algorithm to be used for generating the response, default is "gpt-4o"
     :return: The function `handle_response` returns a tuple containing the `result` and `MESSAGE_TABLE`.
     """
     logger = logging.getLogger("discord")
@@ -141,7 +176,7 @@ async def handle_response(
             file_memory.seek(0)
             # convert back to json.
             json.dump(file_data, file_memory, indent=4)
-    else:
+    elif request_type == "GENERAL":
         with open(MEMORY_FIVE_SIARA, "r+", encoding=ENCODING) as file_memory:
             # First we load existing data into a dict.
             file_data = json.load(file_memory)
@@ -171,17 +206,18 @@ async def handle_response(
         "Rozmiar zapytania przed dodaniem historii %s", chat_gpt_config_request_size
     )
     if request_type == "MUSIC":
-        algorithm = "gpt-4o"
         table = MESSAGE_TABLE_MUZYKA
         token_amount = 10700
     elif request_type == "RANDOM":
-        algorithm = "gpt-4o"
+        table = MESSAGE_TABLE
+        token_amount = 10700
+    elif request_type == "GENERAL":
         table = MESSAGE_TABLE
         token_amount = 10700
     else:
-        table = MESSAGE_TABLE
-        algorithm = "gpt-4o"
-        token_amount = 10700
+        table = []
+        token_amount = 10000
+
 
     prompt_gpt_request_size = num_tokens_from_string(
         {"role": "user", "content": final_prompt}, "gpt-4"
@@ -206,9 +242,19 @@ async def handle_response(
     history.append(temp)
     logger.info("Rozmiar zapytania po wyslaniu %s", chat_gpt_config_request_size)
     try:
-        response = await OPENAICLIENT.chat.completions.create(
-            model=algorithm, messages=history
+        # ...przygotowanie messages/system prompt/itp. jak masz...
+        # retry/backoff + deadline (zachowuje Twoją semantykę logowania)
+        timeout_sec = 120
+        max_retries = 3
+        deadline = time.time() + timeout_sec
+        for _ in range(max_retries):
+            if time.time() > deadline:
+                break
+            response = await asyncio.wait_for(
+                _openai_call(messages=history, model=algorithm),
+                timeout=max(0.1, deadline - time.time())
             )
+
     except openai.APITimeoutError as e:
         # Handle timeout error, e.g. retry or log
         result = f"*Kondziu patrzy na terminal, czeka, czeka, czeka,.... Jeszcze chwile czeka Przypierdala w niego pięścią....* Nie mogę się połączyć z Openai spróbuj od nowa. *Na ekranie pojawia się*: {e}"
@@ -272,6 +318,7 @@ async def handle_response(
             file_music_memory.seek(0)
             # convert back to json.
             json.dump(file_data, file_music_memory, indent=4)
+        return result, MESSAGE_TABLE_MUZYKA
     elif request_type == "RANDOM":
         with open(MEMORY_FIVE_SIARA, "r+", encoding=ENCODING) as file_memory:
             # First we load existing data into a dict.
@@ -281,7 +328,8 @@ async def handle_response(
             file_memory.seek(0)
             # convert back to json.
             json.dump(file_data, file_memory, indent=4)
-    else:
+        return result, MESSAGE_TABLE
+    elif request_type == "GENERAL":
         with open(MEMORY_FIVE_SIARA, "r+", encoding=ENCODING) as file_memory:
             # First we load existing data into a dict.
             file_data = json.load(file_memory)
@@ -291,7 +339,8 @@ async def handle_response(
             # convert back to json.
             json.dump(file_data, file_memory, indent=4)
         return result, MESSAGE_TABLE
-
+    else:
+        return result, []
 
 async def get_random_cyclic_message(client):
     """

librarian_commands.py

@@ -222,7 +222,7 @@ class DataModule(commands.Cog):
             global MESSAGE_TABLE  # pylint: disable=global-statement
 
             result, MESSAGE_TABLE = await handle_response(
-                prompt, vykidailo, bartender, MESSAGE_TABLE, username, "CONVERSATION"
+                prompt, vykidailo, bartender, MESSAGE_TABLE, username, "GENERAL"
             )
             if len(result) < 1500:
                 await ctx.send(result)