Partial + reformatting

ai_functions.py

@@ -21,7 +21,7 @@ from constants import (
     WORD_REACTIONS,
 )
 
-#this do per user
+# this do per user
 VECTOR_STORE_ID = -1
 
 
@@ -47,23 +47,26 @@ async def _openai_call(messages, model, temperature=0.2):
 
     else:
         logger.info("4.0+")
-    # Responses API (zalecane dla 4o/4.1*)
+        # Responses API (zalecane dla 4o/4.1*)
         resp = await OPENAICLIENT.responses.create(
             model=model,
             temperature=temperature,
             input=messages,
         )
         # SDK zapewnia output_text dla zwykłych odpowiedzi
-        return (getattr(resp.output_text, "output_text", None) or "").strip() or str(resp.output_text)
+        return (getattr(resp.output_text, "output_text", None) or "").strip() or str(
+            resp.output_text
+        )
 
 
 def create_vector_store():
     # Create a vector store caled "Financial Statements"
     return OPENAICLIENT.beta.vector_stores.create_and_poll(name="Hammer Stash")
-    #expires_after={
-    #"anchor": "last_active_at",
-    #"days": 7}
-    #)
+    # expires_after={
+    # "anchor": "last_active_at",
+    # "days": 7}
+    # )
+
 
 def upload_files_to_vector_store(assistant):
 
@@ -71,15 +74,14 @@ def upload_files_to_vector_store(assistant):
     file_paths = ["edgar/goog-10k.pdf", "edgar/brka-10k.txt"]
     file_streams = [open(path, "rb") for path in file_paths]
 
-    #file = client.beta.vector_stores.files.create_and_poll(
-    #vector_store_id="vs_abc123",
-    #file_id="file-abc123"
-    #)
-    #batch = client.beta.vector_stores.file_batches.create_and_poll(
-    #vector_store_id="vs_abc123",
-    #file_ids=['file_1', 'file_2', 'file_3', 'file_4', 'file_5']
-    #)
-
+    # file = client.beta.vector_stores.files.create_and_poll(
+    # vector_store_id="vs_abc123",
+    # file_id="file-abc123"
+    # )
+    # batch = client.beta.vector_stores.file_batches.create_and_poll(
+    # vector_store_id="vs_abc123",
+    # file_ids=['file_1', 'file_2', 'file_3', 'file_4', 'file_5']
+    # )
 
     # Use the upload and poll SDK helper to upload the files, add them to the vector store,
     # and poll the status of the file batch for completion.
@@ -91,10 +93,11 @@ def upload_files_to_vector_store(assistant):
     print(file_batch.status)
     print(file_batch.file_counts)
     assistant = OPENAICLIENT.beta.assistants.update(
-    assistant_id=assistant.id,
-    tool_resources={"file_search": {"vector_store_ids": [VECTOR_STORE_ID]}},
+        assistant_id=assistant.id,
+        tool_resources={"file_search": {"vector_store_ids": [VECTOR_STORE_ID]}},
     )
 
+
 def delete_files_from_vector_store(assistant, file_id):
     result = OPENAICLIENT.beta.vector_stores.file_batches.delete(
         vector_store_id=VECTOR_STORE_ID, files=file_id
@@ -103,8 +106,8 @@ def delete_files_from_vector_store(assistant, file_id):
     # You can print the status and the file counts of the batch to see the result of this operation.
     print(result)
     assistant = OPENAICLIENT.beta.assistants.update(
-    assistant_id=assistant.id,
-    tool_resources={"file_search": {"vector_store_ids": [VECTOR_STORE_ID]}},
+        assistant_id=assistant.id,
+        tool_resources={"file_search": {"vector_store_ids": [VECTOR_STORE_ID]}},
     )
 
 
@@ -133,7 +136,14 @@ def num_tokens_from_string(message, model):
 
 
 async def handle_response(
-    prompt, vykidailo, bartender, history, username, request_type, algorithm="gpt-4o", none_request=""
+    prompt,
+    vykidailo,
+    bartender,
+    history,
+    username,
+    request_type,
+    algorithm="gpt-4o",
+    none_request="",
 ):
     """
     Handle responses by appending them to a history, use OpenAI to
@@ -222,7 +232,6 @@ async def handle_response(
             table = []
             token_amount = 10000
 
-
         prompt_gpt_request_size = num_tokens_from_string(
             {"role": "user", "content": final_prompt}, "gpt-4"
         )
@@ -254,7 +263,7 @@ async def handle_response(
         deadline = time.time() + timeout_sec
         response = await asyncio.wait_for(
             _openai_call(messages=history, model=algorithm),
-            timeout=max(0.1, deadline - time.time())
+            timeout=max(0.1, deadline - time.time()),
         )
 
     except openai.APITimeoutError as e:
@@ -336,6 +345,7 @@ async def handle_response(
     else:
         return response, []
 
+
 async def get_random_cyclic_message(client):
     """
     The function `get_random_cyclic_message` returns a random cyclic message from a list of cyclic
@@ -438,7 +448,7 @@ async def chat_with_assistant(message, assistant_name):
                 logger.info(block.text.value)
                 chat_response += block.text.value
                 await discord_friendly_send(message.channel, chat_response)
-                #await message.channel.send(chat_response)
+                # await message.channel.send(chat_response)
             done = True
         elif run.status == "cancelled":
             await discord_friendly_send(message.channel, "Cos sie wywaliło")