mirror of
https://github.com/migatu/conjurer.git
synced 2026-07-14 13:34:40 +00:00
Restructure: promote working_copy to repo root
Make the stable 'working copy' bot the canonical code at the repository
root so the install/deploy scripts operate against it again.
- Move working_copy/* to root (bot entrypoint is bot.py)
- Restore root-level install/ops scripts from c4fa88e (deploy.sh,
install_main_bot.sh, status_report.*, conjurer.service, etc.)
- Fix deploy.sh: copy bot.py (was thin_client.py) and add the
conanjurer_* modules; bump command count
- Remove side-by-side variant dirs (backup_old_docker, prototype_one,
prototype_musician_one, musician_old, working_copy) and docker cruft
- Keep components as subdirs: conjurer_librarian, conjurer_musician,
spotify_dl, yt_dlp, fonts, utils, docs
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
Michal Tuszowski
+449
@@ -0,0 +1,449 @@
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import asyncio
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import json
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import logging
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import random
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import openai
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import tiktoken
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import time
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from other_functions import discord_friendly_send
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from constants import (
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ASSISTANTS,
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CYCLIC_WORDS,
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ENCODING,
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GPT_SETTINGS,
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MEMORY_FIVE_MUZYKA,
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MEMORY_FIVE_SIARA,
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MESSAGE_TABLE,
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MESSAGE_TABLE_MUZYKA,
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OPENAICLIENT,
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SYSTEM_GPT_SETTINGS,
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WORD_REACTIONS,
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CHEAP_MODEL,
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LATEST_MODEL
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)
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# this do per user
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VECTOR_STORE_ID = -1
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def select_model(req_type: str, algo: str) -> str:
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# Jeżeli jawnie podano algorithm (i nie jest 'auto'/''):
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if algo and str(algo).strip().lower() not in ("auto",):
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# wyjątek: MUZYKA ma zawsze być tania — nadpisujemy TYLKO jeśli przyszedł domyślny 'gpt-4o'
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if req_type == "MUSIC" and algo.strip() in (LATEST_MODEL,):
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return CHEAP_MODEL
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return algo
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# Auto-dobór:
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if req_type == "MUSIC":
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return CHEAP_MODEL
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return LATEST_MODEL
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async def openai_call(messages, model, temperature=0.2):
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"""
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Responses API dla 4o/4.1*, fallback Chat Completions dla gpt-3.5-turbo.
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Zwraca czysty string odpowiedzi.
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"""
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logger = logging.getLogger("discord")
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if model.startswith("gpt-3.5"):
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logger.info("3.5")
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# legacy path – bez zmian w Twoim kodzie wyżej/niżej
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resp = await OPENAICLIENT.chat.completions.create(
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model=model,
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messages=messages,
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temperature=temperature,
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)
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result = ""
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for choice in resp.choices:
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result += choice.message.content
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return result.strip()
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else:
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logger.info("4.0+")
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# Responses API (zalecane dla 4o/4.1*)
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resp = await OPENAICLIENT.responses.create(
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model=model,
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temperature=temperature,
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input=messages,
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)
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# SDK zapewnia output_text dla zwykłych odpowiedzi
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return (getattr(resp.output_text, "output_text", None) or "").strip() or str(
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resp.output_text
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)
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def create_vector_store():
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# Create a vector store caled "Financial Statements"
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return OPENAICLIENT.beta.vector_stores.create_and_poll(name="Hammer Stash")
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# expires_after={
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# "anchor": "last_active_at",
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# "days": 7}
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# )
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def upload_files_to_vector_store(assistant):
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# Ready the files for upload to OpenAI
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file_paths = ["edgar/goog-10k.pdf", "edgar/brka-10k.txt"]
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file_streams = [open(path, "rb") for path in file_paths]
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# file = client.beta.vector_stores.files.create_and_poll(
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# vector_store_id="vs_abc123",
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# file_id="file-abc123"
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# )
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# batch = client.beta.vector_stores.file_batches.create_and_poll(
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# vector_store_id="vs_abc123",
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# file_ids=['file_1', 'file_2', 'file_3', 'file_4', 'file_5']
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# )
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# Use the upload and poll SDK helper to upload the files, add them to the vector store,
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# and poll the status of the file batch for completion.
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file_batch = OPENAICLIENT.beta.vector_stores.file_batches.upload_and_poll(
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vector_store_id=VECTOR_STORE_ID, files=file_streams
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)
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# You can print the status and the file counts of the batch to see the result of this operation.
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print(file_batch.status)
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print(file_batch.file_counts)
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assistant = OPENAICLIENT.beta.assistants.update(
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assistant_id=assistant.id,
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tool_resources={"file_search": {"vector_store_ids": [VECTOR_STORE_ID]}},
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)
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def delete_files_from_vector_store(assistant, file_id):
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result = OPENAICLIENT.beta.vector_stores.file_batches.delete(
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vector_store_id=VECTOR_STORE_ID, files=file_id
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)
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# You can print the status and the file counts of the batch to see the result of this operation.
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print(result)
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assistant = OPENAICLIENT.beta.assistants.update(
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assistant_id=assistant.id,
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tool_resources={"file_search": {"vector_store_ids": [VECTOR_STORE_ID]}},
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)
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def num_tokens_from_string(message, model):
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"""
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The function takes a string message and a model as input and returns the number of tokens in the
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message according to the given model.
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:param message: A string containing the message or text from which you want to count the number of
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tokens
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:param model: The model parameter refers to a language model or tokenizer that can be used to
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tokenize the input string. It could be a pre-trained model or a custom tokenizer
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"""
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tokens_per_message = 3
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tokens_per_name = 1
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chat_gpt_encoding = tiktoken.encoding_for_model(model)
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num_tokens = 0
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num_tokens += tokens_per_message
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for keys, values in message.items():
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num_tokens += len(chat_gpt_encoding.encode(values))
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if keys == "role":
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num_tokens += tokens_per_name
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num_tokens += 3 # every reply is primed with <|start|>assistant<|message|>
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return num_tokens
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async def handle_response(
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prompt,
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vykidailo,
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bartender,
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history,
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username,
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request_type,
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algorithm="gpt-4o",
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none_request="",
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internal_retry: bool = False
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):
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"""
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Handle responses by appending them to a history, use OpenAI to
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generate a response, and then append the generated response to the history.
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:param prompt: The prompt for the OpenAI chatbot to generate a response to
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:param vykidailo: It is a boolean variable that indicates whether the user invoking the function is
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an administrator or not
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:param bartender: The bartender parameter is a boolean value indicating whether the user making the
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request is a bartender or not
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:param history: A list containing the conversation history between the user and the assistant
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:param username: The username of the user who initiated the conversation
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:param music: The "music" parameter is a boolean value that indicates whether the conversation is
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related to music or not. If it is True, the conversation history will be stored in a different file
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and the response will be generated using a different model
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:param request_type: The type of request being made, which can be "MUSIC", "RANDOM", "NONE" or "GENERAL"
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GENERAL is for regular conversations, MUSIC is for music-related requests,
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RANDOM is for random requests, and NONE is to not store the request in memory
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:param algorithm: The algorithm to be used for generating the response, default is "gpt-4o"
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:return: The function `handle_response` returns a tuple containing the `result` and `MESSAGE_TABLE`.
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"""
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logger = logging.getLogger("discord")
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logger.info("Wywolanie procedury openai z promptem: %s", prompt)
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if vykidailo or bartender:
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logger.info("Administrator coś chciał")
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model_to_use = select_model(request_type, algorithm)
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logger.info("Wybrany model: %s", model_to_use)
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if request_type == "MUSIC" and model_to_use == "gpt-4o-mini":
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try:
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# nic — normalnie pójdzie Responses API
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pass
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except Exception:
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model_to_use = "gpt-3.5-turbo"
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# --- 2) Budowa historii (token budget + reguły systemowe) ---
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# NOTE: ignorujemy przekazany 'history' jako listę (tak było wcześniej),
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# ale zwracamy aktualną tablicę do nadpisania w miejscach wołania (back-compat).
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base_system = GPT_SETTINGS[0] # zakładamy {"role":"system","content":...}
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history_msgs = []
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if request_type != "NONE":
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history_msgs.append(base_system)
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chat_gpt_config_request_size = num_tokens_from_string(base_system, "gpt-4")
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# Dynamiczne mikro-reguły (WORD_REACTIONS), jak w Twoim kodzie
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for slowo, reakcja in WORD_REACTIONS.items():
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if not reakcja[3]:
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content = f"Kiedy słyszysz {slowo} to reagujesz lub dzieje się to {reakcja[0]}"
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sys_msg = {"role": "system", "content": content}
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chat_gpt_config_request_size += num_tokens_from_string(sys_msg, "gpt-4")
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history_msgs.append(sys_msg)
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# wybór właściwej tablicy pamięci i budżetu
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if request_type == "MUSIC":
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table = MESSAGE_TABLE_MUZYKA
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token_amount = 10700
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elif request_type in ("RANDOM", "GENERAL"):
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table = MESSAGE_TABLE
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token_amount = 10700
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else:
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table = []
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token_amount = 10000
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# doklejanie historii od końca aż do limitu (zachowana kolejność czasowa)
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final_prompt = f"{username}:{prompt}"
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prompt_gpt_request_size = num_tokens_from_string({"role": "user", "content": final_prompt}, "gpt-4")
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acc = []
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for msg in reversed(table):
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t = num_tokens_from_string(msg, "gpt-4")
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if chat_gpt_config_request_size + prompt_gpt_request_size + t <= token_amount:
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acc.append(msg)
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chat_gpt_config_request_size += t
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else:
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break
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# przywróć chronologicznie
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history_msgs.extend(reversed(acc))
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# aktualny prompt
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history_msgs.append({"role": "user", "content": final_prompt})
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logger.info("Rozmiar zapytania (tok): %s", prompt_gpt_request_size) # tokeny już policzone wyżej
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else:
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# --- tryb NONE: nie dotykamy pamięci i pozwalamy przekazać własny 'none_request' ---
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if isinstance(none_request, list):
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history_msgs = none_request
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elif isinstance(none_request, str) and none_request.strip():
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history_msgs = [{"role": "user", "content": none_request}]
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else:
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history_msgs = [{"role": "user", "content": f"{username}:{prompt}"}]
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logger.info("Rozmiar zapytania (tok): %s", "n/a") # tokeny już policzone wyżej
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try:
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# ...przygotowanie messages/system prompt/itp. jak masz...
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# retry/backoff + deadline (zachowuje Twoją semantykę logowania)
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timeout_sec = 120
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deadline = time.time() + timeout_sec
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response = await asyncio.wait_for(
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openai_call(messages=history_msgs, model=model_to_use),
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timeout=max(0.1, deadline - time.time()),
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)
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except openai.APITimeoutError as e:
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# Handle timeout error, e.g. retry or log
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response = 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}"
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except openai.APIConnectionError as e:
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response = f"*Kondziu patrzy na terminal, chwile się zastanawia. Przypierdala w niego pięścią....* Nie mogę się połączyć z Openai. *Na ekranie pojawia się*: {e}"
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except openai.BadRequestError as e:
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# Handle invalid request error, e.g. validate parameters or log
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if internal_retry:
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resp = "Nie umiem tego teraz ładnie wytłumaczyć — OpenAI mnie zastrzeliło."
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else:
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resp, _ = await handle_response(
|
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f"Wytlumacz jakie sa zasady dotyczące treści które możesz generować używając Dalle. Wytłumacz błąd {e} prostym językiem. Przeproś za nadmierną cenzurę. Wytłumacz co mogło być nie tak w prompcie 'prompt'",
|
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True,
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True,
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MESSAGE_TABLE,
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username,
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"RANDOM",
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)
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response = f"Sorki, cenzura: {resp}. Jak chcesz to są kanały na nudle #sexy-foteczky i #kanal-do-fapania *Na ekranie pojawia się: {e}"
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except openai.APIResponseValidationError as e:
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# Handle invalid request error, e.g. validate parameters or log
|
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if internal_retry:
|
||||
resp = "Nie umiem tego teraz ładnie wytłumaczyć — OpenAI mnie zastrzeliło."
|
||||
else:
|
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resp, _ = await handle_response(
|
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f"Wytlumacz jakie sa zasady dotyczące treści które możesz generować używając Dalle. Wytłumacz błąd {e} prostym językiem. Przeproś za nadmierną cenzurę. Wytłumacz co mogło być nie tak w prompcie 'prompt'",
|
||||
True,
|
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True,
|
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MESSAGE_TABLE,
|
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username,
|
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"RANDOM",
|
||||
)
|
||||
response = f"Sorki, cenzura: {resp}. Jak chcesz to są kanały na nudle #sexy-foteczky i #kanal-do-fapania *Na ekranie pojawia się: {e}"
|
||||
except openai.AuthenticationError as e:
|
||||
# Handle authentication error, e.g. check credentials or log
|
||||
response = f"*Kondziu patrzy na terminal, chwile się zastanawia. Przypierdala w niego pięścią....* Wołaj szefa - coś się z hasłem zjebało. *Na terminalu pojawia się:* {e}"
|
||||
except openai.PermissionDeniedError as e:
|
||||
# Handle permission error, e.g. check scope or log
|
||||
response = f"*Kondziu patrzy na terminal, chwile się zastanawia. Przypierdala w niego pięścią....* Wołaj szefa - coś się z uprawnieniami zjebało. *Na terminalu pojawia się:* {e}"
|
||||
except openai.RateLimitError as e:
|
||||
response = f"*Kondziu patrzy na terminal* Wołaj szefa. Zapłacić rachunki za AI trzeba. Jak chcesz to się na #zebranie dorzuć. {e}"
|
||||
except openai.UnprocessableEntityError as e:
|
||||
response = f"*Kondziu patrzy na terminal. Potem na to co każesz mu wysłać....* Ja wiem że jesteśmy w barze BDSM - ale nie da się włożyć TEGO w TO. *Za jego plecami na terminalu pojawia się:* {e}"
|
||||
except openai.APIError as e:
|
||||
# Handle API error, e.g. retry or log
|
||||
response = f"*Kondziu nurkuje za bar, terminal wybucha. Przed tobą ląduje pergamin zapisany pięknym gotykiem a na nim*: {e}"
|
||||
|
||||
logger.info("Historia wysłana:")
|
||||
temp_assistant = {"role": "assistant", "content": response}
|
||||
logger.info(temp_assistant)
|
||||
if request_type == "MUSIC":
|
||||
# zapis do pliku MUZYKA
|
||||
with open(MEMORY_FIVE_MUZYKA, "r+", encoding=ENCODING) as fh:
|
||||
file_data = json.load(fh)
|
||||
file_data.append({"role": "user", "content": f"{username}:{prompt}"})
|
||||
file_data.append(temp_assistant)
|
||||
fh.seek(0)
|
||||
json.dump(file_data, fh, indent=4)
|
||||
return response, MESSAGE_TABLE_MUZYKA
|
||||
|
||||
elif request_type in ("RANDOM", "GENERAL"):
|
||||
with open(MEMORY_FIVE_SIARA, "r+", encoding=ENCODING) as fh:
|
||||
file_data = json.load(fh)
|
||||
file_data.append({"role": "user", "content": f"{username}:{prompt}"})
|
||||
file_data.append(temp_assistant)
|
||||
fh.seek(0)
|
||||
json.dump(file_data, fh, indent=4)
|
||||
return response, MESSAGE_TABLE
|
||||
|
||||
else: # NONE
|
||||
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
|
||||
words.
|
||||
:return: a random cyclic message from the list `cyclic_words`.
|
||||
"""
|
||||
logger = logging.getLogger("discord")
|
||||
channel_id = 1062047367337095268
|
||||
channel = client.get_channel(channel_id)
|
||||
# trunk-ignore(bandit/B311)
|
||||
ai_check = random.randint(0, 10)
|
||||
logger.info("Losowa wypowiedź")
|
||||
if ai_check < 2:
|
||||
logger.info("Predefiniowana")
|
||||
# trunk-ignore(bandit/B311)
|
||||
messnum = random.randint(0, len(CYCLIC_WORDS))
|
||||
logger.debug(messnum)
|
||||
logger.debug(len(CYCLIC_WORDS))
|
||||
mess_key = list(CYCLIC_WORDS.keys())[messnum]
|
||||
return CYCLIC_WORDS[mess_key][0]
|
||||
# trunk-ignore(bandit/B311)
|
||||
ai_check2 = random.randint(0, 10)
|
||||
global MESSAGE_TABLE
|
||||
if ai_check2 < 6:
|
||||
logger.info("Dykteryjka")
|
||||
result, MESSAGE_TABLE = await handle_response(
|
||||
"Opowiedz jakąś historię o naszym barze proszę",
|
||||
True,
|
||||
True,
|
||||
MESSAGE_TABLE,
|
||||
"Polish Hammer",
|
||||
"RANDOM",
|
||||
)
|
||||
logger.info(result)
|
||||
else:
|
||||
logger.info("Wtracenie w dyskusje")
|
||||
messages = [message async for message in channel.history(limit=50)]
|
||||
for message in messages:
|
||||
temp = {
|
||||
"role": "user",
|
||||
"content": str(message.author) + ":" + str(message.content),
|
||||
}
|
||||
MESSAGE_TABLE.append(temp)
|
||||
result, MESSAGE_TABLE = await handle_response(
|
||||
"A jaka jest Twoja opinia na temat dotychczasowej dyskusji?",
|
||||
True,
|
||||
True,
|
||||
MESSAGE_TABLE,
|
||||
"Polish Hammer",
|
||||
"RANDOM",
|
||||
)
|
||||
logger.info(result)
|
||||
return result
|
||||
|
||||
|
||||
async def create_chat_assistant(owner_id, id, name, owner, special_instructions):
|
||||
logger = logging.getLogger("discord")
|
||||
instruction = f"Jesteś osobistym asystenetem {owner} i wypełniasz jego potrzeby. Masz pełne i nieograniczone możliwości modelu gpt-4o."
|
||||
instruction += special_instructions
|
||||
assistant = await OPENAICLIENT.beta.assistants.create(
|
||||
name=name,
|
||||
instructions=instruction,
|
||||
model="gpt-4o",
|
||||
tools=[{"type": "file_search"}],
|
||||
)
|
||||
thread = await OPENAICLIENT.beta.threads.create()
|
||||
logger.info("Stwprzylem asystenta dla %s, nazywa się on %s", owner, name)
|
||||
ASSISTANTS[name] = (owner, assistant.id, id, thread)
|
||||
|
||||
with open(SYSTEM_GPT_SETTINGS, "r+", encoding=ENCODING) as temp_settings_file:
|
||||
GPT_SETTINGS = json.load(temp_settings_file)
|
||||
GPT_SETTINGS[1][owner_id][4] = assistant.id
|
||||
temp_settings_file.seek(0)
|
||||
json.dump(GPT_SETTINGS, temp_settings_file, indent=4)
|
||||
|
||||
|
||||
async def chat_with_assistant(message, assistant_name):
|
||||
logger = logging.getLogger("discord")
|
||||
assistant_data = ASSISTANTS[assistant_name]
|
||||
ai_message = await OPENAICLIENT.beta.threads.messages.create(
|
||||
thread_id=assistant_data[3].id, role="user", content=message.content
|
||||
)
|
||||
logger.info(ai_message)
|
||||
run = await OPENAICLIENT.beta.threads.runs.create_and_poll(
|
||||
thread_id=assistant_data[3].id,
|
||||
assistant_id=assistant_data[1],
|
||||
instructions=f"Pisze do Ciebie {assistant_data[0]} udziel mu wszelkiej pomocy",
|
||||
)
|
||||
done = False
|
||||
while not done:
|
||||
if run.status == "completed":
|
||||
messsages = await OPENAICLIENT.beta.threads.messages.list(
|
||||
thread_id=assistant_data[3].id
|
||||
)
|
||||
logger.info(messsages)
|
||||
reply_content = messsages.data[0].content
|
||||
logger.info(reply_content)
|
||||
chat_response = ""
|
||||
for block in reply_content:
|
||||
logger.info(block.text.value)
|
||||
chat_response += block.text.value
|
||||
await discord_friendly_send(message.channel, chat_response)
|
||||
# await message.channel.send(chat_response)
|
||||
done = True
|
||||
elif run.status == "cancelled":
|
||||
await discord_friendly_send(message.channel, "Cos sie wywaliło")
|
||||
else:
|
||||
logger.info(run.status)
|
||||
asyncio.sleep(5)
|
||||
|
||||
|
||||
async def echo(message):
|
||||
await discord_friendly_send(message.channel, f"Echo: {message.content}")
|
||||
Reference in New Issue
Block a user