Реализован модуль YandexGPT первой версии. Реализованы методы: генерация ответа с помощью YandexGPT и YandexGPT-lite, перевод текста с помощью YandexGPT, проверка орфографии и пунктуации с помощью YandexGPT, краткий пересказ истории чата с помощью Yandex Text Summarization Model.

src/core/config.yaml

@@ -1,5 +1,11 @@
 TELEGRAM:
     TOKEN: xxxxxxxxxxxxxxxxxxxx
+
+YANDEXGPT:
+    TOKEN: xxxxxxxxxxxxxxxxxxxx
+    CATALOGID: xxxxxxxxxxxxxxxxxxxx
+    PROMPT: Тестовый пример промпта
+
 ROLES:
   ADMIN: 0
   MODERATOR: 1

src/modules/external/yandexgpt/yandexgpt.py

@@ -0,0 +1,224 @@
+import requests
+import json
+import asyncio
+import aiohttp
+
+from ...standard.database import *
+from ...standard.config.config import *
+
+
+class YandexGPT:
+    self.token = None
+    self.catalog_id = None
+    self.language = {
+            "ru": "русский язык",
+            "en": "английский язык",
+            "de": "немецкий язык",
+            "uk": "украинский язык",
+            "es": "испанский язык",
+            "be": "белорусский язык",
+        }
+
+    def __init__(self, token, catalog_id):
+        self.token = token
+        self.catalog_id = catalog_id
+
+    async def async_token_check(self, messages, gpt, max_tokens, del_msg_id=1):
+        url = "https://llm.api.cloud.yandex.net/foundationModels/v1/tokenize"
+        while True:
+            text = ""
+            for message in messages:
+                text += message["text"]
+            try:
+                response = requests.post(url, json={"model": gpt, "text": text})
+            except Exception as e: # TODO: Переделать обработку ошибок
+                print(e)
+                continue
+            if int(response.text) < max_tokens - 2000:
+                break
+            else:
+                messages.pop(del_msg_id)
+        return messages
+
+    async def async_request(*, url, headers, prompt) -> dict:
+        async with aiohttp.ClientSession() as session:
+            async with session.post(url, headers=headers, json=prompt) as response:
+                return await response.json()
+
+    async def async_yandexgpt_lite(self, system_prompt, input_messages, stream=False, temperature=0.6, max_tokens=8000):
+        url = "https://llm.api.cloud.yandex.net/foundationModels/v1/completion"
+        gpt = f"gpt://{self.catalog_id}/yandexgpt-lite/latest"
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Api-Key {self.token}"
+        }
+
+        messages = [{"role": "system", "text": system_prompt}]
+        for message in input_messages:
+            messages.append(message)
+        messages = await self.async_token_check(messages, gpt, max_tokens)
+
+        prompt = {
+            "modelUri": gpt,
+            "completionOptions": {
+                "stream": stream,
+                "temperature": temperature,
+                "maxTokens": max_tokens
+            },
+            "messages": messages
+        }
+
+        response = requests.post(url, headers=headers, json=prompt).text
+        return json.loads(response)["result"]["alternatives"][0]["message"]["text"]
+
+    async def async_yandexgpt(self, system_prompt, input_messages, stream=False, temperature=0.6, max_tokens=8000):
+        url = "https://llm.api.cloud.yandex.net/foundationModels/v1/completion"
+        gpt = f"gpt://{self.catalog_id}/yandexgpt/latest"
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Api-Key {self.token}"
+        }
+
+        messages = [{"role": "system", "text": system_prompt}]
+        for message in input_messages:
+            messages.append(message)
+        messages = await self.async_token_check(messages, gpt, max_tokens)
+
+        prompt = {
+            "modelUri": gpt,
+            "completionOptions": {
+                "stream": stream,
+                "temperature": temperature,
+                "maxTokens": max_tokens
+            },
+            "messages": messages
+        }
+
+        response = requests.post(url, headers=headers, json=prompt).text
+        return json.loads(response)["result"]["alternatives"][0]["message"]["text"]
+
+    async def async_yandexgpt_translate(self, input_language, output_language, text):
+        input_language = self.languages[input_language]
+        output_language = self.languages[output_language]
+
+        return await self.async_yandexgpt(
+            f"Переведи на {output_language} сохранив оригинальный смысл текста. Верни только результат:",
+            [{"role": "user", "text": text}],
+            stream=False, temperature=0.6, max_tokens=8000
+        )
+
+    async def async_yandexgpt_spelling_check(self, input_language, text):
+        input_language = self.languages[input_language]
+
+        return await self.async_yandexgpt(
+            f"Проверьте орфографию и пунктуацию текста на {input_language}. Верни исправленный текст "
+            f"без смысловых искажений:",
+            [{"role": "user", "text": text}],
+            stream=False, temperature=0.6, max_tokens=8000
+        )
+
+    async def async_yandexgpt_text_history(self, messages, stream=False, temperature=0.6, max_tokens=8000):
+        url = "https://llm.api.cloud.yandex.net/foundationModels/v1/completion"
+        gpt = f"gpt://{self.catalog_id}/summarization/latest"
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Api-Key {self.token}"
+        }
+
+        messages = []
+        for message in input_messages:
+            messages.append(message)
+        messages = await self.async_token_check(messages, gpt, max_tokens, del_msg_id=0)
+
+        prompt = {
+            "modelUri": gpt,
+            "completionOptions": {
+                "stream": stream,
+                "temperature": temperature,
+                "maxTokens": max_tokens
+            },
+            "messages": messages
+        }
+
+        response = requests.post(url, headers=headers, json=prompt).text
+        return json.loads(response)["result"]["alternatives"][0]["message"]["text"]
+
+    async def async_yandex_cloud_text_to_speech(self, text, voice, emotion, speed, format, quality):
+        tts = "tts.api.cloud.yandex.net/speech/v1/tts:synthesize"
+        # TODO: Сделать функцию TTS
+        return 0
+
+    async def async_yandex_cloud_vision(self, image, features, language):
+        # TODO: Сделать функцию Vision
+        return 0
+
+    async def collect_messages(self, message_id, chat_id):
+        messages = []
+        # Собираем цепочку сообщений в формате: [{"role": "user", "text": "<Имя_пользователя>: Привет!"},
+        # {"role": "assistant", "text": "Привет!"}]
+        while True:
+            message = get_message_text(chat_id, message_id)
+            if get_message_ai_model(chat_id, start_message_id) != None:
+                messages.append({"role": "assistant", "text": message})
+            else:
+                sender_name = get_user_name(get_message_sender_id(chat_id, start_message_id))
+                messages.append({"role": "user", "text": sender_name + ": " + message})
+            message_id = get_message_answer_to_message_id(chat_id, message_id)
+            if message_id is None:
+                break
+        return messages.reverse()
+
+    async def collecting_messages_for_history(self, start_message_id, end_message_id, chat_id):
+        messages = []
+        # Собираем цепочку сообщений в формате: [{"role": "user", "text": "<Имя_пользователя>: Привет!"},
+        # {"role": "assistant", "text": "Привет!"}]
+        while True:
+            message = get_message_text(chat_id, start_message_id)
+            if get_message_ai_model(chat_id, start_message_id) != None:
+                messages.append({"role": "assistant", "text": message})
+            else:
+                sender_name = get_user_name(get_message_sender_id(chat_id, start_message_id))
+                messages.append({"role": "user", "text": sender_name + ": " + message})
+            start_message_id -= 1
+            if start_message_id <= end_message_id:
+                break
+        return messages.reverse()
+
+    async def yandexgpt_request(self, message_id = None, type = "yandexgpt-lite", chat_id = None,
+                                message_id_end = None):
+        if type == "yandexgpt-lite":
+            messages = await self.collect_messages(message_id, chat_id)
+            return await self.async_yandexgpt_lite(
+                system_prompt=get_yandexgpt_prompt(),
+                input_messages=messages,
+                stream=False, temperature=0.6, max_tokens=8000
+            )
+        elif type == "yandexgpt":
+            messages = await self.collect_messages(message_id, chat_id)
+            return await self.async_yandexgpt(
+                system_prompt=get_yandexgpt_prompt(),
+                input_messages=messages,
+                stream=False, temperature=0.6, max_tokens=8000
+            )
+        elif type == "yandexgpt-translate":
+            return await self.async_yandexgpt_translate(
+                input_language=get_message_language(chat_id, message_id),
+                output_language=get_chat_language(chat_id),
+                text=get_message_text(chat_id, message_id)
+            )
+        elif type == "yandexgpt-spelling-check":
+            return await self.async_yandexgpt_spelling_check(
+                input_language=get_message_language(chat_id, message_id),
+                text=get_message_text(chat_id, message_id)
+            )
+        elif type == "yandexgpt-text-history":
+            messages = await self.collect_messages_for_history(message_id, message_id_end, chat_id)
+            return await self.async_yandexgpt_text_history(
+                messages=messages,
+                stream=False, temperature=0.6, max_tokens=8000
+            )
+        else:
+            return "Ошибка: Неизвестный тип запроса | Error: Unknown request type"
+
+
+

src/modules/standard/config/config.py

@@ -16,4 +16,10 @@ def get_config(is_test: bool = False) -> dict:
 def get_yandexgpt_token() -> str:
     return get_config()["YANDEX_GPT_TOKEN"]
 
+def get_yandexgpt_catalog_id() -> str:
+    return get_config()["YANDEX_GPT_CATALOG_ID"]
+
+def get_yandexgpt_prompt() -> str:
+    return get_config()["YANDEX_GPT_PROMPT"]
+