Merge pull request #391 from LlmKira/main

Docker Build

Dockerfile

@@ -4,7 +4,8 @@ FROM python:3.9-buster as builder
 RUN apt update && \
     apt install -y build-essential && \
     pip install -U pip setuptools wheel && \
-    pip install pdm
+    pip install pdm && \
+    apt install -y ffmpeg
 
 COPY pyproject.toml pdm.lock README.md /project/
 WORKDIR /project

README.md

@@ -42,11 +42,12 @@ This project uses the ToolCall feature.
 It integrates a message queuing and snapshot system, offering plugin mechanisms and authentication prior to plugin
 execution.
 
-The model adheres to the Openai Schema, other models are not supported. Please adapt using gateways independently.
+The model adheres to the Openai Format Schema. Please adapt using [gateway](https://github.com/Portkey-AI/gateway)
+or [one-api](https://github.com/songquanpeng/one-api) independently.
 
-| Demo                              |
-|-----------------------------------|
-| ![sticker](./docs/chain_chat.gif) |
+| Demo                              | Vision With Voice            |
+|-----------------------------------|------------------------------|
+| ![sticker](./docs/chain_chat.gif) | ![vision](./docs/vision.gif) |
 
 ## 🔨 Roadmap
 
@@ -56,10 +57,10 @@ The model adheres to the Openai Schema, other models are not supported. Please a
 - [x] Implementation of a more robust plugin system
 - [x] Project structure simplification
 - [x] Elimination of the Provider system
-- [x] Hook support.
-- [x] Access to TTS.
+- [x] Hook support
+- [x] Access to TTS
+- [x] Add standalone support for gpt-4-turbo and vision
 - [ ] Add LLM reference support to the plugin environment. (extract && search in text)
-- [ ] Add standalone support for Openai's new Schema. (vision)
 
 ## 📦 Features
 

app/middleware/llm_task.py

@@ -22,6 +22,7 @@
     SystemMessage,
     ToolMessage,
     AssistantMessage,
+    UserMessage,
 )
 from llmkira.openai.request import OpenAIResult, OpenAI, OpenAICredential
 from llmkira.task import TaskHeader
@@ -174,7 +175,7 @@ async def build_task_messages(self, remember=True):
         for i, message in enumerate(task_message):
             message: EventMessage
             # message format
-            user_message = message.format_user_message()
+            user_message = await message.format_user_message()
             message_run.append(user_message)
             if remember:
                 await self.message_history.append(messages=[user_message])
@@ -192,14 +193,7 @@ async def request_openai(
         :param disable_tool: 禁用函数
         :param credential: 凭证
         :return: OpenaiResult 返回结果
-        :raise RuntimeError:        # Feel time leave
-        time_feel = await TimeFeelManager(self.session_uid).get_leave()
-        if time_feel:
-            await self.remember(
-                message=SystemMessage(
-                    content=f"statu:[After {time_feel} leave, user is back]"
-                )
-            ) 无法处理消息
+        :raise RuntimeError: 消息为空
         :raise AssertionError: 无法处理消息
         :raise OpenaiError: Openai错误
         """
@@ -231,13 +225,21 @@ async def request_openai(
         # TODO:实现消息时序切片
         # 日志
         logger.info(
-            f"[x] Openai request" f"\n--message {messages} " f"\n--tools {tools}"
+            f"[x] Openai request" f"\n--message {len(messages)} " f"\n--tools {tools}"
         )
+        for msg in messages:
+            if isinstance(msg, UserMessage):
+                if len(str(msg)) < 100:
+                    logger.debug(f"Message: {msg}")
+                else:
+                    logger.debug("Message: UserMessage")
+            else:
+                logger.debug(f"Message:{msg}")
         # 必须校验
         if disable_tool or not tools:
-            logger.debug("llm_task:Tool not enable")
+            logger.debug("llm_task:no tool loaded")
             tools = None
-        # 根据模型选择不同的驱动a
+        # 根据模型选择不同的驱动
         assert messages, RuntimeError("llm_task:message cant be none...")
         messages = await validate_mock(messages)
         endpoint: OpenAI = OpenAI(

app/receiver/function.py

@@ -204,7 +204,7 @@ async def run_pending_task(task: TaskHeader, pending_task: ToolCall):
         # Resign Chain
         # 时序实现，防止过度注册
         if len(task.task_sign.tool_calls_pending) == 1:
-            if has_been_called_recently(userid=task.receiver.uid, n_seconds=5):
+            if not has_been_called_recently(userid=task.receiver.uid, n_seconds=5):
                 logger.debug(
                     "ToolCall run out, resign a new request to request stop sign."
                 )

app/receiver/slack/__init__.py

@@ -6,7 +6,7 @@
 import ssl
 from typing import List
 
-from loguru import logger, Message
+from loguru import logger
 from slack_sdk.web.async_client import AsyncWebClient
 
 from app.middleware.llm_task import OpenaiMiddleware
@@ -16,6 +16,7 @@
 from app.setting.slack import BotSetting
 from llmkira.kv_manager.file import File
 from llmkira.openai import OpenAIResult
+from llmkira.openai.cell import AssistantMessage
 from llmkira.task import Task, TaskHeader
 
 __receiver__ = "slack"
@@ -86,7 +87,10 @@ async def forward(self, receiver: Location, message: List[EventMessage]):
             await self.bot.chat_postMessage(**_message)
 
     async def reply(
-        self, receiver: Location, messages: List[Message], reply_to_message: bool = True
+        self,
+        receiver: Location,
+        messages: List[AssistantMessage],
+        reply_to_message: bool = True,
     ):
         """
         模型直转发，Message是Openai的类型

app/sender/telegram/__init__.py

@@ -21,6 +21,7 @@
     auth_reloader,
     uid_make,
     login,
+    TimerObjectContainer,
 )
 from app.setting.telegram import BotSetting
 from llmkira.kv_manager.env import EnvManager
@@ -38,7 +39,7 @@
 from app.components.credential import split_setting_string, Credential, ProviderError
 
 StepCache = StateMemoryStorage()
-
+FileWindow = TimerObjectContainer()
 TelegramTask = Task(queue=__sender__)
 
 
@@ -67,6 +68,7 @@ async def transcribe(
         files = files if files else []
         messages = messages if messages else []
         event_messages = []
+        files = [file for file in files if file]  # No None
         for index, message in enumerate(messages):
             message_text = getattr(message, "text", "empty")
             event_messages.append(
@@ -144,6 +146,19 @@ async def create_task(message: types.Message, disable_tool_action: bool = True):
                 message.text = message.text
             if not message.text:
                 return None
+            __used_file_id = []
+            photos: List[types.PhotoSize] = FileWindow.get_objects(
+                user_id=message.from_user.id
+            )
+            FileWindow.clear_objects(user_id=message.from_user.id)
+            for photo in photos:
+                __used_file_id.append(photo.file_id)
+                uploaded_file.append(
+                    await self.upload(
+                        file=photo,
+                        uid=uid_make(__sender__, message.from_user.id),
+                    )
+                )
             if message.photo:
                 uploaded_file.append(
                     await self.upload(
@@ -161,12 +176,13 @@ async def create_task(message: types.Message, disable_tool_action: bool = True):
                     )
             if message.reply_to_message:
                 if message.reply_to_message.photo:
-                    uploaded_file.append(
-                        await self.upload(
-                            message.reply_to_message.photo[-1],
-                            uid=uid_make(__sender__, message.from_user.id),
+                    if message.reply_to_message.photo[-1].file_id not in __used_file_id:
+                        uploaded_file.append(
+                            await self.upload(
+                                message.reply_to_message.photo[-1],
+                                uid=uid_make(__sender__, message.from_user.id),
+                            )
                         )
-                    )
                 if message.reply_to_message.document:
                     if message.reply_to_message.document.file_size < 1024 * 1024 * 10:
                         uploaded_file.append(
@@ -367,9 +383,16 @@ async def handle_private_msg(message: types.Message):
             自动响应私聊消息
             """
             message.text = message.text if message.text else message.caption
+
+            # Support for GPT Vision
             if not message.text:
+                if message.photo:
+                    logger.debug("Add a spc image")
+                    FileWindow.add_object(
+                        user_id=message.from_user.id, obj=message.photo[-1]
+                    )
                 return None
-
+            # 扳机
             trigger = await get_trigger_loop(
                 platform_name=__sender__,
                 message=message.text,

app/sender/util_func.py

@@ -3,6 +3,7 @@
 # @Author  : sudoskys
 # @File    : util_func.py
 # @Software: PyCharm
+import time
 from typing import Tuple, Optional, Union
 from urllib.parse import urlparse
 
@@ -111,3 +112,40 @@ async def auth_reloader(snapshot_credential: str, platform: str, user_id: str) -
                 queue_name=snap.channel,
                 task=snap.snapshot_data,
             )
+
+
+class TimerObjectContainer:
+    def __init__(self):
+        self.users = {}
+
+    def add_object(self, user_id, obj):
+        if user_id not in self.users:
+            self.users[user_id] = {}
+        self.users[user_id][obj] = time.time()
+
+    def get_objects(self, user_id, second=1200) -> list:  # 20 minutes = 1200 seconds
+        """
+        获取特定用户的对象列表，并自动删除在指定时间内添加的对象
+        :param user_id: 用户ID
+        :param second: 时间（秒）
+        """
+        if user_id not in self.users:
+            return []
+
+        user_objs = self.users[user_id]
+        valid_objects = {
+            obj: add_time
+            for obj, add_time in user_objs.items()
+            if time.time() - add_time < second
+        }
+
+        self.users[user_id] = valid_objects
+        return list(valid_objects.keys())
+
+    def clear_objects(self, user_id):
+        """
+        清空特定用户的对象
+        :param user_id: 用户ID
+        """
+        if user_id in self.users:
+            self.users[user_id] = {}

llmkira/openai/cell.py

@@ -1,10 +1,13 @@
+import base64
 from abc import ABC
 from typing import Optional, Union, List, Literal, Type, Any
 
 from docstring_parser import parse
 from json_repair import repair_json
 from pydantic import ConfigDict, BaseModel, Field, field_validator, model_validator
 
+from llmkira.openai.utils import resize_openai_image
+
 
 class FunctionChoice(BaseModel):
     name: str
@@ -170,11 +173,91 @@ class SystemMessage(Message):
     name: Optional[str] = None
 
 
+class ImageContent(BaseModel):
+    url: str
+    detail: Optional[str] = "auto"
+
+
+class ContentPart(BaseModel):
+    type: Union[str, Literal["text", "image_url"]]
+    text: Optional[str] = None
+    image_url: Optional[ImageContent] = None
+
+    @model_validator(mode="after")
+    def check_model(self):
+        if self.type == "image_url":
+            if self.image_url is None:
+                raise ValueError("image_url cannot be None")
+        if self.type == "text":
+            if self.text is None:
+                raise ValueError("text cannot be None")
+        return self
+
+    @classmethod
+    def create_text(cls, text: str):
+        """
+        Create a text content part
+        :param text: text
+        :return: ContentPart
+        """
+        assert isinstance(text, str), ValueError("text must be a string")
+        return cls(type="text", text=text)
+
+    @classmethod
+    def create_image(
+        cls, url: Union[str, bytes], detail: Literal["low", "high", "auto"] = "auto"
+    ):
+        """
+        Create an image content part
+        :param url: image url or image bytes
+        :param detail: image detail
+        :return: ContentPart
+        """
+        assert detail in ("low", "high", "auto"), ValueError(
+            "detail must be low, high or auto"
+        )
+        if isinstance(url, bytes):
+            url = resize_openai_image(url, mode=detail)
+            base64_image = base64.b64encode(url).decode("utf-8")
+            url = f"data:image/jpeg;base64,{base64_image}"
+        elif isinstance(url, str):
+            if not url.startswith("http") or not url.startswith(
+                "data:image/jpeg;base64,"
+            ):
+                raise ValueError(
+                    "url must be a http url or `data:image/jpeg;base64,` as base64 image"
+                )
+        else:
+            raise ValueError("url must be a http url or bytes")
+        return cls(type="image_url", image_url=ImageContent(url=url, detail=detail))
+
+
 class UserMessage(Message):
     role: Literal["user"] = "user"
-    content: str
+    content: Union[str, List[ContentPart]]
     name: Optional[str] = None
 
+    @field_validator("content")
+    def check_content(cls, v):
+        if isinstance(v, str):
+            return [ContentPart.create_text(text=v)]
+        elif isinstance(v, list):
+            return v
+        else:
+            raise ValueError("content must be a string or a list of ContentPart")
+
+    def add_text(self, text: str):
+        self.content.append(ContentPart.create_text(text=text))
+        return self
+
+    def add_image(
+        self,
+        image_url: Union[str, bytes],
+        detail: Literal["low", "high", "auto"] = "auto",
+    ):
+        self.content.append(ContentPart.create_image(url=image_url, detail=detail))
+        return self
+
 
 class ToolMessage(Message):
     role: Literal["tool"] = "tool"