beta

README.md

@@ -7,6 +7,4 @@ sdk: gradio
 app_file: app.py
 pinned: false
 license: mit
----
-
-An example chatbot using [Gradio](https://gradio.app), [`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/v0.22.2/en/index), and the [Hugging Face Inference API](https://huggingface.co/docs/api-inference/index).
+---

app.py

@@ -1,63 +0,0 @@
-import gradio as gr
-from huggingface_hub import InferenceClient
-
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
-
-
-if __name__ == "__main__":
-    demo.launch()

config.json

@@ -0,0 +1,7 @@
+{
+    "model": {
+        "api_key": "your_api_key_here",
+        "model_name": "your_model_name_here",
+        "endpoint": "your_model_endpoint_here"
+    }
+}

prompt.json

@@ -0,0 +1,3 @@
+{
+    "assistant":""
+}

requirements.txt

@@ -1 +1,135 @@
-huggingface_hub==0.22.2
+aiofiles==23.2.1
+aiohttp @ file:///Users/runner/miniforge3/conda-bld/aiohttp_1707669845082/work
+aiosignal @ file:///home/conda/feedstock_root/build_artifacts/aiosignal_1667935791922/work
+altair==5.3.0
+annotated-types @ file:///home/conda/feedstock_root/build_artifacts/annotated-types_1696634205638/work
+anyio @ file:///home/conda/feedstock_root/build_artifacts/anyio_1708355285029/work
+appnope @ file:///home/conda/feedstock_root/build_artifacts/appnope_1707233003401/work
+asttokens @ file:///home/conda/feedstock_root/build_artifacts/asttokens_1698341106958/work
+async-timeout @ file:///home/conda/feedstock_root/build_artifacts/async-timeout_1691763562544/work
+attrs @ file:///home/conda/feedstock_root/build_artifacts/attrs_1704011227531/work
+Brotli @ file:///Users/runner/miniforge3/conda-bld/brotli-split_1695989934239/work
+certifi @ file:///home/conda/feedstock_root/build_artifacts/certifi_1707022139797/work/certifi
+charset-normalizer @ file:///home/conda/feedstock_root/build_artifacts/charset-normalizer_1698833585322/work
+click==8.1.7
+comm @ file:///home/conda/feedstock_root/build_artifacts/comm_1710320294760/work
+contourpy==1.2.1
+cycler==0.12.1
+dataclasses-json @ file:///home/conda/feedstock_root/build_artifacts/dataclasses-json_1706837029949/work
+debugpy @ file:///Users/runner/miniforge3/conda-bld/debugpy_1707444662218/work
+decorator @ file:///home/conda/feedstock_root/build_artifacts/decorator_1641555617451/work
+distro==1.9.0
+dnspython==2.6.1
+email_validator==2.1.1
+exceptiongroup @ file:///home/conda/feedstock_root/build_artifacts/exceptiongroup_1704921103267/work
+executing @ file:///home/conda/feedstock_root/build_artifacts/executing_1698579936712/work
+fastapi==0.111.0
+fastapi-cli==0.0.4
+ffmpy==0.3.2
+filelock==3.13.1
+fonttools==4.52.4
+frozenlist @ file:///Users/runner/miniforge3/conda-bld/frozenlist_1702645558715/work
+fsspec==2024.3.1
+gradio==4.32.1
+gradio_client==0.17.0
+greenlet @ file:///Users/runner/miniforge3/conda-bld/greenlet_1703201714305/work
+h11==0.14.0
+httpcore==1.0.5
+httptools==0.6.1
+httpx==0.27.0
+huggingface-hub==0.21.4
+idna @ file:///home/conda/feedstock_root/build_artifacts/idna_1701026962277/work
+importlib_metadata @ file:///home/conda/feedstock_root/build_artifacts/importlib-metadata_1709821103657/work
+importlib_resources==6.4.0
+ipykernel @ file:///Users/runner/miniforge3/conda-bld/ipykernel_1708996616394/work
+ipython @ file:///home/conda/feedstock_root/build_artifacts/ipython_1709559745751/work
+jedi @ file:///home/conda/feedstock_root/build_artifacts/jedi_1696326070614/work
+Jinja2==3.1.3
+jsonpatch @ file:///home/conda/feedstock_root/build_artifacts/jsonpatch_1695536281965/work
+jsonpointer @ file:///Users/runner/miniforge3/conda-bld/jsonpointer_1695397393385/work
+jsonschema==4.22.0
+jsonschema-specifications==2023.12.1
+jupyter_client @ file:///home/conda/feedstock_root/build_artifacts/jupyter_client_1710255804825/work
+jupyter_core @ file:///Users/runner/miniforge3/conda-bld/jupyter_core_1710257589360/work
+kiwisolver==1.4.5
+langchain @ file:///home/conda/feedstock_root/build_artifacts/langchain_1710305624835/work
+langchain-community @ file:///home/conda/feedstock_root/build_artifacts/langchain-community_1710298573995/work
+langchain-core @ file:///home/conda/feedstock_root/build_artifacts/langchain-core_1710294774748/work
+langchain-text-splitters @ file:///home/conda/feedstock_root/build_artifacts/langchain-text-splitters_1709389732771/work
+langsmith @ file:///home/conda/feedstock_root/build_artifacts/langsmith_1710383848363/work
+markdown-it-py==3.0.0
+MarkupSafe==2.1.5
+marshmallow @ file:///home/conda/feedstock_root/build_artifacts/marshmallow_1709595108657/work
+matplotlib==3.9.0
+matplotlib-inline @ file:///home/conda/feedstock_root/build_artifacts/matplotlib-inline_1660814786464/work
+mdurl==0.1.2
+mpmath==1.3.0
+multidict @ file:///Users/runner/miniforge3/conda-bld/multidict_1707040780513/work
+mypy-extensions @ file:///home/conda/feedstock_root/build_artifacts/mypy_extensions_1675543315189/work
+nest_asyncio @ file:///home/conda/feedstock_root/build_artifacts/nest-asyncio_1705850609492/work
+networkx==3.2.1
+numpy @ file:///Users/runner/miniforge3/conda-bld/numpy_1707225421156/work/dist/numpy-1.26.4-cp312-cp312-macosx_11_0_arm64.whl#sha256=011d57633d659db8280a5811d62d0c5a615719a6d7cbd46a04f6ffce0c2a7db3
+openai==1.30.5
+orjson @ file:///Users/runner/miniforge3/conda-bld/orjson_1708717260543/work/target/wheels/orjson-3.9.15-cp312-cp312-macosx_11_0_arm64.whl#sha256=57fbef228e0aecf0299b0b249a966d5125bdf6bd5b3931d7e45746c397a75979
+packaging @ file:///home/conda/feedstock_root/build_artifacts/packaging_1696202382185/work
+pandas==2.2.2
+parso @ file:///home/conda/feedstock_root/build_artifacts/parso_1638334955874/work
+pexpect @ file:///home/conda/feedstock_root/build_artifacts/pexpect_1706113125309/work
+pickleshare @ file:///home/conda/feedstock_root/build_artifacts/pickleshare_1602536217715/work
+pillow==10.3.0
+platformdirs @ file:///home/conda/feedstock_root/build_artifacts/platformdirs_1706713388748/work
+prompt-toolkit @ file:///home/conda/feedstock_root/build_artifacts/prompt-toolkit_1702399386289/work
+psutil @ file:///Users/runner/miniforge3/conda-bld/psutil_1705722460205/work
+ptyprocess @ file:///home/conda/feedstock_root/build_artifacts/ptyprocess_1609419310487/work/dist/ptyprocess-0.7.0-py2.py3-none-any.whl
+pure-eval @ file:///home/conda/feedstock_root/build_artifacts/pure_eval_1642875951954/work
+pydantic @ file:///home/conda/feedstock_root/build_artifacts/pydantic_1709075187841/work
+pydantic_core @ file:///Users/runner/miniforge3/conda-bld/pydantic-core_1708700664642/work
+pydub==0.25.1
+Pygments @ file:///home/conda/feedstock_root/build_artifacts/pygments_1700607939962/work
+pyparsing==3.1.2
+PySocks @ file:///home/conda/feedstock_root/build_artifacts/pysocks_1661604839144/work
+python-dateutil @ file:///home/conda/feedstock_root/build_artifacts/python-dateutil_1709299778482/work
+python-dotenv==1.0.1
+python-multipart==0.0.9
+pytz==2024.1
+PyYAML @ file:///Users/runner/miniforge3/conda-bld/pyyaml_1695373531920/work
+pyzmq @ file:///Users/runner/miniforge3/conda-bld/pyzmq_1701783269366/work
+referencing==0.35.1
+regex==2023.12.25
+requests @ file:///home/conda/feedstock_root/build_artifacts/requests_1684774241324/work
+rich==13.7.1
+rpds-py==0.18.1
+ruff==0.4.6
+safetensors==0.4.2
+semantic-version==2.10.0
+setuptools==69.2.0
+shellingham==1.5.4
+six @ file:///home/conda/feedstock_root/build_artifacts/six_1620240208055/work
+sniffio @ file:///home/conda/feedstock_root/build_artifacts/sniffio_1708952932303/work
+SQLAlchemy @ file:///Users/runner/miniforge3/conda-bld/sqlalchemy_1709646319518/work
+stack-data @ file:///home/conda/feedstock_root/build_artifacts/stack_data_1669632077133/work
+starlette==0.37.2
+sympy==1.12
+tenacity @ file:///home/conda/feedstock_root/build_artifacts/tenacity_1692026804430/work
+tokenizers==0.15.2
+tomlkit==0.12.0
+toolz==0.12.1
+torch==2.2.1
+tornado @ file:///Users/runner/miniforge3/conda-bld/tornado_1708363367885/work
+tqdm==4.66.2
+traitlets @ file:///home/conda/feedstock_root/build_artifacts/traitlets_1710254411456/work
+transformers==4.38.2
+typer==0.12.3
+typing-inspect @ file:///home/conda/feedstock_root/build_artifacts/typing_inspect_1685820062773/work
+typing_extensions @ file:///home/conda/feedstock_root/build_artifacts/typing_extensions_1708904622550/work
+tzdata==2024.1
+ujson==5.10.0
+urllib3 @ file:///home/conda/feedstock_root/build_artifacts/urllib3_1708239446578/work
+uvicorn==0.30.0
+uvloop==0.19.0
+watchfiles==0.22.0
+wcwidth @ file:///home/conda/feedstock_root/build_artifacts/wcwidth_1704731205417/work
+websockets==11.0.3
+wheel==0.42.0
+yarl @ file:///Users/runner/miniforge3/conda-bld/yarl_1705508643525/work
+zipp @ file:///home/conda/feedstock_root/build_artifacts/zipp_1695255097490/work

skills.json

@@ -0,0 +1,38 @@
+[
+    {
+        "triggers": ["调高亮度"],
+        "action": "CMD_LIGHT_UP"
+    },
+    {
+        "triggers": ["调低亮度"],
+        "action": "CMD_LIGHT_DOWN"
+    },
+    {
+        "triggers": ["调高音量"],
+        "action": "CMD_SOUND_UP"
+    },
+    {
+        "triggers": ["调低音量"],
+        "action": "CMD_SOUND_DOWN"
+    },
+    {
+        "triggers": ["重启系统"],
+        "action": "CMD_RESTART"
+    },
+    {
+        "triggers": ["锁定屏幕"],
+        "action": "CMD_LOCK_SCREEN"
+    },
+    {
+        "triggers": ["深色模式"],
+        "action": "CMD_DARKMODE"
+    },
+    {
+        "triggers": ["调节亮度至{level}%"],
+        "action": "CMD_SET_BRIGHTNESS_{{level}}"
+    },
+    {
+        "triggers": ["设置{time}分钟的计时器"],
+        "action": "CMD_SET_TIMER_{{time}}M"
+    }
+]

src/app.py

@@ -0,0 +1,57 @@
+import gradio as gr
+from scene_recognition import recognize_scene
+from dialogue_management import manage_dialogue
+from function_trigger import trigger_function
+from config import load_config
+from skill_repository import load_skills
+
+config = load_config()
+skills = load_skills()
+
+# 场景识别功能
+def recognize(system_time, app_name, system_load):
+    system_data = {
+        'time': system_time,
+        'app_name': app_name,
+        'system_load': system_load
+    }
+    scene = recognize_scene(config, system_data)
+    return scene['type']
+
+# 对话功能
+def respond(user_input):
+    response, action = manage_dialogue(user_input, skills)
+    result = trigger_function(action, config)
+    return response,result
+
+# 创建两个独立的接口
+recognize_interface = gr.Interface(
+    fn=recognize,
+    inputs=[
+        gr.Textbox(label="System Time"),
+        gr.Textbox(label="Application Name"),
+        gr.Number(label="System Load")
+    ],
+    outputs=gr.Textbox(label="Scene Type"),
+    title="Scene Recognition",
+    description="Enter system data to recognize the scene."
+)
+
+respond_interface = gr.Interface(
+    fn=respond,
+    inputs=[
+        gr.Textbox(label="User Input"),
+    ],
+    outputs=[
+        gr.Markdown(label="AI Response"),
+        gr.Textbox(label="Action Result"),
+    ],
+    title="AI Assistant Response",
+    description="Enter your command and the recognized scene type. The AI Assistant will respond accordingly."
+)
+
+# 合并两个接口
+interface = gr.TabbedInterface([recognize_interface, respond_interface], ["Scene Recognition", "AI Assistant Response"])
+
+if __name__ == "__main__":
+    respond_interface.launch()

src/config.py

@@ -0,0 +1,6 @@
+import json
+
+def load_config():
+    with open('../config.json', 'r') as file:
+        config = json.load(file)
+    return config

src/dialogue_management.py

@@ -0,0 +1,22 @@
+from skill_repository import get_skill
+from openai import OpenAI
+import json
+
+def manage_dialogue(user_input, skills):
+    client = OpenAI(api_key="sk-6d543a8d079d4cee83f2bda58a6469d1", base_url="https://api.deepseek.com")
+    print(skills)
+    prompt = f"你是一个具有意图识别能力的助手。你需要仔细判断用户的输入中是否包含命令，当你检测到用户的命令时并且这些命令存在于命令库中时，请严格按照以下格式返回相应的传输指令代码。否则，请进行正常对话。以下是命令库中的全部命令(triggers)及其对应的动作(action)指令代码：{skills} \n严格要求：1. 只有当用户输入匹配命令库中的命令时，才返回相应的指令代码。2. 返回格式必须严格遵守：S:{{指令代码}}。不能有任何拼写或格式错误。3. 当用户输入未包含任何命令时，进行正常对话。\n示例：用户输入：能帮我重启系统吗？ \n输出：S:CMD_RESTART \n用户输入：今天天气怎么样？ \n 输出：今天天气很好，可能会有阵雨。\n 现在，请根据上述规则严格响应以下用户输入："
+    response = client.chat.completions.create(
+        model="deepseek-chat",
+        messages=[
+            {"role": "system", "content": f"{prompt}"},
+            {"role": "user", "content": f"{user_input}"},
+        ],
+        stream=False
+    )
+    answer = response.choices[0].message.content
+    print(answer)
+    if(answer[0]=='S'):
+        return "任务正在执行中...", answer[2:]
+    else:
+        return answer, None

src/flagged/log.csv

@@ -0,0 +1,3 @@
+System Time,Application Name,System Load,Scene Type,flag,username,timestamp
+12,chrome,20,default,,,2024-05-31 14:39:24.845526
+,,0,default,,,2024-05-31 15:53:45.269655

src/function_trigger.py

@@ -0,0 +1,5 @@
+def trigger_function(action, config):
+    if action == None:
+        return "No Action"
+    else:
+        return action

src/scene_recognition.py

@@ -0,0 +1,12 @@
+def recognize_scene(config, system_data):
+    time = system_data['time']
+    app_name = system_data['app_name']
+    system_load = system_data['system_load']
+    
+    # 示例场景识别逻辑，使用系统数据
+    if "office" in app_name.lower() and system_load < 50:
+        return {'type': 'office'}
+    elif "video" in app_name.lower() and system_load >= 50:
+        return {'type': 'video'}
+    else:
+        return {'type': 'default'}

src/skill_repository.py

@@ -0,0 +1,12 @@
+import json
+
+def load_skills():
+    with open('../skills.json', 'r') as file:
+        skills = json.load(file)
+    return skills
+
+def get_skill(user_input, skills):
+    for skill in skills:
+        if any(trigger in user_input for trigger in skill['triggers']):
+            return skill
+    return None