本地化配置

2024-12-11 15:29:38 +08:00 · 2024-12-11 15:29:38 +08:00 · 8a6e754fe0
commit 8a6e754fe0
parent 6710e31ec0
34 changed files with 55 additions and 55 deletions
--- a/asr/funasr/ASR_client.py
+++ b/asr/funasr/ASR_client.py
@ -6,7 +6,7 @@ import argparse
 import json

 parser = argparse.ArgumentParser()
-parser.add_argument("--host", type=str, default="192.168.1.111", required=False, help="host ip, localhost, 0.0.0.0")
+parser.add_argument("--host", type=str, default="127.0.0.1", required=False, help="host ip, localhost, 0.0.0.0")
 parser.add_argument("--port", type=int, default=10197, required=False, help="grpc server port")
 parser.add_argument("--chunk_size", type=int, default=160, help="ms")
 parser.add_argument("--vad_needed", type=bool, default=True)
--- a/asr/funasr/funasr_client_api.py
+++ b/asr/funasr/funasr_client_api.py
@ -27,13 +27,13 @@ class Funasr_websocket_recognizer():
    '''

    parser = argparse.ArgumentParser()
-    parser.add_argument("--host", type=str, default="192.168.1.111", required=False, help="host ip, localhost, 0.0.0.0")
+    parser.add_argument("--host", type=str, default="127.0.0.1", required=False, help="host ip, localhost, 0.0.0.0")
    parser.add_argument("--port", type=int, default=10194, required=False, help="grpc server port")
    parser.add_argument("--chunk_size", type=int, default=160, help="ms")
    parser.add_argument("--vad_needed", type=bool, default=True)
    args = parser.parse_args()

-    def __init__(self, host="192.168.1.111",
+    def __init__(self, host="127.0.0.1",
                 port="10197",
                 is_ssl=True,
                 chunk_size="0, 10, 5",
--- a/cache_data/input.wav
+++ b/cache_data/input.wav
--- a/config.json
+++ b/config.json
@ -27,9 +27,9 @@
    "items": [],
    "source": {
        "automatic_player_status": true,
-        "automatic_player_url": "http://192.168.1.111:6000",
+        "automatic_player_url": "http://127.0.0.1:6000",
        "liveRoom": {
-            "enabled": true,
+            "enabled": false,
            "url": ""
        },
        "record": {
--- a/core/socket_bridge_service.py
+++ b/core/socket_bridge_service.py
@ -51,7 +51,7 @@ class SocketBridgeService:
    async def create_socket_client(self):
        sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
        try:
-            sock.connect(('192.168.1.111', 10001))
+            sock.connect(('127.0.0.1', 10001))
            sock.setblocking(True)  # 设置为阻塞模式
            return sock
        except Exception as e:
--- a/fay.db
+++ b/fay.db
--- a/gui/static/js/index.js
+++ b/gui/static/js/index.js
@ -234,7 +234,7 @@ class FayInterface {
        panelMsg: '', 
        panelReply: '', 
        robot:'static/images/Normal.gif',
-        base_url: 'http://192.168.1.111:5000',
+        base_url: 'http://127.0.0.1:5000',
        play_sound_enabled: false,
        source_record_enabled: false
      };
@ -246,7 +246,7 @@ class FayInterface {
    },
    methods: {
      initFayService() {
-        this.fayService = new FayInterface('ws://192.168.1.111:10003', this.base_url, this);
+        this.fayService = new FayInterface('ws://127.0.0.1:10003', this.base_url, this);
        this.fayService.connectWebSocket();
        this.fayService.websocket.addEventListener('open', () => {
          this.loadUserList();
--- a/gui/static/js/setting.js
+++ b/gui/static/js/setting.js
@ -170,7 +170,7 @@ new Vue({
            }],
            automatic_player_status: false,
            automatic_player_url: "",
-            host_url: "http://192.168.1.111:5000"
+            host_url: "http://127.0.0.1:5000"
        };
    },
    created() {
@ -179,7 +179,7 @@ new Vue({
    },
    methods: {
        initFayService() {
-            this.fayService = new FayInterface('ws://192.168.1.111:10003', this.host_url, this);
+            this.fayService = new FayInterface('ws://127.0.0.1:10003', this.host_url, this);
            this.fayService.connectWebSocket();
        },
        getData() {
--- a/gui/templates/setting.html
+++ b/gui/templates/setting.html
@ -106,7 +106,7 @@
            active-color="#13ce66" 
            inactive-color="#ff4949">
          </el-switch><span class="font_name" style="margin-left: 10px;">自动播放：</span>
-          <input class="section_2" v-model="automatic_player_url" placeholder="http://192.168.1.111:6000" :disabled="!configEditable" />
+          <input class="section_2" v-model="automatic_player_url" placeholder="http://127.0.0.1:6000" :disabled="!configEditable" />
        </div>
        </div>
        <div style="margin-top: 40px; text-align: center;">
--- a/gui/window.py
+++ b/gui/window.py
@ -27,7 +27,7 @@ class MainWindow(QMainWindow):
        #清空缓存
        profile = QWebEngineProfile.defaultProfile()
        profile.clearHttpCache()  
-        self.browser.load(QUrl('http://192.168.1.111:5000'))
+        self.browser.load(QUrl('http://127.0.0.1:5000'))
        self.setCentralWidget(self.browser)
        MyThread(target=self.runnable).start()

--- a/llm/VllmGPT.py
+++ b/llm/VllmGPT.py
@ -4,7 +4,7 @@ import requests

 class VllmGPT:

-    def __init__(self, host="192.168.1.111",
+    def __init__(self, host="127.0.0.1",
                 port="8000",
                 model="THUDM/chatglm3-6b",
                 max_tokens="1024"):
@ -17,7 +17,7 @@ class VllmGPT:

    def question(self,cont):
        chat_list = []
-        url = "http://192.168.1.111:8101/v1/completions"
+        url = "http://127.0.0.1:8101/v1/completions"
        req = json.dumps({
            "model": "THUDM/chatglm3-6b",
            "prompt": cont,
@ -51,6 +51,6 @@ class VllmGPT:
        return res['choices'][0]['message']['content']
    
 if __name__ == "__main__":
-    vllm = VllmGPT('192.168.1.111','8101','Qwen-7B-Chat')
+    vllm = VllmGPT('127.0.0.1','8101','Qwen-7B-Chat')
    req = vllm.question2("你叫什么名字啊今年多大了")
    print(req)
--- a/llm/agent/tools/SendWX.py
+++ b/llm/agent/tools/SendWX.py
@ -4,7 +4,7 @@ from langchain.tools import BaseTool
 import requests
 import json

-url = "http://192.168.1.111:4008/send"
+url = "http://127.0.0.1:4008/send"
 headers = {'Content-Type': 'application/json'}
 data = {
    "message": "你好",
--- a/llm/nlp_ChatGLM3.py
+++ b/llm/nlp_ChatGLM3.py
@ -25,7 +25,7 @@ def question(cont, uid=0, observation=""):
    content = {
        "prompt":"请简单回复我。" +  cont,
        "history":chat_list}
-    url = "http://192.168.1.111:8000/v1/completions"
+    url = "http://127.0.0.1:8000/v1/completions"
    req = json.dumps(content)
    headers = {'content-type': 'application/json'}
    r = requests.post(url, headers=headers, data=req)
--- a/llm/nlp_VisualGLM.py
+++ b/llm/nlp_VisualGLM.py
@ -25,7 +25,7 @@ def question(cont, uid=0, observation=""):
        filepath = os.path.join(current_working_directory, "data", filename)
        cv2.imwrite(filepath, img)
        content["image"] = filepath
-    url = "http://192.168.1.111:8080"
+    url = "http://127.0.0.1:8080"
    print(content)
    req = json.dumps(content)
    headers = {'content-type': 'application/json'}
--- a/llm/nlp_privategpt.py
+++ b/llm/nlp_privategpt.py
@ -2,7 +2,7 @@ import hashlib
 import os
 from pgpt_python.client import PrivateGPTApi

-client = PrivateGPTApi(base_url="http://192.168.1.111:8001")
+client = PrivateGPTApi(base_url="http://127.0.0.1:8001")

 index_name = "knowledge_data"
 folder_path = "llm/privategpt/knowledge_base"
--- a/main.py
+++ b/main.py
@ -120,7 +120,7 @@ if __name__ == '__main__':
    contentdb.init_db()

    #ip替换
-    if config_util.fay_url != "192.168.1.111":
+    if config_util.fay_url != "127.0.0.1":
        replace_ip_in_file("gui/static/js/index.js", config_util.fay_url)
        replace_ip_in_file("gui/static/js/setting.js", config_util.fay_url)

--- a/system.conf
+++ b/system.conf
@ -4,7 +4,7 @@
 #建议使用funasr,请依照asr/funasr/README>md的说明启动
 ASR_mode = funasr
 #ASR二选一（需要运行fay/test/funasr服务）集成达摩院asr项目、感谢中科大脑算法工程师张聪聪提供集成代码
-local_asr_ip=192.168.1.111
+local_asr_ip=127.0.0.1
 local_asr_port=10197

 # ASR二选一（第1次运行建议用这个，免费3个月）， 阿里云 实时语音识别 服务密钥（必须）https://ai.aliyun.com/nls/trans
@ -58,7 +58,7 @@ gpt_base_url=https://api.zyai.online/v1
 #gpt model engine 如：gpt-3.5-turbo、moonshot-v1-8k
 gpt_model_engine=gpt-3.5-turbo

-#gpt(fastgpt)代理(可为空，填写例子：192.168.1.111:7890)
+#gpt(fastgpt)代理(可为空，填写例子：127.0.0.1:7890)
 proxy_config=

 #通义星尘 服务密钥(NLP多选1) https://xingchen.aliyun.com/
@ -66,7 +66,7 @@ xingchen_api_key=
 xingchen_characterid=

 #ollama服务 (NLP多选1) 
-#ollama_ip 可以填写   192.168.1.111 或者 localhost
+#ollama_ip 可以填写   127.0.0.1 或者 localhost
 ollama_ip = localhost
 #ollama_model 可以填写 qwen:latest , llama2:latest , yi:lastest , pi:latest ,  gemma:latest 
 ollama_model = gemma:latest 
@ -75,8 +75,8 @@ ollama_model = gemma:latest
 coze_bot_id=
 coze_api_key=

-#启动模式common、web（服务器或docker请使用web方式，通过http://192.168.1.111:5000控制）
+#启动模式common、web（服务器或docker请使用web方式，通过http://127.0.0.1:5000控制）
 start_mode=web

 #服务器主动地址
-fay_url = 192.168.1.111
+fay_url = 127.0.0.1
--- a/test/ollama/README.md
+++ b/test/ollama/README.md
@ -19,7 +19,7 @@ ollama pull qwen:latest #阿里开源模型
 ```
 chat_module=ollama_api

-ollama_ip =  192.168.1.111 
+ollama_ip =  127.0.0.1 
 ollama_model =  phi:latest # llama2:latest , yi:lastest , pi:latest ,  gemma:latest  (开源大语言模型多选1)
 ```
 服务配置
--- a/test/ovr_lipsync/ffmpeg/doc/ffmpeg-all.html
+++ b/test/ovr_lipsync/ffmpeg/doc/ffmpeg-all.html
@ -23099,12 +23099,12 @@ an external server.
 <p>Example:
 Create a localhost stream on port 5555:
 </p><div class="example">
-<pre class="example-preformatted">ffmpeg -re -i input -f mpegts zmq:tcp://192.168.1.111:5555
+<pre class="example-preformatted">ffmpeg -re -i input -f mpegts zmq:tcp://127.0.0.1:5555
 </pre></div>

 <p>Multiple clients may connect to the stream using:
 </p><div class="example">
-<pre class="example-preformatted">ffplay zmq:tcp://192.168.1.111:5555
+<pre class="example-preformatted">ffplay zmq:tcp://127.0.0.1:5555
 </pre></div>

 <p>Streaming to multiple clients is implemented using a ZeroMQ Pub-Sub pattern.
--- a/test/ovr_lipsync/ffmpeg/doc/ffmpeg-protocols.html
+++ b/test/ovr_lipsync/ffmpeg/doc/ffmpeg-protocols.html
@ -2622,12 +2622,12 @@ an external server.
 <p>Example:
 Create a localhost stream on port 5555:
 </p><div class="example">
-<pre class="example-preformatted">ffmpeg -re -i input -f mpegts zmq:tcp://192.168.1.111:5555
+<pre class="example-preformatted">ffmpeg -re -i input -f mpegts zmq:tcp://127.0.0.1:5555
 </pre></div>

 <p>Multiple clients may connect to the stream using:
 </p><div class="example">
-<pre class="example-preformatted">ffplay zmq:tcp://192.168.1.111:5555
+<pre class="example-preformatted">ffplay zmq:tcp://127.0.0.1:5555
 </pre></div>

 <p>Streaming to multiple clients is implemented using a ZeroMQ Pub-Sub pattern.
--- a/test/ovr_lipsync/ffmpeg/doc/ffplay-all.html
+++ b/test/ovr_lipsync/ffmpeg/doc/ffplay-all.html
@ -11528,12 +11528,12 @@ an external server.
 <p>Example:
 Create a localhost stream on port 5555:
 </p><div class="example">
-<pre class="example-preformatted">ffmpeg -re -i input -f mpegts zmq:tcp://192.168.1.111:5555
+<pre class="example-preformatted">ffmpeg -re -i input -f mpegts zmq:tcp://127.0.0.1:5555
 </pre></div>

 <p>Multiple clients may connect to the stream using:
 </p><div class="example">
-<pre class="example-preformatted">ffplay zmq:tcp://192.168.1.111:5555
+<pre class="example-preformatted">ffplay zmq:tcp://127.0.0.1:5555
 </pre></div>

 <p>Streaming to multiple clients is implemented using a ZeroMQ Pub-Sub pattern.
--- a/test/ovr_lipsync/ffmpeg/doc/ffprobe-all.html
+++ b/test/ovr_lipsync/ffmpeg/doc/ffprobe-all.html
@ -11892,12 +11892,12 @@ an external server.
 <p>Example:
 Create a localhost stream on port 5555:
 </p><div class="example">
-<pre class="example-preformatted">ffmpeg -re -i input -f mpegts zmq:tcp://192.168.1.111:5555
+<pre class="example-preformatted">ffmpeg -re -i input -f mpegts zmq:tcp://127.0.0.1:5555
 </pre></div>

 <p>Multiple clients may connect to the stream using:
 </p><div class="example">
-<pre class="example-preformatted">ffplay zmq:tcp://192.168.1.111:5555
+<pre class="example-preformatted">ffplay zmq:tcp://127.0.0.1:5555
 </pre></div>

 <p>Streaming to multiple clients is implemented using a ZeroMQ Pub-Sub pattern.
--- a/test/python_connector_demo/remote_audio.py
+++ b/test/python_connector_demo/remote_audio.py
@ -58,7 +58,7 @@ def receive_audio(client):

 if __name__ == "__main__":
    client = socket.socket()
-    client.connect(("192.168.1.111", 10001))
+    client.connect(("127.0.0.1", 10001))
    # client.send(b"<username>User</username>")#指定用户名
    # client.send(b"<output>False<output>")#不回传音频（可以通过websocket 10003数字人接口接收音频http路径和本地路径）
    time.sleep(1)
--- a/test/rasa/actions/actions.py
+++ b/test/rasa/actions/actions.py
@ -62,7 +62,7 @@ class ActionGPTResponse(Action):
        current_chat={'role': 'user', 'content': tracker.latest_message.get("text")}
        history.append(current_chat)

-        url = "http://192.168.1.111:8101/v1/chat/completions"
+        url = "http://127.0.0.1:8101/v1/chat/completions"
        req = json.dumps({
            "model": "THUDM/chatglm3-6b",
            "messages": history,
@ -168,7 +168,7 @@ class ActionAskProblem(Action):
        current_chat={'role': 'user', 'content': tracker.latest_message.get("text")}
        history.append(current_chat)

-        url = "http://192.168.1.111:8101/v1/chat/completions"
+        url = "http://127.0.0.1:8101/v1/chat/completions"
        req = json.dumps({
            "model": "THUDM/chatglm3-6b",
            "messages": history,
--- a/test/test_human_ws_api.py
+++ b/test/test_human_ws_api.py
@ -10,7 +10,7 @@ import queue
 # 配置项
 config = {
    "enable_auto_get": True,  # 设置是否启用主动获取播放项
-     "url" : "192.168.1.111" #服务端Url
+     "url" : "127.0.0.1" #服务端Url
 }

 audio_queue = queue.Queue()
--- a/test/test_nlp.py
+++ b/test/test_nlp.py
@ -2,7 +2,7 @@ import requests
 import json

 def test_gpt(prompt):
-    url = 'http://192.168.1.111:5000/v1/chat/completions'  # 替换为您的接口地址
+    url = 'http://127.0.0.1:5000/v1/chat/completions'  # 替换为您的接口地址
    headers = {
        'Content-Type': 'application/json',
        'Authorization': f'Bearer YOUR_API_KEY',  # 如果您的接口需要身份验证
--- a/tts/gptsovits.py
+++ b/tts/gptsovits.py
@ -12,7 +12,7 @@ class Speech:
       pass

    def to_sample(self, text, style) :    
-        url = "http://192.168.1.111:9880"
+        url = "http://127.0.0.1:9880"
        data = {
        "text": text,
        "text_language": "zh",
--- a/tts/gptsovits_v3.py
+++ b/tts/gptsovits_v3.py
@ -15,7 +15,7 @@ class Speech:
       pass

    def to_sample(self, text, style) :    
-        url = "http://192.168.1.111:9880/tts"
+        url = "http://127.0.0.1:9880/tts"
        data = {
        "text": text,                   # str.(required) text to be synthesized
        "text_lang": "zh",              # str.(required) language of the text to be synthesized
--- a/utils/openai_api/langchain_openai_api.py
+++ b/utils/openai_api/langchain_openai_api.py
@ -17,7 +17,7 @@ def initialize_llm_chain(messages: list):
    template = "{input}"
    prompt = PromptTemplate.from_template(template)

-    endpoint_url = "http://192.168.1.111:8000/v1/chat/completions"
+    endpoint_url = "http://127.0.0.1:8000/v1/chat/completions"
    llm = ChatGLM3(
        endpoint_url=endpoint_url,
        max_tokens=8096,
--- a/utils/openai_api/openai_api.py
+++ b/utils/openai_api/openai_api.py
@ -3,7 +3,7 @@ import openai
 
 # 设置OpenAI API的密钥
 # openai.api_key = os.getenv("OPENAI_API_KEY")
-openai.base_url = "http://192.168.1.111:8000/v1/chat/completions"
+openai.base_url = "http://127.0.0.1:8000/v1/chat/completions"
 # 定义API请求的数据
 data = {
    "model": "chatglm3-6b",
--- a/utils/openai_api/openai_api_request.py
+++ b/utils/openai_api/openai_api_request.py
@ -12,7 +12,7 @@ and handle responses.

 from openai import OpenAI

-base_url = "http://192.168.1.111:8000/v1/"
+base_url = "http://127.0.0.1:8000/v1/"
 client = OpenAI(api_key="EMPTY", base_url=base_url)


@ -197,25 +197,25 @@ if __name__ == "__main__":
    # embedding()
    # function_chat()

-#     curl -X POST "http://192.168.1.111:8000/v1/chat/completions" \
+#     curl -X POST "http://127.0.0.1:8000/v1/chat/completions" \
 # -H "Content-Type: application/json" \
 # -d "{\"model\": \"chatglm3-6b\", \"messages\": [{\"role\": \"system\", \"content\": \"You are ChatGLM3, a large language model trained by Zhipu.AI. Follow the user's instructions carefully. Respond using markdown.\"}, {\"role\": \"user\", \"content\": \"你好，给我讲一个故事，大概100字\"}], \"stream\": false, \"max_tokens\": 100, \"temperature\": 0.8, \"top_p\": 0.8}"

-# curl -X POST "http://192.168.1.111:8000/v1/completions" \
+# curl -X POST "http://127.0.0.1:8000/v1/completions" \
 #      -H 'Content-Type: application/json' \
 #      -d '{"prompt": "请用20字内回复我.你今年多大了", "history": []}'
    
-# curl -X POST "http://192.168.1.111:8000/v1/completions" \
+# curl -X POST "http://127.0.0.1:8000/v1/completions" \
 #      -H 'Content-Type: application/json' \
 #      -d '{"prompt": "请用20字内回复我.你今年多大了", "history": [{"你好","你好👋！我是人工智能助手 ChatGLM-6B，很高兴见到你，欢迎问我任何问题。"}]}'


-# curl -X POST "http://192.168.1.111:8000/v1/completions" \
+# curl -X POST "http://127.0.0.1:8000/v1/completions" \
 #      -H 'Content-Type: application/json' \
 #      -d '{"prompt": "请用20字内回复我.你今年多大了", "history": [["你好","你好👋！我是人工智能助手 ChatGLM-6B，很高兴见到你，欢迎问我任何问题。"]]}'


-# curl -X POST "http://192.168.1.111:8000/v1/completions" \
+# curl -X POST "http://127.0.0.1:8000/v1/completions" \
 #      -H 'Content-Type: application/json' \
 #      -d '{"prompt": "请用20字内回复我.你今年多大了", "history": ["你好"]}'
    
--- a/utils/openai_api/openai_request.py
+++ b/utils/openai_api/openai_request.py
@ -22,7 +22,7 @@ def question(cont):
    content = {
        "prompt":"请简单回复我。" +  cont,
        "history":chat_list}
-    url = "http://192.168.1.111:8000/v1/completions"
+    url = "http://127.0.0.1:8000/v1/completions"
    req = json.dumps(content)
    headers = {'content-type': 'application/json'}
    r = requests.post(url, headers=headers, data=req)
--- a/utils/openai_api/readme.txt
+++ b/utils/openai_api/readme.txt
@ -7,10 +7,10 @@ conda install pytorch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 pytorch-cuda=
 启动
 python -m vllm.entrypoints.openai.api_server --tensor-parallel-size=1  --trust-remote-code --max-model-len 1024 --model THUDM/chatglm3-6b

-python -m vllm.entrypoints.openai.api_server --host 192.168.1.111 --port 8101 --tensor-parallel-size=1  --trust-remote-code --max-model-len 1024 --model THUDM/chatglm3-6b
+python -m vllm.entrypoints.openai.api_server --host 127.0.0.1 --port 8101 --tensor-parallel-size=1  --trust-remote-code --max-model-len 1024 --model THUDM/chatglm3-6b

 测试
-curl http://192.168.1.111:8101/v1/completions \
+curl http://127.0.0.1:8101/v1/completions \
    -H "Content-Type: application/json" \
    -d '{
        "model": "THUDM/chatglm3-6b",
@ -20,12 +20,12 @@ curl http://192.168.1.111:8101/v1/completions \
    }'

 多轮对话
-curl -X POST "http://192.168.1.111:8101/v1/completions" \
+curl -X POST "http://127.0.0.1:8101/v1/completions" \
 -H "Content-Type: application/json" \
 -d "{\"model\": \"THUDM/chatglm3-6b\",\"prompt\": \"你叫什么名字\", \"history\": [{\"role\": \"user\", \"content\": \"你出生在哪里.\"}, {\"role\": \"assistant\", \"content\": \"出生在北京\"}]}"


 多轮对话
-curl -X POST "http://192.168.1.111:8101/v1/chat/completions" \
+curl -X POST "http://127.0.0.1:8101/v1/chat/completions" \
 -H "Content-Type: application/json" \
 -d "{\"model\": \"THUDM/chatglm3-6b\", \"messages\": [{\"role\": \"system\", \"content\": \"You are ChatGLM3, a large language model trained by Zhipu.AI. Follow the user's instructions carefully. Respond using markdown.\"}, {\"role\": \"user\", \"content\": \"你好，给我讲一个故事，大概100字\"}], \"stream\": false, \"max_tokens\": 100, \"temperature\": 0.8, \"top_p\": 0.8}"
--- a/utils/openai_api/zhipu_api_request.py
+++ b/utils/openai_api/zhipu_api_request.py
@ -14,7 +14,7 @@ variable formate as xxx.xxx (just for check, not need a real key).

 from zhipuai import ZhipuAI

-base_url = "http://192.168.1.111:8000/v1/"
+base_url = "http://127.0.0.1:8000/v1/"
 client = ZhipuAI(api_key="EMP.TY", base_url=base_url)