feat: 添加数字人服务及相关部署文件

downloads/digital-human.py

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+import json
+import redis
+import uuid
+import requests
+from fastapi.responses import StreamingResponse
+from fastapi import FastAPI, Query, Request
+from pydantic import BaseModel
+from typing import Optional, List
+
+app = FastAPI()
+# 连接到Redis服务器（默认端口是6379）
+redis_instance = redis.Redis(host='localhost', port=6379, db=0)
+mock_time_created = 20230512084843
+mock_id1 = "131424542124"
+mock_id2 = "1231414141541252525"
+mock_user = "abc-123"
+dify_url = "http://<your dify ip>/v1/chat-messages"
+dify_api_key = 'Bearer <your dify api key>'
+
+
+class Message(BaseModel):
+    content: str
+
+
+class Resquest_Body(BaseModel):
+    messages: List[Message] = []
+    app_id: str
+    user: str
+    session_id: str
+    is_stream: bool
+
+
+# 对接dify，非流式传输
+def request_dify_api(question, request, conversation_id):
+    # 目标URL
+    url = dify_url
+    headers_json = {
+        'Content-Type': 'application/json',
+        'Authorization': dify_api_key
+    }
+    # 请求的数据
+    data = {
+        "inputs": {},
+        "query": question,
+        "response_mode": "blocking",
+        "user": mock_user
+    }
+
+    # 发送POST请求
+    response = requests.post(url, data=json.dumps(data), headers=headers_json)
+    data = json.loads(response)
+    return data["answer"]
+
+
+# 对接dify，流式传输
+async def generate_streaming_messages(question, request, session_id, conversation_id):
+    url = dify_url
+    headers_json = {
+        'Content-Type': 'application/json',
+        'Authorization': dify_api_key
+    }
+
+    # 请求的数据
+    request_data = {
+        "inputs": {},
+        "query": question,
+        "conversation_id": conversation_id,
+        "response_mode": "streaming",
+        "user": mock_user
+    }
+    r = requests.post(url, json=request_data, headers=headers_json, verify=False, stream=True)
+    if r.status_code != 200:
+        raise Exception(r.text)
+
+    data = ""
+
+    # 在这里，我们使用了 iter_lines 方法来逐行读取响应体
+    for line in r.iter_lines():
+        if await request.is_disconnected():
+            # 客户端已主动断开，中止流式输出，避免不必要的问题，打印报错信息方便定位
+            print("# 客户端已主动断开，中止流式输出")
+            break
+
+        # 将每一行解码为字符串
+        line = line.decode('utf-8').strip()
+
+        # 接下来我们要处理三种不同的情况：
+        #   1. 如果当前行是空行，则表明前一个数据块已接收完毕（即前文提到的，通过两个换行符结束数据块传输），我们可以对该数据块进行反序列化，并打印出对应的 content 内容；
+        #   2. 如果当前行为非空行，且以 data: 开头，则表明这是一个数据块传输的开始，我们去除 data: 前缀后，首先判断是否是结束符 [DONE]，如果不是，将数据内容保存到 data 变量；
+        #   3. 如果当前行为非空行，但不以 data: 开头，则表明当前行仍然归属上一个正在传输的数据块，我们将当前行的内容追加到 data 变量尾部；
+
+        if len(line) == 0:
+            if data:
+                try:
+                    chunk = json.loads(data)
+                except:
+                    continue
+
+                if chunk["event"] != "message":
+                    continue
+                # 如果redis里未缓存该session_id，则使用reids关联session_id和conversation_id，保证后续实现多轮对话
+                if not redis_instance.exists(session_id):
+                    conversiation_id = str(chunk["conversation_id"])
+                    redis_instance.set(session_id, conversiation_id)
+
+                    # 设置redis中key（session_id）的超时时间，一天换算86400s
+                    redis_instance.expire(session_id, 86400)
+                content = chunk["answer"]
+                new_data = {
+                    "id": mock_id2,
+                    "created": mock_time_created,
+                    "choices": [{
+                        "message": {
+                            "content": content
+                        }
+                    }]
+                }
+                yield f"data: {json.dumps(new_data, ensure_ascii=False)}\n\n"
+
+                data = ""  # 重置 data
+        elif line.startswith("data: "):
+            data = line.lstrip("data: ")
+
+            # 当数据块内容为 [DONE] 时，则表明所有数据块已发送完毕，可断开网络连接
+            if data == "[DONE]":
+                break
+        else:
+            # 仍然在追加内容时，为其添加一个换行符
+            data = data + "\n" + line
+
+            # 发送结束标记
+    yield "data: [DONE]\n\n"
+
+
+@app.post("/digital-human")
+async def digital_human(body: Resquest_Body, request: Request):
+    question = body.messages[0].content
+    session_id = body.session_id
+    conversation_id = ""
+
+    #  如果redis_instance里有缓存session_id，则说明为多轮对话，获取对应的dify中的多轮对话关键参数conversation_id
+    if redis_instance.exists(session_id):
+        # decode()用于将bytes转换为str，因为redis_instance存储的是bytes类型的数据。
+        conversation_id = redis_instance.get(session_id).decode("utf-8")
+
+    #  选择流式传输
+    if body.is_stream:
+        return StreamingResponse(
+            generate_streaming_messages(question, request, session_id, conversation_id),
+            media_type="text/event-stream",
+            headers={
+                "Cache-Control": "no-cache",
+                "Connection": "keep-alive",
+            }
+        )
+
+    #  选择非流式传输
+    answer = request_dify_api(question, request, conversation_id)
+    choices = [{
+        "index": 0,
+        "message": {
+            "content": answer
+        }
+    }]
+    return {
+        "id": mock_id1,
+        "created": mock_time_created,
+        "choices": choices
+    }
+
+
+# 启动应用
+if __name__ == "__main__":
+    import uvicorn
+
+    uvicorn.run(app, host="0.0.0.0", port=8000)

downloads/digital-human.service

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+[Unit]
+Description=Digital Human Service
+After=network.target
+
+[Service]
+Type=simple
+ExecStart=nohup python3 /digital-human.py &
+Restart=on-failure
+
+[Install]
+WantedBy=multi-user.target

downloads/digital-human.sh

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+#!/bin/bash
+
+# 回到根路径
+cd /
+rm -rf /digital-human.rar
+rm -rf /digital-human.py
+rm -rf /etc/systemd/system/digital-human.service
+
+# apt安装rar和redis-server
+sudo apt update
+sudo apt install rar redis-server
+
+#启动redis-server，并设置开机自启动 redis-server
+sudo systemctl enable redis-server
+sudo systemctl start redis-server
+
+# pip安装所需的包
+pip install redis fastapi uvicorn -i https://pypi.tuna.tsinghua.edu.cn/simple 
+
+# 从obs桶获取转发服务代码
+wget https://documentation-samples.obs.cn-north-4.myhuaweicloud.com/solution-as-code-publicbucket/solution-as-code-moudle/building-a-dify-llm-application-development-platform/human/digital-human.rar
+rar x digital-human.rar
+
+# 替换dify对应的url和api key
+sed -i "s/<your dify ip>/$1/g" digital-human.py
+sed -i "s/<your dify api key>/$2/g" digital-human.py
+
+#启动对接数字人的python服务，并设置开机自启动
+mv digital-human.service /etc/systemd/system/digital-human.service
+sudo systemctl daemon-reload
+sudo systemctl enable digital-human.service
+sudo systemctl start digital-human.service
+