feat: 添加数字人服务及相关部署文件

digital-human.py

@@ -1,258 +1,176 @@
-"""
-数字人对接中转服务
------------------
-作为客户端与 Dify LLM 平台之间的中间转发层，处理请求路由、
-认证转发及 Redis 缓存，提升响应效率并保护后端 API Key。
-
-环境变量：
-    DIFY_URL      - Dify 服务地址，如 https://atwdify.antiwearvalve.com/v1
-    DIFY_API_KEY  - Dify API 密钥，如 app-PDkSHiHZsZIluoZF7N2OlNZM
-    REDIS_HOST    - Redis 主机地址，默认 localhost
-    REDIS_PORT    - Redis 端口，默认 6379
-"""
-
-import os
 import json
-import hashlib
-import logging
-from contextlib import asynccontextmanager
-from typing import Any, Dict, Optional
-
-import httpx
 import redis
-from redis.exceptions import ConnectionError as RedisConnectionError
+import uuid
-from fastapi import FastAPI, HTTPException, Request
+import requests
-from fastapi.responses import JSONResponse
+from fastapi.responses import StreamingResponse
+from fastapi import FastAPI, Query, Request
+from pydantic import BaseModel
+from typing import Optional, List
 
-# ──────────────────────────────────────────────────────────────
+app = FastAPI()
-# 日志配置
+# 连接到Redis服务器（默认端口是6379）
-# ──────────────────────────────────────────────────────────────
+redis_instance = redis.Redis(host='localhost', port=6379, db=0)
-logging.basicConfig(
+mock_time_created = 20230512084843
-    level=logging.INFO,
+mock_id1 = "131424542124"
-    format="%(asctime)s [%(levelname)s] %(name)s - %(message)s",
+mock_id2 = "1231414141541252525"
-)
+mock_user = "abc-123"
-logger = logging.getLogger("digital-human")
+dify_url = "http://<your dify ip>/v1/chat-messages"
-
+dify_api_key = 'Bearer <your dify api key>'
-# ──────────────────────────────────────────────────────────────
-# 应用配置（从环境变量读取）
-# ──────────────────────────────────────────────────────────────
-DIFY_URL: str = os.getenv("DIFY_URL", "")
-DIFY_API_KEY: str = os.getenv("DIFY_API_KEY", "")
-REDIS_HOST: str = os.getenv("REDIS_HOST", "localhost")
-REDIS_PORT: int = int(os.getenv("REDIS_PORT", "6379"))
-
-# 验证必填配置
-if not DIFY_URL or not DIFY_API_KEY:
-    logger.warning(
-        "DIFY_URL 或 DIFY_API_KEY 未配置，"
-        "部分功能可能不可用。请通过环境变量设置。"
-    )
-
-# ──────────────────────────────────────────────────────────────
-# Redis 客户端（懒加载）
-# ──────────────────────────────────────────────────────────────
-_redis_client: Optional[redis.Redis] = None
 
 
-def get_redis() -> redis.Redis:
+class Message(BaseModel):
-    """获取 Redis 客户端实例（延迟初始化）。"""
+    content: str
-    global _redis_client
-    if _redis_client is None:
-        _redis_client = redis.Redis(
-            host=REDIS_HOST,
-            port=REDIS_PORT,
-            decode_responses=True,
-            socket_connect_timeout=5,
-        )
-    return _redis_client
 
 
-def get_cache_key(payload: Dict[str, Any]) -> str:
+class Resquest_Body(BaseModel):
-    """根据请求体生成 Redis 缓存键。"""
+    messages: List[Message] = []
-    raw = json.dumps(payload, sort_keys=True)
+    app_id: str
-    return f"dh:cache:{hashlib.md5(raw.encode()).hexdigest()}"
+    user: str
+    session_id: str
+    is_stream: bool
 
 
-# ──────────────────────────────────────────────────────────────
+# 对接dify，非流式传输
-# FastAPI 应用生命周期
+def request_dify_api(question, request, conversation_id):
-# ──────────────────────────────────────────────────────────────
+    # 目标URL
-@asynccontextmanager
+    url = dify_url
-async def lifespan(app: FastAPI):
+    headers_json = {
-    """应用启动 / 关闭钩子。"""
+        'Content-Type': 'application/json',
-    logger.info("数字人对接服务启动中...")
+        'Authorization': dify_api_key
-    logger.info(f"  Dify URL : {DIFY_URL}")
+    }
-    logger.info(f"  Redis    : {REDIS_HOST}:{REDIS_PORT}")
+    # 请求的数据
-
+    data = {
-    # 尝试连接 Redis（仅记录，不阻塞启动）
+        "inputs": {},
-    try:
+        "query": question,
-        get_redis().ping()
+        "response_mode": "blocking",
-        logger.info("Redis 连接成功")
+        "user": mock_user
-    except RedisConnectionError as e:
-        logger.warning(f"Redis 连接失败（服务将继续运行）: {e}")
-
-    yield
-
-    logger.info("数字人对接服务已关闭")
-
-
-app = FastAPI(
-    title="数字人对接中转服务",
-    version="1.0.0",
-    description="对接 Dify LLM 平台的数字人应用中转服务",
-    lifespan=lifespan,
-)
-
-
-# ──────────────────────────────────────────────────────────────
-# 健康检查
-# ──────────────────────────────────────────────────────────────
-@app.get("/")
-async def root():
-    """服务健康检查端点。"""
-    return {
-        "status": "ok",
-        "service": "digital-human-relay",
-        "version": "1.0.0",
     }
 
+    # 发送POST请求
+    response = requests.post(url, data=json.dumps(data), headers=headers_json)
+    data = json.loads(response)
+    return data["answer"]
 
-@app.get("/health")
-async def health_check():
-    """详细健康检查（包含 Redis 状态）。"""
-    redis_ok = False
-    try:
-        get_redis().ping()
-        redis_ok = True
-    except Exception:
-        pass
 
-    return {
+# 对接dify，流式传输
-        "status": "healthy" if redis_ok else "degraded",
+async def generate_streaming_messages(question, request, session_id, conversation_id):
-        "redis": "connected" if redis_ok else "disconnected",
+    url = dify_url
-        "dify_configured": bool(DIFY_URL and DIFY_API_KEY),
+    headers_json = {
+        'Content-Type': 'application/json',
+        'Authorization': dify_api_key
     }
 
-
+    # 请求的数据
-# ──────────────────────────────────────────────────────────────
+    request_data = {
-# Dify 响应格式转 OpenAI 兼容格式
+        "inputs": {},
-# ──────────────────────────────────────────────────────────────
+        "query": question,
-def dify_to_openai(dify_resp: Dict[str, Any]) -> Dict[str, Any]:
+        "conversation_id": conversation_id,
-    """
+        "response_mode": "streaming",
-    将 Dify /chat-messages 的响应转换为 OpenAI /chat/completions 兼容格式。
+        "user": mock_user
-    Dify 响应示例: { answer: "...", conversation_id: "...", task_id: "..." }
-    OpenAI 目标格式: { id, model, choices: [{ message: { role: "assistant", content: "..." } }] }
-    """
-    return {
-        "id": f"chatcmpl-{dify_resp.get('task_id', 'unknown')}",
-        "object": "chat.completion",
-        "created": 0,
-        "model": "dify",
-        "choices": [
-            {
-                "index": 0,
-                "message": {
-                    "role": "assistant",
-                    "content": dify_resp.get("answer", ""),
-                },
-                "finish_reason": "stop",
-            }
-        ],
-        "usage": {
-            "prompt_tokens": 0,
-            "completion_tokens": 0,
-            "total_tokens": 0,
-        },
     }
+    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
-# 核心转发接口
+    for line in r.iter_lines():
-# ──────────────────────────────────────────────────────────────
+        if await request.is_disconnected():
-@app.post("/v1/chat/completions")
+            # 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
-async def chat_completions(request: Request):
+            print("# 客户端已主动断开，中止流式输出")
-    """
-    接收 OpenAI 兼容格式请求，转换为 Dify /chat-messages 格式后转发。
-    OpenAI 格式: { model, messages: [{role, content}], stream }
-    Dify 格式:   { query, user, response_mode, inputs }
-    """
-    body = await request.json()
-
-    # ── 格式转换：OpenAI -> Dify ──────────────────────────────
-    # 提取用户最新消息
-    user_content = ""
-    for msg in reversed(body.get("messages", [])):
-        if msg.get("role") == "user":
-            user_content = msg.get("content", "")
             break
 
-    if not user_content:
+        # 将每一行解码为字符串
-        raise HTTPException(status_code=400, detail="未找到用户消息")
+        line = line.decode('utf-8').strip()
 
-    # 生成或复用 user 标识（用于 Dify 会话上下文）
+        # 接下来我们要处理三种不同的情况：
-    dify_user = body.get("user", "anonymous")
+        #   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；
-    response_mode = "blocking" if not body.get("stream", False) else "streaming"
+        #   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；
 
-    # 构建 Dify 请求体
+        if len(line) == 0:
-    dify_payload = {
+            if data:
-        "query": user_content,
-        "user": dify_user,
-        "response_mode": response_mode,
-        "inputs": body.get("inputs", {}),
-    }
-
-    # 若应用要求 inputs 字段但为空，补上空对象
-    if "inputs" not in dify_payload or dify_payload["inputs"] is None:
-        dify_payload["inputs"] = {}
-
-    # ── 检查 Redis 缓存（基于 OpenAI 原始请求体）──────────────
-    cache_key = get_cache_key(body)
                 try:
-        cached = get_redis().get(cache_key)
+                    chunk = json.loads(data)
-        if cached:
+                except:
-            logger.info(f"缓存命中: {cache_key}")
+                    continue
-            return dify_to_openai(json.loads(cached))
-    except RedisConnectionError:
-        logger.warning("Redis 不可用，跳过缓存读取")
 
-    # ── 转发到 Dify ─────────────────────────────────────────
+                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={
-        "Authorization": f"Bearer {DIFY_API_KEY}",
+                "Cache-Control": "no-cache",
-        "Content-Type": "application/json",
+                "Connection": "keep-alive",
             }
-    dify_endpoint = f"{DIFY_URL.rstrip('/')}/chat-messages"
-
-    try:
-        async with httpx.AsyncClient(timeout=120.0) as client:
-            resp = await client.post(dify_endpoint, json=dify_payload, headers=headers)
-            resp.raise_for_status()
-            result = resp.json()
-    except httpx.HTTPStatusError as e:
-        logger.error(f"Dify 返回错误 {e.response.status_code}: {e.response.text}")
-        raise HTTPException(
-            status_code=e.response.status_code,
-            detail=f"Dify 请求失败: {e.response.text}",
         )
-    except httpx.RequestError as e:
-        logger.error(f"无法连接 Dify 服务: {e}")
-        raise HTTPException(status_code=502, detail=f"无法连接 Dify 服务: {e}")
 
-    # ── 写入缓存（存 Dify 原始格式）───────────────────────────
+    #  选择非流式传输
-    try:
+    answer = request_dify_api(question, request, conversation_id)
-        get_redis().setex(cache_key, 300, json.dumps(result))
+    choices = [{
-    except RedisConnectionError:
+        "index": 0,
-        pass
+        "message": {
-
+            "content": answer
-    # ── 响应转 OpenAI 兼容格式 ─────────────────────────────────
+        }
-    return dify_to_openai(result)
+    }]
+    return {
+        "id": mock_id1,
+        "created": mock_time_created,
+        "choices": choices
+    }
 
 
-# ──────────────────────────────────────────────────────────────
+# 启动应用
-# 错误处理器
+if __name__ == "__main__":
-# ──────────────────────────────────────────────────────────────
+    import uvicorn
-@app.exception_handler(Exception)
+
-async def global_exception_handler(request: Request, exc: Exception):
+    uvicorn.run(app, host="0.0.0.0", port=8000)
-    logger.exception(f"未处理的异常: {exc}")
-    return JSONResponse(
-        status_code=500,
-        content={"error": "Internal Server Error", "detail": str(exc)},
-    )

digital-human2.py

@@ -0,0 +1,258 @@
+"""
+数字人对接中转服务
+-----------------
+作为客户端与 Dify LLM 平台之间的中间转发层，处理请求路由、
+认证转发及 Redis 缓存，提升响应效率并保护后端 API Key。
+
+环境变量：
+    DIFY_URL      - Dify 服务地址，如 https://atwdify.antiwearvalve.com/v1
+    DIFY_API_KEY  - Dify API 密钥，如 app-PDkSHiHZsZIluoZF7N2OlNZM
+    REDIS_HOST    - Redis 主机地址，默认 localhost
+    REDIS_PORT    - Redis 端口，默认 6379
+"""
+
+import os
+import json
+import hashlib
+import logging
+from contextlib import asynccontextmanager
+from typing import Any, Dict, Optional
+
+import httpx
+import redis
+from redis.exceptions import ConnectionError as RedisConnectionError
+from fastapi import FastAPI, HTTPException, Request
+from fastapi.responses import JSONResponse
+
+# ──────────────────────────────────────────────────────────────
+# 日志配置
+# ──────────────────────────────────────────────────────────────
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s [%(levelname)s] %(name)s - %(message)s",
+)
+logger = logging.getLogger("digital-human")
+
+# ──────────────────────────────────────────────────────────────
+# 应用配置（从环境变量读取）
+# ──────────────────────────────────────────────────────────────
+DIFY_URL: str = os.getenv("DIFY_URL", "")
+DIFY_API_KEY: str = os.getenv("DIFY_API_KEY", "")
+REDIS_HOST: str = os.getenv("REDIS_HOST", "localhost")
+REDIS_PORT: int = int(os.getenv("REDIS_PORT", "6379"))
+
+# 验证必填配置
+if not DIFY_URL or not DIFY_API_KEY:
+    logger.warning(
+        "DIFY_URL 或 DIFY_API_KEY 未配置，"
+        "部分功能可能不可用。请通过环境变量设置。"
+    )
+
+# ──────────────────────────────────────────────────────────────
+# Redis 客户端（懒加载）
+# ──────────────────────────────────────────────────────────────
+_redis_client: Optional[redis.Redis] = None
+
+
+def get_redis() -> redis.Redis:
+    """获取 Redis 客户端实例（延迟初始化）。"""
+    global _redis_client
+    if _redis_client is None:
+        _redis_client = redis.Redis(
+            host=REDIS_HOST,
+            port=REDIS_PORT,
+            decode_responses=True,
+            socket_connect_timeout=5,
+        )
+    return _redis_client
+
+
+def get_cache_key(payload: Dict[str, Any]) -> str:
+    """根据请求体生成 Redis 缓存键。"""
+    raw = json.dumps(payload, sort_keys=True)
+    return f"dh:cache:{hashlib.md5(raw.encode()).hexdigest()}"
+
+
+# ──────────────────────────────────────────────────────────────
+# FastAPI 应用生命周期
+# ──────────────────────────────────────────────────────────────
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    """应用启动 / 关闭钩子。"""
+    logger.info("数字人对接服务启动中...")
+    logger.info(f"  Dify URL : {DIFY_URL}")
+    logger.info(f"  Redis    : {REDIS_HOST}:{REDIS_PORT}")
+
+    # 尝试连接 Redis（仅记录，不阻塞启动）
+    try:
+        get_redis().ping()
+        logger.info("Redis 连接成功")
+    except RedisConnectionError as e:
+        logger.warning(f"Redis 连接失败（服务将继续运行）: {e}")
+
+    yield
+
+    logger.info("数字人对接服务已关闭")
+
+
+app = FastAPI(
+    title="数字人对接中转服务",
+    version="1.0.0",
+    description="对接 Dify LLM 平台的数字人应用中转服务",
+    lifespan=lifespan,
+)
+
+
+# ──────────────────────────────────────────────────────────────
+# 健康检查
+# ──────────────────────────────────────────────────────────────
+@app.get("/")
+async def root():
+    """服务健康检查端点。"""
+    return {
+        "status": "ok",
+        "service": "digital-human-relay",
+        "version": "1.0.0",
+    }
+
+
+@app.get("/health")
+async def health_check():
+    """详细健康检查（包含 Redis 状态）。"""
+    redis_ok = False
+    try:
+        get_redis().ping()
+        redis_ok = True
+    except Exception:
+        pass
+
+    return {
+        "status": "healthy" if redis_ok else "degraded",
+        "redis": "connected" if redis_ok else "disconnected",
+        "dify_configured": bool(DIFY_URL and DIFY_API_KEY),
+    }
+
+
+# ──────────────────────────────────────────────────────────────
+# Dify 响应格式转 OpenAI 兼容格式
+# ──────────────────────────────────────────────────────────────
+def dify_to_openai(dify_resp: Dict[str, Any]) -> Dict[str, Any]:
+    """
+    将 Dify /chat-messages 的响应转换为 OpenAI /chat/completions 兼容格式。
+    Dify 响应示例: { answer: "...", conversation_id: "...", task_id: "..." }
+    OpenAI 目标格式: { id, model, choices: [{ message: { role: "assistant", content: "..." } }] }
+    """
+    return {
+        "id": f"chatcmpl-{dify_resp.get('task_id', 'unknown')}",
+        "object": "chat.completion",
+        "created": 0,
+        "model": "dify",
+        "choices": [
+            {
+                "index": 0,
+                "message": {
+                    "role": "assistant",
+                    "content": dify_resp.get("answer", ""),
+                },
+                "finish_reason": "stop",
+            }
+        ],
+        "usage": {
+            "prompt_tokens": 0,
+            "completion_tokens": 0,
+            "total_tokens": 0,
+        },
+    }
+
+
+# ──────────────────────────────────────────────────────────────
+# 核心转发接口
+# ──────────────────────────────────────────────────────────────
+@app.post("/v1/chat/completions")
+async def chat_completions(request: Request):
+    """
+    接收 OpenAI 兼容格式请求，转换为 Dify /chat-messages 格式后转发。
+    OpenAI 格式: { model, messages: [{role, content}], stream }
+    Dify 格式:   { query, user, response_mode, inputs }
+    """
+    body = await request.json()
+
+    # ── 格式转换：OpenAI -> Dify ──────────────────────────────
+    # 提取用户最新消息
+    user_content = ""
+    for msg in reversed(body.get("messages", [])):
+        if msg.get("role") == "user":
+            user_content = msg.get("content", "")
+            break
+
+    if not user_content:
+        raise HTTPException(status_code=400, detail="未找到用户消息")
+
+    # 生成或复用 user 标识（用于 Dify 会话上下文）
+    dify_user = body.get("user", "anonymous")
+    response_mode = "blocking" if not body.get("stream", False) else "streaming"
+
+    # 构建 Dify 请求体
+    dify_payload = {
+        "query": user_content,
+        "user": dify_user,
+        "response_mode": response_mode,
+        "inputs": body.get("inputs", {}),
+    }
+
+    # 若应用要求 inputs 字段但为空，补上空对象
+    if "inputs" not in dify_payload or dify_payload["inputs"] is None:
+        dify_payload["inputs"] = {}
+
+    # ── 检查 Redis 缓存（基于 OpenAI 原始请求体）──────────────
+    cache_key = get_cache_key(body)
+    try:
+        cached = get_redis().get(cache_key)
+        if cached:
+            logger.info(f"缓存命中: {cache_key}")
+            return dify_to_openai(json.loads(cached))
+    except RedisConnectionError:
+        logger.warning("Redis 不可用，跳过缓存读取")
+
+    # ── 转发到 Dify ─────────────────────────────────────────
+    headers = {
+        "Authorization": f"Bearer {DIFY_API_KEY}",
+        "Content-Type": "application/json",
+    }
+    dify_endpoint = f"{DIFY_URL.rstrip('/')}/chat-messages"
+
+    try:
+        async with httpx.AsyncClient(timeout=120.0) as client:
+            resp = await client.post(dify_endpoint, json=dify_payload, headers=headers)
+            resp.raise_for_status()
+            result = resp.json()
+    except httpx.HTTPStatusError as e:
+        logger.error(f"Dify 返回错误 {e.response.status_code}: {e.response.text}")
+        raise HTTPException(
+            status_code=e.response.status_code,
+            detail=f"Dify 请求失败: {e.response.text}",
+        )
+    except httpx.RequestError as e:
+        logger.error(f"无法连接 Dify 服务: {e}")
+        raise HTTPException(status_code=502, detail=f"无法连接 Dify 服务: {e}")
+
+    # ── 写入缓存（存 Dify 原始格式）───────────────────────────
+    try:
+        get_redis().setex(cache_key, 300, json.dumps(result))
+    except RedisConnectionError:
+        pass
+
+    # ── 响应转 OpenAI 兼容格式 ─────────────────────────────────
+    return dify_to_openai(result)
+
+
+# ──────────────────────────────────────────────────────────────
+# 错误处理器
+# ──────────────────────────────────────────────────────────────
+@app.exception_handler(Exception)
+async def global_exception_handler(request: Request, exc: Exception):
+    logger.exception(f"未处理的异常: {exc}")
+    return JSONResponse(
+        status_code=500,
+        content={"error": "Internal Server Error", "detail": str(exc)},
+    )

downloads/digital-human.py

@@ -0,0 +1,176 @@
+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

@@ -0,0 +1,11 @@
+[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

@@ -0,0 +1,33 @@
+#!/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
+