使用fastapi搭建ChatGPT对话后台

Joker-Tong2024-09-27 15:30

使用fastapi搭建ChatGPT对话后台

参考资料：使用fastapi搭建ChatGPT对话后台

效果：在本地构建网页达成类似chatgpt的对话效果，一个字一个字的返回生成结果

ChatGPT初步调用

python 复制代码 
import os
import fastapi
import dotenv
from httpx import AsyncClient
from typing import List,Dict
dotenv.load_dotenv('./env')

# print(os.getenv('OPENAI_API_BASE'))
async def request(val: List[dict[str,str]]):
    """
    发起请求
    val: 对话内容
    """
    url = "https://xiaoai.plus/v1/chat/completions"
    headers ={
        "Content-Type": "application/json",
        "Authorization": "Bearer " + os.getenv("OPENAI_API_KEY")
    }
    params = {
        "model": "gpt-3.5-turbo",
        "messages": val, # [{"role": "user", "content": "Say this is a test!"}]
        "temperature": 0.7,
        "n": 1,
        "max_tokens": 3000,
        "stream": False
    }
    async with AsyncClient() as clinet:
        response = await clinet.post(url, headers=headers,json=params,timeout=60)
        print(response.json())

if __name__ == '__main__':
    import asyncio
    asyncio.run(request([{"role": "user", "content": "Hello!"}]))
bash 复制代码 
{'id': 'chatcmpl-ABYGZNDqhtZn5igtaukBbLPWrdTPZ', 'object': 'chat.completion', 'created': 1727316691, 'model': 'gpt-3.5-turbo', 'choices': [{'index': 0, 'message': {'role': 'assistant', 'content': 'Hello! How can I assist you today?'}, 'finish_reason': 'stop'}], 'usage': {'prompt_tokens': 9, 'completion_tokens': 9, 'total_tokens': 18}, 'system_fingerprint': 'fp_808245b034'}

对回答进行解析, 这里的结果是一次性返回消息内容

bash 复制代码 
{
    "id": "chatcmpl-ABYGZNDqhtZn5igtaukBbLPWrdTPZ",  # 唯一标识符，用于追踪请求
    "object": "chat.completion",  # 对象类型，表示这是一个聊天完成事件
    "created": 1727316691,  # 创建时间戳，表示响应创建的时间
    "model": "gpt-3.5-turbo",  # 使用的模型名称
    "choices": [  # 选择列表，可能包含多个回复，这里只有一个
        {
            "index": 0,  # 当前选择的索引
            "message": {  # 选择的消息内容
                "role": "assistant",  # 消息角色，这里是助手
                "content": "Hello! How can I assist you today?"  # 消息内容
            },
            "finish_reason": "stop"  # 完成原因，这里是"stop"，表示模型决定停止生成更多内容
        }
    ],
    "usage": {  # 使用情况，包括token使用情况
        "prompt_tokens": 9,  # 提示token的数量
        "completion_tokens": 9,  # 完成token的数量
        "total_tokens": 18  # 总token的数量
    },
    "system_fingerprint": "fp_808245b034"  # 系统指纹，用于识别请求的系统环境
}

流式调用ChatGPT

修改上述代码中的"stream": True与print(response.text)部分

python 复制代码 
import os
import fastapi
import dotenv
from httpx import AsyncClient
from typing import List,Dict
dotenv.load_dotenv('./env')

# print(os.getenv('OPENAI_API_BASE'))
async def request(val: List[dict[str,str]]):
    """
    发起请求
    val: 对话内容
    """
    url = "https://xiaoai.plus/v1/chat/completions"
    headers ={
        "Content-Type": "application/json",
        "Authorization": "Bearer " + os.getenv("OPENAI_API_KEY")
    }
    params = {
        "model": "gpt-3.5-turbo",
        "messages": val, # [{"role": "user", "content": "Say this is a test!"}]
        "temperature": 0.7,
        "n": 1,
        "max_tokens": 3000,
        "stream": True
    }
    async with AsyncClient() as clinet:
        response = await clinet.post(url, headers=headers,json=params,timeout=60)
        print(response.text)

if __name__ == '__main__':
    import asyncio
    asyncio.run(request([{"role": "user", "content": "Hello!"}]))

可以看到GPT的结果是一个词一个词的返回的

bash 复制代码 
data: {"id":"chatcmpl-ABYJD1L22azzx2PK9IyqCaw2RrC7J","object":"chat.completion.chunk","created":1727316855,"model":"gpt-3.5-turbo","system_fingerprint":"fp_808245b034","choices":[{"index":0,"delta":{"role":"assistant","content":""},"finish_reason":null}]}

data: {"id":"chatcmpl-ABYJD1L22azzx2PK9IyqCaw2RrC7J","object":"chat.completion.chunk","created":1727316855,"model":"gpt-3.5-turbo","system_fingerprint":"fp_808245b034","choices":[{"index":0,"delta":{"content":"Hello"},"finish_reason":null}]}

data: {"id":"chatcmpl-ABYJD1L22azzx2PK9IyqCaw2RrC7J","object":"chat.completion.chunk","created":1727316855,"model":"gpt-3.5-turbo","system_fingerprint":"fp_808245b034","choices":[{"index":0,"delta":{"content":"!"},"finish_reason":null}]}

data: {"id":"chatcmpl-ABYJD1L22azzx2PK9IyqCaw2RrC7J","object":"chat.completion.chunk","created":1727316855,"model":"gpt-3.5-turbo","system_fingerprint":"fp_808245b034","choices":[{"index":0,"delta":{"content":" How"},"finish_reason":null}]}

data: {"id":"chatcmpl-ABYJD1L22azzx2PK9IyqCaw2RrC7J","object":"chat.completion.chunk","created":1727316855,"model":"gpt-3.5-turbo","system_fingerprint":"fp_808245b034","choices":[{"index":0,"delta":{"content":" can"},"finish_reason":null}]}

data: {"id":"chatcmpl-ABYJD1L22azzx2PK9IyqCaw2RrC7J","object":"chat.completion.chunk","created":1727316855,"model":"gpt-3.5-turbo","system_fingerprint":"fp_808245b034","choices":[{"index":0,"delta":{"content":" I"},"finish_reason":null}]}

data: {"id":"chatcmpl-ABYJD1L22azzx2PK9IyqCaw2RrC7J","object":"chat.completion.chunk","created":1727316855,"model":"gpt-3.5-turbo","system_fingerprint":"fp_808245b034","choices":[{"index":0,"delta":{"content":" assist"},"finish_reason":null}]}

data: {"id":"chatcmpl-ABYJD1L22azzx2PK9IyqCaw2RrC7J","object":"chat.completion.chunk","created":1727316855,"model":"gpt-3.5-turbo","system_fingerprint":"fp_808245b034","choices":[{"index":0,"delta":{"content":" you"},"finish_reason":null}]}

data: {"id":"chatcmpl-ABYJD1L22azzx2PK9IyqCaw2RrC7J","object":"chat.completion.chunk","created":1727316855,"model":"gpt-3.5-turbo","system_fingerprint":"fp_808245b034","choices":[{"index":0,"delta":{"content":" today"},"finish_reason":null}]}

data: {"id":"chatcmpl-ABYJD1L22azzx2PK9IyqCaw2RrC7J","object":"chat.completion.chunk","created":1727316855,"model":"gpt-3.5-turbo","system_fingerprint":"fp_808245b034","choices":[{"index":0,"delta":{"content":"?"},"finish_reason":null}]}

data: {"id":"chatcmpl-ABYJD1L22azzx2PK9IyqCaw2RrC7J","object":"chat.completion.chunk","created":1727316855,"model":"gpt-3.5-turbo","system_fingerprint":"fp_808245b034","choices":[{"index":0,"delta":{},"finish_reason":"stop"}]}

data: [DONE]

逐行处理流式响应

修改相应的代码

python 复制代码 
    # async with AsyncClient() as clinet:
    #     response = await clinet.post(url, headers=headers,json=params,timeout=60)
    #     print(response.text)
    async with AsyncClient() as clinet:
        async with clinet.stream("POST", url, headers=headers, json=params, timeout=60) as response:
            async for line in response.aiter_lines():
                print(line)
python 复制代码 
import os
import fastapi
import dotenv
from httpx import AsyncClient
from typing import List,Dict
import json
from collections import defaultdict
dotenv.load_dotenv('./env')

# print(os.getenv('OPENAI_API_BASE'))
async def request(val: List[dict[str,str]]):
    """
    发起请求
    val: 对话内容
    """
    url = "https://xiaoai.plus/v1/chat/completions"
    headers ={
        "Content-Type": "application/json",
        "Authorization": "Bearer " + os.getenv("OPENAI_API_KEY")
    }
    params = {
        "model": "gpt-3.5-turbo",
        "messages": val, # [{"role": "user", "content": "Say this is a test!"}]
        "temperature": 0.7,
        "n": 1,
        "max_tokens": 3000,
        "stream": True
    }
    # async with AsyncClient() as clinet:
    #     response = await clinet.post(url, headers=headers,json=params,timeout=60)
    #     print(response.text)
    async with AsyncClient() as clinet:
        async with clinet.stream("POST", url, headers=headers, json=params, timeout=60) as response:
            async for line in response.aiter_lines():
                if line.strip() == "":
                    continue
                line = line.replace("data: ","")
                if line.strip() == "[DONE]":
                    return
                data = json.loads(line)
                if data.get("choices") is None or len(data.get("choices")) == 0 or data.get("choices")[0].get("finish_reason") is not None:
                    return
                yield data.get("choices")[0]

async def chat(inp: str):
    message = [{"role": "user", "content": inp}]
    async for i in request(message):
        print(i)
if __name__ == '__main__':
    import asyncio
    asyncio.run(chat("你好啊"))
bash 复制代码 
{'index': 0, 'delta': {'role': 'assistant', 'content': ''}, 'finish_reason': None}
{'index': 0, 'delta': {'content': '你'}, 'finish_reason': None}
{'index': 0, 'delta': {'content': '好'}, 'finish_reason': None}
{'index': 0, 'delta': {'content': '，'}, 'finish_reason': None}
{'index': 0, 'delta': {'content': '有'}, 'finish_reason': None}
{'index': 0, 'delta': {'content': '什'}, 'finish_reason': None}
{'index': 0, 'delta': {'content': '么'}, 'finish_reason': None}
{'index': 0, 'delta': {'content': '可以'}, 'finish_reason': None}
{'index': 0, 'delta': {'content': '帮'}, 'finish_reason': None}
{'index': 0, 'delta': {'content': '助'}, 'finish_reason': None}
{'index': 0, 'delta': {'content': '你'}, 'finish_reason': None}
{'index': 0, 'delta': {'content': '的'}, 'finish_reason': None}
{'index': 0, 'delta': {'content': '吗'}, 'finish_reason': None}
{'index': 0, 'delta': {'content': '？'}, 'finish_reason': None}

封装请求与chat方法

python 复制代码 
import os
import fastapi
import dotenv
from httpx import AsyncClient
from typing import List,Dict
import json
from collections import defaultdict
dotenv.load_dotenv('./env')

# print(os.getenv('OPENAI_API_BASE'))
async def request(val: List[dict[str,str]]):
    """
    发起请求
    val: 对话内容
    """
    url = "https://xiaoai.plus/v1/chat/completions"
    headers ={
        "Content-Type": "application/json",
        "Authorization": "Bearer " + os.getenv("OPENAI_API_KEY")
    }
    params = {
        "model": "gpt-3.5-turbo",
        "messages": val, # [{"role": "user", "content": "Say this is a test!"}]
        "temperature": 0.7,
        "n": 1,
        "max_tokens": 3000,
        "stream": True
    }
    # async with AsyncClient() as clinet:
    #     response = await clinet.post(url, headers=headers,json=params,timeout=60)
    #     print(response.text)
    async with AsyncClient() as clinet:
        async with clinet.stream("POST", url, headers=headers, json=params, timeout=60) as response:
            async for line in response.aiter_lines():
                if line.strip() == "":
                    continue
                line = line.replace("data: ","")
                if line.strip() == "[DONE]":
                    return
                data = json.loads(line)
                if data.get("choices") is None or len(data.get("choices")) == 0 or data.get("choices")[0].get("delta").get("finish_reason") is not None:
                    return
                yield data.get("choices")[0]

async def chat(inp: str):
    message = [{"role": "user", "content": inp}]
    chat_msg = defaultdict(str)
    async for i in request(message):
        if i.get("delta").get("role"):
            chat_msg["role"] = i.get("delta").get("role")
        if i.get("delta").get("content"):
            chat_msg["content"] += i.get("delta").get("content")
    print(chat_msg)
if __name__ == '__main__':
    import asyncio
    asyncio.run(chat("你好啊"))
bash 复制代码 
defaultdict(<class 'str'>, {'role': 'assistant', 'content': '你好！有什么我可以帮助你的吗？'}

使用fastapi进行封装

python 复制代码 
import os
import fastapi
import dotenv
from httpx import AsyncClient
from typing import List,Dict
from fastapi import FastAPI, WebSocket
from fastapi.middleware.cors import CORSMiddleware

import json
from collections import defaultdict
from fastapi.responses import HTMLResponse

app = FastAPI()
dotenv.load_dotenv('./env')


# app.add_middleware(
#     CORSMiddleware,
#     allow_origins=["*"],
#     allow_credentials=True,
#     allow_methods=["*"],
#     allow_headers=["*"],
# )


@app.get("/")
async def root():
    return {"message": "Hello World"}

# print(os.getenv('OPENAI_API_BASE'))
async def request(val: List[dict[str,str]]):
    """
    发起请求
    val: 对话内容
    """
    url = "https://xiaoai.plus/v1/chat/completions"
    headers ={
        "Content-Type": "application/json",
        "Authorization": "Bearer " + os.getenv("OPENAI_API_KEY"),

    }
    params = {
        "model": "gpt-3.5-turbo",
        "messages": val, # [{"role": "user", "content": "Say this is a test!"}]
        "temperature": 0.7,
        "n": 1,
        "max_tokens": 3000,
        "stream": True
    }
    # async with AsyncClient() as clinet:
    #     response = await clinet.post(url, headers=headers,json=params,timeout=60)
    #     print(response.text)
    async with AsyncClient() as clinet:
        async with clinet.stream("POST", url, headers=headers, json=params, timeout=60) as response:
            async for line in response.aiter_lines():
                if line.strip() == "":
                    continue
                line = line.replace("data: ","")
                if line.strip() == "[DONE]":
                    return
                data = json.loads(line)
                if data.get("choices") is None or len(data.get("choices")) == 0 or data.get("choices")[0].get("delta").get("finish_reason") is not None:
                    return
                yield data.get("choices")[0]

@app.websocket("/chat")
async def chat(websocket: WebSocket):
    await websocket.accept()
    message = []
    while True:
        data = await websocket.receive_text()
        if data == "quit": 
            await websocket.close()
            break
        message.append({"role": "user", "content": data})
        chat_msg = defaultdict(str)
        async for i in request(message):
            if i.get("delta").get("role"):
                chat_msg["role"] = i.get("delta").get("role")
            if i.get("delta").get("content"):
                chat_msg["content"] += i.get("delta").get("content")
                await websocket.send_text(i.get("delta").get("content"))
        message.append(chat_msg)

if __name__ == '__main__':
    import uvicorn
    uvicorn.run("main:app", host="127.0.0.1",port=8080,reload=True)

使用html界面调用

html 复制代码 
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<title>Titile</title>
</head>
<body>
    <p>连接状态: <span id="status">未连接</span></p>
    <p>回复消息: <span id="message"></span></p>
    <p><input id="inp"></p>
    <button type="submit" id="submit">提交</button>
<script>
    let status = document.getElementById("status")
    let message = document.getElementById("message")
    let inp = document.getElementById("inp")
    let submit = document.getElementById("submit")

    let socket = new WebSocket("ws://127.0.0.1:8080/chat")
    socket.addEventListener("open", (event)=>{
        status.innerText = "已连接"
    })
    socket.addEventListener("error", (event)=>{
        status.innerText = "已失败"
    })
    socket.addEventListener("close", (event)=>{
        status.innerText = "已关闭"
        console.log("WebSocket closed:", event)
    })
    socket.addEventListener("message", (event)=>{
        message.innerText += event.data
    })
    submit.addEventListener("click", ()=>{
        socket.send(inp.value)
    })
</script>
</body>
</html>
相关推荐
basketball6161 小时前
Python FastAPI 介绍以及常用方法
python·fastapi·vllm·ai infra
Ztiddler6 小时前
Codex重新连接解决方法
chatgpt·openai·codex
吨吨ai1 天前
Codex 长会话上下文管理：会话拆分与状态交接的工程化实践
chatgpt
守城小轩1 天前
AcBoter 多账号管理指南：隐私与设置选项（五）
chatgpt·codex·acboter
ServBay1 天前
ChatGPT Pro 20X 限时回归
gpt·chatgpt·openai
troy1281 天前
Codex 安全盲区：代码漏洞生成实测
windows·python·ci/cd·pycharm·django·github·fastapi
枫叶丹41 天前
开源还是开权重：2026 年 AI 模型战争的控制权之争
人工智能·chatgpt·开源·agent·codex
打工仔折腾 AI2 天前
FastAPI 从本机到生产服务器：Nginx+Gunicorn+Uvicorn 完整部署实录
人工智能·后端·python·nginx·fastapi·gunicorn
小猿君2 天前
Claude 入口砍到只剩一个，GPT-6 已经能自己连干 24 小时
人工智能·chatgpt·agi
西安栈上月明软件科技3 天前
从 Linux 0.01 到 AI 开源：星图邻的开源实践
人工智能·自然语言处理·架构·开源·fastapi
热门推荐
01国内可直接用、免费额度/永久免费的大模型API清单（含 SiliconFlow、火山、阿里、智谱、百度、Kimi、DeepSeek、DMXAPI 等）02蜘蛛磁力 搜索引擎大全，如何使用蜘蛛磁力查找磁力链接03历年考研数学一、数学二、数学三真题试卷及答案PDF04GitHub 镜像站点05微信历史版本含下载地址（ Windows PC | 安卓 | MAC ）及设置微信不更新06人工智能（AI）发展史：详细里程碑072026 国产 AI 大模型横评：DeepSeek、通义千问、Kimi、文心一言、星火、豆包谁更能打？08ZCode 周末送额度活动开启：3 亿 Token 免费领取092026 爱知・名古屋亚运会怎么看？直播平台+赛程安排分享10数学公理体系大全:第六章 选择公理的等价形式及证明