专栏总目录

        按照ollama官方doc的example操作，没有成功与本地ollama上的deepseek-r1:1.5b通讯后，发现vscode可以调用本地ollama上的deepseek模型。

        为了实现与ollama上的deepseek模型通讯，我使用wireshark对本地回环地址进行侦听后，发现了具体方法。

一、研究过程

        vscode上提问，给了如下回答

        如下图所示，上传的内容及参数，关键字在相关内容的的位置

二、对话脚本

        使用python脚本编辑后如下所示

import socket
import json
import json

def get_content(str_data):
    #print(str_data)
    content_str = ''
    for i in str_data.splitlines():
        if 'think' in i:
            continue
        elif '"content"' in i:
            # 给定的JSON字符串
            json_string = i
            # 解析JSON字符串
            data = json.loads(json_string)
            
            # 提取content的值
            content = data['message']['content']

            content_str = content_str + content.replace('/n', '')
            
            stripped_string = content_str.lstrip('\n')
    return stripped_string


def send_post_request(host, port, path, headers, body):
    # 创建一个socket对象
    with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
        # 连接到服务器
        s.connect((host, port))
        # 构造HTTP请求
        request = f"POST {path} HTTP/1.1\r\n"
        for header, value in headers.items():
            request += f"{header}: {value}\r\n"
        request += "\r\n"  # 空行表示头部结束
        request += body
        # 发送HTTP请求
        s.sendall(request.encode('utf-8'))
        # 接收响应
        response = b''
        while True:
            part = s.recv(1024)
            if not part:
                break
            response += part
        return response

def main():
    # 服务器的地址和端口
    host = '127.0.0.1'
    port = 11434
    path = "/api/chat"
    while True:
        question = input('>>>')
        # 构造请求数据
        data = {
            "model": "deepseek-r1:1.5b",
            "messages": [{"role": "user", "content": question}],
            "options": {
                "num_predict": 4096,
                "stop": ["<...begin...of...sentence...>", "<...end...of...sentence...>", "<...User...>", "<...Assistant...>"],
                "num_ctx": 8096
            },
            "keep_alive": 1800
        }
        body = json.dumps(data)

        # 构造HTTP头部
        headers = {
            "Accept": "*/*",
            "Accept-Encoding": "gzip, deflate, br",
            "Authorization": "Bearer undefined",
            "Content-Length": str(len(body)),
            "Content-Type": "application/json",
            "User-Agent": "node-fetch",
            "Host": "127.0.0.1:11434",
            "Connection": "close"
        }

        # 发送POST请求并获取响应
        response = send_post_request(host, port, path, headers, body)
        print("【deepseek】: ",end='')
        #print(response.decode('utf-8'))
        mess = get_content(response.decode('utf-8'))
        print(mess)

if __name__ == '__main__':
    main()

        具体切片、美化步骤再此省略。