This commit is contained in:
黄 杰 2025-06-05 10:49:37 +08:00
commit 09ca834085
13 changed files with 1483 additions and 0 deletions

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## Ignore Visual Studio temporary files, build results, and
## files generated by popular Visual Studio add-ons.
##
## Get latest from https://github.com/github/gitignore/blob/master/VisualStudio.gitignore
# User-specific files
*.rsuser
*.suo
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Microsoft Visual Studio Solution File, Format Version 12.00
# Visual Studio Version 17
VisualStudioVersion = 17.11.35219.272
MinimumVisualStudioVersion = 10.0.40219.1
Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "OLLamaClient", "OLLamaClient\OLLamaClient.csproj", "{917079E4-306C-4793-8659-3B581E904213}"
EndProject
Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "OLlamaClientPP", "OLlamaClientPP\OLlamaClientPP.vcxproj", "{0CE6E127-F334-4D75-9B9D-FEF1528FDF8E}"
EndProject
Global
GlobalSection(SolutionConfigurationPlatforms) = preSolution
Debug|Any CPU = Debug|Any CPU
Debug|x64 = Debug|x64
Debug|x86 = Debug|x86
Release|Any CPU = Release|Any CPU
Release|x64 = Release|x64
Release|x86 = Release|x86
EndGlobalSection
GlobalSection(ProjectConfigurationPlatforms) = postSolution
{917079E4-306C-4793-8659-3B581E904213}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
{917079E4-306C-4793-8659-3B581E904213}.Debug|Any CPU.Build.0 = Debug|Any CPU
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{917079E4-306C-4793-8659-3B581E904213}.Debug|x64.Build.0 = Debug|Any CPU
{917079E4-306C-4793-8659-3B581E904213}.Debug|x86.ActiveCfg = Debug|Any CPU
{917079E4-306C-4793-8659-3B581E904213}.Debug|x86.Build.0 = Debug|Any CPU
{917079E4-306C-4793-8659-3B581E904213}.Release|Any CPU.ActiveCfg = Release|Any CPU
{917079E4-306C-4793-8659-3B581E904213}.Release|Any CPU.Build.0 = Release|Any CPU
{917079E4-306C-4793-8659-3B581E904213}.Release|x64.ActiveCfg = Release|Any CPU
{917079E4-306C-4793-8659-3B581E904213}.Release|x64.Build.0 = Release|Any CPU
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{917079E4-306C-4793-8659-3B581E904213}.Release|x86.Build.0 = Release|Any CPU
{0CE6E127-F334-4D75-9B9D-FEF1528FDF8E}.Debug|Any CPU.ActiveCfg = Debug|x64
{0CE6E127-F334-4D75-9B9D-FEF1528FDF8E}.Debug|Any CPU.Build.0 = Debug|x64
{0CE6E127-F334-4D75-9B9D-FEF1528FDF8E}.Debug|x64.ActiveCfg = Debug|x64
{0CE6E127-F334-4D75-9B9D-FEF1528FDF8E}.Debug|x64.Build.0 = Debug|x64
{0CE6E127-F334-4D75-9B9D-FEF1528FDF8E}.Debug|x86.ActiveCfg = Debug|Win32
{0CE6E127-F334-4D75-9B9D-FEF1528FDF8E}.Debug|x86.Build.0 = Debug|Win32
{0CE6E127-F334-4D75-9B9D-FEF1528FDF8E}.Release|Any CPU.ActiveCfg = Release|x64
{0CE6E127-F334-4D75-9B9D-FEF1528FDF8E}.Release|Any CPU.Build.0 = Release|x64
{0CE6E127-F334-4D75-9B9D-FEF1528FDF8E}.Release|x64.ActiveCfg = Release|x64
{0CE6E127-F334-4D75-9B9D-FEF1528FDF8E}.Release|x64.Build.0 = Release|x64
{0CE6E127-F334-4D75-9B9D-FEF1528FDF8E}.Release|x86.ActiveCfg = Release|Win32
{0CE6E127-F334-4D75-9B9D-FEF1528FDF8E}.Release|x86.Build.0 = Release|Win32
EndGlobalSection
GlobalSection(SolutionProperties) = preSolution
HideSolutionNode = FALSE
EndGlobalSection
GlobalSection(ExtensibilityGlobals) = postSolution
SolutionGuid = {D428276B-7419-4476-8C2B-911CF3C3DDFB}
EndGlobalSection
EndGlobal

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<Project Sdk="Microsoft.NET.Sdk">
<PropertyGroup>
<OutputType>Exe</OutputType>
<TargetFramework>net8.0</TargetFramework>
<ImplicitUsings>enable</ImplicitUsings>
<Nullable>enable</Nullable>
<PublishAot>true</PublishAot>
<InvariantGlobalization>true</InvariantGlobalization>
<AllowUnsafeBlocks>True</AllowUnsafeBlocks>
</PropertyGroup>
<ItemGroup>
<PackageReference Include="Newtonsoft.Json" Version="13.0.3" />
<PackageReference Include="System.Drawing.Common" Version="8.0.8" />
</ItemGroup>
</Project>

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using System;
using System.Collections.Generic;
using System.IO;
using System.Linq;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;
using Newtonsoft.Json;
using System.Drawing;
using System.Windows.Forms;
using Newtonsoft.Json.Linq;
using System.Diagnostics;
namespace OLLamaClient
{
public class _prop
{
public string instruction { get; set; }
public string input { get; set; }
public string output { get; set; }
}
internal class Program
{
const string moduleName = "qwen2.5-coder:32b";
const string _testessage = @"你需要扮演一名抖音客服,你的目标是解决客户的疑问并尽可能拿到客户的联系方式或者引导客户来联系我们的服务人员,你需要参考下面的文档来建立工作内容的知识,并参考聊天的上下文给出回复消息,你只需要输出回复的消息即可,不允许输出其他任何内容
:U代表客户,S代表你自己()
:
S:
U:,?
S:便
U:
S:便
U:
S:,便
U:19921461944
:
:
1.
便
2.
3.
便
4. :
便
便
1XX产品可以贴吗
MO+
V或二维码便
便WX号或二维码便
2//
便便V或二维码
3
便V或二维码
4
便V
5,
5.
便
6.
WX添加您只是给您介绍下
7.
[]
[]
8.
MO+
9. V
wx13636662468[]
10. /
便
WX无法搜索到
:
11.
5-105-10
12.
1-2
13.
使线
14.
TPU材质的PETTPU材质也有
15.
16.
17.
INTEGOMADICO3MSKINTEC等等品牌可以选择
18.
19.
20.
21.
wx13636662468[]
22.
,
";
static List<ollama_chat_message> messages = new List<ollama_chat_message>();
static void Main(string[] args)
{
var str = TestOllamaGenerate(_testessage);
Console.WriteLine(str?.Result);
//多模态的模型才支持
//ImageTest(@"D:\BackGround\9a64abb34b27afbb064c0ad90e0c238b.jpg", "详细描述这张图片的内容");
Console.ReadKey();
}
static async void TestOllamaChat(string str_message)
{
var msg = new ollama_chat_message();
msg.content = str_message;
msg.role = "user";
messages.Add(msg);
var client = new HttpClient();
ollama_chat usedtar = new ollama_chat();
usedtar.model = moduleName;
usedtar.messages = messages;
usedtar.stream = true;
HttpContent content = new StringContent(JsonConvert.SerializeObject(usedtar));
content.Headers.ContentType = new System.Net.Http.Headers.MediaTypeHeaderValue("application/json");
HttpResponseMessage response = await client.PostAsync("http://localhost:11434/api/chat", content);
var responseBody = await response.Content.ReadAsStreamAsync();
StreamReader reader = new StreamReader(responseBody);
string str_ = reader.ReadLine();
StringBuilder assistant_str = new StringBuilder();
while (str_ != null)
{
ollama_chat_response ollama_response = JsonConvert.DeserializeObject<ollama_chat_response>(str_);
Console.Write(ollama_response.message.content);
if (ollama_response.done)
{
Console.WriteLine();
break;
}
else
assistant_str.Append(ollama_response.message.content);
str_ = reader.ReadLine();
}
var ollama_msg = new ollama_chat_message();
ollama_msg.content = assistant_str.ToString();
ollama_msg.role = "assistant";
messages.Add(ollama_msg);
}
static async Task<string> TestOllamaGenerate(string msg)
{
StringBuilder sb = new StringBuilder();
var client = new HttpClient();
ollama_generate usedtar = new ollama_generate();
usedtar.model = moduleName;
usedtar.prompt = msg;
usedtar.stream = true;
var str = JsonConvert.SerializeObject(usedtar);
HttpContent content = new StringContent(str);
content.Headers.ContentType = new System.Net.Http.Headers.MediaTypeHeaderValue("application/json");
HttpResponseMessage response = await client.PostAsync("http://localhost:11434/api/generate", content);
var responseBody = await response.Content.ReadAsStreamAsync();
StreamReader reader = new StreamReader(responseBody);
string str_ = reader.ReadLine();
while (str_ != null)
{
ollama_generate_response ollama_response = JsonConvert.DeserializeObject<ollama_generate_response>(str_);
//Console.Write(ollama_response.response);
sb.Append(ollama_response.response);
if (ollama_response.done)
break;
str_ = reader.ReadLine();
}
return sb.ToString();
}
static void ImageTest(string imagePath, string prop)
{
byte[] bytes = File.ReadAllBytes(imagePath);
var client = new HttpClient();
ollama_generate usedtar = new ollama_generate();
usedtar.model = moduleName;
usedtar.prompt = prop;
usedtar.stream = true;
usedtar.images = new List<string>();
usedtar.images.Add(Convert.ToBase64String(bytes));
var str = JsonConvert.SerializeObject(usedtar);
HttpContent content = new StringContent(str);
content.Headers.ContentType = new System.Net.Http.Headers.MediaTypeHeaderValue("application/json");
HttpResponseMessage response = client.PostAsync("http://localhost:11434/api/generate", content).Result;
var responseBody = response.Content.ReadAsStreamAsync()?.Result;
StreamReader reader = new StreamReader(responseBody);
string str_ = reader.ReadLine();
while (str_ != null)
{
ollama_generate_response ollama_response = JsonConvert.DeserializeObject<ollama_generate_response>(str_);
Console.Write(ollama_response.response);
if (ollama_response.done)
break;
str_ = reader.ReadLine();
}
}
}
}

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using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
namespace OLLamaClient
{
internal class TransformInfo
{
public string q { get; set; }
public string source { get; set; }
public string target { get; set; }
}
internal class TransformResult
{
public string translatedText { get; set; }
public string error { get; set; }
}
}

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using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
namespace OLLamaClient
{
public class ollama_chat
{
public string model { get; set; }
public List<ollama_chat_message> messages { get; set; }
public bool stream { get; set; }
}
}

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using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
namespace OLLamaClient
{
public class ollama_chat_message
{
public string role { get; set; }
public string content { get; set; }
}
}

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using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
namespace OLLamaClient
{
public class ollama_generate
{
public string model { get; set; }
public string prompt { get; set; }
public bool stream { get; set; }
public List<string> images { get; set; }
}
}

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using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
namespace OLLamaClient
{
public class ollama_generate_response
{
public string model { get; set; }
public DateTime created_at { get; set; }
public string response { get; set; }
public bool done { get; set; }
List<int> context { get; set; }
public long total_duration { get; set; }
public long load_duration { get; set; }
public long prompt_eval_count { get; set; }
public long prompt_eval_duration { get; set; }
public long eval_count { get; set; }
public long eval_duration { get; set; }
}
public class ollama_chat_response
{
public string model { get; set; }
public DateTime created_at { get; set; }
public ollama_chat_message message { get; set; }
public string done_reason { get; set; }
public bool done { get; set; }
public long total_duration { get; set; }
public long load_duration { get; set; }
public long prompt_eval_count { get; set; }
public long prompt_eval_duration { get; set; }
public long eval_count { get; set; }
public long eval_duration { get; set; }
}
}

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#include <iostream>
#include "Utils/Utils.h"
std::string GenerateByAI(std::string model, std::string msg)
{
msg = StringHelper::Replace(msg, "\r", " ");
msg = StringHelper::Replace(msg, "\n", " ");
msg = StringHelper::Replace(msg, "\\", "/");
std::string currStr = "";
std::string tmpStr = "";
auto json = StringHelper::Format(R"({"model":"%s","messages":[{"role":"user","content":"%s"}],"stream":true})", model.c_str(), msg.c_str());
auto result = HttpHelper::PostStream(
"http://localhost:11434/api/chat",
Convert::AnsiToUtf8(json),
"Content-Type: application/json",
"",
[&](std::string s)
{
tmpStr += s;
int idx = StringHelper::IndexOf(tmpStr, "\n");
if (idx >= 0)
{
std::string pak = tmpStr.substr(0, idx + 1);
auto j = json::parse(pak);
bool done = j["done"];
if (done == false)
{
if (j.contains("message"))
{
auto message = j["message"];
if (message.contains("content"))
{
std::string content = Convert::Utf8ToAnsi(message["content"]);
printf("%s", content.c_str());
currStr += content;
}
}
}
tmpStr = tmpStr.substr(idx + 1);
}
}
);
return currStr;
}
const char* _testMessage = R"(你需要扮演一名抖音客服,你的目标是解决客户的疑问并尽可能拿到客户的联系方式或者引导客户来联系我们的服务人员,你需要参考下面的文档来建立工作内容的知识,并参考聊天的上下文给出回复消息,你只需要输出回复的消息即可,不允许输出其他任何内容
:U代表客户,S代表你自己()
:
S:
U:,?
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int main()
{
system("ollama list");
std::string msg = GenerateByAI("qwen2.5-coder:32b", _testMessage);
printf("\n----------------------------------\n");
}

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