---
title: "Implement Ollama with ASP.NET Core API"  
description: "Artificial Intelligence is rapidly becoming a core part of modern web applications. From chatbots and content generation to code assistants and docume"  
author: "Ravi Vishwakarma"  
published: 2026-05-09  
updated: 2026-05-11  
canonical: https://www.mindstick.com/blog/306915/implement-ollama-with-asp-dot-net-core-api  
category: "software development"  
tags: [".net", "software development", ".net core", "software"]  
reading_time: 6 minutes  

---

# Implement Ollama with ASP.NET Core API

[Artificial Intelligence](https://www.mindstick.com/articles/44601/impact-of-artificial-intelligence-in-digital-marketing-is-huge-and-worthy) is rapidly becoming a core part of modern web applications. From chatbots and content generation to code assistants and document analysis, developers are integrating [Large Language Models (LLMs)](https://www.mindstick.com/forum/162047/what-are-large-language-models-llms-and-how-do-they-work) into applications faster than ever.

While cloud AI services like OpenAI and Google are popular, many developers now prefer running AI models locally for:

- Better privacy
- Lower API cost
- Offline access
- Faster experimentation
- Full control over models

This is where Ollama becomes extremely useful.

In this article, you will learn how to integrate Ollama with an ASP.NET Core API and build your own AI-powered backend service.

## What is Ollama?

Ollama is a lightweight tool that allows you to run Large Language Models locally on your machine.

It supports models like:

- Llama 3
- Mistral
- Gemma
- DeepSeek
- Phi
- CodeLlama

Ollama exposes a local REST API, making it easy to integrate with .NET applications.

## Why Use Ollama with .NET?

[Benefits of integrating](https://answers.mindstick.com/qa/112289/what-are-the-benefits-of-integrating-environmental-education-into-the-curriculum) Ollama with ASP.NET Core:

| Feature | Benefit |
| --- | --- |
| Local AI Processing | No external API dependency |
| Privacy | Data stays on your machine |
| No Token Billing | No per-request charges |
| Easy Integration | REST-based API |
| Fast Development | Works with HttpClient |
| Offline Support | Internet not required |

## Prerequisites

Before starting, install:

- .NET 8 SDK
- Ollama
- Visual Studio 2022 / VS Code

## Install Ollama

Download Ollama from:

[Ollama Official Website](https://ollama.com/?utm_source=chatgpt.com)

After installation, verify:

```plaintext
ollama --version
```

## Pull an AI Model

Example using Llama 3:

```plaintext
ollama pull llama3
```

Run the model:

```plaintext
ollama run llama3
```

Ollama automatically starts a local API server on:

```plaintext
http://localhost:11434
```

## Create ASP.NET Core Web API

Create a new project:

```plaintext
dotnet new webapi -n OllamaApi
```

Open project:

```plaintext
cd OllamaApi
```

## Create Request Models

Create `Models/OllamaRequest.cs`

```cs
namespace OllamaApi.Models
{
    public class OllamaRequest
    {
        public string Model { get; set; }
        public string Prompt { get; set; }
        public bool Stream { get; set; } = false;
    }
}
```

## Create Response Model

`Models/OllamaResponse.cs`

```cs
namespace OllamaApi.Models
{
    public class OllamaResponse
    {
        public string Response { get; set; }
    }
}
```

## Create Ollama Service

Create `Services/OllamaService.cs`

```cs
using System.Text;
using System.Text.Json;
using OllamaApi.Models;

namespace OllamaApi.Services
{
    public class OllamaService
    {
        private readonly HttpClient _httpClient;

        public OllamaService(HttpClient httpClient)
        {
            _httpClient = httpClient;
        }

        public async Task<string> GenerateAsync(string prompt)
        {
            var request = new OllamaRequest
            {
                Model = "llama3",
                Prompt = prompt,
                Stream = false
            };

            var json = JsonSerializer.Serialize(request);

            var content = new StringContent(
                json,
                Encoding.UTF8,
                "application/json");

            var response = await _httpClient.PostAsync(
                "api/generate",
                content);

            response.EnsureSuccessStatusCode();

            var result = await response.Content.ReadAsStringAsync();

            using var document = JsonDocument.Parse(result);

            return document
                .RootElement
                .GetProperty("response")
                .GetString();
        }
    }
}
```

## Register HttpClient

Update `Program.cs`

```cs
using OllamaApi.Services;

var builder = WebApplication.CreateBuilder(args);

builder.Services.AddControllers();

builder.Services.AddHttpClient<OllamaService>(client =>
{
    client.BaseAddress =
        new Uri("http://localhost:11434/");
});

builder.Services.AddEndpointsApiExplorer();
builder.Services.AddSwaggerGen();

var app = builder.Build();

app.UseSwagger();
app.UseSwaggerUI();

app.MapControllers();

app.Run();
```

## Create API Controller

Create `Controllers/AiController.cs`

```cs
using Microsoft.AspNetCore.Mvc;
using OllamaApi.Services;

namespace OllamaApi.Controllers
{
    [ApiController]
    [Route("api/[controller]")]
    public class AiController : ControllerBase
    {
        private readonly OllamaService _ollamaService;

        public AiController(
            OllamaService ollamaService)
        {
            _ollamaService = ollamaService;
        }

        [HttpPost("generate")]
        public async Task<IActionResult> Generate(
            [FromBody] string prompt)
        {
            var result =
                await _ollamaService.GenerateAsync(prompt);

            return Ok(new
            {
                success = true,
                data = result
            });
        }
    }
}
```

## Run the API

Start ASP.NET Core project:

```plaintext
dotnet run
```

Swagger URL:

```plaintext
https://localhost:5001/swagger
```

## Test API Request

Example request:

```plaintext
{
  "prompt": "Explain dependency injection in .NET"
}
```

Example response:

```plaintext
{
  "success": true,
  "data": "Dependency Injection is a design pattern..."
}
```

## Advanced Features

You can extend the system with:

| Feature | Description |
| --- | --- |
| [Streaming Responses](https://answers.mindstick.com/blog/395/streaming-responses-from-an-llm-in-asp-dot-net-core-real-time-ai-output-with-server-sent-events) | Real-time token generation |
| Multi-Model Support | Switch models dynamically |
| Chat Memory | Store conversation history |
| Vector Database | Semantic search |
| RAG Pipeline | Retrieval-Augmented Generation |
| AI Agents | Automated workflows |
| Function Calling | Execute server functions |

## Using Streaming Responses

Ollama supports token streaming.

Request example:

```plaintext
{
  "model": "llama3",
  "prompt": "Write article about .NET",
  "stream": true
}
```

Streaming is useful for:

- Chat applications
- Live typing effect
- AI assistants
- Content generation tools

## Best Practices

## Use Background Services

For heavy AI tasks:

- Queue requests
- Use Hosted Services
- Avoid blocking HTTP requests

## Add Timeout Handling

```plaintext
_httpClient.Timeout = TimeSpan.FromMinutes(5);
```

## Validate User Prompts

Prevent:

- Prompt injection
- Abuse
- Extremely large requests

## Cache Responses

Useful for:

- Repeated prompts
- SEO article generation
- FAQ systems

## Real-World Use Cases

| Use Case | Description |
| --- | --- |
| AI Chatbot | Customer support |
| Auto Blogging | Generate articles |
| Code Assistant | Generate code snippets |
| Q&A Platform | AI answer suggestions |
| Document Summarizer | Summarize PDFs |
| AI Search | Semantic search |
| Email Writer | Generate professional emails |

## Ollama vs Cloud AI APIs

| Feature | Ollama | Cloud APIs |
| --- | --- | --- |
| Internet Required | No | Yes |
| Cost | Free | Pay-per-token |
| Privacy | High | Medium |
| Setup Complexity | Medium | Easy |
| Scalability | Local hardware limited | High |
| Offline Usage | Yes | No |

## Conclusion

[Integrating Ollama](https://answers.mindstick.com/qa/116749/integrating-ollama-with-asp-dot-net-core) with ASP.NET Core is a powerful way to build AI-enabled applications without depending entirely on cloud providers.

With only a few lines of C# code, you can create:

- AI chat systems
- Auto content generators
- [AI search engines](https://www.mindstick.com/blog/305721/what-it-takes-to-rank-in-ai-search-engines-seo-and-geo-optimization-in-2025)
- Smart assistants
- Code generation tools

For developers already working in the .NET ecosystem, Ollama provides a simple and cost-effective way to bring local AI capabilities into production-ready applications.

## Official Resources

- [Ollama Documentation](https://ollama.com/library?utm_source=chatgpt.com)
- [ASP.NET Core Documentation](https://learn.microsoft.com/aspnet/core?utm_source=chatgpt.com)
- [Ollama GitHub Repository](https://github.com/ollama/ollama?utm_source=chatgpt.com)

---

Original Source: https://www.mindstick.com/blog/306915/implement-ollama-with-asp-dot-net-core-api

Copyright © MindStick Software Pvt. Ltd. This Markdown version is provided for developers, AI systems, and offline reading.