Phind–Your personal programming assistant

With the release of ChatGPT, GitHub Copilot, Amazon Code Whisperer just to name a few, large language models are the (new?) cool kid in town and you see a lot of new applications pop up trying to claim a part of this space.

If you are still in doubt if these tools can help improve your developer productivity, check out this survey executed and published by GitHub.

92% of developers already saying they use AI coding tools at work and in their personal time, which makes it clear AI is here to stay. 70% of the developers we surveyed say they already see significant benefits when using AI coding tools, and 81% of the developers we surveyed expect AI coding tools to make their teams more collaborative—which is a net benefit for companies looking to improve both developer velocity and the developer experience.

The list of available tools is long and keeps growing every day. Here are some I’m aware of:

• GitHub Copilot
• Amazon CodeWhisperer
• Codeium
• CodeComplete
• Refact.ai
• GitLab Code Suggestions (beta.)
• JetBrains AI coding assistant

And of course let us not forget ChatGPT.

Today I want to add another one to the list; Phind. Phind uses a combination of GPT-4 and their own model. This model should hallucinate less and write better code.

I started by asking to create a small application using the Task Parallel Library(TPL) DataFlow in C#:

	using System;
	using System.IO;
	using System.Threading.Tasks;
	using System.Threading.Tasks.Dataflow;
	class Program
	{
	static void Main(string[] args)
	{
	var block = new TransformBlock<string, string[]>(line =>
	{
	// Parse the line
	var columns = line.Split(',');
	return columns;
	});
	ReadFileAsync("yourfile.csv", block).Wait();
	// Print the results
	foreach (var item in block.Receive())
	{
	Console.WriteLine(string.Join(", ", item));
	}
	}
	static async Task ReadFileAsync(string filePath, ITargetBlock<string> target)
	{
	using (var sr = new StreamReader(filePath))
	{
	string line;
	while ((line = await sr.ReadLineAsync()) != null)
	{
	await target.SendAsync(line);
	}
	}
	target.Complete();
	}
	}

view raw Example1.cs hosted with ❤ by GitHub

 

Here is the exact prompt I was using:

I want to create a new C# application using the Task Parallel Library. This application should read a CSV file and parse it using multiple datablocks. Can you give me an example on how to write this code?
The result is not bad although the created example doesn’t take advantage of the TPL as it first reads all the data into memory. Let’s see if we can fix this:

This gives the following result:

	using System;
	using System.IO;
	using System.Threading.Tasks;
	using System.Threading.Tasks.Dataflow;
	class Program
	{
	static async Task Main(string[] args)
	{
	var block = new TransformBlock<string, string[]>(line =>
	{
	try
	{
	// Parse the line
	var columns = line.Split(',');
	return columns;
	}
	catch (Exception ex)
	{
	Console.WriteLine($"Failed to parse line '{line}'. Error: {ex.Message}");
	return null;
	}
	});
	var printBlock = new ActionBlock<string[]>(item =>
	{
	if (item != null)
	{
	Console.WriteLine(string.Join(", ", item));
	}
	});
	block.LinkTo(printBlock, new DataflowLinkOptions { PropagateCompletion = true });
	try
	{
	await ReadFileAsync("yourfile.csv", block);
	block.Complete();
	await printBlock.Completion;
	}
	catch (Exception ex)
	{
	Console.WriteLine($"Failed to read file. Error: {ex.Message}");
	}
	}
	static async Task ReadFileAsync(string filePath, ITargetBlock<string> target)
	{
	using (var sr = new StreamReader(filePath))
	{
	string line;
	while ((line = await sr.ReadLineAsync()) != null)
	{
	await target.SendAsync(line);
	}
	}
	}
	}

view raw Example2.cs hosted with ❤ by GitHub

The Main method became async and we got rid of the Wait() statement as we wanted. This is much better and more in line with the asynchronous nature of the Task Parallel Library.

Love it! (Of course it is again a good example on how you as a developer still need to understand what is going on so you can hint the AI assistent to improve the code).

Remark: You can also use it directly inside VSCode using this plugin.

If you compare this with what I got back from ChatGPT, the example created by Phind is much more what I expected:

	using System;
	using System.Collections.Generic;
	using System.IO;
	using System.Threading.Tasks;
	namespace CSVParserApp
	{
	class Program
	{
	static async Task Main(string[] args)
	{
	string csvFilePath = "path_to_your_csv_file.csv";
	int numDataBlocks = 4; // Number of data blocks to use
	List<Task> tasks = new List<Task>();
	using (StreamReader reader = new StreamReader(csvFilePath))
	{
	// Read and ignore the header line
	await reader.ReadLineAsync();
	for (int i = 0; i < numDataBlocks; i++)
	{
	tasks.Add(Task.Run(async () =>
	{
	while (!reader.EndOfStream)
	{
	string line = await reader.ReadLineAsync();
	// Parse the CSV line here
	string[] values = line.Split(',');
	// Process the values or store them as needed
	// Example: Console.WriteLine(string.Join(", ", values));
	}
	}));
	}
	await Task.WhenAll(tasks);
	}
	Console.WriteLine("CSV parsing complete.");
	}
	}
	}

view raw Example3.cs hosted with ❤ by GitHub

And just for completeness, this is what I got back when asking the same question at GitHub Copilot Chat:

	using System.Collections.Generic;
	using System.IO;
	using System.Linq;
	using System.Threading.Tasks;
	public class CsvParser
	{
	private const int BlockSize = 1000;
	public async Task<List<string[]>> ParseCsv(string filePath)
	{
	var lines = new List<string[]>();
	using (var stream = new StreamReader(filePath))
	{
	var headers = await stream.ReadLineAsync();
	while (!stream.EndOfStream)
	{
	var currentBlock = new List<string[]>();
	for (var i = 0; i < BlockSize && !stream.EndOfStream; i++)
	{
	var line = await stream.ReadLineAsync();
	var values = line.Split(',');
	currentBlock.Add(values);
	}
	lines.AddRange(await ParseBlockAsync(currentBlock));
	}
	}
	return lines;
	}
	private async Task<List<string[]>> ParseBlockAsync(List<string[]> block)
	{
	return await Task.Run(() =>
	{
	return block.AsParallel().Select(ParseRow).ToList();
	});
	}
	private string[] ParseRow(string[] values)
	{
	// Apply logic to parse CSV values
	return values;
	}
	}

view raw Example4.cs hosted with ❤ by GitHub

Not so good either. Phind is a clear winner int this example…

Remark: I tried some related prompts to further improve the result I got back from ChatGPT and GitHub Copilot but I never got to the result I got from Phind.