This is an unofficial library. MistralAI does not provide any official library for Delphi. This repositorty contains Delphi implementation over MistralAI public API.
To initialize API instance you need to obtain API token from.
Once you have a token, you can initialize IMistralAI interface, which is an entry point to the API.
Due to the fact that there can be many parameters and not all of them are required, they are configured using an anonymous function.
uses MistralAI;
var MistralAI: IMistralAI := TMistralAI.Create(API_TOKEN);List the various models available in the API. You can refer to the Models documentation to understand what models are available. See Models Documentation
//uses MistralAI, MistralAI.Models;
var Models := MistralAI.Models.List;
try
for var Model in Models.Data do
Memo1.Lines.Add(Model.id);
finally
Models.Free;
end;Embeddings make it possible to vectorize one or more texts in order, for example, to calculate the similarity between sentences. Each vector resulted will be of dimension 1024. This vector representation captures deep semantic aspects of texts, allowing for more nuanced comparisons. Distance measures such as cosine, Euclidean distance or other custom measures can be applied to these embeddings.
See also tokenization at the MistralAI web site.
//uses MistralAI, MistralAI.Embeddings;
var Embeddings := MistralAI.Embeddings.Create(
procedure (Params: TEmbeddingParams)
begin
Params.Model('mistral-embed'); //By default this is the model used so this line can be omitted
Params.Input(['aba', 'bbb']);
end);
try
for var Value in Embeddings.Data do
begin
Memo1.Lines.Add('-----------------------------' + Value.index.ToString);
for var Item in Value.Embedding do
Memo1.Lines.Add(Item.ToString);
end;
finally
Embeddings.Free;
end;Using the API to create and maintain conversations. You have the option to either wait for a complete response or receive the response sequentially (Streaming mode).
See also Prompting Capabilities at the MistralAI web site.
//uses MistralAI, MistralAI.Chat;
var Chat := MistralAI.Chat.Create(
procedure (Params: TChatParams)
begin
Params.Model('mistral-tiny');
Params.Messages([TChatMessagePayload.User(Memo2.Text)]);
Params.MaxTokens(1024);
end);
try
for var Choice in Chat.Choices do
Memo1.Lines.Add(Choice.Message.Content);
finally
Chat.Free;
end;//uses MistralAI, MistralAI.Chat;
MistralAI.Chat.CreateStream(
procedure(Params: TChatParams)
begin
Params.Model('mistral-medium');
Params.Messages([TChatMessagePayload.User(Memo2.Text)]);
Params.MaxTokens(1024);
Params.Stream;
end,
procedure(var Chat: TChat; IsDone: Boolean; var Cancel: Boolean)
begin
if (not IsDone) and Assigned(Chat) then
begin
Memo1.Text := Memo1.Text + Chat.Choices[0].Delta.Content;
Application.ProcessMessages;
end
else if IsDone then
Memo1.Text := Memo1.Text + '--- Done';
Sleep(30);
end);Function calling allows Mistral models to connect to external tools. By integrating Mistral models with external tools such as user defined functions or APIs, users can easily build applications catering to specific use cases and practical problems.
See also documentation at the MistralAI web site.
Warning : While this technology is powerful, it also carries potential risks. We strongly advise incorporating user confirmation processes before executing real-world actions on behalf of users, such as sending emails, posting online, making purchases, etc.
//uses
// MistralAI, MistralAI.Chat,
// MistralAI.Functions.Core, MistralAI.Functions.Example;
var WeatherFunc: IFunctionCore := TWeatherReportFunction.Create; //plugin in charge of the external API that can be invoked by the model
var Chat := MistralAI.Chat.Create(
procedure (Params: TChatParams)
begin
Params.Model('mistral-small-latest');
Params.Messages([TChatMessagePayload.User(Memo2.Text)]);
Params.SafePrompt(False);
Params.Stream(False);
Params.Temperature(0.7);
Params.TopP(1);
Params.Tools([TChatMessageTool.Add(WeatherFunc)]);
Params.ToolChoice(auto);
Params.MaxTokens(64);
Params.RandomSeed(1337);
end);
try
for var Choice in Chat.Choices do
begin
if Choice.FinishReason = TFinishReason.tool_calls then
CallFunction(Choice.Message.ToolsCalls[0], WeatherFunc)
else
Memo1.Lines.Add(Choice.Message.Content); //Display message content if function is not called
end;
finally
Chat.Free;
end;
procedure CallFunction(const Value: TCalledFunction; Func: IFunctionCore);
begin
var ArgResult := Func.Execute(Value.&Function.Arguments);
var Chat := MistralAI.Chat.Create(
procedure (Params: TChatParams)
begin
Params.Model('open-mixtral-8x22b-2404');
Params.Messages([
TChatMessagePayload.User(Memo2.Text),
TChatMessagePayload.User(ArgResult)
]);
Params.MaxTokens(1024);
end);
try
for var Choice in Chat.Choices do
Memo1.Lines.Add(Choice.Message.Content); //Display message content
finally
Chat.Free;
end;
end;Users have the option to set response_format to {"type": "json_object"} to enable JSON mode. It's important to explicitly ask the model to generate JSON output in your message. Currently, JSON mode is available for all of the models through API.
See also documentation at the MistralAI web site.
//uses MistralAI, MistralAI.Chat;
var Chat := MistralAI.Chat.Create(
procedure (Params: TChatParams)
begin
Params.Model('mistral-tiny');
Params.Messages([TChatMessagePayload.User(Memo2.Text)]);
Params.ResponseFormat(); //Enable JSON mode
Params.MaxTokens(1024);
end);
try
for var Choice in Chat.Choices do
Memo1.Lines.Add(Choice.Message.Content);
finally
Chat.Free;
end;Pull requests are welcome. If you're planning to make a major change, please open an issue first to discuss your proposed changes.
This project is licensed under the MIT License.