kalosm 0.4.0

A simple interface for pretrained AI models
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73

use kalosm::language::*;
use surrealdb::{engine::local::SurrealKv, Surreal};

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    let exists = std::path::Path::new("./db").exists();

    // Create database connection
    let db = Surreal::new::<SurrealKv>("./db/temp.db").await?;

    // Select a specific namespace / database
    db.use_ns("test").use_db("test").await?;

    // Create a chunker splits the document into chunks to be embedded
    let chunker = SemanticChunker::new();

    // Create a table in the surreal database to store the embeddings
    let document_table = db
        .document_table_builder("documents")
        .with_chunker(chunker)
        .at("./db/embeddings.db")
        .build::<Document>()
        .await?;

    // If the database is new, add documents to it
    if !exists {
        std::fs::create_dir_all("documents")?;
        let context = [
            "https://floneum.com/kalosm/docs",
            "https://floneum.com/kalosm/docs/guides/retrieval_augmented_generation",
        ]
        .iter()
        .map(|url| Url::parse(url).unwrap());

        document_table.add_context(context).await?;
    }

    // Create a llama chat model
    let model = Llama::new_chat().await?;
    let mut chat = model.chat().with_system_prompt("The assistant help answer questions based on the context given by the user. The model knows that the information the user gives it is always true.");

    loop {
        // Ask the user for a question
        let user_question = prompt_input("\n> ")?;

        // Search for relevant context in the document engine
        let context = document_table
            .search(&user_question)
            .with_results(1)
            .await?
            .into_iter()
            .map(|document| {
                format!(
                    "Title: {}\nBody: {}\n",
                    document.record.title(),
                    document.record.body()
                )
            })
            .collect::<Vec<_>>()
            .join("\n");

        // Format a prompt with the question and context
        let prompt = format!("{context}\n{user_question}");

        // Display the prompt to the user for debugging purposes
        println!("{}", prompt);

        // And finally, respond to the user
        let mut output_stream = chat(&prompt);
        print!("Bot: ");
        output_stream.to_std_out().await?;
    }
}