shai 0.3.1

A shell AI assistant
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
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160

#![allow(clippy::future_not_send)]

pub(crate) mod anthropic;
pub mod cli;
mod context;
mod model;
mod openai;
mod prompts;
pub(crate) mod sse_parser;

use anthropic::AnthropicModel;
use context::Context;
use futures::Stream;
use model::Task;
use openai::OpenAIGPTModel;
use serde::Deserialize;
use thiserror::Error;

enum ConfigKind {
    Ask(AskConfig),
    Explain(ExplainConfig),
}

impl ConfigKind {
    const fn model(&self) -> &ModelKind {
        match self {
            Self::Ask(config) => &config.model,
            Self::Explain(config) => &config.model,
        }
    }
}

#[derive(Deserialize)]
struct AskConfig {
    operating_system: String,
    shell: String,
    environment: Option<Vec<String>>,
    programs: Option<Vec<String>>,
    cwd: Option<()>,
    depth: Option<u32>,
    model: ModelKind,
}

#[derive(Deserialize)]
struct ExplainConfig {
    operating_system: String,
    shell: String,
    environment: Option<Vec<String>>,
    model: ModelKind,
    cwd: Option<()>,
    depth: Option<u32>,
}

impl Default for AskConfig {
    fn default() -> Self {
        Self {
            operating_system: "Linux".to_string(),
            shell: "Bash".to_string(),
            environment: None,
            programs: None,
            cwd: None,
            depth: None,
            model: ModelKind::OpenAIGPT(OpenAIGPTModel::GPT4oMini),
        }
    }
}

impl Default for ExplainConfig {
    fn default() -> Self {
        Self {
            operating_system: "Linux".to_string(),
            shell: "Bash".to_string(),
            environment: None,
            cwd: None,
            depth: None,
            model: ModelKind::OpenAIGPT(OpenAIGPTModel::GPT4oMini),
        }
    }
}

#[derive(Deserialize, Clone)]
enum ModelKind {
    OpenAIGPT(OpenAIGPTModel),
    Anthropic(AnthropicModel),
    // OpenAssistant // waiting for a minimal API, go guys :D
    // Local // ?
}

#[derive(Debug, Error)]
pub(crate) enum ModelError {
    #[error("{0}")]
    Error(String),
}

impl From<Box<dyn std::error::Error + Send>> for ModelError {
    fn from(e: Box<dyn std::error::Error + Send>) -> Self {
        Self::Error(e.to_string())
    }
}

#[allow(unused)]
async fn model_request(
    model: ModelKind,
    request: String,
    context: Context,
    task: Task,
) -> Result<String, ModelError> {
    match model {
        ModelKind::OpenAIGPT(model) => model
            .send(request, context, task)
            .await
            .map_err(|err| ModelError::Error(err.to_string())),
        ModelKind::Anthropic(model) => model
            .send(request, context, task)
            .await
            .map_err(|err| ModelError::Error(err.to_string())),
    }
}

async fn model_stream_request(
    model: ModelKind,
    request: String,
    context: Context,
    task: Task,
) -> Result<impl Stream<Item = Result<String, ModelError>> + Send, ModelError> {
    match model {
        ModelKind::OpenAIGPT(model) => model
            .send_streaming(request, context, task)
            .await
            .map_err(|e| ModelError::Error(e.to_string())),
        ModelKind::Anthropic(model) => model
            .send_streaming(request, context, task)
            .await
            .map_err(|e| ModelError::Error(e.to_string())),
    }
}

fn build_context_request(request: &str, context: Context) -> String {
    String::from(context) + &format!("Here is your <task>: \n <task>{request}</task>")
}

// #[cfg(test)]
// mod tests {
//     use crate::{
//         context::Context, model::Task, model_stream_request, openai::OpenAIGPTModel::GPT35Turbo,
//         AskConfig, ConfigKind, ModelKind::OpenAIGPT,
//     };
//     use futures_util::StreamExt;
//
//     #[tokio::test]
//     async fn ssh_tunnel() {
//         let mut  response_stream = model_stream_request(OpenAIGPT(GPT35Turbo), 
//             "make an ssh tunnel between port 8080 in this machine and port 1243 in the machine with IP 192.168.0.42".to_string(), 
//             Context::from(ConfigKind::Ask(AskConfig::default())),
//             Task::GenerateCommand
//             ).await.unwrap();
//         while response_stream.next().await.is_some() {
//         }
//     }
// }