use std::time::Instant;
use anyhow::{Ok, Result};
use crate::exec::ExecModel;
use crate::models::{GenerateModel, glm_ocr::generate::GlmOcrGenerateModel};
pub struct GlmOcrExec;
impl ExecModel for GlmOcrExec {
fn run(input: &[String], output: Option<&str>, weight_path: &str) -> Result<()> {
let url = &input[0];
let input_url = if url.starts_with("http://")
|| url.starts_with("https://")
|| url.starts_with("file://")
{
url.clone()
} else {
format!("file://{}", url)
};
let i_start = Instant::now();
let mut model = GlmOcrGenerateModel::init(weight_path, None, None)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in load model is: {:?}", i_duration);
let message = format!(
r#"{{
"model": "ZhipuAI/GLM-OCR",
"messages": [
{{
"role": "user",
"content": [
{{
"type": "image_url",
"image_url": {{
"url": "{}"
}}
}},
{{
"type": "text",
"text": "Text Recognition:"
}}
]
}}
],
"max_tokens": 1024
}}"#,
input_url
);
let mes = serde_json::from_str(&message)?;
let i_start = Instant::now();
let result = model.generate(mes)?;
let i_duration = i_start.elapsed();
println!("Time elapsed in generate is: {:?}", i_duration);
println!("Result: {:?}", result);
if let Some(out) = output {
std::fs::write(out, format!("{:?}", result))?;
println!("Output saved to: {}", out);
}
Ok(())
}
}