Add log entry; disable lots of debugging

README.md

@@ -123,6 +123,12 @@ Draw some stuff on your screen, and then trigger the assistant by *touching/tapp
   * Oh -- I think it's rather important to run each set a few times assuming there is some temperature involved
   * To scale this even further we of course would want to bring in a JUDGE-BOT!
   * Then I could say things like "my new segmentation algorithm improved output quality by 17% per the JUDGE-BOT" etc
+* **2024-12-25** -- CLI simplify and expand
+  * Now you can pass just `-m gpt-4o-mini` and it will guess the engine is `openai`
+  * You can also pass `--engine-api-key` and `--engine-url-base`
+  * So now to use [Groq](https://groq.com/): `./ghostwriter -m llama-3.2-90b-vision-preview --engine-api-key $GROQ_API_KEY --engine openai --engine-base-url https://api.groq.com/openai`
+  * ... but so far Llama 3.2 90b vision is still quite bad with this interface
+  * I turned off a bunch of debugging. Now I'll need to go back and introduce log-level or something
 
 ## Ideas
 * [DONE] Matt showed me his iOS super calc that just came out, take inspiration from that!

src/llm_engine/anthropic.rs

@@ -98,7 +98,7 @@ impl LLMEngine for Anthropic {
         });
 
         // print body for debugging
-        println!("Request: {}", body);
+        // println!("Request: {}", body);
 
         let raw_response = ureq::post(&format!("{}/v1/messages", self.base_url))
             .set("x-api-key", self.api_key.as_str())
@@ -118,7 +118,7 @@ impl LLMEngine for Anthropic {
         };
 
         let json: json = response.into_json().unwrap();
-        println!("Response: {}", json);
+        // println!("Response: {}", json);
         let tool_calls = &json["content"];
         if let Some(tool_call) = tool_calls.get(0) {
             let function_name = tool_call["name"].as_str().unwrap();

src/llm_engine/openai.rs

@@ -97,7 +97,7 @@ impl LLMEngine for OpenAI {
         });
 
         // print body for debugging
-        println!("Request: {}", body);
+        // println!("Request: {}", body);
         let raw_response = ureq::post(format!("{}/v1/chat/completions", self.base_url).as_str())
             .set("Authorization", &format!("Bearer {}", self.api_key))
             .set("Content-Type", "application/json")
@@ -115,7 +115,7 @@ impl LLMEngine for OpenAI {
         };
 
         let json: json = response.into_json().unwrap();
-        println!("Response: {}", json);
+        // println!("Response: {}", json);
 
         let tool_calls = &json["choices"][0]["message"]["tool_calls"];
 

src/main.rs

@@ -134,7 +134,7 @@ fn draw_svg(
 }
 
 fn load_config(filename: &str) -> String {
-    println!("Loading config from {}", filename);
+    // println!("Loading config from {}", filename);
 
     if std::path::Path::new(filename).exists() {
         std::fs::read_to_string(filename).unwrap()
@@ -271,7 +271,7 @@ fn ghostwriter(args: &Args) -> Result<()> {
         } else {
             String::new()
         };
-        println!("Segmentation description: {}", segmentation_description);
+        // println!("Segmentation description: {}", segmentation_description);
 
         let prompt_general_raw = load_config(&args.prompt);
         let prompt_general_json =

src/segmenter.rs

@@ -33,12 +33,12 @@ impl ImageAnalyzer {
         &self,
         image_path: &str,
     ) -> Result<SegmentationResult, Box<dyn std::error::Error>> {
-        println!("Reading image from: {}", image_path);
+        // println!("Reading image from: {}", image_path);
 
         // Read image and convert to grayscale
         let img = image::open(image_path)?.to_rgb8();
         let (width, height) = img.dimensions();
-        println!("Image loaded: {}x{}", width, height);
+        // println!("Image loaded: {}x{}", width, height);
 
         // Convert to grayscale
         let gray: GrayImage = image::imageops::grayscale(&img);
@@ -55,7 +55,7 @@ impl ImageAnalyzer {
 
         // Find contours
         let contours = find_contours(&binary);
-        println!("Found {} contours", contours.len());
+        // println!("Found {} contours", contours.len());
 
         // Process regions
         let mut regions = Vec::new();
@@ -91,7 +91,7 @@ impl ImageAnalyzer {
         regions.sort_by(|a, b| b.area.partial_cmp(&a.area).unwrap());
         regions.truncate(self.max_regions);
 
-        println!("Processed {} significant regions", regions.len());
+        // println!("Processed {} significant regions", regions.len());
 
         Ok(SegmentationResult {
             regions,
@@ -156,12 +156,12 @@ impl ImageAnalyzer {
 }
 
 pub fn analyze_image(image_path: &str) -> Result<String, Box<dyn std::error::Error>> {
-    println!("Reading image from: {}", image_path);
+    // println!("Reading image from: {}", image_path);
 
     // Read image and convert to grayscale
     let img = image::open(image_path)?.to_rgb8();
     let (width, height) = img.dimensions();
-    println!("Image loaded: {}x{}", width, height);
+    // println!("Image loaded: {}x{}", width, height);
 
     // Convert to grayscale
     let gray: GrayImage = image::imageops::grayscale(&img);
@@ -178,16 +178,16 @@ pub fn analyze_image(image_path: &str) -> Result<String, Box<dyn std::error::Err
 
     // Find contours
     let contours = find_contours(&binary);
-    println!("Found {} contours", contours.len());
+    // println!("Found {} contours", contours.len());
 
     // Process regions
     let mut regions = Vec::new();
     let min_area = 50.0; // (width * height) as f32 * 0.001; // Assuming min_region_size is 0.01
-    println!("Min region area: {}", min_area);
+    // println!("Min region area: {}", min_area);
 
     for contour in contours {
         let area = contour_area(&contour.points) as f32;
-        println!("Contour area: {}", area);
+        // println!("Contour area: {}", area);
 
         if area >= min_area {
             let bounds = min_area_rect(&contour.points);
@@ -216,7 +216,7 @@ pub fn analyze_image(image_path: &str) -> Result<String, Box<dyn std::error::Err
     regions.sort_by(|a, b| b.area.partial_cmp(&a.area).unwrap());
     regions.truncate(10); // Assuming max_regions is 10
 
-    println!("Processed {} significant regions", regions.len());
+    // println!("Processed {} significant regions", regions.len());
 
     let mut result = String::new();
     for region in regions {