add back ai primary buffer query (closes #1462)

2025-06-19 17:31:36 +02:00
parent f844a54a87
commit 4ebd486426
4 changed files with 342 additions and 1 deletions
@@ -64,7 +64,7 @@ bindd = Super+Alt, R, Record region (no sound), exec, ~/.config/hypr/hyprland/sc
 bindd = Ctrl+Alt, R, Record screen (no sound), exec, ~/.config/hypr/hyprland/scripts/record.sh --fullscreen # [hidden] Record screen (no sound)
 bindd = Super+Shift+Alt, R, Record screen (with sound), exec, ~/.config/hypr/hyprland/scripts/record.sh --fullscreen-sound # Record screen (with sound)
 # AI
-bindd = Super+Shift+Alt, mouse:273, Generate AI summary for selected text, exec, ~/.config/ags/scripts/ai/primary-buffer-query.sh # AI summary for selected text
+bindd = Super+Shift+Alt, mouse:273, Generate AI summary for selected text, exec, ~/.config/hypr/hyprland/scripts/ai/primary-buffer-query.sh # AI summary for selected text
 #!
 ##! Window
@@ -0,0 +1,201 @@
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@@ -0,0 +1,41 @@
 #!/usr/bin/env bash
 # Default system prompt
 SYSTEM_PROMPT="You are a helpful, quick assistant that provides brief and concise explanation \
 to given content in at most 100 characters. If the given content is not in English, translate \
 it to English. If the content is an English word, provide its meaning. If the content is a name, \
 provide some info about it. For a math expression, provide a simplification, \
 each step on a line following this style: \`2x=11 (subtract 7 from both sides)\`. \
 If you do not know the answer, simply say 'No info available'. \
 Only respond for the appropriate case and use as little text as possible.\
 The content:"
 first_loaded_model=$("$(dirname "$0")/show-loaded-ollama-models.sh" -j | jq -r '.[0].model' 2>/dev/null) || first_loaded_model=""
 model=${first_loaded_model:-"llama3.2"}
 # Parse command-line arguments
 while [[ "$#" -gt 0 ]]; do
    case $1 in
        --model) model="$2"; shift ;; # Set the model from the flag
        *) echo "Unknown parameter: $1"; exit 1 ;;
    esac
    shift
 done
 # Combine the system prompt with the clipboard content
 content=$(wl-paste -p | tr '\n' ' ')
 prompt="$SYSTEM_PROMPT $content"
 # Make the API call with the specified or default model
 response=$(curl http://localhost:11434/api/generate -d \
    "{\"model\": \"$model\",\"prompt\": \"$prompt\",\"stream\": false}" \
    | jq -r '.response')
 # Check if content is a single line and no longer than 30 characters
 if [[ ${#content} -le 30 && "$content" != *$'\n'* ]]; then
    notify-send --app-name="Text selection query" --expire-time=10000 \
        "$content" "$response"
 else
    notify-send --app-name="Text selection query" --expire-time=10000 \
        "AI Response" "$response"
 fi
@@ -0,0 +1,99 @@
 #!/bin/bash
 # From strikeoncmputrz/LLM_Scripts
 # License: Apache-2.0, can be found in the same folder as this script
 # Global Vars
 ollama_url=http://localhost
 port="11434"
 blobs=()
 model_name_paths=()
 #Parse arguments
 while [ "$#" -gt 0 ]; do
  case $1 in
    -h|--help)
      echo 
      echo " Identifies Ollama models running on this operating system by parsing running processes."
      echo 
      echo " Usage: $0 [options]"   
      echo
      echo " Options:"
      echo "  -j, --json_output        Prints result as a json object. Other output disabled. (Default: false)"      
      echo "  -p, --port [port number] Specify Ollama Server port (Default: 11434)"
      echo "  -u, --ollama_url [url]   Specify Ollama Server URL (Default: http://localhost)"
      echo
      echo " Dependencies: jq"
      exit 0
      ;;
    -j|--json_output)
      json_out=1
      shift 1
      ;;
    -u|--ollama_url)
      ollama_url=$2
      shift 2
      ;;
    -p|--port)
      port=$2
      shift 2
      ;;
    *)
      echo "Unknown option: $1"
      exit 1
      ;;
  esac
 done
 compare_running_models_and_modelfiles() { 
    json_match=()
    json_output=()
    local matching_models=()
    OLDIFS=$IFS
    for ((i=0; i<${#model_name_paths[@]}; i++)); do  # Iterate over the array of modelname,blob-path
        for blob in "${blobs[@]}"; do
            IFS=',', read -ra fields <<< "${model_name_paths[i]}"    # Split the string into parts
            if [ "${fields[1]}" == "$blob" ]; then  # Check if current 'field' matches a blob
                matching_models+=( '{ "model": "'"${fields[0]}"'", "path": "'"${fields[1]}"'"}') # Add to list of matching models
            fi
        done
    done
    if [ -z "$json_out" ]; then
        echo -e "\nModel Found: \n $(echo ${matching_models[*]} | jq '.' | sed s/[{}]//g) \n"        
    else
        local json_match="${matching_models[*]}"
        json_output=$(echo $json_match | jq -c -s .)
        echo "$json_output"
    fi
    IFS=$OLDIFS
 }
 get_running_model_paths() {
    blobs=$(ps aux | grep -- '--model' | grep -v grep | grep -Po '(?<=--model\s).*' | cut -d ' ' -f1)
    if [ -z "$blobs" ]; then
        echo -e "\n\n Warning: No running Ollama models detected!\n"
        exit 0
    fi
 }
 parse_modelfiles() {
    if [ -z "$json_out" ]; then
        echo -e "\nConnecting to $ollama_url:$port\n"
        if [ -z "$(curl -s $ollama_url:$port)" ]; then
           echo -e "Could not connect to Ollama. Check the ollama_url parameter and that the server is running\n"
           exit 1
        fi
        curl -s "$ollama_url:$port"
    fi
    local models=( $(curl -s "$ollama_url:$port/api/tags" | jq -r '.models[].name') )
    for model in "${models[@]}"; do
        local modelfile=$(curl -s "$ollama_url:$port/api/show" -d '{ "name": "'"$model"'", "modelfile": true }' | jq   -r '.modelfile')
        model_name_paths+=($model,$(echo "$modelfile" | awk '/^FROM/{print $2}'))
    done
 }
 parse_modelfiles
 get_running_model_paths
 compare_running_models_and_modelfiles