<?php

require_once __DIR__."/lib/index.php";
$debug_level = 0;

function LlamaCli(string|array $prompt, string $system = "You are a helpful assistant", array $options = []) {	

	//
	// ---- 0. OPTIONS (Default and provided) -----
	//
	global $debug_level;

	// Get the options passed
	extract($options);

	// Set defaults for what was not explicitly specified

	$llamacpp_bin         = $llamacpp_bin ?? "/home/frederico/llama.cpp/build/bin/llama-cli";
	$llamacpp_model_path  = $llamacpp_model_path ?? "/home/frederico/llama.cpp/models";
	$llamacpp_model       = $llamacpp_model ?? "Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf";

	$parseCodeInOutput    = $parseCodeInOutput ?? true;
	$previousConversation = $previousConversation ?? []; // expects: [["role"=>"assistant","content"=>"How can I help you?"],["role"=>"user","content"=>"Tell me the capital of France"]]
	$debug_level          = $debug_level ?? 0;

	$context_size         = $context_size ?? 4096;

	//
	// ---- 1. INPUT TO LLM (DSL: adjustments needed) -----
	//
	
	// 1.1 Parse the prompt and resolve actions "@"
	//if (is_array($prompt)) foreach($prompt as $i => $chunk) $prompt[$i] = ExpandFetcherCommands($chunk);
	//else 
	$prompt = ExpandFetcherCommands($prompt);

	// 1.2 Parse expanders / compressors
	while(ParseExpandersIteratorsCompressors($prompt, "input",$options)) { }

	if (is_array($prompt)) die("ERROR: at LLM stage, prompt is an array. Use '>(json|new-line)' compressor.");

	
	// $llm_stdin = $prompt;
	// Llama chat template
	$llm_stdin  = "<|start_header_id|>system<|end_header_id|>$system<|eot_id|>";
	foreach($previousConversation as $message)
		$llm_stdin .= "<|start_header_id|>{$message["role"]}<|end_header_id|>{$message["content"]}<|eot_id|>";
	$llm_stdin .= "<|start_header_id|>user<|end_header_id|>$prompt<|eot_id|>";
	$llm_stdin .= "<|start_header_id|>assistant<|end_header_id|>";
	
	// Create a unique temporary file for STDIN, input data
	$input_file_name = tempnam(sys_get_temp_dir(), 'tmp_');
	if ($debug_level >= 4) file_put_contents("php://stderr","input_file_name $input_file_name content: $llm_stdin\n");
	file_put_contents($input_file_name, $llm_stdin);

	// Create a unique temporary file for STDERR, debug data
	$debug_file_name = tempnam(sys_get_temp_dir(), 'tmp_');
	if ($debug_file_name === false) die("Could not create temporary file\n");


	$command = "$llamacpp_bin \
			-m $llamacpp_model_path/$llamacpp_model \
			-f $input_file_name \
			-c $context_size \
			-no-cnv \
			--simple-io \
			2> $debug_file_name ";
	if ($debug_level >= 3) file_put_contents("php://stderr","Attempting command: $command\n");
	$output = shell_exec($command);


	// Save the DEBUG data from the LLM
	$debug_data = file_get_contents($debug_file_name);
	if ($debug_level >= 5) file_put_contents("php://stderr","debug_file_name $debug_file_name content: $debug_data\n");

	// Clean TEMP files
	if (file_exists($debug_file_name)) unlink($debug_file_name);
	if (file_exists($input_file_name)) unlink($input_file_name);

	//
	// 5. Erase the input from the output
	//

	// 5.1 Llama specific model. produces in this format:
	$output = str_replace("system$system", "", $output);
	$output = str_replace("user$prompt"."assistant", "", $output);
	foreach($previousConversation as $message)
		$output = str_replace($message["role"].$message["content"],"",$output);
	$output = str_replace("[end of text]", "", $output);
	// 5.2 Generic input 
	//$output = str_replace($llm_stdin, "", $output);
	// 5.3 Sanitize output
	$output = trim($output);
	if ($parseCodeInOutput)
		$output = ExtractCodeSections($output);


	return $output;
}

function LlamaCli_raw(string $prompt, string $system = "You are a helpful assistant", array $options = []) { $options["parseCodeInOutput"] = false; return LlamaCli($prompt, $system,$options); }