package main

import (
	"encoding/json"
	"log"
	"net/http"
	"runtime"
)

/*
#include "llama.h"
*/
import "C"

// Constant LLaMA parameters

const (
	ParamContextSize             = 512 // RAM requirements: 512 needs 800MB KV (~3216MB overall), 2048 needs 3200MB KV (~??? overall)
	ParamTopK                    = 40
	ParamTopP                    = 0.95
	ParamTemperature             = 0.08
	ParamRepeatPenalty           = 1.10
	ParamRepeatPenaltyWindowSize = 64
)

func (this *Application) POST_Chat(w http.ResponseWriter, r *http.Request) {
	flusher, ok := w.(http.Flusher)
	if !ok {
		http.Error(w, "The HTTP request does not support live updates", 500)
		return
	}

	// Parse API POST request

	type requestBody struct {
		ConversationID string
		APIKey         string
		Content        string
	}
	var apiParams requestBody
	err := json.NewDecoder(r.Body).Decode(&apiParams)
	if err != nil {
		http.Error(w, err.Error(), 400)
		return
	}

	// Verify API key
	// TODO

	// Wait for a free worker
	select {
	case this.sem <- struct{}{}:
		// OK
	case <-r.Context().Done():
		return // Request cancelled while waiting for free worker
	}

	defer func() { <-this.sem }()

	// Queue request to worker

	w.Header().Set("Content-Type", "text/plain;charset=UTF-8")
	w.WriteHeader(200)
	flusher.Flush() // Flush before any responses, so the webui knows things are happening

	// Start a new LLaMA session

	lparams := C.llama_context_default_params()
	lparams.n_ctx = ParamContextSize

	lcontext := C.llama_init_from_file(C.CString(this.cfg.ModelPath), lparams)
	defer C.llama_free(lcontext)

	// Feed in the conversation so far
	// TODO stash the contexts for reuse with LRU-caching, for faster startup/resumption

	apiParams.Content = " " + apiParams.Content // Add leading space to match LLaMA python behaviour

	llast_n_tokens := make([]C.llama_token, ParamContextSize)

	log.Println("tokenizing supplied prompt...")

	llast_n_tokens_used_size := C.llama_tokenize(lcontext, C.CString(apiParams.Content), &llast_n_tokens[0], ParamContextSize, true)
	if llast_n_tokens_used_size <= 0 {
		log.Printf("llama_tokenize returned non-positive size (%d)", llast_n_tokens_used_size)
		http.Error(w, "Internal error", 500)
		return
	}

	if (ParamContextSize - int(llast_n_tokens_used_size)) <= 4 {
		http.Error(w, "Prompt is too long", 400)
		return
	}

	// We've consumed all the input.

	for i := int(llast_n_tokens_used_size); i < ParamContextSize; i += 1 {
		if err := r.Context().Err(); err != nil {
			return
		}

		// Get the next token from LLaMA

		log.Println("doing llama_eval...")

		evalErr := C.llama_eval(lcontext,
			&llast_n_tokens[0], C.int(i), // tokens + n_tokens is the provided batch of new tokens to process
			C.int(i), // n_past is the number of tokens to use from previous eval calls
			C.int(runtime.GOMAXPROCS(0)))
		if evalErr != 0 {
			log.Printf("llama_eval: %d", evalErr)
			http.Error(w, "Internal error", 500)
			return
		}

		if err := r.Context().Err(); err != nil {
			return
		}

		//

		log.Println("doing llama_sample_top_p_top_k...")

		penalizeStart := 0
		penalizeLen := i
		if i > ParamRepeatPenaltyWindowSize {
			penalizeStart = i - ParamRepeatPenaltyWindowSize
			penalizeLen = ParamRepeatPenaltyWindowSize
		}

		newTokenId := C.llama_sample_top_p_top_k(lcontext,

			// Penalize recent tokens
			&llast_n_tokens[penalizeStart], C.int(penalizeLen),

			// Other static parameters
			ParamTopK, ParamTopP, ParamTemperature, ParamRepeatPenalty)

		if newTokenId == C.llama_token_eos() {
			// The model doesn't have anything to say
			return
		}

		if err := r.Context().Err(); err != nil {
			return
		}

		log.Println("got token OK")

		// The model did have something to say
		tokenStr := C.GoString(C.llama_token_to_str(lcontext, newTokenId))

		// Push this new token into the lembedding_ state, or else we'll just get it over and over again
		llast_n_tokens[i] = newTokenId

		// time.Sleep(1 * time.Second)
		w.Write([]byte(tokenStr)) // fmt.Sprintf(" update %d", i)))
		flusher.Flush()
	}
}