import sys
from typing import List
import traceback
import os
# needs to be imported *before* transformers
if os.path.exists('use_normal_tokenizers'):
    import tokenizers
    BIG_MODEL = False
else:
    import tokenizers_patch
    BIG_MODEL = True
from transformers import AutoModelForCausalLM, AutoTokenizer
import json

# from flask import Flask, request, render_template
# from flask_cors import CORS
# app = Flask(__name__, static_folder='static')
# app.config['TEMPLATES_AUTO_RELOAD'] = True
# CORS(app, resources= {
#     r"/generate": {"origins": origins},
#     r"/infill": {"origins": origins},
# })
# origins=[f"http://localhost:{PORT}", "https://huggingface.co", "https://hf.space"]

PORT = 7860
VERBOSE = False

if BIG_MODEL:
    CUDA = True
    model_name = "facebook/incoder-6B"
else:
    CUDA = False
    model_name = "facebook/incoder-1B"

from fastapi import FastAPI, Request
from fastapi.staticfiles import StaticFiles
from fastapi.responses import FileResponse, StreamingResponse
app = FastAPI(docs_url=None, redoc_url=None)
app.mount("/static", StaticFiles(directory="static"), name="static")


print("loading model")
model = AutoModelForCausalLM.from_pretrained(model_name)
print("loading tokenizer")
tokenizer = AutoTokenizer.from_pretrained(model_name)
print("loading complete")

if CUDA:
    model = model.half().cuda()

BOS = "<|endoftext|>"
EOM = "<|endofmask|>"

def make_sentinel(i):
    return f"<|mask:{i}|>"

SPECIAL_TOKENS = [make_sentinel(i) for i in range(256)] + [EOM]

def generate(input, length_limit=None, temperature=None):
    input_ids = tokenizer(input, return_tensors="pt").input_ids
    if CUDA:
        input_ids = input_ids.cuda()
    max_length = length_limit + input_ids.flatten().size(0)
    if max_length > 256:
        max_length = 256
    output = model.generate(input_ids=input_ids, do_sample=True, top_p=0.95, temperature=temperature, max_length=max_length)
    detok_hypo_str = tokenizer.decode(output.flatten())
    if detok_hypo_str.startswith(BOS):
        detok_hypo_str = detok_hypo_str[len(BOS):]
    return detok_hypo_str

def infill(parts: List[str], length_limit=None, temperature=None, extra_sentinel=False, max_retries=1):
    assert isinstance(parts, list)
    retries_attempted = 0
    done = False

    while (not done) and (retries_attempted < max_retries):
        retries_attempted += 1
        if VERBOSE:
            print(f"retry {retries_attempted}")
        if len(parts) == 1:
            prompt = parts[0]
        else:
            prompt = ""
            # encode parts separated by sentinel
            for sentinel_ix, part in enumerate(parts):
                prompt += part
                if extra_sentinel or (sentinel_ix < len(parts) - 1):
                    prompt += make_sentinel(sentinel_ix)
            
            # prompt += TokenizerWrapper.make_sentinel(0)
        
        infills = []
        complete = []

        done = True

        for sentinel_ix, part in enumerate(parts[:-1]):
            complete.append(part)
            prompt += make_sentinel(sentinel_ix)
            completion = generate(prompt, length_limit, temperature)
            completion = completion[len(prompt):]
            if EOM not in completion:
                if VERBOSE:
                    print(f"warning: {EOM} not found")
                completion += EOM
                # TODO: break inner loop here
                done = False
            completion = completion[:completion.index(EOM) + len(EOM)]
            infilled = completion[:-len(EOM)]
            infills.append(infilled)
            complete.append(infilled)
            prompt += completion
        complete.append(parts[-1])
        text = ''.join(complete)

    if VERBOSE:
        print("generated text:")
        print(prompt)
        print()
        print("parts:")
        print(parts)
        print()
        print("infills:")
        print(infills)
        print()
        print("restitched text:")
        print(text)
        print()
    
    return {
        'text': text,
        'parts': parts,
        'infills': infills,
        'retries_attempted': retries_attempted,
    } 


@app.head("/")
@app.get("/")
def index() -> FileResponse:
    return FileResponse(path="static/index.html", media_type="text/html")

@app.get('/generate')
async def generate_maybe(info: str):
    # form = await info.json()
    form = json.loads(info)
    prompt = form['prompt']
    length_limit = int(form['length'])
    temperature = float(form['temperature'])
    if VERBOSE:
        print(prompt)
    try:
        generation = generate(prompt, length_limit, temperature)
        return {'result': 'success', 'type': 'generate', 'prompt': prompt, 'text': generation}
    except Exception as e:
        traceback.print_exception(*sys.exc_info())
        return {'result': 'error', 'type': 'generate', 'prompt': prompt, 'text': f'There was an error: {e}. Tell Daniel.'}

@app.get('/infill')
async def infill_maybe(info: str):
    # form = await info.json()
    form = json.loads(info)
    length_limit = int(form['length'])
    temperature = float(form['temperature'])
    max_retries = 1
    extra_sentinel = True
    try:
        generation = infill(form['parts'], length_limit, temperature, extra_sentinel=extra_sentinel, max_retries=max_retries)
        generation['result'] = 'success'
        generation['type'] = 'infill'
        return generation
        # return {'result': 'success', 'prefix': prefix, 'suffix': suffix,  'text': generation['text']}
    except Exception as e:
        traceback.print_exception(*sys.exc_info())
        print(e)
        return {'result': 'error', 'type': 'infill', 'text': f'There was an error: {e}.'}


if __name__ == "__main__":
    app.run(host='0.0.0.0', port=PORT, threaded=False)