# from flask import Flask,request,render_template,send_file,jsonify
import os
from transformers import AutoTokenizer, AutoModel
import anvil.server
import pathlib
import textwrap
import import_ipynb
from library import call_gpt, call_gemini, encode_gemini
from background_service import BackgroundTaskService

anvil.server.connect('PLMOIU5VCGGUOJH2XORIBWV3-ZXZVFLWX7QFIIAF4')

# app=Flask(__name__)
MESSAGED={'title':'API Server',
          'messageL':['published server functions:','encode(text)', 
                      'call_gemini(text,key)','call_gpt(text,key,model)',
                      'task_id<=launch(func_name,*args)','poll(task_id)']}

tokenizer = AutoTokenizer.from_pretrained('allenai/specter')
encoder = AutoModel.from_pretrained('allenai/specter')

anvil.server.callable(call_gpt)
anvil.server.callable(call_gemini)
anvil.server.callable(encode_gemini)

service=BackgroundTaskService(max_tasks=10)
service.register(call_gpt)
service.register(call_gemini)

@anvil.server.callable
def launch(func_name,*args):
    global service
    # Launch task
    task_id = service.launch_task(func_name, *args)
    print(f"Task launched with ID: {task_id}")
    return task_id

@anvil.server.callable
def poll(task_id):
    global service
    # Poll for completion; if not complete return "In Progress" else return result
    result = service.get_result(task_id)
    if result=='No such task': return str(result)
    elif result!='In Progress': 
        del service.results[task_id]
        if isinstance(result, (int, float, str, list, dict, tuple)): 
            return result
        else: 
            print(str(result))
            return str(result)
    else: return str(result)

@anvil.server.callable
def encode_anvil(text):
    inputs = tokenizer(text, padding=True, truncation=True, 
                       return_tensors="pt", max_length=512)
    result = encoder(**inputs)
    embeddings = result.last_hidden_state[:, 0, :]
    emb_array = embeddings.detach().numpy()
    embedding=emb_array.tolist()
    return embedding

@anvil.server.callable
def reset_service():
    global call_gpt, call_gemini, service
    service=BackgroundTaskService(max_tasks=10)
    service.register(call_gpt)
    service.register(call_gemini)

@anvil.server.callable
def print_results_table():
    global service
    return(service.results)

anvil.server.wait_forever()

# @app.route('/encode',methods=['GET','POST'])
# def encode():
#     print(request)
#     if request.method=='GET':
#         text=request.args.get('text')
#     elif request.method=='POST':
#         data=request.get_json()
#         if 'text' in data: text=data["text"]
#     if text=='' or text is None: return -1
#     inputs = tokenizer(text, padding=True, truncation=True, 
#                        return_tensors="pt", max_length=512)
#     result = encoder(**inputs)
#     embeddings = result.last_hidden_state[:, 0, :]
#     emb_array = embeddings.detach().numpy()
#     embedding=emb_array.tolist()
#     return jsonify({'embedding': embedding})

# @app.route("/file/<string:filename>")
# def return_file(filename):
#     return send_file('./data/'+filename)

# @app.route('/run',methods=['GET','POST'])
# def run_script():
#     script=''
#     # print(request.method)
#     print(request)
#     if request.method=='GET': 
#         script=request.args.get('script')
#         print('I am in get')
#     elif request.method=='POST':
#         print('I am in post')
#         data=request.get_json()
#         if 'script' in data: script=data['script']
#     if script=='' or script is None: return 'INVALID'
#     os.system(script+' > ./out.txt')
#     with open('./out.txt','r') as f: output=f.read()
#     return output

# @app.route('/',methods=['GET', 'POST'])
# def home():
#     return render_template('home.html',messageD=MESSAGED)

# if __name__=='__main__':
#     app.run(host="0.0.0.0", port=7860)