import gradio as gr
import urllib
import base64
import random
import requests
import bs4
import lxml
import os
from huggingface_hub import InferenceClient,HfApi
import random
import json
import datetime
from pypdf import PdfReader
import uuid
from PIL import Image
from screenshot import create_ss
from agent import (
PREFIX,
GET_CHART,
COMPRESS_DATA_PROMPT,
COMPRESS_DATA_PROMPT_SMALL,
LOG_PROMPT,
LOG_RESPONSE,
)
api=HfApi()
client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
############ Document Functions #################
def find_all(url):
return_list=[]
print (url)
#if action_input in query.tasks:
print (f"trying URL:: {url}")
try:
if url != "" and url != None:
out = []
source = requests.get(url)
#source = urllib.request.urlopen(url).read()
soup = bs4.BeautifulSoup(source.content,'lxml')
rawp=(f'RAW TEXT RETURNED: {soup.text}')
cnt=0
cnt+=len(rawp)
out.append(rawp)
out.append("HTML fragments: ")
q=("a","p","span","content","article")
for p in soup.find_all("a"):
out.append([{"LINK TITLE":p.get('title'),"URL":p.get('href'),"STRING":p.string}])
print(rawp)
return True, rawp
else:
return False, "Enter Valid URL"
except Exception as e:
print (e)
return False, f'Error: {e}'
return "MAIN", None, history, task
def read_txt(txt_path):
text=""
with open(txt_path,"r") as f:
text = f.read()
f.close()
print (text)
return text
def read_pdf(pdf_path):
text=""
reader = PdfReader(f'{pdf_path}')
number_of_pages = len(reader.pages)
for i in range(number_of_pages):
page = reader.pages[i]
text = f'{text}\n{page.extract_text()}'
print (text)
return text
error_box=[]
def read_pdf_online(url):
uid=uuid.uuid4()
print(f"reading {url}")
response = requests.get(url, stream=True)
print(response.status_code)
text=""
try:
if response.status_code == 200:
with open("test.pdf", "wb") as f:
f.write(response.content)
#f.close()
#out = Path("./data.pdf")
#print (out)
reader = PdfReader("test.pdf")
number_of_pages = len(reader.pages)
print(number_of_pages)
for i in range(number_of_pages):
page = reader.pages[i]
text = f'{text}\n{page.extract_text()}'
print(f"PDF_TEXT:: {text}")
return text
else:
text = response.status_code
error_box.append(url)
print(text)
return text
except Exception as e:
print (e)
return e
VERBOSE = True
MAX_HISTORY = 100
MAX_DATA = 20000
def format_prompt(message, history):
prompt = ""
for user_prompt, bot_response in history:
prompt += f"[INST] {user_prompt} [/INST]"
prompt += f" {bot_response} "
prompt += f"[INST] {message} [/INST]"
return prompt
def run_gpt_no_prefix(
prompt_template,
stop_tokens,
max_tokens,
seed,
**prompt_kwargs,
):
print(seed)
try:
generate_kwargs = dict(
temperature=0.9,
max_new_tokens=max_tokens,
top_p=0.95,
repetition_penalty=1.0,
do_sample=True,
seed=seed,
)
content = prompt_template.format(**prompt_kwargs)
#if VERBOSE:
print(LOG_PROMPT.format(content))
#formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history)
#formatted_prompt = format_prompt(f'{content}', history)
stream = client.text_generation(content, **generate_kwargs, stream=True, details=True, return_full_text=False)
resp = ""
for response in stream:
resp += response.token.text
#yield resp
#if VERBOSE:
print(LOG_RESPONSE.format(resp))
return resp
except Exception as e:
print(f'no_prefix_error:: {e}')
return "Error"
def run_gpt(
prompt_template,
stop_tokens,
max_tokens,
seed,
**prompt_kwargs,
):
print(seed)
timestamp=datetime.datetime.now()
generate_kwargs = dict(
temperature=0.9,
max_new_tokens=max_tokens,
top_p=0.95,
repetition_penalty=1.0,
do_sample=True,
seed=seed,
)
content = PREFIX.format(
timestamp=timestamp,
purpose="Compile the provided data and complete the users task"
) + prompt_template.format(**prompt_kwargs)
#if VERBOSE:
print(LOG_PROMPT.format(content))
#formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history)
#formatted_prompt = format_prompt(f'{content}', history)
stream = client.text_generation(content, **generate_kwargs, stream=True, details=True, return_full_text=False)
resp = ""
for response in stream:
resp += response.token.text
#yield resp
if VERBOSE:
print(LOG_RESPONSE.format(resp))
return resp
def compress_data(c, instruct, history, seed):
#seed=random.randint(1,1000000000)
print (c)
#tot=len(purpose)
#print(tot)
divr=int(c)/MAX_DATA
divi=int(divr)+1 if divr != int(divr) else int(divr)
chunk = int(int(c)/divr)
print(f'chunk:: {chunk}')
print(f'divr:: {divr}')
print (f'divi:: {divi}')
out = []
#out=""
s=0
e=chunk
print(f'e:: {e}')
new_history=""
#task = f'Compile this data to fulfill the task: {task}, and complete the purpose: {purpose}\n'
for z in range(divi):
print(f's:e :: {s}:{e}')
hist = history[s:e]
resp = run_gpt(
COMPRESS_DATA_PROMPT_SMALL,
stop_tokens=["observation:", "task:", "action:", "thought:"],
max_tokens=8192,
seed=seed,
direction=instruct,
knowledge="",
history=hist,
).strip("\n")
out.append(resp)
#new_history = resp
print (resp)
#out+=resp
e=e+chunk
s=s+chunk
return out
def get_chart(inp,seed):
#seed=random.randint(1,1000000000)
try:
resp = run_gpt_no_prefix(
GET_CHART,
stop_tokens=[],
max_tokens=8192,
seed=seed,
inp=inp,
).strip("\n")
print(resp)
except Exception as e:
print(f'Error:: {e}')
resp = e
return resp
def format_json(inp):
print("FORMATTING:::")
print(type(inp))
print("###########")
print(inp)
print("###########")
print("###########")
new_str=""
matches=["```","#","//"]
for i,line in enumerate(inp):
line = line.strip()
print(line)
#if not any(x in line for x in matches):
new_str+=line.strip("\n").strip("```").strip("#").strip("//")
print("###########")
print("###########")
#inp = inp.strip("<\s>")
new_str=new_str.strip("")
out_json=eval(new_str)
print(out_json)
print("###########")
print("###########")
return out_json
this=["1.25"]
css="""
#wrap { width: 100%; height: 100%; padding: 0; overflow: auto; }
#frame { width: 100%; border: 1px solid black; }
#frame { zoom: $ZOOM; -moz-transform: scale($ZOOM); -moz-transform-origin: 0 0; }
"""
def mm(graph,zoom):
code_out=""
for ea in graph.split("\n"):
code=ea.strip().strip("\n")
code_out+=code
#out_html=f'''