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| import gradio as gr | |
| import requests | |
| import bs4 | |
| import lxml | |
| import os | |
| from huggingface_hub import InferenceClient,HfApi | |
| import random | |
| import json | |
| import datetime | |
| import xmltodict | |
| from prompts import ( | |
| COMPRESS_HISTORY_PROMPT, | |
| COMPRESS_DATA_PROMPT, | |
| COMPRESS_DATA_PROMPT_SMALL, | |
| PREFIX, | |
| ) | |
| client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1") | |
| reponame="Omnibus/tmp" | |
| save_data=f'https://huggingface.co/datasets/{reponame}/raw/main/' | |
| token_self = os.environ['HF_TOKEN'] | |
| api=HfApi(token=token_self) | |
| def parse_action(string: str): | |
| print("PARSING:") | |
| print(string) | |
| assert string.startswith("action:") | |
| idx = string.find("action_input=") | |
| print(idx) | |
| if idx == -1: | |
| print ("idx == -1") | |
| print (string[8:]) | |
| return string[8:], None | |
| print ("last return:") | |
| print (string[8 : idx - 1]) | |
| print (string[idx + 13 :].strip("'").strip('"')) | |
| return string[8 : idx - 1], string[idx + 13 :].strip("'").strip('"') | |
| MAX_HISTORY = 100 | |
| MAX_DATA = 40000 | |
| def format_prompt(message, history): | |
| prompt = "<s>" | |
| for user_prompt, bot_response in history: | |
| prompt += f"[INST] {user_prompt} [/INST]" | |
| prompt += f" {bot_response}</s> " | |
| prompt += f"[INST] {message} [/INST]" | |
| return prompt | |
| def run_gpt( | |
| prompt_template, | |
| stop_tokens, | |
| max_tokens, | |
| seed, | |
| purpose, | |
| **prompt_kwargs, | |
| ): | |
| timestamp=datetime.datetime.now() | |
| print(seed) | |
| 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=purpose, | |
| ) + prompt_template.format(**prompt_kwargs) | |
| #formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history) | |
| #formatted_prompt = format_prompt(f'{content}', **prompt_kwargs['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 | |
| return resp | |
| def compress_data(c,purpose, task, history): | |
| seed=random.randint(1,1000000000) | |
| print (c) | |
| 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] | |
| print(f'hist::\n{hist}') | |
| resp = run_gpt( | |
| COMPRESS_DATA_PROMPT, | |
| stop_tokens=["observation:", "task:", "action:", "thought:"], | |
| max_tokens=2048, | |
| seed=seed, | |
| purpose=purpose, | |
| task=task, | |
| knowledge=new_history, | |
| history=hist, | |
| ).strip("\n") | |
| new_history = resp | |
| print (resp) | |
| out+=resp | |
| e=e+chunk | |
| s=s+chunk | |
| ''' | |
| resp = run_gpt( | |
| COMPRESS_DATA_PROMPT, | |
| stop_tokens=["observation:", "task:", "action:", "thought:"], | |
| max_tokens=2048, | |
| seed=seed, | |
| purpose=purpose, | |
| task=task, | |
| knowledge=new_history, | |
| history=result, | |
| ) | |
| ''' | |
| print ("final" + resp) | |
| history = "result: {}\n".format(resp) | |
| return history | |
| def summarize(inp,history,data=None): | |
| json_box=[] | |
| if inp == "": | |
| inp = "Process this data" | |
| #inp = format_prompt(inp,history) | |
| task = "Compile a detailed report" | |
| history.clear() | |
| yield "",[(inp,"Working on it...")] | |
| if data != "Error" and data != "": | |
| print(inp) | |
| out = str(data) | |
| rl = len(out) | |
| print(f'rl:: {rl}') | |
| c=1 | |
| for i in str(out): | |
| if i == " " or i=="," or i=="\n": | |
| c +=1 | |
| print (f'c:: {c}') | |
| #json_out = compress_data(c,inp,task,out) | |
| #def compress_data(c,purpose, task, history): | |
| purpose=inp | |
| seed=random.randint(1,1000000000) | |
| print (c) | |
| 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="" | |
| 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}') | |
| mes= f'Working on data chunk: {s}:{e}' | |
| hist = out[s:e] | |
| print(f'hist::\n{hist}') | |
| yield "", [(inp,f'{mes}\n{new_history}')] | |
| resp = run_gpt( | |
| COMPRESS_DATA_PROMPT, | |
| stop_tokens=[], | |
| max_tokens=2048, | |
| seed=seed, | |
| purpose=purpose, | |
| task=task, | |
| knowledge=new_history, | |
| history=hist, | |
| ) | |
| new_history = resp | |
| print (resp) | |
| out+=resp | |
| e=e+chunk | |
| s=s+chunk | |
| #history = "preliminary result: {}\n".format(resp) | |
| #yield "", (inp,f'{mes}\n{history}') | |
| print ("final" + resp) | |
| out_hist = "result:\n{}".format(resp) | |
| #return history | |
| yield "", [(inp,out_hist)] | |
| out = str(out_hist) | |
| rawp = out | |
| else: | |
| rawp = "Provide a valid data source" | |
| history.append((inp,rawp)) | |
| yield "", history | |
| def find_rss(): | |
| lod="" | |
| out_box=[] | |
| yield [],[(None,"loading sources")] | |
| with open ('feeds.json','r') as j: | |
| cont = json.loads(j.read()) | |
| #print(cont) | |
| for ea in cont: | |
| #lod="" | |
| print (ea['link']) | |
| rss_url=ea['link'] | |
| link_box=[] | |
| r = requests.get(f'{rss_url}') | |
| if r.status_code == 200: | |
| try: | |
| if ".json" in rss_url: | |
| lod = json.loads(r.text) | |
| if ".xml" in rss_url: | |
| lod = xmltodict.parse(r.content) | |
| if ".rss" in rss_url: | |
| lod = xmltodict.parse(r.content) | |
| else: | |
| try: | |
| lod = xmltodict.parse(r.content) | |
| except Exception as e: | |
| lod=f'{rss_url} ::ERROR:: {e}' | |
| except Exception as e: | |
| lod=f'{rss_url} ::ERROR:: {e}' | |
| else: | |
| lod = f'{rss_url} ::ERROR::COULD NOT CONNECT:: {r.status_code}' | |
| pass | |
| try: | |
| print(lod['rss']['channel']['item'][0].keys()) | |
| print(lod['rss'].keys()) | |
| for i,ea in enumerate(lod['rss']['channel']['item']): | |
| try: | |
| r_link = ea['link'] | |
| r_title = ea['title'] | |
| r_description = ea['description'] | |
| lods = {"title":r_title, "description":r_description,"link":r_link} | |
| except Exception: | |
| try: | |
| r_link = ea['link'] | |
| r_title = ea['source'] | |
| r_description = 'No Description provided' | |
| lods = {"title":r_title, "description":r_description,"link":r_link} | |
| except Exception as e: | |
| print(e) | |
| pass | |
| #lods = {"title":"ERROR", "description":{e},"link":"ERROR"} | |
| """ | |
| r_link = lod['rss']['channel']['item'][i]['link'] | |
| r_title = lod['rss']['channel']['item'][i]['title'] | |
| r_description = lod['rss']['channel']['item'][i]['description']""" | |
| link_box.append(lods) | |
| lod={lod['rss']['channel']['title']:link_box} | |
| out_box.append(lod) | |
| except Exception as e: | |
| #print(f'{ea["source"]}') | |
| #print(f'{ea["link"]}') | |
| #lod = f'{rss_url} ::ERROR:: {e}' | |
| print(f'Exception::{e}') | |
| print(f'Exception::{ea.keys()}') | |
| #out_box.append(lod) | |
| #user_repo=save_data.split('datasets/',1)[1].split('/raw',1)[0] | |
| timestamp=str(datetime.datetime.now()) | |
| timename=timestamp.replace(" ","--").replace(":","-").replace(".","-") | |
| json_object = json.dumps(out_box) | |
| #json_object = json.dumps(out_box,indent=4) | |
| with open("tmp1.json", "w") as outfile: | |
| outfile.write(json_object) | |
| api.upload_file( | |
| path_or_fileobj="tmp1.json", | |
| path_in_repo=f"/rss/{timename}.json", | |
| repo_id=reponame, | |
| #repo_id=save_data.split('datasets/',1)[1].split('/raw',1)[0], | |
| token=token_self, | |
| repo_type="dataset", | |
| ) | |
| yield out_box,[(None,f'Source is current as of:\n{timestamp} UTC\n\nThe current Date and Time is:\n{timestamp} UTC')] | |
| def load_data(): | |
| yield None,[(None,f'Loading data source, please wait')] | |
| f_ist = (api.list_repo_files(repo_id=reponame, repo_type="dataset")) | |
| f_ist.sort(reverse=True) | |
| print(f_ist) | |
| r = requests.get(f'{save_data}{f_ist[0]}') | |
| lod = json.loads(r.text) | |
| timestamp=str(datetime.datetime.now()) | |
| filename=f_ist[0].split("/")[1].split(".json")[0].replace("--"," ") | |
| print (filename) | |
| filename_start = filename.split(" ")[0] | |
| filename_end = filename.split(" ")[1] | |
| filename_end = filename_end.replace("-"[0],":").replace("-"[0],":").replace("-"[0],".") | |
| #filename_end_far=filename_end.split(":")[2] | |
| print (filename) | |
| yield lod,[(None,f'Source is current as of:\n{filename_start} {filename_end} UTC\n\nThe current Date and Time is:\n{timestamp} UTC')] | |
| with gr.Blocks() as app: | |
| cb = gr.Chatbot(height=500) | |
| with gr.Row(): | |
| inst = gr.Textbox(label="Instructions") | |
| sub_btn=gr.Button("Submit") | |
| with gr.Row(): | |
| load_btn = gr.Button("Load RSS") | |
| u_btn=gr.Button("Update [RSS Data]") | |
| with gr.Row(): | |
| out_json = gr.JSON() | |
| fil = gr.Textbox() | |
| load_btn.click(load_data,None,[out_json,cb]) | |
| u_btn.click(find_rss,None,[out_json,cb]) | |
| sub_btn.click(summarize,[inst,cb,out_json],[inst,cb]) | |
| app.launch() | |