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'''
''' #url=f"https://omnibus-mermaid-script.static.hf.space/index.html?mermaid={code_out}" url=f"https://omnibus-mermaid-script.static.hf.space/index.html?mermaid={urllib.parse.quote_plus(code_out)}" out_html=f'''
''' return out_html,url def summarize(inp,history,seed,data=None,files=None,directory=None,url=None,pdf_url=None,pdf_batch=None): json_box=[] chart_out="" if inp == "": inp = "Process this data" history.clear() history = [(inp,"Working on it...")] yield "",history,chart_out,chart_out,json_box,"" if pdf_batch.startswith("http"): lab="PDF Batch" c=0 data="" for i in str(pdf_batch): if i==",": c+=1 print (f'c:: {c}') try: for i in range(c+1): batch_url = pdf_batch.split(",",c)[i] bb = read_pdf_online(batch_url) data=f'{data}\nFile Name URL ({batch_url}):\n{bb}' except Exception as e: print(e) #data=f'{data}\nError reading URL ({batch_url})' if directory: lab="Directory" for ea in directory: print(ea) if pdf_url.startswith("http"): lab="PDF URL" print("PDF_URL") out = read_pdf_online(pdf_url) data=out if url.startswith("http"): lab="Raw HTML" val, out = find_all(url) if not val: data="Error" rawp = str(out) else: data=out if files: lab="Files" for i, file in enumerate(files): try: print (file) if file.endswith(".pdf"): zz=read_pdf(file) print (zz) data=f'{data}\nFile Name ({file}):\n{zz}' elif file.endswith(".txt"): zz=read_txt(file) print (zz) data=f'{data}\nFile Name ({file}):\n{zz}' except Exception as e: data=f'{data}\nError opening File Name ({file})' print (e) if data != "Error" and data != "": history.clear() history = [(inp,f"Data: Loaded, processing...")] yield "",history,chart_out,chart_out,json_box,"" 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,out,seed) out = str(json_out) try: json_out=format_json(json_out) except Exception as e: print (e) history.clear() history = [(inp,"Building Chart...")] yield "",history,chart_out,chart_out,json_out,"" chart_out = get_chart(str(json_out),seed) chart_list=chart_out.split("\n") go=True cnti=1 line_out="" for ii, line in enumerate(chart_list): if go: line=line.strip().replace('"',"") if "```" in chart_list[ii]: while True: line_out+=chart_list[ii+cnti].strip().replace("\n"," ").replace('"',"").replace("/"," ").replace("."," ").replace(":"," ").replace("#","") if not line_out.strip().endswith(";"): line_out+=";" line_out+="\n" cnti+=1 if "```" in chart_list[ii+cnti]: go=False break chart_html,chart_url=mm(line_out,1) #print(chart_out) else: rawp = "Provide a valid data source" history.clear() history.append((inp,chart_out)) yield "", history,chart_html,line_out,json_out,chart_url ################################# def clear_fn(): return "",[(None,None)] def create_image(url): print(url) with open("tmp.svg","w") as svg: svg.write(url) with open("tmp.svg", "rb") as f: encoded_image = base64.b64encode(f.read()) this = Image.open("tmp.svg") out_im = this.save("tmp.png") with open("image.png","wb") as file: #file.write(eval(encoded_image)) file.write(encoded_image) #output = cairosvg.svg2png( # bytestring=open('tmp.svg').read().encode('utf-8'), write_to="output.png") return "tmp.png" score_js=""" function(text_input) { console.log(text_input); const iframe = document.getElementById("frame").contentWindow.document.getElementById('chart').innerHTML; console.log(iframe); return [iframe]; } """ def zoom_update(inp): this.clear() this.append(str(inp)) return gr.update() with gr.Blocks() as app: gr.HTML("""

Text -to- Chart

Mixtral 8x7B

""") chatbot = gr.Chatbot(label="Mixtral 8x7B Chatbot",show_copy_button=True) with gr.Row(): with gr.Column(scale=3): prompt=gr.Textbox(label = "Instructions (optional)") with gr.Column(scale=1): button=gr.Button() #models_dd=gr.Dropdown(choices=[m for m in return_list],interactive=True) with gr.Row(): stop_button=gr.Button("Stop") clear_btn = gr.Button("Clear") with gr.Row(): with gr.Tab("Text"): data=gr.Textbox(label="Input Data (paste text)", lines=6) with gr.Tab("File"): file=gr.Files(label="Input File(s) (.pdf .txt)") with gr.Tab("Folder"): directory=gr.File(label="Folder", file_count='directory') with gr.Tab("Raw HTML"): url = gr.Textbox(label="URL") with gr.Tab("PDF URL"): pdf_url = gr.Textbox(label="PDF URL") with gr.Tab("PDF Batch"): pdf_batch = gr.Textbox(label="PDF URL Batch (comma separated)") m_box=gr.HTML() e_box=gr.Textbox(label="Graph Code",interactive=True) with gr.Row(): upd_button=gr.Button("Update Chart") create_im=gr.Button("Create Image") with gr.Row(): with gr.Column(scale=3): svg_img=gr.Image() with gr.Column(scale=1): wid=gr.Number(label="Width",value=1000) hgt=gr.Number(label="Height",value=4000) seed_slider=gr.Slider(label="Seed",step=1,minimum=1,maximum=9999999999999999999,value=1,interactive=True) zoom_btn=gr.Slider(label="Zoom",step=0.01,minimum=0.1,maximum=20,value=1,interactive=True) url_box=gr.Textbox(label="Graph URL",interactive=True) json_out=gr.JSON() #text=gr.JSON() #get_score.click(return_score,score,[score],_js=score_js) score=gr.Textbox() def return_score(text): print(text) return text create_im.click(create_ss,[e_box,wid,hgt],svg_img) #create_im.click(return_score,score,[score],_js=score_js).then(create_image,score,svg_img) #zoom_btn.change(zoom_update,zoom_btn,None) upd_button.click(mm,[e_box,zoom_btn],[m_box,url_box]) #inp_query.change(search_models,inp_query,models_dd) clear_btn.click(clear_fn,None,[prompt,chatbot]) #go=button.click(summarize,[prompt,chatbot,report_check,chart_check,data,file,directory,url,pdf_url,pdf_batch],[prompt,chatbot,e_box,json_out]) go=button.click(summarize,[prompt,chatbot,seed_slider,data,file,directory,url,pdf_url,pdf_batch],[prompt,chatbot,m_box,e_box,json_out,url_box]) stop_button.click(None,None,None,cancels=[go]) #app.queue(default_concurrency_limit=20).launch(show_api=False) app.queue(default_concurrency_limit=20).launch(show_api=False)