Spaces:
Build error
Build error
| import gradio as gr | |
| #import urllib.request | |
| import requests | |
| import bs4 | |
| import lxml | |
| import os | |
| #import subprocess | |
| from huggingface_hub import InferenceClient,HfApi | |
| import random | |
| import json | |
| import datetime | |
| from pypdf import PdfReader | |
| import uuid | |
| #from query import tasks | |
| from agent import ( | |
| PREFIX, | |
| COMPRESS_DATA_PROMPT, | |
| COMPRESS_DATA_PROMPT_SMALL, | |
| LOG_PROMPT, | |
| LOG_RESPONSE, | |
| ) | |
| 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 find_all(url): | |
| return_list=[] | |
| print (url) | |
| print (f"trying URL:: {url}") | |
| try: | |
| if url != "" and url != None: | |
| out = [] | |
| source = requests.get(url) | |
| print(source.status_code) | |
| if source.status_code ==200: | |
| print('trying') | |
| soup = bs4.BeautifulSoup(source.content,'lxml') | |
| rawp=(f'RAW TEXT RETURNED: {soup.text}') | |
| print (rawp) | |
| 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}]) | |
| c=0 | |
| out = str(out) | |
| rl = len(out) | |
| print(f'rl:: {rl}') | |
| for i in str(out): | |
| if i == " " or i=="," or i=="\n" or i=="/" or i=="." or i=="<": | |
| c +=1 | |
| print (f'c:: {c}') | |
| #if c > MAX_HISTORY: | |
| #print("compressing...") | |
| #rawp = compress_data(c,purpose,task,out,result) | |
| #result += rawp | |
| rawp=out | |
| return True, rawp | |
| else: | |
| return False, f'Status:: {source.status_code}' | |
| else: | |
| print('passing') | |
| return False, "Enter Valid URL" | |
| except Exception as e: | |
| print (e) | |
| return False, f'Error: {e}' | |
| 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 = "<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, | |
| **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=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, | |
| ) | |
| out.append(resp) | |
| #new_history = resp | |
| print (resp) | |
| #out+=resp | |
| e=e+chunk | |
| s=s+chunk | |
| return out | |
| def compress_data_og(c, instruct, history): | |
| 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, | |
| stop_tokens=["observation:", "task:", "action:", "thought:"], | |
| max_tokens=8192, | |
| seed=seed, | |
| direction=instruct, | |
| knowledge=new_history, | |
| history=hist, | |
| ) | |
| 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=8192, | |
| seed=seed, | |
| direction=instruct, | |
| knowledge=new_history, | |
| history="All data has been recieved.", | |
| )''' | |
| print ("final" + resp) | |
| #history = "observation: {}\n".format(resp) | |
| return resp | |
| RECALL_MEMORY="""The user will give you a query and a list | |
| Your duty is to choose the words from the list that are closely related to the search query. | |
| If there are no relevant keywords found in the provided list return 'NONE' | |
| Respond with only a list, or NONE | |
| Respond only in this format: | |
| [keyword1,keyword2,keyword3] | |
| USER QUERY: | |
| {prompt} | |
| KEYWORD LIST: | |
| {keywords} | |
| """ | |
| def get_mem(prompt,kw): | |
| seed=random.randint(1,1000000000) | |
| generate_kwargs = dict( | |
| temperature=0.6, | |
| max_new_tokens=1024, | |
| top_p=0.6, | |
| repetition_penalty=1.0, | |
| do_sample=True, | |
| seed=seed, | |
| ) | |
| content = RECALL_MEMORY.format(keywords=kw,prompt=prompt) | |
| stream = client.text_generation(content, **generate_kwargs, stream=True, details=True, return_full_text=False) | |
| resp = "" | |
| for response in stream: | |
| resp += response.token.text | |
| print (resp) | |
| return resp | |
| def summarize(inp,history,report_check,sum_check,mem_check,data=None,files=None,url=None,pdf_url=None,pdf_batch=None): | |
| json_box=[] | |
| if inp == "": | |
| inp = "Process this data" | |
| history.clear() | |
| history = [(inp,"Working on it...")] | |
| yield "",history,error_box,json_box | |
| if pdf_batch.startswith("http"): | |
| 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 pdf_url.startswith("http"): | |
| print("PDF_URL") | |
| out = read_pdf_online(pdf_url) | |
| data=out | |
| if url.startswith("http"): | |
| val, out = find_all(url) | |
| if not val: | |
| data="Error" | |
| rawp = str(out) | |
| else: | |
| data=out | |
| if 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 != "": | |
| 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}') | |
| if mem_check: | |
| json_out = save_memory(inp,out) | |
| rawp = "Complete" | |
| if sum_check: | |
| json_out = compress_data(c,inp,out) | |
| out = str(json_out) | |
| if report_check: | |
| 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'c2:: {c}') | |
| rawp = compress_data_og(c,inp,out) | |
| else: | |
| rawp = out | |
| json_out = format_json(json_out) | |
| else: | |
| rawp = "Provide a valid data source" | |
| history.clear() | |
| history.append((inp,rawp)) | |
| yield "", history,error_box,json_out | |
| SAVE_MEMORY = """ | |
| You are attempting to complete the task | |
| task: {task} | |
| Data: | |
| {history} | |
| Instructions: | |
| Compile and categorize the data above into a JSON dictionary string | |
| Include ALL text, datapoints, titles, descriptions, and source urls indexed into an easy to search JSON format | |
| Required keys: | |
| "keywords":["short", "list", "of", "important", "keywords", "found", "in", "this", "entry"], | |
| "title":"title of entry", | |
| "description":"A sentence summarizing the topic of this entry", | |
| "content":"A brief paragraph summarizing the important datapoints found in this entry", | |
| "url":"https://url.source" | |
| """ | |
| 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("</s>") | |
| out_json=eval(new_str) | |
| print(out_json) | |
| print("###########") | |
| print("###########") | |
| return out_json | |
| def format_json_og(inp): | |
| new_json=[] | |
| start_json={} | |
| print("FORMATTING:::") | |
| for i,line in enumerate(inp): | |
| line = line.strip() | |
| if "{" in line: | |
| print (line) | |
| start_json={} | |
| #print(f'test:: {line}') | |
| if "keywords" in line and ":" in line: | |
| start_json['keywords']=line.split(":")[1].strip(",") | |
| print (line) | |
| if "title" in line and ":" in line: | |
| start_json['title']=line.split(":")[1].strip(",") | |
| print (line) | |
| if "description" in line and ":" in line: | |
| start_json['description']=line.split(":")[1].strip(",") | |
| print (line) | |
| if "content" in line and ":" in line: | |
| start_json['content']=line.split(":")[1].strip(",") | |
| print (line) | |
| if "url" in line and ":" in line: | |
| start_json['url']=line.split(":")[1].strip(",") | |
| print (line) | |
| if "}" in line: | |
| new_json.append(start_json) | |
| print (new_json) | |
| return new_json | |
| def create_index(): | |
| uid=uuid.uuid4() | |
| ####### load index ############### | |
| r = requests.get(f'{save_data}mem-test2/index.json') | |
| print(f'status code main:: {r.status_code}') | |
| if r.status_code==200: | |
| ind = json.loads(r.text) | |
| print (f'ind::\n{ind}') | |
| if not r.status_code==200: | |
| print("Create new IND") | |
| ind = [{}] | |
| ####### load main ############### | |
| m = requests.get(f'{save_data}mem-test2/main.json') | |
| print(f'status code main:: {m.status_code}') | |
| if m.status_code==200: | |
| main = json.loads(m.text) | |
| #print (f'main::\n{main}') | |
| if not r.status_code==200: | |
| main = [] | |
| try: | |
| for ea in main: | |
| #print(f'###### EACH::: {ea}') | |
| print(f"KEYWORDS:: {ea['keywords']}") | |
| except Exception as e: | |
| print(f"ERROR:: {e}") | |
| for ea in main: | |
| try: | |
| for k in ea['keywords']: | |
| print(k) | |
| print(ea['file_name']) | |
| #for ii in ind[0]: | |
| try: | |
| if k in ind[0].keys(): | |
| print("Adding to list") | |
| if not ea['file_name'] in ind[0][k]: | |
| ind[0][k].append(ea['file_name']) | |
| else: | |
| print("Adding new Value") | |
| ind[0].update({k:[ea['file_name']]}) | |
| except Exception as e: | |
| print (e) | |
| ind[0].append({k:[ea['file_name']]}) | |
| #ind.append({k:[ea['file_name']]}) | |
| except Exception as e: | |
| print (e) | |
| json_object = json.dumps(ind, indent=4) | |
| with open(f"tmp3-{uid}.json", "w") as outfile3: | |
| outfile3.write(json_object) | |
| outfile3.close() | |
| api.upload_file( | |
| path_or_fileobj=f"tmp3-{uid}.json", | |
| path_in_repo=f"/mem-test2/index.json", | |
| repo_id=reponame, | |
| #repo_id=save_data.split('datasets/',1)[1].split('/raw',1)[0], | |
| token=token_self, | |
| repo_type="dataset", | |
| ) | |
| def save_memory(purpose, history): | |
| uid=uuid.uuid4() | |
| history=str(history) | |
| c=1 | |
| inp = str(history) | |
| rl = len(inp) | |
| print(f'rl:: {rl}') | |
| for i in str(inp): | |
| if i == " " or i=="," or i=="\n" or i=="/" or i=="\\" or i=="." or i=="<": | |
| c +=1 | |
| print (f'c:: {c}') | |
| 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_box = [] | |
| #out="" | |
| s=0 | |
| ee=chunk | |
| print(f'e:: {ee}') | |
| new_history="" | |
| task = f'Index this Data\n' | |
| for z in range(divi): | |
| print(f's:e :: {s}:{ee}') | |
| hist = inp[s:ee] | |
| resp = run_gpt( | |
| SAVE_MEMORY, | |
| stop_tokens=["observation:", "task:", "action:", "thought:"], | |
| max_tokens=4096, | |
| seed=seed, | |
| purpose=purpose, | |
| task=task, | |
| history=hist, | |
| ).strip('\n') | |
| #new_history = resp | |
| #print (resp) | |
| #out+=resp | |
| #print ("final1" + resp) | |
| try: | |
| resp='[{'+resp.split('[{')[1].split('</s>')[0] | |
| #print ("final2\n" + resp) | |
| #print(f"keywords:: {resp['keywords']}") | |
| except Exception as e: | |
| resp = resp | |
| print(e) | |
| timestamp=str(datetime.datetime.now()) | |
| timename=timestamp.replace(" ","--").replace(":","-").replace(".","-") | |
| json_object=resp | |
| #json_object = json.dumps(out_box) | |
| #json_object = json.dumps(out_box,indent=4) | |
| with open(f"tmp-{uid}.json", "w") as outfile: | |
| outfile.write(json_object) | |
| outfile.close() | |
| api.upload_file( | |
| path_or_fileobj=f"tmp-{uid}.json", | |
| path_in_repo=f"/mem-test2/{timename}---{s}-{ee}.json", | |
| repo_id=reponame, | |
| #repo_id=save_data.split('datasets/',1)[1].split('/raw',1)[0], | |
| token=token_self, | |
| repo_type="dataset", | |
| ) | |
| lines = resp.strip().strip("\n").split("\n") | |
| #formatted_json=format_json(lines) | |
| r = requests.get(f'{save_data}mem-test2/main.json') | |
| print(f'status code main:: {r.status_code}') | |
| try: | |
| print(f"KEYWORDS:: {json_object['keywords']}") | |
| except Exception as e: | |
| print(f"KEYWORDS:: {e}") | |
| if r.status_code==200: | |
| lod = json.loads(r.text) | |
| #lod = eval(lod) | |
| print (f'lod:: {lod}') | |
| if not r.status_code==200: | |
| lod = [] | |
| key_box=[] | |
| desc="" | |
| for i,line in enumerate(lines): | |
| #print(f'LINE:: {line}') | |
| if ":" in line: | |
| print(f'line:: {line}') | |
| if "keywords" in line and ":" in line: | |
| print(f'trying:: {line}') | |
| keyw=line.split(":")[1] | |
| print (keyw) | |
| try: | |
| print (keyw.split("[")[1].split("]")[0]) | |
| keyw=keyw.split("[")[1].split("]")[0] | |
| for ea in keyw.split(","): | |
| s1="" | |
| ea=ea.strip().strip("\n") | |
| for ev in ea: | |
| if ev.isalnum(): | |
| s1+=ev | |
| if ev == " ": | |
| s1+=ev | |
| #ea=s1 | |
| print(s1) | |
| key_box.append(s1) | |
| except Exception as e: | |
| print(f'ERROR SAVING KEYWORD:: {e}') | |
| if "description" in line and ":" in line: | |
| #print(f'trying:: {line}') | |
| desc=line.split(":")[1] | |
| if key_box and desc: | |
| lod.append({"file_name":f"{timename}---{s}-{ee}","keywords":key_box,"description":str(desc),"index":f"{s}:{ee}"}) | |
| key_box = [] | |
| desc="" | |
| json_object = json.dumps(lod, indent=4) | |
| with open(f"tmp2-{uid}.json", "w") as outfile2: | |
| outfile2.write(json_object) | |
| outfile2.close() | |
| api.upload_file( | |
| path_or_fileobj=f"tmp2-{uid}.json", | |
| path_in_repo=f"/mem-test2/main.json", | |
| repo_id=reponame, | |
| #repo_id=save_data.split('datasets/',1)[1].split('/raw',1)[0], | |
| token=token_self, | |
| repo_type="dataset", | |
| ) | |
| ee=ee+chunk | |
| s=s+chunk | |
| out_box.append(resp) | |
| create_index() | |
| return out_box | |
| def valid_list(inp): | |
| out_list=[] | |
| inp_typ = type(inp) | |
| print(inp_typ) | |
| if inp_typ==type(str(inp)): | |
| print("STRING") | |
| #new_list = new_list.replace(", ",",").replace(" ,",",") | |
| new_list=inp.split("[")[1].split("]",-1)[0] | |
| print(new_list) | |
| print(type(new_list)) | |
| for ea in new_list.split(","): | |
| ea = ea.replace("'","").replace('"',"") | |
| out_list.append(ea) | |
| print(out_list) | |
| print(type(out_list)) | |
| def recall_memory(inp,history): | |
| error_box="" | |
| json_out={} | |
| if not history: | |
| history=[] | |
| r = requests.get(f'{save_data}mem-test2/index.json') | |
| print(f'status code main:: {r.status_code}') | |
| if r.status_code==200: | |
| mem = json.loads(r.text) | |
| print (f'ind::\n{mem}') | |
| if not r.status_code==200: | |
| print("Create new IND") | |
| out="MEMORY FILE NOT FOUND" | |
| return out,out,out,out | |
| mem_keys = mem[0].keys() | |
| rawp = get_mem(inp,mem_keys) | |
| valid_list(rawp) | |
| #valid_list(["123","333"]) | |
| history.clear() | |
| history.append((inp,rawp)) | |
| yield "", history,error_box,json_out | |
| ################################# | |
| def clear_fn(): | |
| return "",[(None,None)] | |
| with gr.Blocks() as app: | |
| gr.HTML("""<center><h1>Mixtral 8x7B TLDR Summarizer + Web</h1><h3>Summarize Data of unlimited length</h3>""") | |
| 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): | |
| report_check=gr.Checkbox(label="Return Report", value=True) | |
| sum_check=gr.Checkbox(label="Summarize", value=True) | |
| mem_check=gr.Checkbox(label="Memory", value=True) | |
| #sum_mem_check=gr.Radio(label="Output",choices=["Summary","Memory"]) | |
| 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("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)") | |
| with gr.Tab("Memory"): | |
| mem_inp = gr.Textbox(label="Query") | |
| mem = gr.Button() | |
| json_out=gr.JSON() | |
| e_box=gr.Textbox() | |
| mem.click(recall_memory,mem_inp,[prompt,chatbot,e_box,json_out]) | |
| #text=gr.JSON() | |
| #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,sum_check,mem_check,data,file,url,pdf_url,pdf_batch],[prompt,chatbot,e_box,json_out]) | |
| stop_button.click(None,None,None,cancels=[go]) | |
| app.queue(default_concurrency_limit=20).launch(show_api=False) |