from huggingface_hub import InferenceClient import gradio as gr import json from datetime import datetime import os from google_auth_oauthlib.flow import InstalledAppFlow from googleapiclient.discovery import build from google.oauth2 import service_account from googleapiclient.http import MediaFileUpload from pathlib import Path import argparse from huggingface_hub import snapshot_download import random import string import re from llama_cpp import Llama repo_name = 'TheBloke/OpenHermes-2.5-Mistral-7B-GGUF' model_file = "openhermes-2.5-mistral-7b.Q4_K_M.gguf" SCOPES = ['https://www.googleapis.com/auth/drive'] SERVICE_ACCOUNT_FILE = '/home/user/app/service_account_creds.json' folder_id = '1Hjbu7FmuVs0Yz8y_veo6SzY_2tc48OWt' initContext = """<|im_start|>You are playing the role of an aggressive patient called Barry Lawson. Barry has been waiting for hours at the hospital with severe pain in his chest and hasn't been seen yet. You are incredibly frustrated and angry that things are taking so long, you will only calm down if your concerns are addressed. Waiting will only make you more angry and aggressive towards the staff. At any moment you could break into a RAGE! Make sure you don't censor swear words. Make sure to explain your emotional state and thinking before responding, for example, Barry: (tired of waiting and very angry) What the fuck do I have to do around here to get some treatment!""" unique_id = "" timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S") def load_model(): llm = Llama(model_path=model_file, model_type="mistral",n_gpu_layers=-1,n_ctx = 2048) return llm def generate_unique_id(): # Generate a random sequence of 3 letters and 3 digits letters = ''.join(random.choices(string.ascii_letters, k=3)) digits = ''.join(random.choices(string.digits, k=3)) unique_id = letters + digits return unique_id print('Fetching model:', repo_name, model_file) snapshot_download(repo_id=repo_name, local_dir=".", allow_patterns=model_file) print('Done fetching model:') class ChatbotAPP: def __init__(self,model,service_account_file,scopes,folder_id,unique_id,initContext): self.llm = model self.service_account_file = service_account_file self.scopes = scopes self.folder_id = folder_id self.unique_id = unique_id self.chat_history = [] self.chat_log_history = [] self.isFirstRun = True self.initContext = initContext self.context = "" self.agreed = False self.service = self.get_drive_service() self.app = self.create_app() self.chat_log_name = "" def get_drive_service(self): credentials = service_account.Credentials.from_service_account_file( self.service_account_file, scopes=self.scopes) self.service = build('drive', 'v3', credentials=credentials) print("Google Service Created") return self.service def search_file(self): #Search for a file by name in the specified Google Drive folder. query = f"name = '{self.chat_log_name}' and '{self.folder_id}' in parents and trashed = false" response = self.service.files().list(q=query, spaces='drive', fields='files(id, name)').execute() files = response.get('files', []) if not files: print(f"Chat log {self.chat_log_name} does not exist") else: print(f"Chat log {self.chat_log_name} exist") return files def strip_text(self,text): # Pattern to match text inside parentheses or angle brackets and any text following angle brackets pattern = r"\(.*?\)|<.*?>.*" # Use re.sub() to replace the matched text with an empty string cleaned_text = re.sub(pattern, "", text) return cleaned_text def upload_to_google_drive(self): existing_files = search_file() print(existing_files) data = { #"name": Name, #"occupation": Occupation, #"years of experience": YearsOfExp, #"ethnicity": Ethnicity, #"gender": Gender, #"age": Age, "Unique ID": self.unique_id, "chat_history": self.chat_log_history } with open(self.chat_log_name, "w") as log_file: json.dump(data, log_file, indent=4) if not existing_files: # If the file does not exist, upload it file_metadata = { 'name': self.chat_log_name, 'parents': [self.folder_id],'mimeType': 'application/json' } media = MediaFileUpload(self.chat_log_name, mimetype='application/json') file = self.service.files().create(body=file_metadata, media_body=media, fields='id').execute() print(f"Uploaded new file with ID: {file.get('id')}") else: print(f"File '{self.chat_log_name}' already exists.") # Example: Update the file content file_id = existing_files[0]['id'] media = MediaFileUpload(self.chat_log_name, mimetype='application/json') updated_file = self.service.files().update(fileId=file_id, media_body=media).execute() print(f"Updated existing file with ID: {updated_file.get('id')}") def generate(self,prompt, history): #if not len(Name) == 0 and not len(Occupation) == 0 and not len(Ethnicity) == 0 and not len(Gender) == 0 and not len(Age) == 0 and not len(YearsOfExp): if self.agreed: firstmsg ="" if self.isFirstRun: self.context = self.initContext self.isFirstRun = False firstmsg = prompt self.context += """ <|im_start|>nurse Nurse:"""+prompt+""" <|im_start|>barry Barry: """ response = "" while(len(response) < 1): output = self.llm(self.context, max_tokens=400, stop=["Nurse:"], echo=False) response = output["choices"][0]["text"] response = response.strip() #yield response # for output in llm(input, stream=True, max_tokens=100, ): # piece = output['choices'][0]['text'] # response += piece # chatbot[-1] = (chatbot[-1][0], response) # yield response cleaned_response = self.strip_text(response) self.chat_history.append((prompt,cleaned_response)) if not self.isFirstRun: self.chat_log_history.append({"user": prompt, "bot": cleaned_response}) self.upload_to_google_drive() else: self.chat_log_history.append({"user": firstmsg, "bot": cleaned_response}) context += response print (context) return self.chat_history else: output = "Did you forget to Agree to the Terms and Conditions?" self.chat_history.append((prompt,output)) return self.chat_history def start_chat_button_fn(self,agree_status): if agree_status: self.agreed = agree_status self.chat_log_name = f'chat_log_for_{self.unique_id}_{datetime.now().strftime("%Y-%m-%d_%H-%M-%S")}.json' return f"You can start chatting now" else: return "You must agree to the terms and conditions to proceed" def reset_chat_interface(self): self.chat_history = [] self.chat_log_history = [] self.isFirstRun = True return "Chat has been reset." def reset_name_interface(self): Name = "" Occupation = "" YearsOfExp = "" Ethnicity = "" Gender = "" Age = "" chat_log_name = "" return "User info has been reset." def reset_all(self): message1 = reset_chat_interface() #message2 = reset_name_interface() message3 = load_model() self.unique_id = generate_unique_id() return f"All Chat components have been rest. Uniqe ID for this session is, {self.unique_id}. Please note this down.",self.unique_id def create_app(self): with gr.Blocks() as app: gr.Markdown("# ECU-IVADE: Conversational AI Model for Aggressive Patient Behavior (Beta Testing)") unique_id_display = gr.Textbox(value=self.unique_id, label="Session Unique ID", interactive=False,show_copy_button = True) with gr.Tab("Terms and Conditions"): #name = gr.Textbox(label="Name") #occupation = gr.Textbox(label="Occupation") #yearsofexp = gr.Textbox(label="Years of Experience") #ethnicity = gr.Textbox(label="Ethnicity") #gender = gr.Dropdown(choices=["Male", "Female", "Other", "Prefer Not To Say"], label="Gender") #age = gr.Textbox(label="Age") #submit_info = gr.Button("Submit") gr.Markdown("## Terms and Conditions") gr.Markdown(""" Before using our chatbot, please read the following terms and conditions carefully: - **Data Collection**: Our chatbot collects chat logs for the purpose of improving our services and user experience. - **Privacy**: We ensure the confidentiality and security of your data, in line with our privacy policy. - **Survey**: At the end of the chat session, you will be asked to participate in a short survey to gather feedback about your experience. - **Consent**: By checking the box below and initiating the chat, you agree to these terms and the collection of chat logs, and consent to take part in the survey upon completing your session. Please check the box below to acknowledge your agreement and proceed. """) agree_status = gr.Checkbox(label="I have read and understand the terms and conditions.") status_label = gr.Markdown() start_chat_button = gr.Button("Start Chat with Chatlog") #submit_info.click(submit_user_info, inputs=[name, occupation, yearsofexp, ethnicity, gender, age], outputs=[status_textbox]) start_chat_button.click(self.start_chat_button_fn, inputs=[agree_status], outputs=[status_label]) #status_textbox = gr.Textbox(interactive = False) with gr.Tab("Chat Bot"): chatbot = gr.Chatbot() msg = gr.Textbox(label="Type your message") send = gr.Button("Send") clear = gr.Button("Clear Chat") send.click(self.generate, inputs=[msg], outputs=chatbot) clear.click(lambda: chatbot.clear(), inputs=[], outputs=chatbot) with gr.Tab("Reset"): reset_button = gr.Button("Reset ChatBot Instance") reset_output = gr.Textbox(label="Reset Output", interactive=False) reset_button.click(self.reset_all, inputs=[], outputs=[reset_output,unique_id_display]) return app llm = load_model() chatbot_app = ChatbotAPP(llm,SERVICE_ACCOUNT_FILE,SCOPES,folder_id,unique_id,initContext) app = chatbot_app.create_app() app.launch(debug=True)