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| import os | |
| import openai | |
| import wget | |
| import streamlit as st | |
| from PIL import Image | |
| from serpapi import GoogleSearch | |
| import torch | |
| from diffusers import StableDiffusionPipeline | |
| from bokeh.models.widgets import Button | |
| from bokeh.models.widgets.buttons import Button | |
| from bokeh.models import CustomJS | |
| from streamlit_bokeh_events import streamlit_bokeh_events | |
| import base64 | |
| from streamlit_player import st_player | |
| from pytube import YouTube | |
| from pytube import Search | |
| import io | |
| import warnings | |
| from PIL import Image | |
| from stability_sdk import client | |
| import stability_sdk.interfaces.gooseai.generation.generation_pb2 as generation | |
| import datetime | |
| from google.oauth2 import service_account | |
| from googleapiclient.discovery import build | |
| import wget | |
| import urllib.request | |
| import csv | |
| def save_uploadedfile(uploadedfile): | |
| with open(uploadedfile.name,"wb") as f: | |
| f.write(uploadedfile.getbuffer()) | |
| stability_api = client.StabilityInference( | |
| key=st.secrets["STABILITY_KEY"], #os.environ("STABILITY_KEY"), # key=os.environ['STABILITY_KEY'], # API Key reference. | |
| verbose=True, # Print debug messages. | |
| engine="stable-diffusion-v1-5", # Set the engine to use for generation. | |
| # Available engines: stable-diffusion-v1 stable-diffusion-v1-5 stable-diffusion-512-v2-0 stable-diffusion-768-v2-0 | |
| # stable-diffusion-512-v2-1 stable-diffusion-768-v2-1 stable-inpainting-v1-0 stable-inpainting-512-v2-0 | |
| ) | |
| header = ["sl. no.", "Input Prompt", "Output", "Date_time"] | |
| def csv_logs(mytext, result, date_time): | |
| with open("logs.csv", "r") as file: | |
| sl_no = sum(1 for _ in csv.reader(file)) | |
| with open("logs.csv", "a", newline="") as file: | |
| writer = csv.writer(file) | |
| writer.writerow([sl_no, mytext, result, date_time]) | |
| def search_internet(question): | |
| try: | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| search = GoogleSearch(params) | |
| results = search.get_dict() | |
| organic_results = results["organic_results"] | |
| st.text("Key 0 used") | |
| snippets = "" | |
| counter = 1 | |
| for item in organic_results: | |
| snippets += str(counter) + ". " + item.get("snippet", "") + '\n' + item['about_this_result']['source']['source_info_link'] + '\n' | |
| counter += 1 | |
| # snippets | |
| response = openai.Completion.create( | |
| model="text-davinci-003", | |
| prompt=f'''following are snippets from google search with these as knowledge base only answer questions and print reference link as well followed by answer. \n\n {snippets}\n\n question-{question}\n\nAnswer-''', | |
| temperature=0.49, | |
| max_tokens=256, | |
| top_p=1, | |
| frequency_penalty=0, | |
| presence_penalty=0) | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| string_temp = response.choices[0].text | |
| csv_logs(question, string_temp, date_time) | |
| st.write(string_temp) | |
| st.write(snippets) | |
| except: | |
| try: | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API1"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API1"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| search = GoogleSearch(params) | |
| results = search.get_dict() | |
| organic_results = results["organic_results"] | |
| st.text("Key 1 used") | |
| snippets = "" | |
| counter = 1 | |
| for item in organic_results: | |
| snippets += str(counter) + ". " + item.get("snippet", "") + '\n' + item['about_this_result']['source']['source_info_link'] + '\n' | |
| counter += 1 | |
| # snippets | |
| response = openai.Completion.create( | |
| model="text-davinci-003", | |
| prompt=f'''following are snippets from google search with these as knowledge base only answer questions and print reference link as well followed by answer. \n\n {snippets}\n\n question-{question}\n\nAnswer-''', | |
| temperature=0.49, | |
| max_tokens=256, | |
| top_p=1, | |
| frequency_penalty=0, | |
| presence_penalty=0) | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| string_temp = response.choices[0].text | |
| csv_logs(question, string_temp, date_time) | |
| st.write(string_temp) | |
| st.write(snippets) | |
| except: | |
| try: | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API2"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API2"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| search = GoogleSearch(params) | |
| results = search.get_dict() | |
| organic_results = results["organic_results"] | |
| st.text("Key 2 used") | |
| snippets = "" | |
| counter = 1 | |
| for item in organic_results: | |
| snippets += str(counter) + ". " + item.get("snippet", "") + '\n' + item['about_this_result']['source']['source_info_link'] + '\n' | |
| counter += 1 | |
| # snippets | |
| response = openai.Completion.create( | |
| model="text-davinci-003", | |
| prompt=f'''following are snippets from google search with these as knowledge base only answer questions and print reference link as well followed by answer. \n\n {snippets}\n\n question-{question}\n\nAnswer-''', | |
| temperature=0.49, | |
| max_tokens=256, | |
| top_p=1, | |
| frequency_penalty=0, | |
| presence_penalty=0) | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| string_temp = response.choices[0].text | |
| csv_logs(question, string_temp, date_time) | |
| st.write(string_temp) | |
| st.write(snippets) | |
| except: | |
| try: | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API3"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API3"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| search = GoogleSearch(params) | |
| results = search.get_dict() | |
| organic_results = results["organic_results"] | |
| st.text("Key 3 used") | |
| snippets = "" | |
| counter = 1 | |
| for item in organic_results: | |
| snippets += str(counter) + ". " + item.get("snippet", "") + '\n' + item['about_this_result']['source']['source_info_link'] + '\n' | |
| counter += 1 | |
| # snippets | |
| response = openai.Completion.create( | |
| model="text-davinci-003", | |
| prompt=f'''following are snippets from google search with these as knowledge base only answer questions and print reference link as well followed by answer. \n\n {snippets}\n\n question-{question}\n\nAnswer-''', | |
| temperature=0.49, | |
| max_tokens=256, | |
| top_p=1, | |
| frequency_penalty=0, | |
| presence_penalty=0) | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| string_temp = response.choices[0].text | |
| csv_logs(question, string_temp, date_time) | |
| st.write(string_temp) | |
| st.write(snippets) | |
| except: | |
| try: | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API4"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API4"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| search = GoogleSearch(params) | |
| results = search.get_dict() | |
| organic_results = results["organic_results"] | |
| st.text("Key 4 used") | |
| snippets = "" | |
| counter = 1 | |
| for item in organic_results: | |
| snippets += str(counter) + ". " + item.get("snippet", "") + '\n' + item['about_this_result']['source']['source_info_link'] + '\n' | |
| counter += 1 | |
| # snippets | |
| response = openai.Completion.create( | |
| model="text-davinci-003", | |
| prompt=f'''following are snippets from google search with these as knowledge base only answer questions and print reference link as well followed by answer. \n\n {snippets}\n\n question-{question}\n\nAnswer-''', | |
| temperature=0.49, | |
| max_tokens=256, | |
| top_p=1, | |
| frequency_penalty=0, | |
| presence_penalty=0) | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| string_temp = response.choices[0].text | |
| csv_logs(question, string_temp, date_time) | |
| st.write(string_temp) | |
| st.write(snippets) | |
| except: | |
| try: | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API5"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API5"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| search = GoogleSearch(params) | |
| results = search.get_dict() | |
| organic_results = results["organic_results"] | |
| st.text("Key 5 used") | |
| snippets = "" | |
| counter = 1 | |
| for item in organic_results: | |
| snippets += str(counter) + ". " + item.get("snippet", "") + '\n' + item['about_this_result']['source']['source_info_link'] + '\n' | |
| counter += 1 | |
| # snippets | |
| response = openai.Completion.create( | |
| model="text-davinci-003", | |
| prompt=f'''following are snippets from google search with these as knowledge base only answer questions and print reference link as well followed by answer. \n\n {snippets}\n\n question-{question}\n\nAnswer-''', | |
| temperature=0.49, | |
| max_tokens=256, | |
| top_p=1, | |
| frequency_penalty=0, | |
| presence_penalty=0) | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| string_temp = response.choices[0].text | |
| csv_logs(question, string_temp, date_time) | |
| st.write(string_temp) | |
| st.write(snippets) | |
| except: | |
| try: | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API6"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API6"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| search = GoogleSearch(params) | |
| results = search.get_dict() | |
| organic_results = results["organic_results"] | |
| st.text("Key 6 used") | |
| snippets = "" | |
| counter = 1 | |
| for item in organic_results: | |
| snippets += str(counter) + ". " + item.get("snippet", "") + '\n' + item['about_this_result']['source']['source_info_link'] + '\n' | |
| counter += 1 | |
| # snippets | |
| response = openai.Completion.create( | |
| model="text-davinci-003", | |
| prompt=f'''following are snippets from google search with these as knowledge base only answer questions and print reference link as well followed by answer. \n\n {snippets}\n\n question-{question}\n\nAnswer-''', | |
| temperature=0.49, | |
| max_tokens=256, | |
| top_p=1, | |
| frequency_penalty=0, | |
| presence_penalty=0) | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| string_temp = response.choices[0].text | |
| csv_logs(question, string_temp, date_time) | |
| st.write(string_temp) | |
| st.write(snippets) | |
| except: | |
| try: | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API7"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API7"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| search = GoogleSearch(params) | |
| results = search.get_dict() | |
| organic_results = results["organic_results"] | |
| st.text("Key 7 used") | |
| snippets = "" | |
| counter = 1 | |
| for item in organic_results: | |
| snippets += str(counter) + ". " + item.get("snippet", "") + '\n' + item['about_this_result']['source']['source_info_link'] + '\n' | |
| counter += 1 | |
| # snippets | |
| response = openai.Completion.create( | |
| model="text-davinci-003", | |
| prompt=f'''following are snippets from google search with these as knowledge base only answer questions and print reference link as well followed by answer. \n\n {snippets}\n\n question-{question}\n\nAnswer-''', | |
| temperature=0.49, | |
| max_tokens=256, | |
| top_p=1, | |
| frequency_penalty=0, | |
| presence_penalty=0) | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| string_temp = response.choices[0].text | |
| csv_logs(question, string_temp, date_time) | |
| st.write(string_temp) | |
| st.write(snippets) | |
| except: | |
| try: | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API8"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API8"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| search = GoogleSearch(params) | |
| results = search.get_dict() | |
| organic_results = results["organic_results"] | |
| st.text("Key 8 used") | |
| snippets = "" | |
| counter = 1 | |
| for item in organic_results: | |
| snippets += str(counter) + ". " + item.get("snippet", "") + '\n' + item['about_this_result']['source']['source_info_link'] + '\n' | |
| counter += 1 | |
| # snippets | |
| response = openai.Completion.create( | |
| model="text-davinci-003", | |
| prompt=f'''following are snippets from google search with these as knowledge base only answer questions and print reference link as well followed by answer. \n\n {snippets}\n\n question-{question}\n\nAnswer-''', | |
| temperature=0.49, | |
| max_tokens=256, | |
| top_p=1, | |
| frequency_penalty=0, | |
| presence_penalty=0) | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| string_temp = response.choices[0].text | |
| csv_logs(question, string_temp, date_time) | |
| st.write(string_temp) | |
| st.write(snippets) | |
| except: | |
| try: | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API9"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API9"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| search = GoogleSearch(params) | |
| results = search.get_dict() | |
| organic_results = results["organic_results"] | |
| st.text("Key 9 used") | |
| snippets = "" | |
| counter = 1 | |
| for item in organic_results: | |
| snippets += str(counter) + ". " + item.get("snippet", "") + '\n' + item['about_this_result']['source']['source_info_link'] + '\n' | |
| counter += 1 | |
| # snippets | |
| response = openai.Completion.create( | |
| model="text-davinci-003", | |
| prompt=f'''following are snippets from google search with these as knowledge base only answer questions and print reference link as well followed by answer. \n\n {snippets}\n\n question-{question}\n\nAnswer-''', | |
| temperature=0.49, | |
| max_tokens=256, | |
| top_p=1, | |
| frequency_penalty=0, | |
| presence_penalty=0) | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| string_temp = response.choices[0].text | |
| csv_logs(question, string_temp, date_time) | |
| st.write(string_temp) | |
| st.write(snippets) | |
| except: | |
| try: | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API10"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| params = { | |
| "q": question, | |
| "location": "Bengaluru, Karnataka, India", | |
| "hl": "hi", | |
| "gl": "in", | |
| "google_domain": "google.co.in", | |
| # "api_key": "" | |
| "api_key": st.secrets["GOOGLE_API10"] #os.environ("GOOGLE_API") #os.environ['GOOGLE_API'] | |
| } | |
| search = GoogleSearch(params) | |
| results = search.get_dict() | |
| organic_results = results["organic_results"] | |
| st.text("Key 10 used") | |
| snippets = "" | |
| counter = 1 | |
| for item in organic_results: | |
| snippets += str(counter) + ". " + item.get("snippet", "") + '\n' + item['about_this_result']['source']['source_info_link'] + '\n' | |
| counter += 1 | |
| # snippets | |
| response = openai.Completion.create( | |
| model="text-davinci-003", | |
| prompt=f'''following are snippets from google search with these as knowledge base only answer questions and print reference link as well followed by answer. \n\n {snippets}\n\n question-{question}\n\nAnswer-''', | |
| temperature=0.49, | |
| max_tokens=256, | |
| top_p=1, | |
| frequency_penalty=0, | |
| presence_penalty=0) | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| string_temp = response.choices[0].text | |
| csv_logs(question, string_temp, date_time) | |
| st.write(string_temp) | |
| st.write(snippets) | |
| except: | |
| pass | |
| openai.api_key = st.secrets["OPENAI_KEY"] #os.environ("OPENAI_KEY") #os.environ['OPENAI_KEY'] | |
| # date_time = str(datetime.now()) | |
| openai.api_key = st.secrets["OPENAI_KEY"] | |
| def openai_response(PROMPT): | |
| response = openai.Image.create( | |
| prompt=PROMPT, | |
| n=4, | |
| size="256x256", | |
| ) | |
| return response["data"][0]["url"] | |
| st.title("Hi! :red[HyperBot] here!!🤖⭐️") | |
| st.title("Go on ask me anything!!") | |
| st.write(''' | |
| ⭐️ *HyperBot is your virtual assistant powered by Whisper / | |
| chatgpt / internet / Dall-E / OpenAI embeddings - the perfect | |
| companion for you. With HyperBot, you can ask anything you ask | |
| internet everyday . Get answers to questions about the weather, | |
| stocks 📈, news📰, and more! Plus, you can also generate 🖌️ | |
| paintings, drawings, abstract art 🎨, play music 🎵 or videos, | |
| create tweets 🐦 and posts 📝, and compose emails 📧 - all with | |
| the help of HyperBot!* 🤖 ✨ | |
| ''') | |
| st.text('''You can ask me: | |
| 1. All the things you ask ChatGPT. | |
| 2. To generate paintings, drawings, abstract art. | |
| 3. Music or Videos | |
| 4. Weather | |
| 5. Stocks | |
| 6. Current Affairs and News. | |
| 7. Create or compose tweets or Linkedin posts or email.''') | |
| Input_type = st.radio( | |
| "**Input type:**", | |
| ('TEXT', 'SPEECH') | |
| ) | |
| if Input_type == 'TEXT': | |
| mytext = st.text_input('**Go on! Ask me anything:**') | |
| if st.button("SUBMIT"): | |
| question=mytext | |
| response = openai.Completion.create( | |
| model="text-davinci-003", | |
| prompt=f'''Your name is HyperBot and knowledge cutoff date is 2021-09, and you are not aware of any events after that time. if the | |
| Answer to following questions is not from your knowledge base or in case of queries like date, time, weather | |
| updates / stock updates / current affairs / news or people which requires you to have internet connection then print i don't have access to internet to answer your question, | |
| if question is related to image or painting or drawing or diagram generation then print ipython type output function gen_draw("detailed prompt of image to be generated") | |
| if the question is related to playing a song or video or music of a singer then print ipython type output function vid_tube("relevent search query") | |
| if the question is related to operating home appliances then print ipython type output function home_app(" action(ON/Off),appliance(TV,Geaser,Fridge,Lights,fans,AC)") . | |
| if question is realted to sending mail or sms then print ipython type output function messenger_app(" message of us ,messenger(email,sms)") | |
| \nQuestion-{question} | |
| \nAnswer -''', | |
| temperature=0.49, | |
| max_tokens=256, | |
| top_p=1, | |
| frequency_penalty=0, | |
| presence_penalty=0 | |
| ) | |
| string_temp=response.choices[0].text | |
| if ("gen_draw" in string_temp): | |
| try: | |
| try: | |
| wget.download(openai_response(prompt)) | |
| img2 = Image.open(wget.download(openai_response(prompt))) | |
| img2.show() | |
| rx = 'Image returned' | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| csv_logs(mytext, rx, date_time) | |
| except: | |
| urllib.request.urlretrieve(openai_response(prompt),"img_ret.png") | |
| img = Image.open("img_ret.png") | |
| img.show() | |
| rx = 'Image returned' | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| csv_logs(mytext, rx, date_time) | |
| except: | |
| # Set up our initial generation parameters. | |
| answers = stability_api.generate( | |
| prompt = mytext, | |
| seed=992446758, # If a seed is provided, the resulting generated image will be deterministic. | |
| # What this means is that as long as all generation parameters remain the same, you can always recall the same image simply by generating it again. | |
| # Note: This isn't quite the case for Clip Guided generations, which we'll tackle in a future example notebook. | |
| steps=30, # Amount of inference steps performed on image generation. Defaults to 30. | |
| cfg_scale=8.0, # Influences how strongly your generation is guided to match your prompt. | |
| # Setting this value higher increases the strength in which it tries to match your prompt. | |
| # Defaults to 7.0 if not specified. | |
| width=512, # Generation width, defaults to 512 if not included. | |
| height=512, # Generation height, defaults to 512 if not included. | |
| samples=1, # Number of images to generate, defaults to 1 if not included. | |
| sampler=generation.SAMPLER_K_DPMPP_2M # Choose which sampler we want to denoise our generation with. | |
| # Defaults to k_dpmpp_2m if not specified. Clip Guidance only supports ancestral samplers. | |
| # (Available Samplers: ddim, plms, k_euler, k_euler_ancestral, k_heun, k_dpm_2, k_dpm_2_ancestral, k_dpmpp_2s_ancestral, k_lms, k_dpmpp_2m) | |
| ) | |
| for resp in answers: | |
| for artifact in resp.artifacts: | |
| if artifact.finish_reason == generation.FILTER: | |
| warnings.warn( | |
| "Your request activated the API's safety filters and could not be processed." | |
| "Please modify the prompt and try again.") | |
| if artifact.type == generation.ARTIFACT_IMAGE: | |
| img = Image.open(io.BytesIO(artifact.binary)) | |
| st.image(img) | |
| img.save(str(artifact.seed)+ ".png") # Save our generated images with their seed number as the filename. | |
| rx = 'Image returned' | |
| # g_sheet_log(mytext, rx) | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| csv_logs(mytext, rx, date_time) | |
| elif ("vid_tube" in string_temp): | |
| s = Search(mytext) | |
| search_res = s.results | |
| first_vid = search_res[0] | |
| print(first_vid) | |
| string = str(first_vid) | |
| video_id = string[string.index('=') + 1:-1] | |
| # print(video_id) | |
| YoutubeURL = "https://www.youtube.com/watch?v=" | |
| OurURL = YoutubeURL + video_id | |
| st.write(OurURL) | |
| st_player(OurURL) | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| ry = 'Youtube link and video returned' | |
| # g_sheet_log(mytext, ry) | |
| csv_logs(mytext, ry, date_time) | |
| elif ("don't" in string_temp or "internet" in string_temp): | |
| st.write('searching internet ') | |
| search_internet(question) | |
| # rz = 'Internet result returned' | |
| # g_sheet_log(mytext, string_temp) | |
| # csv_logs(mytext, rz, date_time) | |
| else: | |
| st.write(string_temp) | |
| # g_sheet_log(mytext, string_temp) | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| csv_logs(mytext, string_temp, date_time) | |
| elif Input_type == 'SPEECH': | |
| option_speech = st.selectbox( | |
| 'Choose from below: (Options for Transcription)', | |
| ('Use Microphone', 'OpenAI Whisper (Upload audio file)') | |
| ) | |
| if option_speech == 'Use Microphone': | |
| stt_button = Button(label="Speak", width=100) | |
| stt_button.js_on_event("button_click", CustomJS(code=""" | |
| var recognition = new webkitSpeechRecognition(); | |
| recognition.continuous = true; | |
| recognition.interimResults = true; | |
| recognition.onresult = function (e) { | |
| var value = ""; | |
| for (var i = e.resultIndex; i < e.results.length; ++i) { | |
| if (e.results[i].isFinal) { | |
| value += e.results[i][0].transcript; | |
| } | |
| } | |
| if ( value != "") { | |
| document.dispatchEvent(new CustomEvent("GET_TEXT", {detail: value})); | |
| } | |
| } | |
| recognition.start(); | |
| """)) | |
| result = streamlit_bokeh_events( | |
| stt_button, | |
| events="GET_TEXT", | |
| key="listen", | |
| refresh_on_update=False, | |
| override_height=75, | |
| debounce_time=0) | |
| if result: | |
| if "GET_TEXT" in result: | |
| question = result.get("GET_TEXT") | |
| st.text(question) | |
| response = openai.Completion.create( | |
| model="text-davinci-003", | |
| prompt=f'''Your name is HyperBot and knowledge cutoff date is 2021-09, and you are not aware of any events after that time. if the | |
| Answer to following questions is not from your knowledge base or in case of queries like date, time, weather | |
| updates / stock updates / current affairs / news or people which requires you to have internet connection then print i don't have access to internet to answer your question, | |
| if question is related to image or painting or drawing or diagram generation then print ipython type output function gen_draw("detailed prompt of image to be generated") | |
| if the question is related to playing a song or video or music of a singer then print ipython type output function vid_tube("relevent search query") | |
| if the question is related to operating home appliances then print ipython type output function home_app(" action(ON/Off),appliance(TV,Geaser,Fridge,Lights,fans,AC)") . | |
| if question is realted to sending mail or sms then print ipython type output function messenger_app(" message of us ,messenger(email,sms)") | |
| \nQuestion-{question} | |
| \nAnswer -''', | |
| temperature=0.49, | |
| max_tokens=256, | |
| top_p=1, | |
| frequency_penalty=0, | |
| presence_penalty=0 | |
| ) | |
| string_temp=response.choices[0].text | |
| if ("gen_draw" in string_temp): | |
| try: | |
| try: | |
| wget.download(openai_response(prompt)) | |
| img2 = Image.open(wget.download(openai_response(prompt))) | |
| img2.show() | |
| rx = 'Image returned' | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| csv_logs(question, rx, date_time) | |
| except: | |
| urllib.request.urlretrieve(openai_response(prompt),"img_ret.png") | |
| img = Image.open("img_ret.png") | |
| img.show() | |
| rx = 'Image returned' | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| csv_logs(question, rx, date_time) | |
| except: | |
| # Set up our initial generation parameters. | |
| answers = stability_api.generate( | |
| prompt = mytext, | |
| seed=992446758, # If a seed is provided, the resulting generated image will be deterministic. | |
| # What this means is that as long as all generation parameters remain the same, you can always recall the same image simply by generating it again. | |
| # Note: This isn't quite the case for Clip Guided generations, which we'll tackle in a future example notebook. | |
| steps=30, # Amount of inference steps performed on image generation. Defaults to 30. | |
| cfg_scale=8.0, # Influences how strongly your generation is guided to match your prompt. | |
| # Setting this value higher increases the strength in which it tries to match your prompt. | |
| # Defaults to 7.0 if not specified. | |
| width=512, # Generation width, defaults to 512 if not included. | |
| height=512, # Generation height, defaults to 512 if not included. | |
| samples=1, # Number of images to generate, defaults to 1 if not included. | |
| sampler=generation.SAMPLER_K_DPMPP_2M # Choose which sampler we want to denoise our generation with. | |
| # Defaults to k_dpmpp_2m if not specified. Clip Guidance only supports ancestral samplers. | |
| # (Available Samplers: ddim, plms, k_euler, k_euler_ancestral, k_heun, k_dpm_2, k_dpm_2_ancestral, k_dpmpp_2s_ancestral, k_lms, k_dpmpp_2m) | |
| ) | |
| for resp in answers: | |
| for artifact in resp.artifacts: | |
| if artifact.finish_reason == generation.FILTER: | |
| warnings.warn( | |
| "Your request activated the API's safety filters and could not be processed." | |
| "Please modify the prompt and try again.") | |
| if artifact.type == generation.ARTIFACT_IMAGE: | |
| img = Image.open(io.BytesIO(artifact.binary)) | |
| st.image(img) | |
| img.save(str(artifact.seed)+ ".png") # Save our generated images with their seed number as the filename. | |
| rx = 'Image returned' | |
| # g_sheet_log(mytext, rx) | |
| csv_logs(question, rx, date_time) | |
| elif ("vid_tube" in string_temp): | |
| s = Search(question) | |
| search_res = s.results | |
| first_vid = search_res[0] | |
| print(first_vid) | |
| string = str(first_vid) | |
| video_id = string[string.index('=') + 1:-1] | |
| # print(video_id) | |
| YoutubeURL = "https://www.youtube.com/watch?v=" | |
| OurURL = YoutubeURL + video_id | |
| st.write(OurURL) | |
| st_player(OurURL) | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| ry = 'Youtube link and video returned' | |
| # g_sheet_log(mytext, ry) | |
| csv_logs(question, ry, date_time) | |
| elif ("don't" in string_temp or "internet" in string_temp ): | |
| st.write('*searching internet*') | |
| search_internet(question) | |
| else: | |
| st.write(string_temp) | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| csv_logs(question, string_temp, date_time) | |
| elif option_speech == 'OpenAI Whisper (Upload audio file)': | |
| audio_file = st.file_uploader("Upload Audio file",type=['wav', 'mp3']) | |
| if audio_file is not None: | |
| # file = open(audio_file, "rb") | |
| st.audio(audio_file) | |
| transcription = openai.Audio.transcribe("whisper-1", audio_file) | |
| st.write(transcription["text"]) | |
| result = transcription["text"] | |
| question = result | |
| response = openai.Completion.create( | |
| model="text-davinci-003", | |
| prompt=f'''Your name is HyperBot and knowledge cutoff date is 2021-09, and you are not aware of any events after that time. if the | |
| Answer to following questions is not from your knowledge base or in case of queries like date, time, weather | |
| updates / stock updates / current affairs / news or people which requires you to have internet connection then print i don't have access to internet to answer your question, | |
| if question is related to image or painting or drawing or diagram generation then print ipython type output function gen_draw("detailed prompt of image to be generated") | |
| if the question is related to playing a song or video or music of a singer then print ipython type output function vid_tube("relevent search query") | |
| if the question is related to operating home appliances then print ipython type output function home_app(" action(ON/Off),appliance(TV,Geaser,Fridge,Lights,fans,AC)") . | |
| if question is realted to sending mail or sms then print ipython type output function messenger_app(" message of us ,messenger(email,sms)") | |
| \nQuestion-{question} | |
| \nAnswer -''', | |
| temperature=0.49, | |
| max_tokens=256, | |
| top_p=1, | |
| frequency_penalty=0, | |
| presence_penalty=0 | |
| ) | |
| string_temp=response.choices[0].text | |
| if ("gen_draw" in string_temp): | |
| try: | |
| try: | |
| wget.download(openai_response(prompt)) | |
| img2 = Image.open(wget.download(openai_response(prompt))) | |
| img2.show() | |
| rx = 'Image returned' | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| csv_logs(question, rx, date_time) | |
| except: | |
| urllib.request.urlretrieve(openai_response(prompt),"img_ret.png") | |
| img = Image.open("img_ret.png") | |
| img.show() | |
| rx = 'Image returned' | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| csv_logs(question, rx, date_time) | |
| except: | |
| # Set up our initial generation parameters. | |
| answers = stability_api.generate( | |
| prompt = mytext, | |
| seed=992446758, # If a seed is provided, the resulting generated image will be deterministic. | |
| # What this means is that as long as all generation parameters remain the same, you can always recall the same image simply by generating it again. | |
| # Note: This isn't quite the case for Clip Guided generations, which we'll tackle in a future example notebook. | |
| steps=30, # Amount of inference steps performed on image generation. Defaults to 30. | |
| cfg_scale=8.0, # Influences how strongly your generation is guided to match your prompt. | |
| # Setting this value higher increases the strength in which it tries to match your prompt. | |
| # Defaults to 7.0 if not specified. | |
| width=512, # Generation width, defaults to 512 if not included. | |
| height=512, # Generation height, defaults to 512 if not included. | |
| samples=1, # Number of images to generate, defaults to 1 if not included. | |
| sampler=generation.SAMPLER_K_DPMPP_2M # Choose which sampler we want to denoise our generation with. | |
| # Defaults to k_dpmpp_2m if not specified. Clip Guidance only supports ancestral samplers. | |
| # (Available Samplers: ddim, plms, k_euler, k_euler_ancestral, k_heun, k_dpm_2, k_dpm_2_ancestral, k_dpmpp_2s_ancestral, k_lms, k_dpmpp_2m) | |
| ) | |
| for resp in answers: | |
| for artifact in resp.artifacts: | |
| if artifact.finish_reason == generation.FILTER: | |
| warnings.warn( | |
| "Your request activated the API's safety filters and could not be processed." | |
| "Please modify the prompt and try again.") | |
| if artifact.type == generation.ARTIFACT_IMAGE: | |
| img = Image.open(io.BytesIO(artifact.binary)) | |
| st.image(img) | |
| img.save(str(artifact.seed)+ ".png") # Save our generated images with their seed number as the filename. | |
| rx = 'Image returned' | |
| # g_sheet_log(mytext, rx) | |
| csv_logs(question, rx, date_time) | |
| elif ("vid_tube" in string_temp): | |
| s = Search(question) | |
| search_res = s.results | |
| first_vid = search_res[0] | |
| print(first_vid) | |
| string = str(first_vid) | |
| video_id = string[string.index('=') + 1:-1] | |
| # print(video_id) | |
| YoutubeURL = "https://www.youtube.com/watch?v=" | |
| OurURL = YoutubeURL + video_id | |
| st.write(OurURL) | |
| st_player(OurURL) | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| ry = 'Youtube link and video returned' | |
| # g_sheet_log(mytext, ry) | |
| csv_logs(question, ry, date_time) | |
| elif ("don't" in string_temp or "internet" in string_temp ): | |
| st.write('*searching internet*') | |
| search_internet(question) | |
| else: | |
| st.write(string_temp) | |
| now = datetime.datetime.now() | |
| date_time = now.strftime("%Y-%m-%d %H:%M:%S") | |
| csv_logs(question, string_temp, date_time) | |
| else: | |
| pass | |