|
|
import streamlit as st |
|
|
from langchain import OpenAI, PromptTemplate, LLMChain |
|
|
from langchain.text_splitter import CharacterTextSplitter |
|
|
from langchain.chains.mapreduce import MapReduceChain |
|
|
from langchain.prompts import PromptTemplate |
|
|
from langchain.chat_models import AzureChatOpenAI |
|
|
from langchain.chains.summarize import load_summarize_chain |
|
|
from langchain.chains import AnalyzeDocumentChain |
|
|
from PyPDF2 import PdfReader |
|
|
from langchain.document_loaders import TextLoader |
|
|
from langchain.indexes import VectorstoreIndexCreator |
|
|
from langchain.document_loaders import PyPDFLoader |
|
|
import os |
|
|
import openai |
|
|
import requests |
|
|
import time |
|
|
import os |
|
|
import urllib.request |
|
|
from PIL import Image |
|
|
import os |
|
|
|
|
|
|
|
|
os.environ["OPENAI_API_TYPE"] = "azure" |
|
|
os.environ["OPENAI_API_VERSION"] = "2023-03-15-preview" |
|
|
|
|
|
image_api_base = 'https://openaistudio255.openai.azure.com/' |
|
|
image_api_key = os.environ["OPENAI_SECRETKEY"] |
|
|
|
|
|
|
|
|
openai.api_type = "azure" |
|
|
openai.api_base = "https://embeddinguseopenai.openai.azure.com/" |
|
|
openai.api_version = "2023-03-15-preview" |
|
|
openai.api_key = os.environ["OPENAI_API_KEY"] |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
image = Image.open('Wipro logo.png') |
|
|
st.image(image) |
|
|
|
|
|
st.title(" ideate sustainabile product designs with AI") |
|
|
|
|
|
|
|
|
st.header("What is your idea? Type it here and the AI will co-design your concept") |
|
|
|
|
|
yourquestion = st.text_input('Your topic', 'modern car design with solar panels on the top') |
|
|
st.write('Your input is ', yourquestion) |
|
|
|
|
|
|
|
|
|
|
|
if st.button("Visuvalize for ideas "): |
|
|
body = { "caption": yourquestion , "resolution": "512x512" } |
|
|
|
|
|
imageapi_version = '2022-08-03-preview' |
|
|
url = "{}dalle/text-to-image?api-version={}".format(image_api_base, imageapi_version) |
|
|
headers= { "api-key": image_api_key, "Content-Type": "application/json" } |
|
|
|
|
|
|
|
|
submission = requests.post(url, headers=headers, json=body) |
|
|
operation_location = submission.headers['Operation-Location'] |
|
|
retry_after = submission.headers['Retry-after'] |
|
|
status = "" |
|
|
|
|
|
while (status != "Succeeded"): |
|
|
time.sleep(int(retry_after)) |
|
|
response = requests.get(operation_location, headers=headers) |
|
|
status = response.json()['status'] |
|
|
image_url = response.json()['result']['contentUrl'] |
|
|
|
|
|
st.image(image_url, width = 512) |
|
|
|
|
|
|
|
|
if True==False: |
|
|
if st.button("Ask for ideas "): |
|
|
template = """ |
|
|
You are an AI assistant. |
|
|
{concept} |
|
|
""" |
|
|
|
|
|
yourquestionideas = "List creative ideas of " + yourquestion |
|
|
|
|
|
response = openai.ChatCompletion.create( |
|
|
engine="gpt-35-turbo", |
|
|
messages = [{"role":"system","content":"You are an AI assistant that can come up with creative product ideas."},{"role":"user","content":yourquestionideas}], |
|
|
temperature=0.99, |
|
|
max_tokens=800, |
|
|
top_p=1, |
|
|
frequency_penalty=0, |
|
|
presence_penalty=0, |
|
|
stop=None) |
|
|
|
|
|
|
|
|
st.write(response) |
|
|
|
