| 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 os |
|
|
|
|
| os.environ["OPENAI_API_TYPE"] = "azure" |
| os.environ["OPENAI_API_VERSION"] = "2023-03-15-preview" |
|
|
| 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"] |
| |
|
|
|
|
|
|
|
|
| st.title("Wipro demo with azure cognitive 2 ") |
|
|
|
|
| atemprature = st.slider('Fact vs Creative?', 0, 10, 1) |
| atemprature = atemprature / 10.0 |
|
|
|
|
| yourquestion = st.text_input('Your Question', 'First identify the indicators required as per EFRAG Environmental document. List these indicators. For each of these indicators, find out how Wipro is performing.') |
| st.write('Your input is ', yourquestion) |
|
|
|
|
|
|
|
|
|
|
| if st.button("Ask Questions "): |
| template = """ |
| You are an AI assistant. |
| {concept} |
| """ |
|
|
| response = openai.ChatCompletion.create( |
| engine="gpt-35-turbo", |
| messages = [{"role":"system","content":"You are an AI assistant that helps people find information."},{"role":"user","content":yourquestion}], |
| temperature=atemprature, |
| max_tokens=800, |
| top_p=1, |
| frequency_penalty=0, |
| presence_penalty=0, |
| stop=None) |
|
|
| |
| st.write(response) |
|
|
|
|
| if st.button("Ask Questions Simplify "): |
| template = """ |
| You are an AI assistant. |
| {concept} |
| """ |
|
|
| response = openai.ChatCompletion.create( |
| engine="gpt-35-turbo", |
| messages = [{"role":"system","content":"You are an AI assistant that helps people find information. Please explain the information like i am a five."},{"role":"user","content":yourquestion}], |
| temperature=0, |
| max_tokens=800, |
| top_p=1, |
| frequency_penalty=0, |
| presence_penalty=0, |
| stop=None) |
|
|
| |
| st.write(response) |
|
|
| if st.button("Ask trying here "): |
| template = """ |
| You are an expert on topics of Sustainability, Climate action and UN Sustainable Development Goals. |
| Explain the concept of {concept} like i am a five |
| """ |
|
|
| prompt = PromptTemplate( |
| input_variables=["concept"], |
| template=template, |
| ) |
|
|
|
|
| from langchain.chains import LLMChain |
| chain = LLMChain(llm=llm, prompt=prompt) |
|
|
| |
| st.write(chain.run(yourquestion)) |
|
|
|
|
|
|
| if st.button("Ask Hindi "): |
| template = """ |
| You are an expert on topics of Sustainability, Climate action and UN Sustainable Development Goals. |
| Explain the concept of {concept} in Hindi |
| """ |
|
|
| prompt = PromptTemplate( |
| input_variables=["concept"], |
| template=template, |
| ) |
|
|
|
|
| from langchain.chains import LLMChain |
| chain = LLMChain(llm=llm, prompt=prompt) |
|
|
| |
| st.write(chain.run(yourquestion)) |
|
|
