Update app.py

app.py

@@ -5,6 +5,81 @@ from transformers import pipeline
 model = whisper.load_model("base")
 sentiment_analysis = pipeline("sentiment-analysis", framework="pt", model="SamLowe/roberta-base-go_emotions")
 
+
+import gradio as gr
+import whisper
+from transformers import pipeline
+import gradio as gr
+import pandas as pd
+from io import StringIO
+import os,re
+from langchain.llms import OpenAI
+import pandas as pd
+
+from langchain.document_loaders import UnstructuredPDFLoader
+
+from langchain.prompts import PromptTemplate
+from langchain.chains import LLMChain
+
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.vectorstores import Chroma
+from langchain.text_splitter import CharacterTextSplitter
+from langchain.llms import OpenAI
+from langchain.chains import RetrievalQA
+from langchain.document_loaders import TextLoader
+from langchain.prompts import PromptTemplate
+from langchain.callbacks.stdout import StdOutCallbackHandler
+from langchain.chat_models.openai import ChatOpenAI
+from langchain.prompts.prompt import PromptTemplate
+
+from langchain.llms import OpenAI
+from langchain.prompts import PromptTemplate
+from langchain.chains import LLMChain
+model = whisper.load_model("base")
+sentiment_analysis = pipeline("sentiment-analysis", framework="pt", model="SamLowe/roberta-base-go_emotions")
+
+def predict(text):
+   
+    prompt_template = """Ignore all previous instructions. You are the world's hearing aid company markerting agent.
+    I am going to give you a text of a customer. Analyze it and you have 4 products in list which you have to suggest to the customer: 
+    ampli-mini it is mainly works for Maximum comfort and discretion, ampli-connect it is mainly works for Connected to the things you love, 
+    ampli-energy it is mainly works for Full of energy, like you, ampli-easy it is mainly works for Allow yourself to hear well.
+    You can also be creative, funny, or show emotions at time.
+    also share the book a appointment link of your company https://www.amplifon.com/uk/book-an-appointment
+    Question: {question}
+    Product details:"""
+
+    prompt_template_lang = """
+    You are the world's best languages translator. Will give you some text or paragraph which you have to convert into Tamil, Hindi, Kannada
+    and French.
+    Input Text: {text}
+    Tamil: 
+    Hindi:
+    Kannada:
+    French:
+    """
+    PROMPT = PromptTemplate(
+        template=prompt_template, input_variables=["question"]
+    )
+    PROMPT_lang = PromptTemplate(
+        template=prompt_template_lang, input_variables=["text"]
+    )
+   
+    llm = OpenAI()
+   
+    chain = LLMChain(llm=llm, prompt=PROMPT)
+    chain_lang = LLMChain(llm=llm, prompt=PROMPT_lang)
+    
+    resp = chain.run(question=text)
+    resp_lang = chain_lang.run(text=resp)
+    
+ 
+
+    
+    return [resp, resp_lang]
+    
+
+
 def analyze_sentiment(text):
     results = sentiment_analysis(text)
     sentiment_results = {result['label']: result['score'] for result in results}