Update app.py

app.py

@@ -1,31 +1,30 @@
 import streamlit as st
-from langchain.chat_models import ChatOpenAI
-from langchain.prompts.chat import ChatPromptTemplate
-
+from langchain import OpenAI
+from langchain.chains import LLMChain
+from langchain.prompts import ChatPromptTemplate
 import os 
 
 os.environ["OPENAI_API_KEY"] = os.getenv("k1")
 
-st.title("Summarization Application :robot_face:")
-
-options = ["English","Telugu","Hindi","French","German","Russian","Spanish"]
 
-input_langauge = st.selectbox("Input Langauge: ",options)
+llm = OpenAI(api_key = os.environ["OPENAI_API_KEY"],model="gpt-3.5-turbo", temperature=0)
 
 
-text = st.text_input("Text Input: ")
+st.title("Summarization Application :robot_face:")
 
-if st.button("Submit"):
+options = ["English", "Telugu", "Hindi", "French", "German", "Russian", "Spanish"]
 
-    llm = ChatOpenAI(model = "gpt-3.5-turbo",temperature = 0)
+input_language = st.selectbox("Input Language: ", options)
 
-    prompt = ChatPromptTemplate.from_messages([("system","you are an expert summarizer for {lang} text."),
-            ("human","{text}")])
+text = st.text_area("Text Input: ")
 
-    chain = prompt|llm
+if st.button("Submit"):
+    prompt = ChatPromptTemplate.from_messages([("system", "You are an expert summarizer for {lang} texts."),
+                                               ("human", "{text}")])
 
-    re = chain.invoke({"lang":input_langauge, "text":text})
+    chain = LLMChain(prompt=prompt, llm=llm)
 
-    st.write("Response: ")
+    response = chain.run({"lang": input_language, "text": text})
 
-    st.write(re.content)
+    st.write("Summary: ")
+    st.write(response)