Update app.py

app.py

@@ -1,75 +1,75 @@
-import streamlit as st
-from langchain_community.llms import Ollama
-from langchain.chains import LLMChain
-from langchain_core.prompts import ChatPromptTemplate
-from langchain_core.output_parsers import StrOutputParser
-from langchain_huggingface import HuggingFaceEndpoint
-# from dotenv import load_dotenv
-# load_dotenv()
-
-# Initialize Ollama LLM
-# llm = HuggingFaceEndpoint(repo_id="tiiuae/falcon-7b-instruct", model_kwargs={"temperature": 0.7, "max_length": 512})
-parser = StrOutputParser()
-
-repo_id = "mistralai/Mistral-7B-Instruct-v0.2"
-
-llm = HuggingFaceEndpoint(
-    repo_id=repo_id,
-    temperature=0.5
-    )
-
-
-system_template = """You are an AI assistant specialized in writing personalized, professional emails. 
-    Your task is to generate an email based on the provided information. 
-    The email should be engaging, concise, and highlight the key benefits of the project. Use bullet pointers. Maximum words allowed are 250. Always start with Subject line."""
-
-user_template = """Write a personalized email to {name} about the {project} project. 
-    Highlight the following key benefits:
-    {key_benefits}
-    
-    The email should be professional, engaging, and no longer than 3 paragraphs."""
-
-prompt_template = ChatPromptTemplate.from_messages(
-    [("system", system_template), ("user", user_template)]
-)
-
-# Create an LLMChain
-email_chain = prompt_template|llm
-# |parser
-
-# Streamlit UI
-st.title("Personalized Email Generator")
-
-name = st.text_input("Recipient's Name")
-project = st.text_input("Project Name")
-key_benefits = st.text_area("Key Benefits (one per line)")
-
-if st.button("Generate Email"):
-    if name and project and key_benefits:
-        benefits_list = key_benefits.split('\n')
-        benefits_str = ", ".join(benefits_list)
-        
-        email = email_chain.invoke({"name": name, "project": project, "key_benefits": key_benefits})
-        st.subheader("Generated Email:")
-        st.text_area("", email, height=300)
-    else:
-        st.error("Please fill in all fields.")
-
-# Instructions
-st.sidebar.header("Instructions")
-st.sidebar.info(
-    "1. Enter the recipient's name.\n"
-    "2. Specify the project name.\n"
-    "3. List key benefits, one per line.\n"
-    "4. Click 'Generate Email' to create a personalized email."
-)
-
-# About
-st.sidebar.header("About")
-st.sidebar.info(
-    "This app uses Langchain with Ollama to generate personalized emails "
-    "based on the provided information. It demonstrates how Large Language Models "
-    "can be used for dynamic content creation."
-)
-
-
+import streamlit as st
+from langchain_community.llms import Ollama
+from langchain.chains import LLMChain
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.output_parsers import StrOutputParser
+from langchain_huggingface import HuggingFaceEndpoint
+# from dotenv import load_dotenv
+# load_dotenv()
+
+# Initialize Ollama LLM
+# llm = HuggingFaceEndpoint(repo_id="tiiuae/falcon-7b-instruct", model_kwargs={"temperature": 0.7, "max_length": 512})
+parser = StrOutputParser()
+
+repo_id = "mistralai/Mistral-7B-Instruct-v0.2"
+
+llm = HuggingFaceEndpoint(
+    repo_id=repo_id,
+    temperature=0.5
+    )
+
+
+system_template = """You are an AI assistant specialized in writing personalized, professional emails. 
+    Your task is to generate an email based on the provided information. 
+    The email should be engaging, concise, and highlight the key benefits of the project. Use bullet pointers. Maximum words allowed are 250. Always start with Subject line."""
+
+user_template = """Write a personalized email to {name} about the {project} project. 
+    Highlight the following key benefits:
+    {key_benefits}
+    
+    The email should be professional, engaging, and no longer than 3 paragraphs."""
+
+prompt_template = ChatPromptTemplate.from_messages(
+    [("system", system_template), ("user", user_template)]
+)
+
+# Create an LLMChain
+email_chain = prompt_template|llm
+# |parser
+
+# Streamlit UI
+st.title("Personalized Email Generator")
+
+name = st.text_input("Recipient's Name")
+project = st.text_input("Project Name")
+key_benefits = st.text_area("Key Benefits (one per line)")
+
+if st.button("Generate Email"):
+    if name and project and key_benefits:
+        benefits_list = key_benefits.split('\n')
+        benefits_str = ", ".join(benefits_list)
+        
+        email = email_chain.invoke({"name": name, "project": project, "key_benefits": key_benefits})
+        st.subheader("Generated Email:")
+        st.text_area("", email, height=300)
+    else:
+        st.error("Please fill in all fields.")
+
+# Instructions
+st.sidebar.header("Instructions")
+st.sidebar.info(
+    "1. Enter the recipient's name.\n"
+    "2. Specify the project name.\n"
+    "3. List key benefits, one per line.\n"
+    "4. Click 'Generate Email' to create a personalized email."
+)
+
+# About
+st.sidebar.header("About")
+st.sidebar.info(
+    "This app uses Langchain with Huggingface to generate personalized emails "
+    "based on the provided information. It demonstrates how Large Language Models "
+    "can be used for dynamic content creation."
+)
+
+