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app.py

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+import streamlit as st
+from langchain.prompts import ChatPromptTemplate
+from langchain.schema import SystemMessage, HumanMessage
+from langchain_huggingface import ChatHuggingFace, HuggingFaceEndpoint
+from dotenv import load_dotenv
+import os
+
+load_dotenv()
+HF_TOKEN = os.environ.get('HF_TOKEN')
+os.environ['HF_TOKEN'] = HF_TOKEN
+
+llm = HuggingFaceEndpoint(
+    repo_id="TinyLlama/TinyLlama-1.1B-Chat-v1.0",
+    task="text-generation",
+    huggingfacehub_api_token=HF_TOKEN
+)
+llm = ChatHuggingFace(llm=llm)
+
+def getLLamaresponse(input_text, no_words, blog_style):
+    if not input_text or not no_words:
+        return "⚠️ Please enter a valid topic and word count."
+
+    try:
+        template = """
+        Write a blog for {blog_style} job profile on the topic "{input_text}" 
+        within {no_words} words.
+        """
+
+        prompt = ChatPromptTemplate.from_template(template)
+
+        messages = [
+            SystemMessage(content="You are a helpful blog writer."),
+            HumanMessage(content=prompt.format(blog_style=blog_style, input_text=input_text, no_words=no_words))
+        ]
+
+        response = llm.invoke(messages)  
+        return response.content if response else "⚠️ No response from the model."
+
+    except Exception as e:
+        return f"❌ Error: {str(e)}"
+
+
+st.set_page_config(
+    page_title="Generate Blogs",
+    page_icon='🤖',
+    layout='centered',
+    initial_sidebar_state='collapsed'
+)
+
+st.header("Generate Blogs 🤖")
+
+
+input_text = st.text_input("Enter the Blog Topic")
+
+col1, col2 = st.columns([5, 5])
+with col1:
+    no_words = st.text_input('Number of Words')
+with col2:
+    blog_style = st.selectbox('Writing the blog for', 
+                              ('Researchers', 'Data Scientist', 'Common People'), 
+                              index=0)
+
+submit = st.button("Generate")
+if submit:
+    response = getLLamaresponse(input_text, no_words, blog_style)
+    st.write(response)

requirements.txt

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+sentence-transformers
+uvicorn
+ctransformers
+langchain
+python-box
+streamlit