Blog Generator Agent

.github/workflows/main.yaml

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+name: Sync to Hugging Face Space
+on:
+  push:
+    branches: [main]
+
+  # to run this workflow manually from the Actions tab 
+  workflow_dispatch:
+
+jobs:
+  sync-to-hub:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+        with:
+          fetch-depth: 0
+          lfs: false
+
+      - name: Ignore large files
+        run : git filter-branch --index-filter 'git rm -rf --cached --ignore-unmatch' HEAD
+
+      - name: Push to hub
+        env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+        run: git push --force https://msaifee:$HF_TOKEN@huggingface.co/spaces/msaifee/BlogGeneratorAgent main

app.py

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+import streamlit as st
+from dotenv import load_dotenv
+import os
+from langchain_groq import ChatGroq
+from typing_extensions import TypedDict
+from langgraph.graph import add_messages, StateGraph, END, START
+from langchain_core.messages import AIMessage, HumanMessage
+from typing import Annotated, List
+
+# Load environment variables
+load_dotenv()
+
+# Set up Groq client
+os.environ["GROQ_API_KEY"] = os.getenv("GROQ_API_KEY")
+llm = ChatGroq(model="qwen-2.5-32b")
+
+# Define BlogState TypedDict
+class BlogState(TypedDict):
+    topic: str
+    title: str
+    blog_content: Annotated[List, add_messages]
+    reviewed_content: Annotated[List, add_messages]
+    is_blog_ready: str
+
+# Initialize session state
+if 'blog_state' not in st.session_state:
+    st.session_state.blog_state = None
+if 'graph' not in st.session_state:
+    st.session_state.graph = None
+
+def init_graph():
+    builder = StateGraph(BlogState)
+    
+    builder.add_node("title_generator", generate_title)
+    builder.add_node("content_generator", generate_content)
+    builder.add_node("content_reviewer", review_content)
+    builder.add_node("quality_check", evaluate_content)
+    
+    builder.add_edge(START, "title_generator")
+    builder.add_edge("title_generator", "content_generator")
+    builder.add_edge("content_generator", "content_reviewer")
+    builder.add_edge("content_reviewer", "quality_check")
+    
+    builder.add_conditional_edges(
+        "quality_check",
+        route_based_on_verdict,
+        {"Pass": END, "Fail": "content_generator"}
+    )
+    return builder.compile()
+
+# Node functions with state management
+def generate_title(state: BlogState):
+    prompt = f"""Generate compelling blog title options about {state["topic"]} that are:
+    - SEO-friendly
+    - Attention-grabbing
+    - Between 6-12 words"""
+    
+    with st.status("🚀 Generating Titles..."):
+        response = llm.invoke(prompt)
+        state["title"] = response.content.split("\n")[0].strip('"')
+        st.write(f"Selected title: **{state['title']}**")
+    return state
+
+def generate_content(state: BlogState):
+    prompt = f"""Write a comprehensive blog post titled "{state["title"]}" with:
+    1. Engaging introduction with hook
+    2. 3-5 subheadings with detailed content
+    3. Practical examples/statistics
+    4. Clear transitions between sections
+    5. Actionable conclusion
+    Style: Professional yet conversational (Flesch-Kincaid 60-70). Use markdown formatting"""
+    
+    with st.status("📝 Generating Content..."):
+        response = llm.invoke(prompt)
+        state["blog_content"].append(AIMessage(content=response.content))
+        st.markdown(response.content)
+    return state
+
+def review_content(state: BlogState):
+    content = state["blog_content"][-1].content
+    prompt = f"""Critically review this blog content:
+    - Clarity & Structure
+    - Grammar & Style
+    - SEO optimization
+    - Reader engagement
+    Provide specific improvement suggestions. Content:\n{content}"""
+    
+    with st.status("🔍 Reviewing Content..."):
+        feedback = llm.invoke(prompt)
+        state["reviewed_content"].append(HumanMessage(content=feedback.content))
+        st.write(feedback.content)
+    return state
+
+def evaluate_content(state: BlogState):
+    content = state["blog_content"][-1].content
+    feedback = state["reviewed_content"][-1].content
+    
+    prompt = f"""Evaluate blog content against editorial feedback (Pass/Fail):
+    Content: {content}
+    Feedback: {feedback}
+    Answer only Pass or Fail:"""
+    
+    with st.status("✅ Evaluating Quality..."):
+        response = llm.invoke(prompt)
+        verdict = response.content.strip().upper()
+        state["is_blog_ready"] = "Pass" if "PASS" in verdict else "Fail"
+        state["reviewed_content"].append(AIMessage(
+            content=f"Verdict: {response.content}"
+        ))
+        st.write(f"Final Verdict: **{state['is_blog_ready']}**")
+    return state
+
+def route_based_on_verdict(state: BlogState):
+    return "Pass" if state["is_blog_ready"] == "Pass" else "Fail"
+
+# Streamlit UI components
+st.title("AI Blog Generation Assistant")
+st.markdown("### Generate high-quality blog posts with AI-powered review process")
+
+topic = st.text_input("Enter your blog topic:", placeholder="Generative AI in Healthcare")
+generate_btn = st.button("Generate Blog Post")
+
+
+if generate_btn and topic:
+    st.session_state.graph = init_graph()
+    st.session_state.blog_state = BlogState(
+        topic=topic,
+        title="",
+        blog_content=[],
+        reviewed_content=[],
+        is_blog_ready=""
+    )
+    
+    # Execute the graph
+    final_state = st.session_state.graph.invoke(st.session_state.blog_state)
+    st.session_state.blog_state = final_state
+    
+    # Display results
+    st.success("Blog post generation complete!")
+    st.markdown("---")
+    st.subheader("Final Blog Post")
+    st.markdown(final_state["blog_content"][-1].content)
+    
+    st.markdown("---")
+    st.subheader("Quality Assurance Report")
+    st.write(final_state["reviewed_content"][-1].content)
+    # st.write(f"Final Verdict: {final_state['is_blog_ready']}")
+    
+
+elif generate_btn and not topic:
+    st.error("Please enter a blog topic to get started!")
+
+if st.session_state.blog_state:
+    with st.sidebar:
+        st.subheader("Generation Details")
+        st.write(f"**Topic:** {st.session_state.blog_state['topic']}")
+        st.write(f"**Status**: {'✅ Approved' if st.session_state.blog_state['is_blog_ready'] == 'Pass' else '❌ Needs Revision'}")
+        st.write(f"**Review Cycles**: {len(st.session_state.blog_state['reviewed_content']) - 1}")
+        
+        if st.button("Reset Session"):
+            st.session_state.clear()
+            st.rerun()

requirements.txt

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+langchain
+langgraph
+langchain_community
+langchain_core
+langchain_groq
+langchain_openai
+faiss_cpu
+streamlit