import streamlit as st
from crewai import Agent, Task, Crew
from langchain_google_genai import ChatGoogleGenerativeAI
from dotenv import load_dotenv
import os

# Load environment variables
load_dotenv()
GOOGLE_API_KEY = os.getenv('GOOGLE_API_KEY')

# Define LLM (check if there's a synchronous alternative or ensure async handling)
llm = ChatGoogleGenerativeAI(
    model="gemini-1.5-flash",
    verbose=True,
    temperature=0.5,
    google_api_key=GOOGLE_API_KEY
)

# Define Agents
planner = Agent(
    role="Content Planner",
    goal="Plan engaging and factually accurate content on {topic}",
    backstory="You're working on planning a blog article "
              "about the topic: {topic}."
              "You collect information that helps the "
              "audience learn something "
              "and make informed decisions. "
              "Your work is the basis for "
              "the Content Writer to write an article on this topic.",
    allow_delegation=False,
    verbose=True
)

writer = Agent(
    role="Content Writer",
    goal="Write a compelling and well-structured blog post on {topic}.",
    backstory="You're a writer who uses the content plan to create a detailed blog post. "
              "Ensure it aligns with SEO best practices and the brand's voice.",
    allow_delegation=False,
    verbose=True
)

editor = Agent(
    role="Editor",
    goal="Edit a given blog post to align with the writing style of the organization.",
    backstory="You are an editor who receives a blog post "
              "from the Content Writer. "
              "Your goal is to review the blog post "
              "to ensure that it follows journalistic best practices,"
              "provides balanced viewpoints "
              "when providing opinions or assertions, "
              "and also avoids major controversial topics "
              "or opinions when possible.",
    allow_delegation=False,
    verbose=True
)

# Define Tasks
plan = Task(
    description=(
        "1. Prioritize the latest trends, key players, "
        "and noteworthy news on {topic}.\n"
        "2. Identify the target audience, considering "
        "their interests and pain points.\n"
        "3. Develop a detailed content outline including "
        "an introduction, key points, and a call to action.\n"
        "4. Include SEO keywords and relevant data or sources."
    ),
    expected_output="A comprehensive content plan document "
                    "with an outline, audience analysis, "
                    "SEO keywords, and resources.",
    agent=planner,
)

write = Task(
    description=(
        "1. Use the content plan to craft a compelling "
        "blog post on {topic}.\n"
        "2. Incorporate SEO keywords naturally.\n"
        "3. Sections/Subtitles are properly named "
        "in an engaging manner.\n"
        "4. Ensure the post is structured with an "
        "engaging introduction, insightful body, "
        "and a summarizing conclusion.\n"
        "5. Proofread for grammatical errors and "
        "alignment with the brand's voice.\n"
    ),
    expected_output="A well-written blog post "
                    "in markdown format, ready for publication, "
                    "each section should have 2 or 3 paragraphs.",
    agent=writer,
)

edit = Task(
    description=("Proofread the given blog post for "
                 "grammatical errors and "
                 "alignment with the brand's voice."),
    expected_output="A well-written blog post in markdown format, "
                    "ready for publication, "
                    "each section should have 2 or 3 paragraphs.",
    agent=editor
)

# Define Crew
crew = Crew(
    agents=[planner, writer, editor],
    tasks=[plan, write, edit],
    verbose=2
)

# Streamlit App
def main():
    st.title("Content Creation Assistant")

    # Input for topic
    topic = st.text_input("Enter the topic for the blog post:")

    if st.button("Generate Content"):
        if topic:
            with st.spinner('Generating content...'):
                try:
                    result = crew.kickoff(inputs={"topic": topic})
                    st.markdown(result)
                except Exception as e:
                    st.error(f"An error occurred: {e}")
        else:
            st.error("Please enter a topic.")

if __name__ == "__main__":
    main()