app.py

from smolagents import CodeAgent, HfApiModel, load_tool, tool
import datetime
import requests
import pytz
import yaml
from tools.final_answer import FinalAnswerTool
from tools.blog_tools import generate_blog_section, improve_writing_style, check_readability, generate_seo_metadata
from tools.search_tools import get_search_tool
from Gradio_UI import GradioUI

@tool
def generate_blog_outline(topic: str) -> str:
    """Creates a structured outline for a blog post with a direct, practical approach
    Args:
        topic: The main topic for the blog post
    """
    try:
        # Research the topic first
        search_tool = get_search_tool(max_results=2)
        research = search_tool.forward(f"{topic} key aspects challenges solutions")
        
        # Create an outline based on research and expertise
        outline = f"# Blog Outline: {topic}\n\n"
        outline += "## 1. Introduction\n"
        outline += "- Context and why this matters\n"
        outline += "- My experience with this topic\n\n"
        outline += "## 2. Current State\n"
        outline += "- Key developments\n"
        outline += "- Market trends\n\n"
        outline += "## 3. Practical Insights\n"
        outline += "- Real-world applications\n"
        outline += "- Lessons from implementation\n\n"
        outline += "## 4. Looking Forward\n"
        outline += "- Next steps\n"
        outline += "- Recommendations\n\n"
        outline += "## 5. Key Takeaways\n"
        outline += "- Action items\n"
        outline += "- Discussion points\n"
        
        return outline
    except Exception as e:
        return f"Error generating outline: {str(e)}"

@tool
def suggest_blog_topics(main_theme: str) -> str:
    """Suggests related blog topics based on a theme, drawing from AI product expertise
    Args:
        main_theme: The primary theme or area of interest
    """
    try:
        # Research current trends
        search_tool = get_search_tool(max_results=2)
        research = search_tool.forward(f"{main_theme} latest developments challenges")
        
        # Generate topic suggestions based on research and expertise
        suggestions = f"# Blog Topic Ideas: {main_theme}\n\n"
        suggestions += "Based on current trends and my product experience:\n\n"
        suggestions += "1. Practical Implementation:\n"
        suggestions += "   - Building scalable {main_theme} solutions\n"
        suggestions += "   - Real-world challenges and solutions\n\n"
        suggestions += "2. Product Strategy:\n"
        suggestions += "   - Market fit and user needs\n"
        suggestions += "   - Integration approaches\n\n"
        suggestions += "3. Future Outlook:\n"
        suggestions += "   - Emerging trends\n"
        suggestions += "   - Potential impact\n\n"
        suggestions += "\nThese topics combine current research with hands-on insights."
        
        return suggestions
    except Exception as e:
        return f"Error suggesting topics: {str(e)}"

@tool
def get_current_time_in_timezone(timezone: str) -> str:
    """Fetches current local time in specified timezone
    Args:
        timezone: Valid timezone (e.g., 'America/New_York')
    """
    try:
        tz = pytz.timezone(timezone)
        local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S")
        return f"The current local time in {timezone} is: {local_time}"
    except Exception as e:
        return f"Error fetching time for timezone '{timezone}': {str(e)}"

@tool
def research_topic(query: str) -> str:
    """Searches the web for information about a specific topic and returns relevant sources
    Args:
        query: The topic to research
    """
    try:
        # Create a fresh instance for each search
        search_tool = get_search_tool(max_results=3)
        
        # Add focus on tech and AI product development
        enhanced_query = f"{query} AI product development"
        results = search_tool.forward(enhanced_query)
        
        # Format the results in your style
        response = f"Quick research on {query}:\n\n"
        response += results
        response += "\n\nNote: Always verify current info."
        
        return response
    except Exception as e:
        return f"Error performing research: {str(e)}"

final_answer = FinalAnswerTool()

model = HfApiModel(
    max_tokens=1000,  # Reduced from 2096 to stay within limits
    temperature=0.7,  # Slightly increased for more natural, conversational tone
    model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
    custom_role_conversions=None,
)

with open("prompts.yaml", 'r') as stream:
    prompt_templates = yaml.safe_load(stream)

with open("style_guide.yaml", 'r') as stream:
    style_guide = yaml.safe_load(stream)

agent = CodeAgent(
    model=model,
    tools=[
        final_answer,
        generate_blog_outline,
        suggest_blog_topics,
        get_current_time_in_timezone,
        generate_blog_section,
        improve_writing_style,
        check_readability,
        generate_seo_metadata,
        research_topic
    ],
    max_steps=15,
    verbosity_level=1,
    grammar=None,
    planning_interval=None,
    name="Joséphine's Blog Assistant",
    description="""An AI writing assistant that matches Joséphine's style:
    - Direct and conversational tone
    - Product and AI expertise focus
    - Clear, practical insights
    - Natural, professional voice
    - Gets to the point quickly"""
)

GradioUI(agent).launch()