import pandas as pd
import json
import os


#class FewShotPosts:
 #   def __init__(self, file_path="data/processed_posts.json"):
  #      self.df = None
   #     self.unique_tags = None
    #    self.load_posts(file_path)


class FewShotPosts:
    def __init__(self, persona_name):
        """Dynamically load JSON based on the selected persona."""
        self.df = None
        self.unique_tags = None
        self.file_path = f"processed_{persona_name.lower()}_posts.json"

        if os.path.exists(self.file_path):  # Check if JSON exists
            self.load_posts(self.file_path)
        else:
            raise FileNotFoundError(f"Processed JSON file not found for persona: {persona_name}")


    def load_posts(self, file_path):
        with open(file_path, encoding="utf-8") as f:
            posts = json.load(f)
            self.df = pd.json_normalize(posts)
            self.df['length'] = self.df['line_count'].apply(self.categorize_length)
            # collect unique tags
            all_tags = self.df['tags'].apply(lambda x: x).sum()
            self.unique_tags = list(set(all_tags))

    def get_filtered_posts(self, length, language, tag):
        df_filtered = self.df[
            (self.df['tags'].apply(lambda tags: tag in tags)) &  # Tags contain 'Influencer'
            (self.df['language'] == language) &  # Language is 'English'
            (self.df['length'] == length)  # Line count is less than 5
        ]
        return df_filtered.to_dict(orient='records')

    def categorize_length(self, line_count):
        if line_count < 5:
            return "Short"
        elif 5 <= line_count <= 10:
            return "Medium"
        else:
            return "Long"

    def get_tags(self):
        return self.unique_tags


#if __name__ == "__main__":
 #   fs = FewShotPosts()
  #  # print(fs.get_tags())
   # posts = fs.get_filtered_posts("Short","English","Economy")
    #print(posts)