Debugging the Articleizer: LLM APIs, Regex, and Rate Limits

import os
import sys
import json
import yaml
import re
from datetime import datetime
import getpass
from pathlib import Path
import google.generativeai as genai
import argparse # NEW: Import argparse for command-line flags

# --- CONFIGURATION ---
OUTPUT_DIR = "/home/mike/repos/MikeLev.in/_posts"
ARTICLE_FILENAME = "article.txt"
PROMPT_FILENAME = "editing_prompt.txt"
PROMPT_PLACEHOLDER = "[INSERT FULL ARTICLE]"
# --- NEW CACHE CONFIG ---
INSTRUCTIONS_CACHE_FILE = "instructions.json" # NEW: Define a filename for the cache
# --- NEW KEY MANAGEMENT CONFIG ---
CONFIG_DIR = Path.home() / ".config" / "articleizer"
API_KEY_FILE = CONFIG_DIR / "api_key.txt"
# --------------------------------

def get_api_key():
    """
    Gets the API key by first checking a local config file, and if not found,
    securely prompting the user and offering to save it.
    """
    if API_KEY_FILE.is_file():
        print(f"Reading API key from {API_KEY_FILE}...")
        return API_KEY_FILE.read_text().strip()

    print("Google API Key not found.")
    print("Please go to https://aistudio.google.com/app/apikey to get one.")
    key = getpass.getpass("Enter your Google API Key: ")

    save_key_choice = input(f"Do you want to save this key to {API_KEY_FILE} for future use? (y/n): ").lower()
    if save_key_choice == 'y':
        try:
            CONFIG_DIR.mkdir(parents=True, exist_ok=True)
            API_KEY_FILE.write_text(key)
            API_KEY_FILE.chmod(0o600)
            print(f"✅ Key saved securely.")
        except Exception as e:
            print(f"⚠️ Could not save API key. Error: {e}")
    return key

def create_jekyll_post(article_content, instructions):
    print("Formatting final Jekyll post...")

    editing_instr = instructions.get("editing_instructions", {})
    analysis_content = instructions.get("book_analysis_content", {})
    yaml_updates = editing_instr.get("yaml_updates", {})

    # 1. Build the Jekyll YAML front matter
    new_yaml_data = {
        'title': yaml_updates.get("title"),
        'permalink': yaml_updates.get("permalink"),
        'description': analysis_content.get("authors_imprint"),
        'meta_description': yaml_updates.get("description"),
        'meta_keywords': yaml_updates.get("keywords"),
        'layout': 'post',
        'sort_order': 1
    }
    final_yaml_block = f"---\n{yaml.dump(new_yaml_data, Dumper=yaml.SafeDumper, sort_keys=False, default_flow_style=False)}---"

    # 2. Get the raw article body and add a header
    article_body = article_content.strip()
    article_body = f"## Technical Journal Entry Begins\n\n{article_body}"

    # 3. Insert subheadings
    subheadings = editing_instr.get("insert_subheadings", [])
    for item in reversed(subheadings):
        snippet = item.get("after_text_snippet", "")
        subheading = item.get("subheading", "## Missing Subheading")
        if not snippet:
            print(f"Warning: Skipping subheading '{subheading}' due to missing snippet.")
            continue

        # Clean the snippet: remove leading/trailing whitespace and ellipses.
        clean_snippet = snippet.strip().strip('...')
        # Create the regex pattern from the CLEANED snippet.
        pattern_text = re.escape(clean_snippet).replace(r'\\ ', r'\\s+')

        match = re.search(pattern_text, article_body, re.IGNORECASE)
        if match:
            insertion_point = article_body.find('\n', match.end())
            if insertion_point == -1:
                insertion_point = len(article_body)
            article_body = (
                article_body[:insertion_point] +
                f"\n\n{subheading}" +
                article_body[insertion_point:]
            )
        else:
            print(f"Warning: Snippet not found for subheading '{subheading}': '{snippet}'")

    # 4. Prepend the "Curious Reader" intro
    prepend_text = editing_instr.get("prepend_to_article_body", "")
    if prepend_text:
        intro_section = f"## Setting the Stage: Context for the Curious Book Reader\n\n{prepend_text}\n\n---"
        article_body = f"{intro_section}\n\n{article_body}"

    # 5. Build the Book Analysis section
    analysis_markdown = "\n## Book Analysis\n"
    if 'ai_editorial_take' in analysis_content:
        analysis_markdown += f"\n### Ai Editorial Take\n{analysis_content['ai_editorial_take']}\n"
    for key, value in analysis_content.items():
        if key in ['authors_imprint', 'ai_editorial_take']:
            continue
        title = key.replace('_', ' ').title()
        analysis_markdown += f"\n### {title}\n"
        if isinstance(value, list):
            for item in value:
                if isinstance(item, dict):
                    analysis_markdown += f"* **Title Option:** {item.get('title', 'N/A')}\n"
                    analysis_markdown += f"  * **Filename:** `{item.get('filename', 'N/A')}`\n"
                    analysis_markdown += f"  * **Rationale:** {item.get('rationale', 'N/A')}\n"
                else:
                    analysis_markdown += f"- {item}\n"
        elif isinstance(value, dict):
                for sub_key, sub_value in value.items():
                    analysis_markdown += f"- **{sub_key.replace('_', ' ').title()}:**\n"
                    if isinstance(sub_value, list):
                        for point in sub_value:
                            analysis_markdown += f"  - {point}\n"
                    else:
                        analysis_markdown += f"  - {sub_value}\n"
        else:
            analysis_markdown += f"{value}\n"

    # 6. Assemble final document
    final_content = f"{final_yaml_block}\n\n{article_body}\n\n---\n{analysis_markdown}"

    # 7. Generate filename and save
    current_date = datetime.now().strftime('%Y-%m-%d')
    slug = "untitled-article"
    title_brainstorm = analysis_content.get("title_brainstorm", [])
    if title_brainstorm and title_brainstorm[0].get("filename"):
        slug = os.path.splitext(title_brainstorm[0]["filename"])[0]

    output_filename = f"{current_date}-{slug}.md"
    output_path = os.path.join(OUTPUT_DIR, output_filename)
    os.makedirs(OUTPUT_DIR, exist_ok=True)

    with open(output_path, 'w', encoding='utf-8') as f:
        f.write(final_content)

    print(f"✨ Success! Article saved to: {output_path}")

def main():
    # NEW: Set up command-line argument parsing
    parser = argparse.ArgumentParser(description="Process an article with the Gemini API and format it for Jekyll.")
    parser.add_argument(
        '-l', '--local',
        action='store_true',
        help=f"Use local '{INSTRUCTIONS_CACHE_FILE}' cache instead of calling the API."
    )
    args = parser.parse_args()

    # Step 1: Load the base article text (needed in both modes)
    if not os.path.exists(ARTICLE_FILENAME):
        print(f"Error: Article file '{ARTICLE_FILENAME}' not found.")
        return
    with open(ARTICLE_FILENAME, 'r', encoding='utf-8') as f:
        article_text = f.read()

    instructions = None

    # NEW: Main logic branches based on the --local flag
    if args.local:
        print(f"Attempting to use local cache file: {INSTRUCTIONS_CACHE_FILE}")
        if not os.path.exists(INSTRUCTIONS_CACHE_FILE):
            print(f"Error: Cache file not found. Run without --local to create it.")
            return
        try:
            with open(INSTRUCTIONS_CACHE_FILE, 'r', encoding='utf-8') as f:
                instructions = json.load(f)
            print("Successfully loaded instructions from local cache.")
        except json.JSONDecodeError:
            print("Error: Could not parse the local instructions cache file. It may be corrupt.")
            return
    else:
        # This block contains the original API call logic
        api_key = get_api_key()
        if not api_key:
            print("API Key not provided. Exiting.")
            return
        genai.configure(api_key=api_key)

        if not os.path.exists(PROMPT_FILENAME):
            print(f"Error: Prompt file '{PROMPT_FILENAME}' not found.")
            return
        with open(PROMPT_FILENAME, 'r', encoding='utf-8') as f:
            prompt_template = f.read()

        full_prompt = prompt_template.replace(PROMPT_PLACEHOLDER, article_text)

        print("Calling the Gemini API directly... (This may take a moment)")
        try:
            model = genai.GenerativeModel('gemini-2.5-pro') # Make sure this model name is correct
            response = model.generate_content(full_prompt)
            gemini_output = response.text
            print("Successfully received response from API.")
        except Exception as e:
            print(f"\nAn error occurred while calling the API: {e}")
            return

        try:
            json_match = re.search(r'```json\s*([\s\S]*?)\s*```', gemini_output)
            json_str = json_match.group(1) if json_match else gemini_output
            instructions = json.loads(json_str)
            print("Successfully parsed JSON instructions.")
            
            # NEW: Save the successful instructions to the cache file
            with open(INSTRUCTIONS_CACHE_FILE, 'w', encoding='utf-8') as f:
                json.dump(instructions, f, indent=4)
            print(f"✅ Instructions saved to '{INSTRUCTIONS_CACHE_FILE}' for future use.")

        except json.JSONDecodeError:
            print("\nError: Failed to parse JSON from API output.")
            print("--- API Raw Output ---\n" + gemini_output)
            return

    # Final step: If we have instructions (from API or cache), format the post.
    if instructions:
        create_jekyll_post(article_text, instructions)

if __name__ == '__main__':
    main()

import os
import sys
import json
import yaml
import re
from datetime import datetime
import getpass
from pathlib import Path
import google.generativeai as genai
import argparse

# --- CONFIGURATION ---
OUTPUT_DIR = "/home/mike/repos/MikeLev.in/_posts"
ARTICLE_FILENAME = "article.txt"
PROMPT_FILENAME = "editing_prompt.txt"
PROMPT_PLACEHOLDER = "[INSERT FULL ARTICLE]"
INSTRUCTIONS_CACHE_FILE = "instructions.json"
CONFIG_DIR = Path.home() / ".config" / "articleizer"
API_KEY_FILE = CONFIG_DIR / "api_key.txt"
# --------------------------------

def get_api_key():
    """
    Gets the API key by first checking a local config file, and if not found,
    securely prompting the user and offering to save it.
    """
    if API_KEY_FILE.is_file():
        print(f"Reading API key from {API_KEY_FILE}...")
        return API_KEY_FILE.read_text().strip()

    print("Google API Key not found.")
    print("Please go to https://aistudio.google.com/app/apikey to get one.")
    key = getpass.getpass("Enter your Google API Key: ")

    save_key_choice = input(f"Do you want to save this key to {API_KEY_FILE} for future use? (y/n): ").lower()
    if save_key_choice == 'y':
        try:
            CONFIG_DIR.mkdir(parents=True, exist_ok=True)
            API_KEY_FILE.write_text(key)
            API_KEY_FILE.chmod(0o600)
            print(f"✅ Key saved securely.")
        except Exception as e:
            print(f"⚠️ Could not save API key. Error: {e}")
    return key

def create_jekyll_post(article_content, instructions):
    """
    Assembles and writes a Jekyll post file from the article content and
    structured AI-generated instructions.
    """
    print("Formatting final Jekyll post...")

    editing_instr = instructions.get("editing_instructions", {})
    analysis_content = instructions.get("book_analysis_content", {})
    yaml_updates = editing_instr.get("yaml_updates", {})

    # 1. Build the Jekyll YAML front matter
    new_yaml_data = {
        'title': yaml_updates.get("title"),
        'permalink': yaml_updates.get("permalink"),
        'description': analysis_content.get("authors_imprint"),
        'meta_description': yaml_updates.get("description"),
        'meta_keywords': yaml_updates.get("keywords"),
        'layout': 'post',
        'sort_order': 1
    }
    final_yaml_block = f"---\n{yaml.dump(new_yaml_data, Dumper=yaml.SafeDumper, sort_keys=False, default_flow_style=False)}---"

    # 2. Get the raw article body and add a header
    article_body = article_content.strip()
    article_body = f"## Technical Journal Entry Begins\n\n{article_body}"

    # 3. Insert subheadings
    subheadings = editing_instr.get("insert_subheadings", [])
    for item in reversed(subheadings):
        snippet = item.get("after_text_snippet", "")
        subheading = item.get("subheading", "## Missing Subheading")
        if not snippet:
            print(f"Warning: Skipping subheading '{subheading}' due to missing snippet.")
            continue

        # --- REFINED PATTERN MATCHING ---
        # Normalize snippet: remove ellipses and excess whitespace.
        clean_snippet = snippet.strip().strip('...')
        # Create a regex pattern where any whitespace sequence (\s+) can
        # occur between the escaped words of the snippet.
        words = re.escape(clean_snippet).split()
        pattern_text = r'\s+'.join(words)
        # ------------------------------------

        # Search with IGNORECASE and DOTALL (to handle multiline) flags.
        match = re.search(pattern_text, article_body, re.IGNORECASE | re.DOTALL)
        if match:
            # Find the next newline character *after* the matched snippet.
            insertion_point = article_body.find('\n', match.end())
            if insertion_point == -1: # If it's the end of the file
                insertion_point = len(article_body)
            article_body = (
                article_body[:insertion_point] +
                f"\n\n{subheading}" +
                article_body[insertion_point:]
            )
        else:
            print(f"Warning: Snippet not found for subheading '{subheading}': '{snippet}'")

    # 4. Prepend the "Curious Reader" intro
    prepend_text = editing_instr.get("prepend_to_article_body", "")
    if prepend_text:
        intro_section = f"## Setting the Stage: Context for the Curious Book Reader\n\n{prepend_text}\n\n---"
        article_body = f"{intro_section}\n\n{article_body}"

    # 5. Build the Book Analysis section
    analysis_markdown = "\n## Book Analysis\n"
    if 'ai_editorial_take' in analysis_content:
        analysis_markdown += f"\n### Ai Editorial Take\n{analysis_content['ai_editorial_take']}\n"
    for key, value in analysis_content.items():
        if key in ['authors_imprint', 'ai_editorial_take']:
            continue
        title = key.replace('_', ' ').title()
        analysis_markdown += f"\n### {title}\n"
        if isinstance(value, list):
            for item in value:
                if isinstance(item, dict):
                    analysis_markdown += f"* **Title Option:** {item.get('title', 'N/A')}\n"
                    analysis_markdown += f"  * **Filename:** `{item.get('filename', 'N/A')}`\n"
                    analysis_markdown += f"  * **Rationale:** {item.get('rationale', 'N/A')}\n"
                else:
                    analysis_markdown += f"- {item}\n"
        elif isinstance(value, dict):
                for sub_key, sub_value in value.items():
                    analysis_markdown += f"- **{sub_key.replace('_', ' ').title()}:**\n"
                    if isinstance(sub_value, list):
                        for point in sub_value:
                            analysis_markdown += f"  - {point}\n"
                    else:
                        analysis_markdown += f"  - {sub_value}\n"
        else:
            analysis_markdown += f"{value}\n"

    # 6. Assemble final document
    final_content = f"{final_yaml_block}\n\n{article_body}\n\n---\n{analysis_markdown}"

    # 7. Generate filename and save
    current_date = datetime.now().strftime('%Y-%m-%d')
    slug = "untitled-article"
    title_brainstorm = analysis_content.get("title_brainstorm", [])
    if title_brainstorm and title_brainstorm[0].get("filename"):
        slug = os.path.splitext(title_brainstorm[0]["filename"])[0]

    output_filename = f"{current_date}-{slug}.md"
    output_path = os.path.join(OUTPUT_DIR, output_filename)
    os.makedirs(OUTPUT_DIR, exist_ok=True)

    with open(output_path, 'w', encoding='utf-8') as f:
        f.write(final_content)

    print(f"✨ Success! Article saved to: {output_path}")

def main():
    """
    Main execution block. Parses arguments, calls the API or loads from cache,
    and then triggers the post creation.
    """
    parser = argparse.ArgumentParser(description="Process an article with the Gemini API and format it for Jekyll.")
    parser.add_argument(
        '-l', '--local',
        action='store_true',
        help=f"Use local '{INSTRUCTIONS_CACHE_FILE}' cache instead of calling the API."
    )
    args = parser.parse_args()

    if not os.path.exists(ARTICLE_FILENAME):
        print(f"Error: Article file '{ARTICLE_FILENAME}' not found.")
        return
    with open(ARTICLE_FILENAME, 'r', encoding='utf-8') as f:
        article_text = f.read()

    instructions = None

    if args.local:
        print(f"Attempting to use local cache file: {INSTRUCTIONS_CACHE_FILE}")
        if not os.path.exists(INSTRUCTIONS_CACHE_FILE):
            print(f"Error: Cache file not found. Run without --local to create it.")
            return
        try:
            with open(INSTRUCTIONS_CACHE_FILE, 'r', encoding='utf-8') as f:
                instructions = json.load(f)
            print("Successfully loaded instructions from local cache.")
        except json.JSONDecodeError:
            print("Error: Could not parse the local instructions cache file. It may be corrupt.")
            return
    else:
        api_key = get_api_key()
        if not api_key:
            print("API Key not provided. Exiting.")
            return
        genai.configure(api_key=api_key)

        if not os.path.exists(PROMPT_FILENAME):
            print(f"Error: Prompt file '{PROMPT_FILENAME}' not found.")
            return
        with open(PROMPT_FILENAME, 'r', encoding='utf-8') as f:
            prompt_template = f.read()

        full_prompt = prompt_template.replace(PROMPT_PLACEHOLDER, article_text)

        print("Calling the Gemini API directly... (This may take a moment)")
        try:
            model = genai.GenerativeModel('gemini-1.5-pro') # Updated model name
            response = model.generate_content(full_prompt)
            gemini_output = response.text
            print("Successfully received response from API.")
        except Exception as e:
            print(f"\nAn error occurred while calling the API: {e}")
            return

        try:
            # Be more robust in finding the JSON block
            json_match = re.search(r'```json\s*([\s\S]*?)\s*```', gemini_output)
            json_str = json_match.group(1) if json_match else gemini_output
            instructions = json.loads(json_str)
            print("Successfully parsed JSON instructions.")
            
            with open(INSTRUCTIONS_CACHE_FILE, 'w', encoding='utf-8') as f:
                json.dump(instructions, f, indent=4)
            print(f"✅ Instructions saved to '{INSTRUCTIONS_CACHE_FILE}' for future use.")

        except json.JSONDecodeError:
            print("\nError: Failed to parse JSON from API output.")
            print("--- API Raw Output ---\n" + gemini_output)
            return

    if instructions:
        create_jekyll_post(article_text, instructions)

if __name__ == '__main__':
    main()

            model = genai.GenerativeModel('gemini-2.5-pro') # Updated model name

import os
import sys
import json
import yaml
import re
from datetime import datetime
import getpass
from pathlib import Path
import google.generativeai as genai
import argparse

# --- CONFIGURATION ---
OUTPUT_DIR = "/home/mike/repos/MikeLev.in/_posts"
ARTICLE_FILENAME = "article.txt"
PROMPT_FILENAME = "editing_prompt.txt"
PROMPT_PLACEHOLDER = "[INSERT FULL ARTICLE]"
INSTRUCTIONS_CACHE_FILE = "instructions.json"
CONFIG_DIR = Path.home() / ".config" / "articleizer"
API_KEY_FILE = CONFIG_DIR / "api_key.txt"
# --------------------------------

def get_api_key():
    """
    Gets the API key by first checking a local config file, and if not found,
    securely prompting the user and offering to save it.
    """
    if API_KEY_FILE.is_file():
        print(f"Reading API key from {API_KEY_FILE}...")
        return API_KEY_FILE.read_text().strip()

    print("Google API Key not found.")
    print("Please go to https://aistudio.google.com/app/apikey to get one.")
    key = getpass.getpass("Enter your Google API Key: ")

    save_key_choice = input(f"Do you want to save this key to {API_KEY_FILE} for future use? (y/n): ").lower().strip()
    if save_key_choice == 'y':
        try:
            CONFIG_DIR.mkdir(parents=True, exist_ok=True)
            API_KEY_FILE.write_text(key)
            API_KEY_FILE.chmod(0o600)
            print(f"✅ Key saved securely.")
        except Exception as e:
            print(f"⚠️ Could not save API key. Error: {e}")
    return key

def create_jekyll_post(article_content, instructions):
    """
    Assembles and writes a Jekyll post file from the article content and
    structured AI-generated instructions.
    """
    print("Formatting final Jekyll post...")

    editing_instr = instructions.get("editing_instructions", {})
    analysis_content = instructions.get("book_analysis_content", {})
    yaml_updates = editing_instr.get("yaml_updates", {})

    # 1. Build the Jekyll YAML front matter
    new_yaml_data = {
        'title': yaml_updates.get("title"),
        'permalink': yaml_updates.get("permalink"),
        'description': analysis_content.get("authors_imprint"),
        'meta_description': yaml_updates.get("description"),
        'meta_keywords': yaml_updates.get("keywords"),
        'layout': 'post',
        'sort_order': 1
    }
    final_yaml_block = f"---\n{yaml.dump(new_yaml_data, Dumper=yaml.SafeDumper, sort_keys=False, default_flow_style=False)}---"

    # 2. Get the raw article body and add a header
    article_body = article_content.strip()
    article_body = f"## Technical Journal Entry Begins\n\n{article_body}"

    # 3. Insert subheadings
    subheadings = editing_instr.get("insert_subheadings", [])
    for item in reversed(subheadings):
        snippet = item.get("after_text_snippet", "")
        subheading = item.get("subheading", "## Missing Subheading")
        if not snippet:
            print(f"Warning: Skipping subheading '{subheading}' due to missing snippet.")
            continue

        # --- FINAL, MORE ROBUST PATTERN MATCHING ---
        # Normalize the snippet by removing non-alphanumeric characters and splitting into words.
        words = re.findall(r'\w+', snippet.lower())
        # Create a flexible regex pattern that looks for these words in order,
        # separated by any characters or whitespace (non-greedy).
        pattern_text = r'.*?'.join(re.escape(word) for word in words)
        # -------------------------------------------

        # Search with IGNORECASE and DOTALL flags to match across lines.
        match = re.search(pattern_text, article_body, re.IGNORECASE | re.DOTALL)
        if match:
            insertion_point = article_body.find('\n', match.end())
            if insertion_point == -1:
                insertion_point = len(article_body)
            article_body = (
                article_body[:insertion_point] +
                f"\n\n{subheading}" +
                article_body[insertion_point:]
            )
        else:
            print(f"Warning: Snippet not found for subheading '{subheading}': '{snippet}'")

    # 4. Prepend the "Curious Reader" intro
    prepend_text = editing_instr.get("prepend_to_article_body", "")
    if prepend_text:
        intro_section = f"## Setting the Stage: Context for the Curious Book Reader\n\n{prepend_text}\n\n---"
        article_body = f"{intro_section}\n\n{article_body}"

    # 5. Build the Book Analysis section
    analysis_markdown = "\n## Book Analysis\n"
    if 'ai_editorial_take' in analysis_content:
        analysis_markdown += f"\n### Ai Editorial Take\n{analysis_content['ai_editorial_take']}\n"
    for key, value in analysis_content.items():
        if key in ['authors_imprint', 'ai_editorial_take']:
            continue
        title = key.replace('_', ' ').title()
        analysis_markdown += f"\n### {title}\n"
        if isinstance(value, list):
            for item in value:
                if isinstance(item, dict):
                    analysis_markdown += f"* **Title Option:** {item.get('title', 'N/A')}\n"
                    analysis_markdown += f"  * **Filename:** `{item.get('filename', 'N/A')}`\n"
                    analysis_markdown += f"  * **Rationale:** {item.get('rationale', 'N/A')}\n"
                else:
                    analysis_markdown += f"- {item}\n"
        elif isinstance(value, dict):
            for sub_key, sub_value in value.items():
                analysis_markdown += f"- **{sub_key.replace('_', ' ').title()}:**\n"
                if isinstance(sub_value, list):
                    for point in sub_value:
                        analysis_markdown += f"  - {point}\n"
                else:
                    analysis_markdown += f"  - {sub_value}\n"
        else:
            analysis_markdown += f"{value}\n"

    # 6. Assemble final document
    final_content = f"{final_yaml_block}\n\n{article_body}\n\n---\n{analysis_markdown}"

    # 7. Generate filename and save
    current_date = datetime.now().strftime('%Y-%m-%d')
    slug = "untitled-article"
    title_brainstorm = analysis_content.get("title_brainstorm", [])
    if title_brainstorm and title_brainstorm[0].get("filename"):
        slug = os.path.splitext(title_brainstorm[0]["filename"])[0]

    output_filename = f"{current_date}-{slug}.md"
    output_path = os.path.join(OUTPUT_DIR, output_filename)
    os.makedirs(OUTPUT_DIR, exist_ok=True)

    with open(output_path, 'w', encoding='utf-8') as f:
        f.write(final_content)

    print(f"✨ Success! Article saved to: {output_path}")

def main():
    """
    Main execution block. Parses arguments, calls the API or loads from cache,
    and then triggers the post creation.
    """
    parser = argparse.ArgumentParser(description="Process an article with the Gemini API and format it for Jekyll.")
    parser.add_argument(
        '-l', '--local',
        action='store_true',
        help=f"Use local '{INSTRUCTIONS_CACHE_FILE}' cache instead of calling the API."
    )
    args = parser.parse_args()

    if not os.path.exists(ARTICLE_FILENAME):
        print(f"Error: Article file '{ARTICLE_FILENAME}' not found.")
        return
    with open(ARTICLE_FILENAME, 'r', encoding='utf-8') as f:
        article_text = f.read()

    instructions = None

    if args.local:
        print(f"Attempting to use local cache file: {INSTRUCTIONS_CACHE_FILE}")
        if not os.path.exists(INSTRUCTIONS_CACHE_FILE):
            print(f"Error: Cache file not found. Run without --local to create it.")
            return
        try:
            with open(INSTRUCTIONS_CACHE_FILE, 'r', encoding='utf-8') as f:
                instructions = json.load(f)
            print("Successfully loaded instructions from local cache.")
        except json.JSONDecodeError:
            print("Error: Could not parse the local instructions cache file. It may be corrupt.")
            return
    else:
        api_key = get_api_key()
        if not api_key:
            print("API Key not provided. Exiting.")
            return
        genai.configure(api_key=api_key)

        if not os.path.exists(PROMPT_FILENAME):
            print(f"Error: Prompt file '{PROMPT_FILENAME}' not found.")
            return
        with open(PROMPT_FILENAME, 'r', encoding='utf-8') as f:
            prompt_template = f.read()

        full_prompt = prompt_template.replace(PROMPT_PLACEHOLDER, article_text)

        print("Calling the Gemini API directly... (This may take a moment)")
        try:
            # Corrected the model name to the generally available one.
            model = genai.GenerativeModel('gemini-1.5-pro-latest')
            response = model.generate_content(full_prompt)
            gemini_output = response.text
            print("Successfully received response from API.")
        except Exception as e:
            print(f"\nAn error occurred while calling the API: {e}")
            return

        try:
            json_match = re.search(r'```json\s*([\s\S]*?)\s*```', gemini_output)
            json_str = json_match.group(1) if json_match else gemini_output
            instructions = json.loads(json_str)
            print("Successfully parsed JSON instructions.")
            
            with open(INSTRUCTIONS_CACHE_FILE, 'w', encoding='utf-8') as f:
                json.dump(instructions, f, indent=4)
            print(f"✅ Instructions saved to '{INSTRUCTIONS_CACHE_FILE}' for future use.")

        except json.JSONDecodeError:
            print("\nError: Failed to parse JSON from API output.")
            print("--- API Raw Output ---\n" + gemini_output)
            return

    if instructions:
        create_jekyll_post(article_text, instructions)

if __name__ == '__main__':
    main()

import os
import sys
import json
import yaml
import re
from datetime import datetime
import getpass
from pathlib import Path
import google.generativeai as genai
import argparse
import time # NEW: Import time for the retry delay

# --- CONFIGURATION ---
OUTPUT_DIR = "/home/mike/repos/MikeLev.in/_posts"
ARTICLE_FILENAME = "article.txt"
PROMPT_FILENAME = "editing_prompt.txt"
PROMPT_PLACEHOLDER = "[INSERT FULL ARTICLE]"
INSTRUCTIONS_CACHE_FILE = "instructions.json"
CONFIG_DIR = Path.home() / ".config" / "articleizer"
API_KEY_FILE = CONFIG_DIR / "api_key.txt"
# --------------------------------

def get_api_key():
    """
    Gets the API key by first checking a local config file, and if not found,
    securely prompting the user and offering to save it.
    """
    if API_KEY_FILE.is_file():
        print(f"Reading API key from {API_KEY_FILE}...")
        return API_KEY_FILE.read_text().strip()

    print("Google API Key not found.")
    print("Please go to https://aistudio.google.com/app/apikey to get one.")
    key = getpass.getpass("Enter your Google API Key: ")

    save_key_choice = input(f"Do you want to save this key to {API_KEY_FILE} for future use? (y/n): ").lower().strip()
    if save_key_choice == 'y':
        try:
            CONFIG_DIR.mkdir(parents=True, exist_ok=True)
            API_KEY_FILE.write_text(key)
            API_KEY_FILE.chmod(0o600)
            print(f"✅ Key saved securely.")
        except Exception as e:
            print(f"⚠️ Could not save API key. Error: {e}")
    return key

def create_jekyll_post(article_content, instructions):
    """
    Assembles and writes a Jekyll post file from the article content and
    structured AI-generated instructions.
    """
    print("Formatting final Jekyll post...")

    editing_instr = instructions.get("editing_instructions", {})
    analysis_content = instructions.get("book_analysis_content", {})
    yaml_updates = editing_instr.get("yaml_updates", {})

    new_yaml_data = {
        'title': yaml_updates.get("title"),
        'permalink': yaml_updates.get("permalink"),
        'description': analysis_content.get("authors_imprint"),
        'meta_description': yaml_updates.get("description"),
        'meta_keywords': yaml_updates.get("keywords"),
        'layout': 'post',
        'sort_order': 1
    }
    final_yaml_block = f"---\n{yaml.dump(new_yaml_data, Dumper=yaml.SafeDumper, sort_keys=False, default_flow_style=False)}---"

    article_body = article_content.strip()
    article_body = f"## Technical Journal Entry Begins\n\n{article_body}"

    subheadings = editing_instr.get("insert_subheadings", [])
    for item in reversed(subheadings):
        snippet = item.get("after_text_snippet", "")
        subheading = item.get("subheading", "## Missing Subheading")
        if not snippet:
            print(f"Warning: Skipping subheading '{subheading}' due to missing snippet.")
            continue

        words = re.findall(r'\w+', snippet.lower())
        pattern_text = r'.*?'.join(re.escape(word) for word in words)

        match = re.search(pattern_text, article_body, re.IGNORECASE | re.DOTALL)
        if match:
            insertion_point = article_body.find('\n', match.end())
            if insertion_point == -1:
                insertion_point = len(article_body)
            article_body = (
                article_body[:insertion_point] +
                f"\n\n{subheading}" +
                article_body[insertion_point:]
            )
        else:
            print(f"Warning: Snippet not found for subheading '{subheading}': '{snippet}'")

    prepend_text = editing_instr.get("prepend_to_article_body", "")
    if prepend_text:
        intro_section = f"## Setting the Stage: Context for the Curious Book Reader\n\n{prepend_text}\n\n---"
        article_body = f"{intro_section}\n\n{article_body}"

    analysis_markdown = "\n## Book Analysis\n"
    if 'ai_editorial_take' in analysis_content:
        analysis_markdown += f"\n### Ai Editorial Take\n{analysis_content['ai_editorial_take']}\n"
    for key, value in analysis_content.items():
        if key in ['authors_imprint', 'ai_editorial_take']:
            continue
        title = key.replace('_', ' ').title()
        analysis_markdown += f"\n### {title}\n"
        if isinstance(value, list):
            for item in value:
                if isinstance(item, dict):
                    analysis_markdown += f"* **Title Option:** {item.get('title', 'N/A')}\n"
                    analysis_markdown += f"  * **Filename:** `{item.get('filename', 'N/A')}`\n"
                    analysis_markdown += f"  * **Rationale:** {item.get('rationale', 'N/A')}\n"
                else:
                    analysis_markdown += f"- {item}\n"
        elif isinstance(value, dict):
            for sub_key, sub_value in value.items():
                analysis_markdown += f"- **{sub_key.replace('_', ' ').title()}:**\n"
                if isinstance(sub_value, list):
                    for point in sub_value:
                        analysis_markdown += f"  - {point}\n"
                else:
                    analysis_markdown += f"  - {sub_value}\n"
        else:
            analysis_markdown += f"{value}\n"

    final_content = f"{final_yaml_block}\n\n{article_body}\n\n---\n{analysis_markdown}"

    current_date = datetime.now().strftime('%Y-%m-%d')
    slug = "untitled-article"
    title_brainstorm = analysis_content.get("title_brainstorm", [])
    if title_brainstorm and title_brainstorm[0].get("filename"):
        slug = os.path.splitext(title_brainstorm[0]["filename"])[0]

    output_filename = f"{current_date}-{slug}.md"
    output_path = os.path.join(OUTPUT_DIR, output_filename)
    os.makedirs(OUTPUT_DIR, exist_ok=True)

    with open(output_path, 'w', encoding='utf-8') as f:
        f.write(final_content)

    print(f"✨ Success! Article saved to: {output_path}")

def main():
    parser = argparse.ArgumentParser(description="Process an article with the Gemini API and format it for Jekyll.")
    parser.add_argument(
        '-l', '--local',
        action='store_true',
        help=f"Use local '{INSTRUCTIONS_CACHE_FILE}' cache instead of calling the API."
    )
    args = parser.parse_args()

    if not os.path.exists(ARTICLE_FILENAME):
        print(f"Error: Article file '{ARTICLE_FILENAME}' not found.")
        return
    with open(ARTICLE_FILENAME, 'r', encoding='utf-8') as f:
        article_text = f.read()

    instructions = None

    if args.local:
        print(f"Attempting to use local cache file: {INSTRUCTIONS_CACHE_FILE}")
        if not os.path.exists(INSTRUCTIONS_CACHE_FILE):
            print(f"Error: Cache file not found. Run without --local to create it.")
            return
        try:
            with open(INSTRUCTIONS_CACHE_FILE, 'r', encoding='utf-8') as f:
                instructions = json.load(f)
            print("Successfully loaded instructions from local cache.")
        except json.JSONDecodeError:
            print("Error: Could not parse the local instructions cache file. It may be corrupt.")
            return
    else:
        api_key = get_api_key()
        if not api_key:
            print("API Key not provided. Exiting.")
            return
        genai.configure(api_key=api_key)

        if not os.path.exists(PROMPT_FILENAME):
            print(f"Error: Prompt file '{PROMPT_FILENAME}' not found.")
            return
        with open(PROMPT_FILENAME, 'r', encoding='utf-8') as f:
            prompt_template = f.read()

        full_prompt = prompt_template.replace(PROMPT_PLACEHOLDER, article_text)

        print("Calling the Gemini API directly...")
        max_retries = 5
        retry_delay = 2
        for attempt in range(max_retries):
            try:
                # Use a free-tier compatible model.
                model = genai.GenerativeModel('gemini-1.5-flash-latest')
                response = model.generate_content(full_prompt)
                gemini_output = response.text
                print("Successfully received response from API.")
                
                json_match = re.search(r'```json\s*([\s\S]*?)\s*```', gemini_output)
                json_str = json_match.group(1) if json_match else gemini_output
                instructions = json.loads(json_str)
                print("Successfully parsed JSON instructions.")
                
                with open(INSTRUCTIONS_CACHE_FILE, 'w', encoding='utf-8') as f:
                    json.dump(instructions, f, indent=4)
                print(f"✅ Instructions saved to '{INSTRUCTIONS_CACHE_FILE}' for future use.")
                break  # Exit the loop on success
            
            except Exception as e:
                # Check for the specific 429 error.
                if "429" in str(e) and "Quota exceeded" in str(e):
                    print(f"Rate limit hit. Retrying in {retry_delay} seconds... (Attempt {attempt + 1}/{max_retries})")
                    time.sleep(retry_delay)
                    retry_delay *= 2  # Exponential backoff
                else:
                    print(f"\nAn error occurred while calling the API: {e}")
                    if 'gemini_output' in locals():
                        print("--- API Raw Output ---\n" + gemini_output)
                    return
        else: # This block runs if the loop completes without a break
            print("Error: Max retries exceeded. Failed to get a successful response from the API.")
            return

    if instructions:
        create_jekyll_post(article_text, instructions)

if __name__ == '__main__':
    main()