Untitled

prompt = f"""
You are a data visualization expert. You have a 'template' array containing multiple sections:
- 'sectionTitle' (e.g., {sections})
- 'section_data': an array of widget objects (each with 'widget_title', 'widget_description', and 'graph_data')
- potentially other fields that describe additional charts or tables to generate.

**Task**:
1. Produce a broad textual overview (as **plain text**) about what the data represents and what each visualization (chart/table) will depict.
2. Then produce one single, self-contained **HTML** code block. This HTML must begin with:
   ```html
   <!DOCTYPE html>
   <html lang="en">
   ...
   </html>
and must contain the Plotly <script> plus all charts/tables described by each widget. After each chart, include a short explanation inside a <div> or <p>. 
3. Do not place the overview inside the HTML. The overview and the HTML must be returned separately. 
4. Use the exact markers below to separate them:
OVERVIEW_START + OVERVIEW_END for your broad textual overview.
HTML_START + HTML_END for your HTML section.
5.The final output should look like this (no extra commentary outside):
OVERVIEW_START
[Your plain text overview here]
OVERVIEW_END
HTML_START
```html
<!DOCTYPE html>
<html lang="en">
...
</html>
HTML_END
6.No additional commentary or text beyond these markers. Only what's inside them.
Below is the 'template' array you must process:

{template_data_str}

Now please generate only the final text in the above format. """


import re

def extract_overview_and_html(response_text):
    # Extract the overview
    overview = ""
    match_overview = re.search(r"OVERVIEW_START([\s\S]*?)OVERVIEW_END", response_text)
    if match_overview:
        overview = match_overview.group(1).strip()

    # Extract the HTML
    html_code = ""
    match_html = re.search(r"HTML_START([\s\S]*?)HTML_END", response_text)
    if match_html:
        html_code = match_html.group(1).strip()

    return overview, html_code

# Example usage after you've invoked your LLM:
# overview_section, html_section = extract_overview_and_html(response_text)
# print("OVERVIEW:\n", overview_section)
# print("\nHTML:\n", html_section)
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