Attachments.with_prompt

    Add a text prompt to accompany the file attachments.

USAGE
Attachments.with_prompt(prompt)

    This method enables the fluent interface for combining prompt text with file attachments,
    following Talk Box's chainable API design. The prompt provides context and instructions
    for how the AI should analyze or interact with the attached files.

Parameters

    prompt
        The text prompt to include with the file attachments. This should provide clear
        instructions about what you want the AI to do with the attached files.

Returns

    Attachments
        Returns self for method chaining.

Examples

    **Specific Analysis Request**

    ```python
    import talk_box as tb

    files = (
        tb.Attachments("financial_report.pdf")
        .with_prompt(
            "Extract the key financial metrics and identify any concerning trends "
            "in this quarterly report. Focus on revenue, profit margins, and cash flow."
        )
    )
    ```

    **Code Review with Specific Criteria**

    ```python
    code_review = tb.Attachments("src/main.py", "tests/test_main.py").with_prompt(
        "Review this Python code for:

” “1. Code quality and best practices” “2. Potential bugs or security issues” “3. Test coverage and completeness” “4. Performance optimization opportunities” ) ```

    **Creative Content Generation**

    ```python
    references = (
        tb.Attachments("brand_guide.pdf", "competitor_analysis.md")
        .with_prompt(
            "Based on our brand guidelines and competitor analysis, create a "
            "marketing strategy for our new product launch. Focus on differentiation "
            "and brand consistency."
        )
    )
    ```

    **Data Analysis with Context**

    ```python
    data_files = (
        tb.Attachments("sales_data.csv", "market_context.md")
        .with_prompt(
            "Analyze the sales data in the context of the market information provided. "
            "Identify trends, anomalies, and actionable insights for the sales team."
        )
    )
    ```

    **Multi-file Comparison**

    ```python
    comparison = (
        tb.Attachments("version1.py", "version2.py")
        .with_prompt(
            "Compare these two versions of the code and explain:

” “- What changed between versions” “- Whether the changes improve or degrade the code” “- Any potential issues introduced” ) ) ```

Notes

    - the prompt is combined with file content when sent to the AI model
    - clear, specific prompts lead to better analysis results
    - you can include formatting instructions (bullets, sections, etc.)
    - the prompt applies to all attached files collectively