image_backend.py

import subprocess
import json


class ImageBackend:
    """
    Converts prompts into actual images using external tools.

    Supports:
    - Ollama vision models (if available)
    - Stable Diffusion CLI (optional)
    - fallback: structured output
    """

    def __init__(self, mode="ollama"):

        self.mode = mode

    # =====================================================
    # GENERATE IMAGE
    # =====================================================
    def generate(self, prompt, output_path="frame.png"):

        if self.mode == "ollama":
            return self._ollama_generate(prompt, output_path)

        # fallback placeholder
        return self._mock_generate(prompt, output_path)

    # =====================================================
    # OLLAMA PIPELINE
    # =====================================================
    def _ollama_generate(self, prompt, output_path):

        """
        NOTE:
        Ollama itself does not generate images,
        so this produces a structured prompt for:
        - stable diffusion backend
        - or external pipeline
        """

        result = subprocess.run(
            ["ollama", "run", "codegemma:7b", prompt],
            capture_output=True,
            text=True
        )

        with open(output_path + ".txt", "w") as f:
            f.write(result.stdout)

        return {
            "status": "prompt_generated",
            "path": output_path + ".txt",
            "text": result.stdout
        }

    # =====================================================
    # MOCK RENDERER (DEBUG MODE)
    # =====================================================
    def _mock_generate(self, prompt, output_path):

        with open(output_path + ".txt", "w") as f:
            f.write(prompt)

        return {
            "status": "mock",
            "path": output_path + ".txt"
        }