Method process

nodes.py:222–282

(self, model_name, precision, positive_prompt, negative_prompt, quantization='disabled', use_disk_cache=True, device="gpu", extender_args=None)

    def process(self, model_name, precision, positive_prompt, negative_prompt, quantization='disabled', use_disk_cache=True, device="gpu", extender_args=None):
        from .nodes_model_loading import LoadWanVideoT5TextEncoder
        pbar = ProgressBar(3)

        echoshot = True if "[1]" in positive_prompt else False

        # Handle prompt extension with in-memory cache
        orig_prompt = positive_prompt
        if extender_args is not None:
            extender_key = (orig_prompt, str(extender_args))
            if extender_key in _extender_cache:
                positive_prompt = _extender_cache[extender_key]
                log.info(f"Loaded extended prompt from in-memory cache: {positive_prompt}")
            else:
                from .qwen.qwen import QwenLoader, WanVideoPromptExtender
                log.info("Using WanVideoPromptExtender to process prompts")
                qwen, = QwenLoader().load(
                    extender_args["model"], 
                    load_device="main_device" if device == "gpu" else "cpu", 
                    precision=precision)
                positive_prompt, = WanVideoPromptExtender().generate(
                    qwen=qwen,
                    max_new_tokens=extender_args["max_new_tokens"],
                    prompt=orig_prompt,
                    device=device,
                    force_offload=False,
                    custom_system_prompt=extender_args["system_prompt"],
                    seed=extender_args["seed"]
                )
                log.info(f"Extended positive prompt: {positive_prompt}")
                _extender_cache[extender_key] = positive_prompt
                del qwen
            pbar.update(1)

        # Now check disk cache using the (possibly extended) prompt
        if use_disk_cache:
            context, context_null = get_cached_text_embeds(positive_prompt, negative_prompt)
            if context is not None and context_null is not None:
                return{
                    "prompt_embeds": context,
                    "negative_prompt_embeds": context_null,
                    "echoshot": echoshot,
                },{"prompt_embeds": context_null}, positive_prompt

        t5, = LoadWanVideoT5TextEncoder().loadmodel(model_name, precision, "main_device", quantization)
        pbar.update(1)

        prompt_embeds_dict, = WanVideoTextEncode().process(
            positive_prompt=positive_prompt,
            negative_prompt=negative_prompt,
            t5=t5,
            force_offload=False,
            model_to_offload=None,
            use_disk_cache=use_disk_cache,
            device=device
        )
        pbar.update(1)
        del t5