diffusers prompt handle BREAK

CHANGELOG.md

@@ -23,6 +23,7 @@
   - Fix **DPM SDE** scheduler  
   - Better support for SD 1.5 **inpainting** models  
   - Add support for **OpenAI Consistency decoder VAE**
+  - Enhance prompt parsing with long prompts and support for *BREAK* keyword
   - Update to `diffusers==0.23.0`  
 - **Extra networks**  
   - Use multi-threading for 5x load speedup  

modules/processing_diffusers.py

@@ -183,6 +183,8 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
             negative_prompts = [negative_prompts]
         while len(negative_prompts) < len(prompts):
             negative_prompts.append(negative_prompts[-1])
+        while len(prompts) < len(negative_prompts):
+            prompts.append(prompts[-1])
         if type(prompts_2) is str:
             prompts_2 = [prompts_2]
         if type(prompts_2) is list:

modules/prompt_parser_diffusers.py

@@ -69,7 +69,7 @@ def encode_prompts(pipeline, prompts: list, negative_prompts: list, clip_skip: t
         negative_embeds = []
         negative_pooleds = []
         for i in range(len(prompts)):
-            prompt_embed, positive_pooled, negative_embed, negative_pooled = get_weighted_text_embeddings_sdxl(pipeline,prompts[i], negative_prompts[i], clip_skip)
+            prompt_embed, positive_pooled, negative_embed, negative_pooled = get_weighted_text_embeddings(pipeline,prompts[i], negative_prompts[i], clip_skip)
             prompt_embeds.append(prompt_embed)
             positive_pooleds.append(positive_pooled)
             negative_embeds.append(negative_embed)
@@ -113,6 +113,7 @@ def prepare_embedding_providers(pipe, clip_skip):
         embeddings_providers.append(embedding)
     return embeddings_providers
 
+
 def pad_to_same_length(embeds):
     try: #SDXL
         empty_embed = shared.sd_model.encode_prompt("")
@@ -127,7 +128,8 @@ def pad_to_same_length(embeds):
             embeds[i] = embed
     return embeds
 
-def get_weighted_text_embeddings_sdxl(pipe, prompt: str = "", neg_prompt: str = "", clip_skip: int = None):
+
+def get_weighted_text_embeddings(pipe, prompt: str = "", neg_prompt: str = "", clip_skip: int = None):
     prompt_2 = prompt.split("TE2:")[-1]
     neg_prompt_2 = neg_prompt.split("TE2:")[-1]
     prompt = prompt.split("TE2:")[0]
@@ -152,8 +154,20 @@ def get_weighted_text_embeddings_sdxl(pipe, prompt: str = "", neg_prompt: str =
     negative_pooled_prompt_embeds =  None
 
     for i in range(len(embedding_providers)):
-        embed, ptokens = embedding_providers[i].get_embeddings_for_weighted_prompt_fragments(text_batch=[positives[i]], fragment_weights_batch=[positive_weights[i]], device=pipe.device, should_return_tokens=True)
-        prompt_embeds.append(embed)
+        # add BREAK keyword that splits the prompt into multiple fragments
+        text = positives[i]
+        weights = positive_weights[i]
+        text.append('BREAK')
+        weights.append(-1)
+        provider_embed = []
+        while 'BREAK' in text:
+            pos = text.index('BREAK')
+            embed, ptokens = embedding_providers[i].get_embeddings_for_weighted_prompt_fragments(text_batch=[text[:pos]], fragment_weights_batch=[weights[:pos]], device=pipe.device, should_return_tokens=True)
+            provider_embed.append(embed)
+            text = text[pos+1:]
+            weights = weights[pos+1:]
+        prompt_embeds.append(torch.cat(provider_embed, dim=1))
+        # negative prompt has no keywords
         embed, ntokens = embedding_providers[i].get_embeddings_for_weighted_prompt_fragments(text_batch=[negatives[i]], fragment_weights_batch=[negative_weights[i]],device=pipe.device, should_return_tokens=True)
         negative_prompt_embeds.append(embed)