1 files changed, 28 insertions, 6 deletions
diff --git a/src/mcp_sd15/model_manager.py b/src/mcp_sd15/model_manager.py
index c2bd166..e87a813 100644
--- a/src/mcp_sd15/model_manager.py
+++ b/src/mcp_sd15/model_manager.py
@@ -31,9 +31,12 @@ class ModelManager:
 
     def text_to_image(self, request: TextToImageRequest, seed: int) -> Image.Image:
         width, height = request.size.dimensions
+        prompt_embeds, negative_prompt_embeds = self._embed_prompts(
+            request.positive_prompt, request.negative_prompt
+        )
         result = self.base(
-            prompt=request.positive_prompt,
-            negative_prompt=request.negative_prompt,
+            prompt_embeds=prompt_embeds,
+            negative_prompt_embeds=negative_prompt_embeds,
             width=width,
             height=height,
             num_inference_steps=self.config.generation.steps,
@@ -53,9 +56,12 @@ class ModelManager:
         else:
             control_image = self._openpose(image, full=request.control_mode == "openpose_full")
         pipeline = self._pipeline_for(str(request.control_mode), inpaint=False)
+        prompt_embeds, negative_prompt_embeds = self._embed_prompts(
+            request.positive_prompt, request.negative_prompt
+        )
         result = pipeline(
-            prompt=request.positive_prompt,
-            negative_prompt=request.negative_prompt,
+            prompt_embeds=prompt_embeds,
+            negative_prompt_embeds=negative_prompt_embeds,
             image=control_image,
             width=width,
             height=height,
@@ -78,9 +84,12 @@ class ModelManager:
         mask = mask.resize((width, height), Image.Resampling.NEAREST)
         control_image = self._inpaint_condition(image, mask)
         pipeline = self._pipeline_for("inpaint", inpaint=True)
+        prompt_embeds, negative_prompt_embeds = self._embed_prompts(
+            request.positive_prompt, request.negative_prompt
+        )
         result = pipeline(
-            prompt=request.positive_prompt,
-            negative_prompt=request.negative_prompt,
+            prompt_embeds=prompt_embeds,
+            negative_prompt_embeds=negative_prompt_embeds,
             image=image,
             mask_image=mask,
             control_image=control_image,
@@ -140,3 +149,16 @@ class ModelManager:
         if not images or len(images) != 1 or not isinstance(images[0], Image.Image):
             raise GenerationError("Diffusers did not return exactly one image")
         return images[0]
+
+    def _embed_prompts(self, positive: str, negative: str) -> tuple[Any, Any]:
+        """Generate prompt embeds via sd_embed to bypass the 77-token limit."""
+        from sd_embed.embedding_funcs import get_weighted_text_embeddings_sd15
+
+        prompt_embeds, neg_prompt_embeds = get_weighted_text_embeddings_sd15(
+            self.base,
+            prompt=positive,
+            neg_prompt=negative or "",
+            pad_last_block=self.config.generation.pad_last_block,
+            clip_skip=self.config.generation.clip_skip,
+        )
+        return prompt_embeds, neg_prompt_embeds