Storytelling chatbot updates (#1066)

* initial changes for gemini storybot

* storybot updates for gemini

* more storybot updates

* interim interruptible commit

* cleanup

* cleanup

* cleanup

* cleanup

examples/storytelling-chatbot/src/processors.py

@@ -37,8 +37,7 @@ class StoryPromptFrame(TextFrame):
 
 
 class StoryImageProcessor(FrameProcessor):
-    """
-    Processor for image prompt frames that will be sent to the FAL service.
+    """Processor for image prompt frames that will be sent to the FAL service.
 
     This processor is responsible for consuming frames of type `StoryImageFrame`.
     It processes them by passing it to the FAL service.
@@ -68,8 +67,7 @@ class StoryImageProcessor(FrameProcessor):
 
 
 class StoryProcessor(FrameProcessor):
-    """
-    Primary frame processor. It takes the frames generated by the LLM
+    """Primary frame processor. It takes the frames generated by the LLM
     and processes them into image prompts and story pages (sentences).
     For a clearer picture of how this works, reference prompts.py
 
@@ -97,44 +95,10 @@ class StoryProcessor(FrameProcessor):
             await self.push_frame(sounds["talking"])
 
         elif isinstance(frame, TextFrame):
-            # We want to look for sentence breaks in the text
-            # but since TextFrames are streamed from the LLM
-            # we need to keep a buffer of the text we've seen so far
+            # Add new text to the buffer
             self._text += frame.text
-
-            # IMAGE PROMPT
-            # Looking for: < [image prompt] > in the LLM response
-            # We prompted our LLM to add an image prompt in the response
-            # so we use regex matching to find it and yield a StoryImageFrame
-            if re.search(r"<.*?>", self._text):
-                if not re.search(r"<.*?>.*?>", self._text):
-                    # Pass any frames until we have a closing bracket
-                    # otherwise the image prompt will be passed to TTS
-                    pass
-                # Extract the image prompt from the text using regex
-                image_prompt = re.search(r"<(.*?)>", self._text).group(1)
-                # Remove the image prompt from the text
-                self._text = re.sub(r"<.*?>", "", self._text, count=1)
-                # Process the image prompt frame
-                await self.push_frame(StoryImageFrame(image_prompt))
-
-            # STORY PAGE
-            # Looking for: [break] in the LLM response
-            # We prompted our LLM to add a [break] after each sentence
-            # so we use regex matching to find it in the LLM response
-            if re.search(r".*\[[bB]reak\].*", self._text):
-                # Remove the [break] token from the text
-                # so it isn't spoken out loud by the TTS
-                self._text = re.sub(r"\[[bB]reak\]", "", self._text, flags=re.IGNORECASE)
-                self._text = self._text.replace("\n", " ")
-                if len(self._text) > 2:
-                    # Append the sentence to the story
-                    self._story.append(self._text)
-                    await self.push_frame(StoryPageFrame(self._text))
-                    # Assert that it's the LLMs turn, until we're finished
-                    await self.push_frame(DailyTransportMessageFrame(CUE_ASSISTANT_TURN))
-                # Clear the buffer
-                self._text = ""
+            # Process any complete patterns in the order they appear
+            await self.process_text_content()
 
         # End of a full LLM response
         # Driven by the prompt, the LLM should have asked the user for input
@@ -150,3 +114,38 @@ class StoryProcessor(FrameProcessor):
         # Anything that is not a TextFrame pass through
         else:
             await self.push_frame(frame)
+
+    async def process_text_content(self):
+        """Process text content in order of appearance, handling both image prompts and story breaks."""
+        while True:
+            # Find the first occurrence of each pattern
+            image_match = re.search(r"<(.*?)>", self._text)
+            break_match = re.search(r"\[[bB]reak\]", self._text)
+
+            # If neither pattern is found, we're done processing
+            if not image_match and not break_match:
+                break
+
+            # Find which pattern comes first in the text
+            image_pos = image_match.start() if image_match else float("inf")
+            break_pos = break_match.start() if break_match else float("inf")
+
+            if image_pos < break_pos:
+                # Process image prompt first
+                image_prompt = image_match.group(1)
+                # Remove the image prompt from the text
+                self._text = self._text[: image_match.start()] + self._text[image_match.end() :]
+                await self.push_frame(StoryImageFrame(image_prompt))
+            else:
+                # Process story break first
+                parts = re.split(r"\[[bB]reak\]", self._text, flags=re.IGNORECASE, maxsplit=1)
+                before_break = parts[0].replace("\n", " ").strip()
+
+                if len(before_break) > 2:
+                    self._story.append(before_break)
+                    await self.push_frame(StoryPageFrame(before_break))
+                    # await self.push_frame(sounds["ding"])
+                    await self.push_frame(DailyTransportMessageFrame(CUE_ASSISTANT_TURN))
+
+                # Keep the remainder (if any) in the buffer
+                self._text = parts[1].strip() if len(parts) > 1 else ""