added fuzz example

src/examples/starter-apps/telestrator/telestrator-fuzz.py

@@ -0,0 +1,210 @@
+import asyncio
+import aiohttp
+import logging
+import os
+import random
+from typing import AsyncGenerator
+
+from dailyai.pipeline.frames import Frame, LLMMessagesQueueFrame, RequestVideoImageFrame, LLMResponseEndFrame, TelestratorImageFrame, ImageFrame, TextFrame
+from dailyai.pipeline.pipeline import Pipeline
+from dailyai.pipeline.frame_processor import FrameProcessor
+from dailyai.services.daily_transport_service import DailyTransportService
+from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
+from dailyai.services.open_ai_services import OpenAILLMService, OpenAIVisionService
+from dailyai.services.fal_ai_services import FalImageGenService
+from dailyai.services.deepgram_ai_services import DeepgramTTSService
+from dailyai.services.ai_services import FrameLogger
+from dailyai.pipeline.aggregators import (
+    LLMAssistantContextAggregator,
+    LLMUserContextAggregator,
+    LLMFullResponseAggregator
+)
+from dailyai.pipeline.frames import VideoImageFrame, VisionFrame
+from examples.support.runner import configure
+
+logging.basicConfig(format=f"%(levelno)s %(asctime)s %(message)s")
+logger = logging.getLogger("dailyai")
+logger.setLevel(logging.DEBUG)
+
+narrators = [{"voice_id": "wDRBdcyPzQOCeq51IxW5",
+              "prompt": "Describe the image in one sentence."},
+             {"voice_id": "M3bAX0o3Ptb2l6XqwQJV",
+              "prompt": "Describe the image in one sentence, in the style of John Oliver's Last Week Tonight show."},
+             {"voice_id": "lJm5d2ZZ3UE4qYOxl2t7",
+              "prompt": "Describe the image in one sentence, in the style of Oprah Winfrey."},
+             {"voice_id": "7SNUlQ8GAbnZxRO9CKOt",
+              "prompt": "Describe the image in one sentence, in the style of a royal pronouncement by the Queen of England."},
+             {"voice_id": "gvpBhHjzfd7M2WedYVUI",
+              "prompt": "Describe the image in one sentence, in the style of Captain Picard from Star Trek."},
+             {"voice_id": "bnyr1EF3snReVXauGBNn",
+              "prompt": "Describe the image in one sentence, in the style of Maya Angelou."}]
+
+# random.shuffle(narrators)
+print(f"$$$ narrators: {narrators}")
+narrator = {"narrator": narrators[0]}
+
+
+class TranslationProcessor(FrameProcessor):
+    def __init__(self, in_language, out_language):
+        self._in_language = in_language
+        self._out_language = out_language
+
+    async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
+        if isinstance(frame, TextFrame):
+            context = [
+                {
+                    "role": "system",
+                    "content": f"You will be provided with a sentence in {self._in_language}, and your task is to translate it into {self._out_language}.",
+                },
+                {"role": "user", "content": frame.text},
+            ]
+
+            yield LLMMessagesQueueFrame(context)
+        else:
+            yield frame
+
+
+class NarratorShuffle(FrameProcessor):
+    def __init__(self, narrator, narrators):
+        self._narrator = narrator
+        self._narrators = narrators
+        self._i = 0
+
+    async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
+        if isinstance(frame, (ImageFrame, TelestratorImageFrame)):
+            self._i += 1
+            if self._i >= len(self._narrators):
+                print(f"### shuffling narrators")
+                random.shuffle(self._narrators)
+                self._i = 0
+
+            self._narrator["narrator"] = self._narrators[self._i]
+            print(f"### new narrator is {self._narrator}")
+        yield frame
+
+
+class VideoImageFrameProcessor(FrameProcessor):
+    def __init__(self, narrator):
+        self._narrator = narrator
+
+    async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
+        if isinstance(frame, (VideoImageFrame, TelestratorImageFrame)):
+            yield VisionFrame(self._narrator["narrator"]["prompt"], frame.image)
+        else:
+            yield frame
+
+
+class ImageRefresher(FrameProcessor):
+    async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
+        if isinstance(frame, LLMResponseEndFrame):
+            yield RequestVideoImageFrame(participantId=None)
+            yield frame
+        else:
+            yield frame
+
+
+class TelestratorImageWrapper(FrameProcessor):
+    async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
+        if isinstance(frame, ImageFrame):
+            yield TelestratorImageFrame(None, frame.image)
+        else:
+            yield frame
+
+
+async def main(room_url: str, token):
+    async with aiohttp.ClientSession() as session:
+        transport = DailyTransportService(
+            room_url,
+            token,
+            "Respond bot",
+            duration_minutes=5,
+            start_transcription=True,
+            mic_enabled=True,
+            mic_sample_rate=16000,
+            camera_enabled=True,
+            camera_width=1024,
+            camera_height=576,
+            vad_enabled=False,
+            receive_video=True,
+            receive_video_fps=0
+        )
+
+        tts = ElevenLabsTTSService(
+            aiohttp_session=session,
+            api_key=os.getenv("ELEVENLABS_API_KEY"),
+            narrator=narrator,
+            aggregate_sentences=False
+        )
+
+        llm = OpenAILLMService(
+            api_key=os.getenv("OPENAI_CHATGPT_API_KEY"),
+            model="gpt-4-turbo-preview")
+
+        vs = OpenAIVisionService(api_key=os.getenv("OPENAI_CHATGPT_API_KEY"))
+        vifp = VideoImageFrameProcessor(narrator)
+        ir = ImageRefresher()
+        img = FalImageGenService(
+            image_size="1024x1024",
+            aiohttp_session=session,
+            key_id=os.getenv("FAL_KEY_ID"),
+            key_secret=os.getenv("FAL_KEY_SECRET"),
+        )
+        tiw = TelestratorImageWrapper()
+        lfra = LLMFullResponseAggregator()
+        lfra1 = LLMFullResponseAggregator()
+        lfra2 = LLMFullResponseAggregator()
+        lfra3 = LLMFullResponseAggregator()
+        lfra4 = LLMFullResponseAggregator()
+        fl0 = FrameLogger("@@@ About to describe")
+        fl1 = FrameLogger("!!! About to image gen")
+        f4 = FrameLogger("((( partway through )))")
+        f5 = FrameLogger("!!! f5")
+        ns = NarratorShuffle(narrator, narrators)
+        t1 = TranslationProcessor("English", "Spanish")
+        t2 = TranslationProcessor("Spanish", "German")
+        t3 = TranslationProcessor("German", "Japanese")
+        t4 = TranslationProcessor("Japanese", "English")
+        pipeline = Pipeline(
+            processors=[
+                fl0,
+                vifp,
+                vs,
+                lfra,
+                tts,
+                f4,
+                t1,
+                llm,
+                lfra1,
+                f5,
+                tts,
+
+                t2,
+                llm,
+                lfra2,
+                tts,
+                t3,
+                llm,
+                lfra3,
+                tts,
+                t4,
+                llm,
+                lfra4,
+                tts,
+                fl1,
+                img,
+                tiw,
+            ],
+        )
+
+        @transport.event_handler("on_first_other_participant_joined")
+        async def on_first_other_participant_joined(transport):
+            await pipeline.queue_frames([RequestVideoImageFrame(participantId=None)])
+
+        transport.transcription_settings["extra"]["endpointing"] = True
+        transport.transcription_settings["extra"]["punctuate"] = True
+        await transport.run(pipeline)
+
+
+if __name__ == "__main__":
+    (url, token) = configure()
+    asyncio.run(main(url, token))

src/examples/starter-apps/telestrator/telestrator-haiku.py

@@ -0,0 +1,191 @@
+import asyncio
+import aiohttp
+import logging
+import os
+import random
+from typing import AsyncGenerator
+
+from dailyai.pipeline.frames import Frame, LLMMessagesQueueFrame, RequestVideoImageFrame, LLMResponseEndFrame, TelestratorImageFrame, ImageFrame, TextFrame
+from dailyai.pipeline.pipeline import Pipeline
+from dailyai.pipeline.frame_processor import FrameProcessor
+from dailyai.services.daily_transport_service import DailyTransportService
+from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
+from dailyai.services.open_ai_services import OpenAILLMService, OpenAIVisionService
+from dailyai.services.fal_ai_services import FalImageGenService
+from dailyai.services.deepgram_ai_services import DeepgramTTSService
+from dailyai.services.ai_services import FrameLogger
+from dailyai.pipeline.aggregators import (
+    LLMAssistantContextAggregator,
+    LLMUserContextAggregator,
+    LLMFullResponseAggregator
+)
+from dailyai.pipeline.frames import VideoImageFrame, VisionFrame
+from examples.support.runner import configure
+
+logging.basicConfig(format=f"%(levelno)s %(asctime)s %(message)s")
+logger = logging.getLogger("dailyai")
+logger.setLevel(logging.DEBUG)
+
+narrators = [{"voice_id": "wDRBdcyPzQOCeq51IxW5",
+              "prompt": "Describe the image in a haiku."},
+             {"voice_id": "M3bAX0o3Ptb2l6XqwQJV",
+              "prompt": "Describe the image in one sentence, in the style of John Oliver's Last Week Tonight show."},
+             {"voice_id": "lJm5d2ZZ3UE4qYOxl2t7",
+              "prompt": "Describe the image in one sentence, in the style of Oprah Winfrey."},
+             {"voice_id": "7SNUlQ8GAbnZxRO9CKOt",
+              "prompt": "Describe the image in one sentence, in the style of a royal pronouncement by the Queen of England."},
+             {"voice_id": "gvpBhHjzfd7M2WedYVUI",
+              "prompt": "Describe the image in one sentence, in the style of Captain Picard from Star Trek."},
+             {"voice_id": "bnyr1EF3snReVXauGBNn",
+              "prompt": "Describe the image in one sentence, in the style of Maya Angelou."}]
+
+# random.shuffle(narrators)
+print(f"$$$ narrators: {narrators}")
+narrator = {"narrator": narrators[0]}
+
+
+class TranslationProcessor(FrameProcessor):
+    def __init__(self, in_language, out_language):
+        self._in_language = in_language
+        self._out_language = out_language
+
+    async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
+        if isinstance(frame, TextFrame):
+            context = [
+                {
+                    "role": "system",
+                    "content": f"You will be provided with a sentence in {self._in_language}, and your task is to translate it into {self._out_language}.",
+                },
+                {"role": "user", "content": frame.text},
+            ]
+
+            yield LLMMessagesQueueFrame(context)
+        else:
+            yield frame
+
+
+class NarratorShuffle(FrameProcessor):
+    def __init__(self, narrator, narrators):
+        self._narrator = narrator
+        self._narrators = narrators
+        self._i = 0
+
+    async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
+        if isinstance(frame, (ImageFrame, TelestratorImageFrame)):
+            self._i += 1
+            if self._i >= len(self._narrators):
+                print(f"### shuffling narrators")
+                random.shuffle(self._narrators)
+                self._i = 0
+
+            self._narrator["narrator"] = self._narrators[self._i]
+            print(f"### new narrator is {self._narrator}")
+        yield frame
+
+
+class VideoImageFrameProcessor(FrameProcessor):
+    def __init__(self, narrator):
+        self._narrator = narrator
+
+    async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
+        if isinstance(frame, (VideoImageFrame, TelestratorImageFrame)):
+            yield VisionFrame(self._narrator["narrator"]["prompt"], frame.image)
+        else:
+            yield frame
+
+
+class ImageRefresher(FrameProcessor):
+    async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
+        if isinstance(frame, LLMResponseEndFrame):
+            yield RequestVideoImageFrame(participantId=None)
+            yield frame
+        else:
+            yield frame
+
+
+class TelestratorImageWrapper(FrameProcessor):
+    async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
+        if isinstance(frame, ImageFrame):
+            yield TelestratorImageFrame(None, frame.image)
+        else:
+            yield frame
+
+
+async def main(room_url: str, token):
+    async with aiohttp.ClientSession() as session:
+        transport = DailyTransportService(
+            room_url,
+            token,
+            "Respond bot",
+            duration_minutes=5,
+            start_transcription=True,
+            mic_enabled=True,
+            mic_sample_rate=16000,
+            camera_enabled=True,
+            camera_width=1024,
+            camera_height=1024,
+            vad_enabled=False,
+            receive_video=True,
+            receive_video_fps=0
+        )
+
+        tts = ElevenLabsTTSService(
+            aiohttp_session=session,
+            api_key=os.getenv("ELEVENLABS_API_KEY"),
+            narrator=narrator,
+            aggregate_sentences=False
+        )
+
+        llm = OpenAILLMService(
+            api_key=os.getenv("OPENAI_CHATGPT_API_KEY"),
+            model="gpt-4-turbo-preview")
+
+        vs = OpenAIVisionService(api_key=os.getenv("OPENAI_CHATGPT_API_KEY"))
+        vifp = VideoImageFrameProcessor(narrator)
+        ir = ImageRefresher()
+        img = FalImageGenService(
+            image_size="1024x1024",
+            aiohttp_session=session,
+            key_id=os.getenv("FAL_KEY_ID"),
+            key_secret=os.getenv("FAL_KEY_SECRET"),
+        )
+        tiw = TelestratorImageWrapper()
+        lfra = LLMFullResponseAggregator()
+        lfra1 = LLMFullResponseAggregator()
+        lfra2 = LLMFullResponseAggregator()
+        lfra3 = LLMFullResponseAggregator()
+        lfra4 = LLMFullResponseAggregator()
+        fl0 = FrameLogger("@@@ About to describe")
+        fl1 = FrameLogger("!!! About to image gen")
+        f4 = FrameLogger("((( partway through )))")
+        f5 = FrameLogger("!!! f5")
+        ns = NarratorShuffle(narrator, narrators)
+        t1 = TranslationProcessor("English", "Spanish")
+        t2 = TranslationProcessor("Spanish", "German")
+        t3 = TranslationProcessor("German", "Japanese")
+        t4 = TranslationProcessor("Japanese", "English")
+        pipeline = Pipeline(
+            processors=[
+                fl0,
+                vifp,
+                vs,
+                lfra,
+                tts,
+                fl1,
+                img,
+                tiw,
+            ],
+        )
+
+        @transport.event_handler("on_first_other_participant_joined")
+        async def on_first_other_participant_joined(transport):
+            await pipeline.queue_frames([RequestVideoImageFrame(participantId=None)])
+
+        transport.transcription_settings["extra"]["endpointing"] = True
+        transport.transcription_settings["extra"]["punctuate"] = True
+        await transport.run(pipeline)
+
+
+if __name__ == "__main__":
+    (url, token) = configure()
+    asyncio.run(main(url, token))

src/examples/starter-apps/telestrator/telestrator-wordcount.py

@@ -0,0 +1,191 @@
+import asyncio
+import aiohttp
+import logging
+import os
+import random
+from typing import AsyncGenerator
+
+from dailyai.pipeline.frames import Frame, LLMMessagesQueueFrame, RequestVideoImageFrame, LLMResponseEndFrame, TelestratorImageFrame, ImageFrame, TextFrame
+from dailyai.pipeline.pipeline import Pipeline
+from dailyai.pipeline.frame_processor import FrameProcessor
+from dailyai.services.daily_transport_service import DailyTransportService
+from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
+from dailyai.services.open_ai_services import OpenAILLMService, OpenAIVisionService
+from dailyai.services.fal_ai_services import FalImageGenService
+from dailyai.services.deepgram_ai_services import DeepgramTTSService
+from dailyai.services.ai_services import FrameLogger
+from dailyai.pipeline.aggregators import (
+    LLMAssistantContextAggregator,
+    LLMUserContextAggregator,
+    LLMFullResponseAggregator
+)
+from dailyai.pipeline.frames import VideoImageFrame, VisionFrame
+from examples.support.runner import configure
+
+logging.basicConfig(format=f"%(levelno)s %(asctime)s %(message)s")
+logger = logging.getLogger("dailyai")
+logger.setLevel(logging.DEBUG)
+
+narrators = [{"voice_id": "wDRBdcyPzQOCeq51IxW5",
+              "prompt": "Describe the image in nine words."},
+             {"voice_id": "M3bAX0o3Ptb2l6XqwQJV",
+              "prompt": "Describe the image in one sentence, in the style of John Oliver's Last Week Tonight show."},
+             {"voice_id": "lJm5d2ZZ3UE4qYOxl2t7",
+              "prompt": "Describe the image in one sentence, in the style of Oprah Winfrey."},
+             {"voice_id": "7SNUlQ8GAbnZxRO9CKOt",
+              "prompt": "Describe the image in one sentence, in the style of a royal pronouncement by the Queen of England."},
+             {"voice_id": "gvpBhHjzfd7M2WedYVUI",
+              "prompt": "Describe the image in one sentence, in the style of Captain Picard from Star Trek."},
+             {"voice_id": "bnyr1EF3snReVXauGBNn",
+              "prompt": "Describe the image in one sentence, in the style of Maya Angelou."}]
+
+# random.shuffle(narrators)
+print(f"$$$ narrators: {narrators}")
+narrator = {"narrator": narrators[0]}
+
+
+class TranslationProcessor(FrameProcessor):
+    def __init__(self, in_language, out_language):
+        self._in_language = in_language
+        self._out_language = out_language
+
+    async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
+        if isinstance(frame, TextFrame):
+            context = [
+                {
+                    "role": "system",
+                    "content": f"You will be provided with a sentence in {self._in_language}, and your task is to translate it into {self._out_language}.",
+                },
+                {"role": "user", "content": frame.text},
+            ]
+
+            yield LLMMessagesQueueFrame(context)
+        else:
+            yield frame
+
+
+class NarratorShuffle(FrameProcessor):
+    def __init__(self, narrator, narrators):
+        self._narrator = narrator
+        self._narrators = narrators
+        self._i = 0
+
+    async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
+        if isinstance(frame, (ImageFrame, TelestratorImageFrame)):
+            self._i += 1
+            if self._i >= len(self._narrators):
+                print(f"### shuffling narrators")
+                random.shuffle(self._narrators)
+                self._i = 0
+
+            self._narrator["narrator"] = self._narrators[self._i]
+            print(f"### new narrator is {self._narrator}")
+        yield frame
+
+
+class VideoImageFrameProcessor(FrameProcessor):
+    def __init__(self, narrator):
+        self._narrator = narrator
+
+    async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
+        if isinstance(frame, (VideoImageFrame, TelestratorImageFrame)):
+            yield VisionFrame(self._narrator["narrator"]["prompt"], frame.image)
+        else:
+            yield frame
+
+
+class ImageRefresher(FrameProcessor):
+    async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
+        if isinstance(frame, LLMResponseEndFrame):
+            yield RequestVideoImageFrame(participantId=None)
+            yield frame
+        else:
+            yield frame
+
+
+class TelestratorImageWrapper(FrameProcessor):
+    async def process_frame(self, frame: Frame) -> AsyncGenerator[Frame, None]:
+        if isinstance(frame, ImageFrame):
+            yield TelestratorImageFrame(None, frame.image)
+        else:
+            yield frame
+
+
+async def main(room_url: str, token):
+    async with aiohttp.ClientSession() as session:
+        transport = DailyTransportService(
+            room_url,
+            token,
+            "Respond bot",
+            duration_minutes=5,
+            start_transcription=True,
+            mic_enabled=True,
+            mic_sample_rate=16000,
+            camera_enabled=True,
+            camera_width=1024,
+            camera_height=1024,
+            vad_enabled=False,
+            receive_video=True,
+            receive_video_fps=0
+        )
+
+        tts = ElevenLabsTTSService(
+            aiohttp_session=session,
+            api_key=os.getenv("ELEVENLABS_API_KEY"),
+            narrator=narrator,
+            aggregate_sentences=False
+        )
+
+        llm = OpenAILLMService(
+            api_key=os.getenv("OPENAI_CHATGPT_API_KEY"),
+            model="gpt-4-turbo-preview")
+
+        vs = OpenAIVisionService(api_key=os.getenv("OPENAI_CHATGPT_API_KEY"))
+        vifp = VideoImageFrameProcessor(narrator)
+        ir = ImageRefresher()
+        img = FalImageGenService(
+            image_size="1024x1024",
+            aiohttp_session=session,
+            key_id=os.getenv("FAL_KEY_ID"),
+            key_secret=os.getenv("FAL_KEY_SECRET"),
+        )
+        tiw = TelestratorImageWrapper()
+        lfra = LLMFullResponseAggregator()
+        lfra1 = LLMFullResponseAggregator()
+        lfra2 = LLMFullResponseAggregator()
+        lfra3 = LLMFullResponseAggregator()
+        lfra4 = LLMFullResponseAggregator()
+        fl0 = FrameLogger("@@@ About to describe")
+        fl1 = FrameLogger("!!! About to image gen")
+        f4 = FrameLogger("((( partway through )))")
+        f5 = FrameLogger("!!! f5")
+        ns = NarratorShuffle(narrator, narrators)
+        t1 = TranslationProcessor("English", "Spanish")
+        t2 = TranslationProcessor("Spanish", "German")
+        t3 = TranslationProcessor("German", "Japanese")
+        t4 = TranslationProcessor("Japanese", "English")
+        pipeline = Pipeline(
+            processors=[
+                fl0,
+                vifp,
+                vs,
+                lfra,
+                tts,
+                fl1,
+                img,
+                tiw,
+            ],
+        )
+
+        @transport.event_handler("on_first_other_participant_joined")
+        async def on_first_other_participant_joined(transport):
+            await pipeline.queue_frames([RequestVideoImageFrame(participantId=None)])
+
+        transport.transcription_settings["extra"]["endpointing"] = True
+        transport.transcription_settings["extra"]["punctuate"] = True
+        await transport.run(pipeline)
+
+
+if __name__ == "__main__":
+    (url, token) = configure()
+    asyncio.run(main(url, token))

src/examples/starter-apps/telestrator/telestrator.py

@@ -26,37 +26,18 @@ logging.basicConfig(format=f"%(levelno)s %(asctime)s %(message)s")
 logger = logging.getLogger("dailyai")
 logger.setLevel(logging.DEBUG)
 
-narrators = [
-    {
-        "voice_id": "wDRBdcyPzQOCeq51IxW5",
-        "prompt": "Describe the image in one sentence, in the style of David Attenborough."
-    },
-    {
-        "voice_id": "M3bAX0o3Ptb2l6XqwQJV",
-        "prompt": "Describe the image in one sentence, in the style of John Oliver's Last Week Tonight show."
-    },
-    {
-        "voice_id": "lJm5d2ZZ3UE4qYOxl2t7",
-        "prompt": "Describe the image in one sentence, in the style of Oprah Winfrey."
-    },
-    {
-        "voice_id": "7SNUlQ8GAbnZxRO9CKOt",
-        "prompt": "Describe the image in one sentence, in the style of a royal pronouncement by the Queen of England."
-    },
-    {
-        "voice_id": "PWEz02ggFiibL6P5PKRx",
-        "prompt": "Describe the image in one sentence, in the style of Kanye West."
-    },
-    {
-        "voice_id": "gvpBhHjzfd7M2WedYVUI",
-        "prompt": "Describe the image in one sentence, in the style of Captain Picard from Star Trek."
-    },
-    {
-        "voice_id": "bnyr1EF3snReVXauGBNn",
-        "prompt": "Describe the image in one sentence, in the style of Maya Angelou."
-
-    }
-]
+narrators = [{"voice_id": "wDRBdcyPzQOCeq51IxW5",
+              "prompt": "Describe the image in one sentence, in the style of David Attenborough."},
+             {"voice_id": "M3bAX0o3Ptb2l6XqwQJV",
+              "prompt": "Describe the image in one sentence, in the style of John Oliver's Last Week Tonight show."},
+             {"voice_id": "lJm5d2ZZ3UE4qYOxl2t7",
+              "prompt": "Describe the image in one sentence, in the style of Oprah Winfrey."},
+             {"voice_id": "7SNUlQ8GAbnZxRO9CKOt",
+              "prompt": "Describe the image in one sentence, in the style of a royal pronouncement by the Queen of England."},
+             {"voice_id": "gvpBhHjzfd7M2WedYVUI",
+              "prompt": "Describe the image in one sentence, in the style of Captain Picard from Star Trek."},
+             {"voice_id": "bnyr1EF3snReVXauGBNn",
+              "prompt": "Describe the image in one sentence, in the style of Maya Angelou."}]
 
 random.shuffle(narrators)
 print(f"$$$ narrators: {narrators}")