some sample and readme updates

README.md

@@ -35,7 +35,7 @@ pip install path_to_this_repo
 Tou can run the simple sample like so:
 
 ```
-python src/samples/simple-sample/simple-sample.py -u your_room_url -k your_daily_api_key
+python src/samples/theoretical-to-real/01-say-one-thing.py -u <url of your Daily meeting> -k <your Daily API Key>
 ```
 
 Note that the sample uses Azure's TTS and LLM services. You'll need to set the following environment variables for the sample to work:

src/samples/deprecated/README.md

@@ -0,0 +1 @@
+These samples need to be updated! Don't rely on them.

src/samples/theoretical-to-real/01-say-one-thing.py

@@ -36,6 +36,7 @@ async def main(room_url):
     async def on_participant_joined(transport, participant):
         if participant["info"]["isLocal"]:
             return
+
         async for audio in audio_generator:
             transport.output_queue.put(QueueFrame(FrameType.AUDIO_FRAME, audio))
 
@@ -52,6 +53,6 @@ if __name__ == "__main__":
         "-u", "--url", type=str, required=True, help="URL of the Daily room to join"
     )
 
-    args: argparse.Namespace = parser.parse_args()
+    args, unknown = parser.parse_known_args()
 
     asyncio.run(main(args.url))

src/samples/theoretical-to-real/05-queued.py

@@ -1,124 +0,0 @@
-import argparse
-import asyncio
-
-from asyncio.queues import Queue
-import re
-
-from dailyai.queue_frame import QueueFrame, FrameType
-from dailyai.services.azure_ai_services import AzureLLMService
-from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
-from dailyai.services.open_ai_services import OpenAIImageGenService
-from dailyai.services.daily_transport_service import DailyTransportService
-
-async def main(room_url):
-    meeting_duration_minutes = 5
-    transport = DailyTransportService(
-        room_url,
-        None,
-        "Month Narration Bot",
-        meeting_duration_minutes,
-    )
-    transport.mic_enabled = True
-    transport.camera_enabled = True
-    transport.mic_sample_rate = 16000
-    transport.camera_width = 1024
-    transport.camera_height = 1024
-
-    llm = AzureLLMService()
-    tts = ElevenLabsTTSService(voice_id="ErXwobaYiN019PkySvjV")
-    dalle = OpenAIImageGenService()
-
-    # Get a complete audio chunk from the given text. Splitting this into its own
-    # coroutine lets us ensure proper ordering of the audio chunks on the output queue.
-    async def get_all_audio(text):
-        all_audio = bytearray()
-        async for audio in tts.run_tts(text):
-            all_audio.extend(audio)
-
-        return all_audio
-
-    async def get_month_data(month):
-        image_text = ""
-        tts_tasks = []
-        first_sentence = True
-        async for sentence in llm.run_llm_async_sentences(
-            [
-                {
-                    "role": "system",
-                    "content": f"Describe a nature photograph suitable for use in a calendar, for the month of {month}. Include only the image description with no preamble. Limit the description to one sentence, please."
-                }
-            ]
-        ):
-            image_text += sentence
-
-            if first_sentence:
-                sentence = f"{month}: {sentence}"
-            else:
-                first_sentence = False
-
-            tts_tasks.append(get_all_audio(sentence))
-
-        tts_tasks.insert(0, dalle.run_image_gen(image_text, "1024x1024"))
-
-        print(f"waiting for tasks to finish for {month}")
-        data = await asyncio.gather(
-            *tts_tasks
-        )
-
-        print(f"done gathering tts tasks for {month}")
-
-        return {
-            "month": month,
-            "text": image_text,
-            "image": data[0][1],
-            "audio": data[1:],
-        }
-
-    months: list[str] = [
-        "January",
-        "February",
-        "March",
-        "April",
-        "May",
-        "June",
-        "July",
-        "August",
-        "September",
-        "October",
-        "November",
-        "December",
-    ]
-
-    @transport.event_handler("on_first_other_participant_joined")
-    async def on_first_other_participant_joined(transport):
-        # This will play the months in the order they're completed. The benefit
-        # is we'll have as little delay as possible before the first month, and
-        # likely no delay between months, but the months won't display in order.
-        for month_data_task in asyncio.as_completed(month_tasks):
-            data = await month_data_task
-            transport.output_queue.put(
-                [
-                    QueueFrame(FrameType.IMAGE_FRAME, data["image"]),
-                    QueueFrame(FrameType.AUDIO_FRAME, data["audio"][0]),
-                ]
-            )
-            for audio in data["audio"][1:]:
-                transport.output_queue.put(QueueFrame(FrameType.AUDIO_FRAME, audio))
-
-        # wait for the output queue to be empty, then leave the meeting
-        transport.output_queue.join()
-        transport.stop()
-
-    month_tasks = [asyncio.create_task(get_month_data(month)) for month in months]
-
-    await transport.run()
-
-if __name__=="__main__":
-    parser = argparse.ArgumentParser(description="Simple Daily Bot Sample")
-    parser.add_argument(
-        "-u", "--url", type=str, required=True, help="URL of the Daily room to join"
-    )
-
-    args, unknown = parser.parse_known_args()
-
-    asyncio.run(main(args.url))

src/samples/theoretical-to-real/05-sync-speech-and-text.py

@@ -1,15 +1,13 @@
 import argparse
-
 import asyncio
 
 from asyncio.queues import Queue
 import re
 
 from dailyai.queue_frame import QueueFrame, FrameType
-from dailyai.services.azure_ai_services import AzureLLMService, AzureTTSService
+from dailyai.services.azure_ai_services import AzureLLMService
-from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
-from dailyai.services.open_ai_services import OpenAILLMService, OpenAIImageGenService
 from dailyai.services.elevenlabs_ai_service import ElevenLabsTTSService
+from dailyai.services.open_ai_services import OpenAIImageGenService
 from dailyai.services.daily_transport_service import DailyTransportService
 
 async def main(room_url):
@@ -27,7 +25,7 @@ async def main(room_url):
     transport.camera_height = 1024
 
     llm = AzureLLMService()
-    tts = ElevenLabsTTSService()
+    tts = ElevenLabsTTSService(voice_id="ErXwobaYiN019PkySvjV")
     dalle = OpenAIImageGenService()
 
     # Get a complete audio chunk from the given text. Splitting this into its own
@@ -41,9 +39,9 @@ async def main(room_url):
 
     async def get_month_data(month):
         image_text = ""
-        current_clause = ""
         tts_tasks = []
-        async for text in llm.run_llm_async(
+        first_sentence = True
+        async for sentence in llm.run_llm_async_sentences(
             [
                 {
                     "role": "system",
@@ -51,18 +49,24 @@ async def main(room_url):
                 }
             ]
         ):
-            image_text += text
+            image_text += sentence
-            current_clause += text
+
-            if re.match(r"^.*[.!?]$", text):
+            if first_sentence:
-                tts_tasks.append(get_all_audio(current_clause))
+                sentence = f"{month}: {sentence}"
-                current_clause = ""
+            else:
+                first_sentence = False
+
+            tts_tasks.append(get_all_audio(sentence))
 
         tts_tasks.insert(0, dalle.run_image_gen(image_text, "1024x1024"))
 
+        print(f"waiting for tasks to finish for {month}")
         data = await asyncio.gather(
             *tts_tasks
         )
 
+        print(f"done gathering tts tasks for {month}")
+
         return {
             "month": month,
             "text": image_text,
@@ -75,9 +79,6 @@ async def main(room_url):
         "February",
         "March",
         "April",
-    ]
-
-    unused_months = [
         "May",
         "June",
         "July",
@@ -88,11 +89,11 @@ async def main(room_url):
         "December",
     ]
 
-    @transport.event_handler("on_participant_joined")
+    @transport.event_handler("on_first_other_participant_joined")
-    async def on_participant_joined(transport, participant):
+    async def on_first_other_participant_joined(transport):
-        if participant["id"] == transport.my_participant_id:
+        # This will play the months in the order they're completed. The benefit
-            return
+        # is we'll have as little delay as possible before the first month, and
-
+        # likely no delay between months, but the months won't display in order.
         for month_data_task in asyncio.as_completed(month_tasks):
             data = await month_data_task
             transport.output_queue.put(
@@ -118,6 +119,6 @@ if __name__=="__main__":
         "-u", "--url", type=str, required=True, help="URL of the Daily room to join"
     )
 
-    args: argparse.Namespace = parser.parse_args()
+    args, unknown = parser.parse_known_args()
 
     asyncio.run(main(args.url))

src/samples/theoretical-to-real/06-listen-and-respond.py

@@ -67,7 +67,7 @@ if __name__ == "__main__":
         help="Daily API Key (needed to create token)",
     )
 
-    args: argparse.Namespace = parser.parse_args()
+    args, unknown = parser.parse_known_args()
 
     # Create a meeting token for the given room with an expiration 1 hour in the future.
     room_name: str = urllib.parse.urlparse(args.url).path[1:]