initial commit of screen capture in 99-anthropic-hackathon.py

examples/foundational/99-anthropic-hackathon.py

@@ -0,0 +1,175 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import aiohttp
+import os
+import sys
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.services.cartesia import CartesiaTTSService
+from pipecat.services.anthropic import AnthropicLLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+from pipecat.frames.frames import Frame, ImageRawFrame
+from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
+from pipecat.services.anthropic import AnthropicLLMContext
+
+from runner import configure
+
+from loguru import logger
+
+from dotenv import load_dotenv
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+video_participant_id = None
+
+most_recent_image_frame = None
+
+
+class ImageFrameCatcher(FrameProcessor):
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        global most_recent_image_frame
+
+        await super().process_frame(frame, direction)
+        if isinstance(frame, ImageRawFrame):
+            logger.debug(f"ImageLogger: {frame}")
+            most_recent_image_frame = frame
+        else:
+            await self.push_frame(frame, direction)
+
+
+async def get_weather(function_name, tool_call_id, arguments, llm, context, result_callback):
+    location = arguments["location"]
+    await result_callback(f"The weather in {location} is currently 72 degrees and sunny.")
+
+
+async def main():
+    global llm
+
+    async with aiohttp.ClientSession() as session:
+        (room_url, token) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Respond bot",
+            DailyParams(
+                audio_out_enabled=True,
+                transcription_enabled=True,
+                vad_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(),
+            ),
+        )
+
+        tts = CartesiaTTSService(
+            api_key=os.getenv("CARTESIA_API_KEY"),
+            voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22",  # British Lady
+        )
+
+        llm = AnthropicLLMService(
+            api_key=os.getenv("ANTHROPIC_API_KEY"),
+            model="claude-3-5-sonnet-20240620",
+            enable_prompt_caching_beta=True,
+        )
+        llm.register_function("get_weather", get_weather)
+
+        tools = [
+            {
+                "name": "get_weather",
+                "description": "Get the current weather in a given location",
+                "input_schema": {
+                    "type": "object",
+                    "properties": {
+                        "location": {
+                            "type": "string",
+                            "description": "The city and state, e.g. San Francisco, CA",
+                        }
+                    },
+                    "required": ["location"],
+                },
+            },
+        ]
+
+        # todo: test with very short initial user message
+
+        system_prompt = """\
+You are a helpful assistant who converses with a user and answers questions. Respond concisely to general questions. Keep
+your answers brief unless explicitly asked for more information.
+
+Your response will be turned into speech so use only simple words and punctuation.
+        """
+
+        messages = [
+            {
+                "role": "system",
+                "content": [
+                    {
+                        "type": "text",
+                        "text": system_prompt,
+                    }
+                ],
+            },
+            {"role": "user", "content": "Start the conversation by saying 'hello'."},
+        ]
+
+        context = OpenAILLMContext(messages, tools)
+        context_aggregator = llm.create_context_aggregator(context)
+
+        pipeline = Pipeline(
+            [
+                transport.input(),  # Transport user input
+                ImageFrameCatcher(),
+                context_aggregator.user(),  # User speech to text
+                llm,  # LLM
+                tts,  # TTS
+                transport.output(),  # Transport bot output
+                context_aggregator.assistant(),  # Assistant spoken responses and tool context
+            ]
+        )
+
+        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True, enable_metrics=True))
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            global video_participant_id
+            video_participant_id = participant["id"]
+            await transport.capture_participant_transcription(video_participant_id)
+            await transport.capture_participant_video(
+                video_participant_id, framerate=1, video_source="screenVideo"
+            )
+            # Kick off the conversation.
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_app_message")
+        async def on_app_message(transport, message, sender):
+            c = AnthropicLLMContext.upgrade_to_anthropic(context)
+            logger.debug(f"Received app message: {message} - {context}")
+            frame = most_recent_image_frame
+            if not frame:
+                logger.debug("No image frame to send")
+                return
+            c.add_image_frame_message(
+                format=frame.format,
+                size=frame.size,
+                image=frame.image,
+                text=message["message"],
+            )
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        runner = PipelineRunner()
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

src/pipecat/transports/services/daily.py

@@ -495,9 +495,12 @@ class DailyTransportClient(EventHandler):
         video_source: str = "camera",
         color_format: str = "RGB",
     ):
-        # Only enable camera subscription on this participant
+        # Try to enable camera and screen subscription on this participant
         await self.update_subscriptions(
-            participant_settings={participant_id: {"media": "subscribed"}}
+            # participant_settings={participant_id: {"media": "subscribed"}}
+            participant_settings={
+                participant_id: {"media": {"camera": "subscribed", "screenVideo": "subscribed"}}
+            }
         )
 
         self._video_renderers[participant_id] = callback