Reorganize examples into topic-based subfolders

Move 304 examples from a flat numbered directory into 14 descriptive
subfolders: getting-started, services (speech + function-calling),
transcription, vision, realtime, persistent-context,
context-summarization, update-settings (stt/tts/llm), turn-management,
thinking-and-mcp, transports, video-avatar, video-processing, and
features.

Strip numbered prefixes from filenames (e.g. 07c-interruptible-deepgram.py
becomes services/speech/deepgram.py) since the folder context makes them
redundant. Keep numbered prefixes only in getting-started/ where ordering
matters.

Update eval script paths and README to match the new structure.

examples/getting-started/01-say-one-thing.py

@@ -0,0 +1,69 @@
+#
+# Copyright (c) 2024-2026, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import os
+
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.frames.frames import EndFrame, TTSSpeakFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineTask
+from pipecat.runner.types import RunnerArguments
+from pipecat.runner.utils import create_transport
+from pipecat.services.cartesia.tts import CartesiaTTSService
+from pipecat.transports.base_transport import BaseTransport, TransportParams
+from pipecat.transports.daily.transport import DailyParams
+from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+
+load_dotenv(override=True)
+
+
+# We use lambdas to defer transport parameter creation until the transport
+# type is selected at runtime.
+transport_params = {
+    "daily": lambda: DailyParams(audio_out_enabled=True),
+    "twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True),
+    "webrtc": lambda: TransportParams(audio_out_enabled=True),
+}
+
+
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
+    logger.info(f"Starting bot")
+
+    tts = CartesiaTTSService(
+        api_key=os.getenv("CARTESIA_API_KEY"),
+        settings=CartesiaTTSService.Settings(
+            voice="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
+        ),
+    )
+
+    task = PipelineTask(
+        Pipeline([tts, transport.output()]),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+    )
+
+    # Register an event handler so we can play the audio when the client joins
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
+
+    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
+
+    await runner.run(task)
+
+
+async def bot(runner_args: RunnerArguments):
+    """Main bot entry point compatible with Pipecat Cloud."""
+    transport = await create_transport(runner_args, transport_params)
+    await run_bot(transport, runner_args)
+
+
+if __name__ == "__main__":
+    from pipecat.runner.run import main
+
+    main()