Initial

examples/foundational/55zzq-update-settings-sarvam-llm.py

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+#
+# Copyright (c) 2024-2026, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import os
+from typing import Any
+
+from dotenv import load_dotenv
+from loguru import logger
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.llm_context import LLMContext
+from pipecat.processors.aggregators.llm_response_universal import (
+    LLMContextAggregatorPair,
+    LLMUserAggregatorParams,
+)
+from pipecat.runner.types import RunnerArguments
+from pipecat.runner.utils import create_transport
+from pipecat.services.openai.base_llm import OpenAILLMSettings
+from pipecat.services.sarvam.llm import SarvamLLMService
+from pipecat.services.sarvam.stt import SarvamSTTService
+from pipecat.services.sarvam.tts import SarvamTTSService
+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)
+
+transport_params = {
+    "daily": lambda: DailyParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+    ),
+    "twilio": lambda: FastAPIWebsocketParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+    ),
+    "webrtc": lambda: TransportParams(
+        audio_in_enabled=True,
+        audio_out_enabled=True,
+    ),
+}
+
+
+def _require_env(name: str) -> str:
+    value = os.getenv(name)
+    if not value:
+        raise ValueError(f"Environment variable `{name}` is required.")
+    return value
+
+
+async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
+    logger.info("Starting bot")
+
+    stt = SarvamSTTService(
+        model="saaras:v3",
+        api_key=_require_env("SARVAM_API_KEY"),
+    )
+
+    tts = SarvamTTSService(
+        model="bulbul:v3",
+        api_key=_require_env("SARVAM_API_KEY"),
+    )
+
+    llm = SarvamLLMService(
+        api_key=_require_env("SARVAM_API_KEY"),
+        model="sarvam-30b",
+    )
+
+    messages: list[Any] = [
+        {
+            "role": "system",
+            "content": (
+                "You are a helpful LLM in a WebRTC call. Your goal is to "
+                "demonstrate your capabilities in a succinct way. Your output "
+                "will be spoken aloud, so avoid special characters that can't "
+                "easily be spoken, such as emojis or bullet points. Respond to "
+                "what the user said in a creative and helpful way."
+            ),
+        },
+    ]
+
+    context = LLMContext(messages)
+    user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
+        context,
+        user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
+    )
+
+    pipeline = Pipeline(
+        [
+            transport.input(),
+            stt,
+            user_aggregator,
+            llm,
+            tts,
+            transport.output(),
+            assistant_aggregator,
+        ]
+    )
+
+    task = PipelineTask(
+        pipeline,
+        params=PipelineParams(
+            enable_metrics=True,
+            enable_usage_metrics=True,
+        ),
+        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
+    )
+
+    @transport.event_handler("on_client_connected")
+    async def on_client_connected(transport, client):
+        logger.info("Client connected")
+        messages.append({"role": "system", "content": "Please introduce yourself to the user."})
+        await task.queue_frames([LLMRunFrame()])
+
+        await asyncio.sleep(10)
+        logger.info("Updating Sarvam LLM settings: temperature=0.1")
+        await task.queue_frame(LLMUpdateSettingsFrame(delta=OpenAILLMSettings(temperature=0.1)))
+
+    @transport.event_handler("on_client_disconnected")
+    async def on_client_disconnected(transport, client):
+        logger.info("Client disconnected")
+        await task.cancel()
+
+    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()