Merge pull request #3981 from dhruvladia-sarvam/feat/sarvam-llm-integration
Sarvam LLM Integration
This commit is contained in:
Mark Backman
@@ -88,7 +88,7 @@ Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.yout
|
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| Category | Services |
|
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| ------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
|
||||
| Speech-to-Text | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/stt/elevenlabs), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Gradium](https://docs.pipecat.ai/server/services/stt/gradium), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [SambaNova (Whisper)](https://docs.pipecat.ai/server/services/stt/sambanova), [Sarvam](https://docs.pipecat.ai/server/services/stt/sarvam), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/server/services/stt/speechmatics), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper) |
|
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| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [Mistral](https://docs.pipecat.ai/server/services/llm/mistral), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova) [Together AI](https://docs.pipecat.ai/server/services/llm/together) |
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| LLMs | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [Mistral](https://docs.pipecat.ai/server/services/llm/mistral), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova), [Sarvam](https://docs.pipecat.ai/server/services/llm/sarvam), [Together AI](https://docs.pipecat.ai/server/services/llm/together) |
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| Text-to-Speech | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Camb AI](https://docs.pipecat.ai/server/services/tts/camb), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Gradium](https://docs.pipecat.ai/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [Resemble](https://docs.pipecat.ai/server/services/tts/resemble), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [Speechmatics](https://docs.pipecat.ai/server/services/tts/speechmatics), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) |
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| Speech-to-Speech | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [Grok Voice Agent](https://docs.pipecat.ai/server/services/s2s/grok), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai), [Ultravox](https://docs.pipecat.ai/server/services/s2s/ultravox), |
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| Transport | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local |
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@@ -98,7 +98,7 @@ Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.yout
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| Vision & Image | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/google-imagen), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream) |
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| Audio Processing | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [ai-coustics](https://docs.pipecat.ai/server/utilities/audio/aic-filter) |
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| Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry) |
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| Community | [Browse community integrations →](https://docs.pipecat.ai/server/services/community-integrations) |
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| Community | [Browse community integrations →](https://docs.pipecat.ai/server/services/community-integrations) |
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📚 [View full services documentation →](https://docs.pipecat.ai/server/services/supported-services)
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1
changelog/3978.added.md
Normal file
1
changelog/3978.added.md
Normal file
@@ -0,0 +1 @@
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- Added `SarvamLLMService` with support for `sarvam-30b`, `sarvam-30b-16k`, `sarvam-105b` and `sarvam-105b-32k`
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@@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import (
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)
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from pipecat.runner.types import RunnerArguments
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from pipecat.runner.utils import create_transport
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from pipecat.services.openai.llm import OpenAILLMService
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from pipecat.services.sarvam.llm import SarvamLLMService
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from pipecat.services.sarvam.stt import SarvamSTTService
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from pipecat.services.sarvam.tts import SarvamHttpTTSService
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from pipecat.transcriptions.language import Language
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@@ -72,9 +72,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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),
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)
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llm = OpenAILLMService(
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api_key=os.getenv("OPENAI_API_KEY"),
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settings=OpenAILLMService.Settings(
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llm = SarvamLLMService(
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api_key=os.getenv("SARVAM_API_KEY"),
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settings=SarvamLLMService.Settings(
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system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
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),
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)
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@@ -21,7 +21,7 @@ from pipecat.processors.aggregators.llm_response_universal import (
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)
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from pipecat.runner.types import RunnerArguments
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from pipecat.runner.utils import create_transport
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from pipecat.services.openai.llm import OpenAILLMService
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from pipecat.services.sarvam.llm import SarvamLLMService
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from pipecat.services.sarvam.stt import SarvamSTTService
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from pipecat.services.sarvam.tts import SarvamTTSService
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from pipecat.transports.base_transport import BaseTransport, TransportParams
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@@ -55,20 +55,20 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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stt = SarvamSTTService(
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api_key=os.getenv("SARVAM_API_KEY"),
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settings=SarvamSTTService.Settings(
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model="saarika:v2.5",
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model="saaras:v3",
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),
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)
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tts = SarvamTTSService(
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api_key=os.getenv("SARVAM_API_KEY"),
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settings=SarvamTTSService.Settings(
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model="bulbul:v2",
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voice="manisha",
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model="bulbul:v3",
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voice="shubh",
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),
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)
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llm = OpenAILLMService(
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api_key=os.getenv("OPENAI_API_KEY"),
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settings=OpenAILLMService.Settings(
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llm = SarvamLLMService(
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api_key=os.getenv("SARVAM_API_KEY"),
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settings=SarvamLLMService.Settings(
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system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
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),
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)
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@@ -96,6 +96,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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params=PipelineParams(
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enable_metrics=True,
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enable_usage_metrics=True,
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allow_interruptions=True,
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),
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)
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178
examples/foundational/14y-function-calling-sarvam.py
Normal file
178
examples/foundational/14y-function-calling-sarvam.py
Normal file
@@ -0,0 +1,178 @@
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#
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# Copyright (c) 2024-2026, Daily
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#
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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import os
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from dotenv import load_dotenv
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from loguru import logger
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from pipecat.adapters.schemas.function_schema import FunctionSchema
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from pipecat.adapters.schemas.tools_schema import ToolsSchema
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from pipecat.audio.vad.silero import SileroVADAnalyzer
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from pipecat.frames.frames import LLMRunFrame, TTSSpeakFrame
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from pipecat.pipeline.pipeline import Pipeline
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from pipecat.pipeline.runner import PipelineRunner
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from pipecat.pipeline.task import PipelineParams, PipelineTask
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from pipecat.processors.aggregators.llm_context import LLMContext
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from pipecat.processors.aggregators.llm_response_universal import (
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LLMContextAggregatorPair,
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LLMUserAggregatorParams,
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)
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from pipecat.runner.types import RunnerArguments
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from pipecat.runner.utils import create_transport
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from pipecat.services.llm_service import FunctionCallParams
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from pipecat.services.sarvam.llm import SarvamLLMService
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from pipecat.services.sarvam.stt import SarvamSTTService
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from pipecat.services.sarvam.tts import SarvamTTSService
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from pipecat.transports.base_transport import BaseTransport, TransportParams
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from pipecat.transports.daily.transport import DailyParams
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from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
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load_dotenv(override=True)
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async def fetch_weather_from_api(params: FunctionCallParams):
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await params.result_callback({"conditions": "nice", "temperature": "75"})
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async def fetch_restaurant_recommendation(params: FunctionCallParams):
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await params.result_callback({"name": "The Golden Dragon"})
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# We use lambdas to defer transport parameter creation until the transport
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# type is selected at runtime.
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transport_params = {
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"daily": lambda: DailyParams(
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audio_in_enabled=True,
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audio_out_enabled=True,
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),
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"twilio": lambda: FastAPIWebsocketParams(
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audio_in_enabled=True,
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audio_out_enabled=True,
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),
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"webrtc": lambda: TransportParams(
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audio_in_enabled=True,
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audio_out_enabled=True,
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),
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}
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async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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logger.info(f"Starting bot")
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stt = SarvamSTTService(
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api_key=os.getenv("SARVAM_API_KEY"),
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settings=SarvamSTTService.Settings(
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model="saaras:v3",
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),
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)
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tts = SarvamTTSService(
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api_key=os.getenv("SARVAM_API_KEY"),
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settings=SarvamTTSService.Settings(
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model="bulbul:v3",
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voice="shubh",
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),
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)
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llm = SarvamLLMService(
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api_key=os.getenv("SARVAM_API_KEY"),
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settings=SarvamLLMService.Settings(
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system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
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),
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)
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# You can also register a function_name of None to get all functions
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# sent to the same callback with an additional function_name parameter.
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llm.register_function("get_current_weather", fetch_weather_from_api)
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llm.register_function("get_restaurant_recommendation", fetch_restaurant_recommendation)
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@llm.event_handler("on_function_calls_started")
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async def on_function_calls_started(service, function_calls):
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await tts.queue_frame(TTSSpeakFrame("Let me check on that."))
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weather_function = FunctionSchema(
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name="get_current_weather",
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description="Get the current weather",
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properties={
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"location": {
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"type": "string",
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"description": "The city and state, e.g. San Francisco, CA",
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},
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"format": {
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"type": "string",
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"enum": ["celsius", "fahrenheit"],
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"description": "The temperature unit to use. Infer this from the user's location.",
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},
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},
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required=["location", "format"],
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)
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restaurant_function = FunctionSchema(
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name="get_restaurant_recommendation",
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description="Get a restaurant recommendation",
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properties={
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"location": {
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"type": "string",
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"description": "The city and state, e.g. San Francisco, CA",
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},
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},
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required=["location"],
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)
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tools = ToolsSchema(standard_tools=[weather_function, restaurant_function])
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context = LLMContext(tools=tools)
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user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
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context,
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user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
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)
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pipeline = Pipeline(
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[
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transport.input(),
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stt,
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user_aggregator,
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llm,
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tts,
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transport.output(),
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assistant_aggregator,
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]
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)
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|
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task = PipelineTask(
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pipeline,
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params=PipelineParams(
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enable_metrics=True,
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enable_usage_metrics=True,
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),
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idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
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)
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|
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@transport.event_handler("on_client_connected")
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async def on_client_connected(transport, client):
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logger.info(f"Client connected")
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# Kick off the conversation.
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context.add_message({"role": "user", "content": "Please introduce yourself to the user."})
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await task.queue_frames([LLMRunFrame()])
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@transport.event_handler("on_client_disconnected")
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async def on_client_disconnected(transport, client):
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logger.info(f"Client disconnected")
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await task.cancel()
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runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
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await runner.run(task)
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|
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async def bot(runner_args: RunnerArguments):
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"""Main bot entry point compatible with Pipecat Cloud."""
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transport = await create_transport(runner_args, transport_params)
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await run_bot(transport, runner_args)
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|
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|
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if __name__ == "__main__":
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from pipecat.runner.run import main
|
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|
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main()
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137
examples/foundational/55zzq-update-settings-sarvam-llm.py
Normal file
137
examples/foundational/55zzq-update-settings-sarvam-llm.py
Normal file
@@ -0,0 +1,137 @@
|
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#
|
||||
# Copyright (c) 2024-2026, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
import asyncio
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import os
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from typing import Any
|
||||
|
||||
from dotenv import load_dotenv
|
||||
from loguru import logger
|
||||
|
||||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
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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.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(
|
||||
settings=SarvamSTTService.Settings(model="saaras:v3"),
|
||||
api_key=_require_env("SARVAM_API_KEY"),
|
||||
)
|
||||
|
||||
tts = SarvamTTSService(
|
||||
settings=SarvamTTSService.Settings(model="bulbul:v3"),
|
||||
api_key=_require_env("SARVAM_API_KEY"),
|
||||
)
|
||||
|
||||
llm = SarvamLLMService(
|
||||
api_key=_require_env("SARVAM_API_KEY"),
|
||||
settings=SarvamLLMService.Settings(model="sarvam-30b"),
|
||||
system_instruction=(
|
||||
"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()
|
||||
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")
|
||||
context.add_message({"role": "user", "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=SarvamLLMService.Settings(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()
|
||||
@@ -186,6 +186,7 @@ TESTS_14 = [
|
||||
("14v-function-calling-openai.py", EVAL_WEATHER),
|
||||
("14w-function-calling-mistral.py", EVAL_WEATHER),
|
||||
("14x-function-calling-openpipe.py", EVAL_WEATHER),
|
||||
("14y-function-calling-sarvam.py", EVAL_WEATHER),
|
||||
("14-function-calling-openai-responses.py", EVAL_WEATHER),
|
||||
("14-function-calling-openai-responses.py", EVAL_WEATHER_AND_RESTAURANT),
|
||||
# Video
|
||||
|
||||
@@ -4,5 +4,4 @@
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
|
||||
from .tts import *
|
||||
|
||||
160
src/pipecat/services/sarvam/llm.py
Normal file
160
src/pipecat/services/sarvam/llm.py
Normal file
@@ -0,0 +1,160 @@
|
||||
#
|
||||
# Copyright (c) 2024-2026, Daily
|
||||
#
|
||||
# SPDX-License-Identifier: BSD 2-Clause License
|
||||
#
|
||||
|
||||
"""Sarvam LLM service implementation using OpenAI-compatible interface."""
|
||||
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Literal, Mapping, Optional
|
||||
|
||||
from loguru import logger
|
||||
from openai import NOT_GIVEN
|
||||
|
||||
from pipecat.adapters.services.open_ai_adapter import OpenAILLMInvocationParams
|
||||
from pipecat.services.openai.base_llm import OpenAILLMSettings
|
||||
from pipecat.services.openai.llm import OpenAILLMService
|
||||
from pipecat.services.sarvam._sdk import sdk_headers
|
||||
from pipecat.services.settings import NOT_GIVEN as _NOT_GIVEN
|
||||
from pipecat.services.settings import _NotGiven, is_given
|
||||
|
||||
|
||||
@dataclass
|
||||
class SarvamLLMSettings(OpenAILLMSettings):
|
||||
"""Settings for SarvamLLMService.
|
||||
|
||||
Parameters:
|
||||
wiki_grounding: Sarvam wiki grounding toggle.
|
||||
reasoning_effort: Reasoning effort level (low, medium, high).
|
||||
"""
|
||||
|
||||
wiki_grounding: bool | None | _NotGiven = field(default_factory=lambda: _NOT_GIVEN)
|
||||
reasoning_effort: Literal["low", "medium", "high"] | None | _NotGiven = field(
|
||||
default_factory=lambda: _NOT_GIVEN
|
||||
)
|
||||
|
||||
|
||||
class SarvamLLMService(OpenAILLMService):
|
||||
"""A service for interacting with Sarvam's API using the OpenAI-compatible interface.
|
||||
|
||||
This service extends OpenAILLMService to connect to Sarvam's API endpoint while
|
||||
maintaining full compatibility with OpenAI's interface and functionality.
|
||||
"""
|
||||
|
||||
_SUPPORTED_MODELS = frozenset(
|
||||
{"sarvam-30b", "sarvam-30b-16k", "sarvam-105b", "sarvam-105b-32k"}
|
||||
)
|
||||
Settings = SarvamLLMSettings
|
||||
_settings: Settings
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
api_key: str,
|
||||
base_url: str = "https://api.sarvam.ai/v1",
|
||||
settings: Optional[Settings] = None,
|
||||
default_headers: Optional[Mapping[str, str]] = None,
|
||||
**kwargs,
|
||||
):
|
||||
"""Initialize Sarvam LLM service.
|
||||
|
||||
Args:
|
||||
api_key: Sarvam API key used for both OpenAI auth and Sarvam subscription header.
|
||||
base_url: Sarvam OpenAI-compatible base URL.
|
||||
settings: Runtime-updatable settings.
|
||||
default_headers: Additional HTTP headers to include in requests.
|
||||
**kwargs: Additional keyword arguments passed to ``OpenAILLMService``.
|
||||
"""
|
||||
# Initialize only Sarvam-specific defaults; inherited defaults are
|
||||
# provided by the OpenAI base service initialization.
|
||||
default_settings = self.Settings(
|
||||
model="sarvam-30b",
|
||||
wiki_grounding=None,
|
||||
reasoning_effort=None,
|
||||
)
|
||||
|
||||
# Apply settings delta (canonical API, always wins)
|
||||
if settings is not None:
|
||||
default_settings.apply_update(settings)
|
||||
|
||||
self._validate_model(default_settings.model)
|
||||
|
||||
super().__init__(
|
||||
api_key=api_key,
|
||||
base_url=base_url,
|
||||
settings=default_settings,
|
||||
default_headers=default_headers,
|
||||
**kwargs,
|
||||
)
|
||||
|
||||
def create_client(
|
||||
self,
|
||||
api_key=None,
|
||||
base_url=None,
|
||||
organization=None,
|
||||
project=None,
|
||||
default_headers=None,
|
||||
**kwargs,
|
||||
):
|
||||
"""Create OpenAI-compatible client for Sarvam API endpoint.
|
||||
|
||||
Ensures Sarvam auth and SDK identification headers are always attached.
|
||||
"""
|
||||
merged_headers = dict(default_headers or {})
|
||||
# sdk_headers() carries Pipecat User-Agent and should override caller-provided value.
|
||||
merged_headers.update(sdk_headers())
|
||||
if api_key:
|
||||
merged_headers["api-subscription-key"] = api_key
|
||||
|
||||
logger.debug(f"Creating Sarvam client with API {base_url}")
|
||||
return super().create_client(
|
||||
api_key=api_key,
|
||||
base_url=base_url,
|
||||
organization=organization,
|
||||
project=project,
|
||||
default_headers=merged_headers,
|
||||
**kwargs,
|
||||
)
|
||||
|
||||
def build_chat_completion_params(self, params_from_context: OpenAILLMInvocationParams) -> dict:
|
||||
"""Build parameters for Sarvam chat completion request.
|
||||
|
||||
Starts from OpenAI-compatible defaults, then removes unsupported
|
||||
request fields and applies Sarvam-specific options.
|
||||
"""
|
||||
self._validate_tool_parameters(params_from_context)
|
||||
|
||||
params = super().build_chat_completion_params(params_from_context)
|
||||
params.pop("stream_options", None)
|
||||
params.pop("max_completion_tokens", None)
|
||||
params.pop("service_tier", None)
|
||||
|
||||
if is_given(self._settings.wiki_grounding) and self._settings.wiki_grounding is not None:
|
||||
params["wiki_grounding"] = self._settings.wiki_grounding
|
||||
if (
|
||||
is_given(self._settings.reasoning_effort)
|
||||
and self._settings.reasoning_effort is not None
|
||||
):
|
||||
params["reasoning_effort"] = self._settings.reasoning_effort
|
||||
|
||||
return params
|
||||
|
||||
def _validate_model(self, model: str):
|
||||
if model not in self._SUPPORTED_MODELS:
|
||||
allowed = ", ".join(sorted(self._SUPPORTED_MODELS))
|
||||
raise ValueError(f"Unsupported Sarvam LLM model '{model}'. Allowed values: {allowed}.")
|
||||
|
||||
def _validate_tool_parameters(self, params_from_context: OpenAILLMInvocationParams):
|
||||
tools = params_from_context.get("tools", NOT_GIVEN)
|
||||
tool_choice = params_from_context.get("tool_choice", NOT_GIVEN)
|
||||
|
||||
has_tools = (
|
||||
tools is not NOT_GIVEN
|
||||
and tools is not None
|
||||
and (not isinstance(tools, list) or len(tools) > 0)
|
||||
)
|
||||
has_tool_choice = tool_choice is not NOT_GIVEN and tool_choice is not None
|
||||
|
||||
if has_tool_choice and not has_tools:
|
||||
raise ValueError("Sarvam requires non-empty `tools` when `tool_choice` is provided.")
|
||||
Reference in New Issue
Block a user