apunkt/dograh
1
0
Fork 0
mirror of https://github.com/dograh-hq/dograh.git synced 2026-06-07 07:55:16 +02:00
Code Issues Projects Releases Packages Wiki Activity

Add Sarvam LLM, update Sarvam STT models, expose usage_info on run detail (#351)

Browse source 
* Add Sarvam LLM provider, update Sarvam STT models, expose usage_info on run detail.
Depends on pipecat PR dograh-hq/pipecat#43 for STT string language support.
Submodule bump will follow after that merges.

* test: cover Sarvam STT language mapping; link Sarvam docs

---------

Co-authored-by: Sabiha Khan <sabihak89@gmail.com>
This commit is contained in:
Abhay Babbar 2026-06-01 10:29:31 +05:30 • committed by GitHub
parent 13b30dee9e
commit 98d2b24cba
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
10 changed files with 272 additions and 9 deletions
Download patch file Download diff file Expand all files Collapse all files

2
api/routes/workflow.py
View file

@ -32,6 +32,7 @@ from api.services.configuration.resolve import (
)
from api.services.mps_service_key_client import mps_service_key_client
from api.services.posthog_client import capture_event
from api.services.pricing.run_usage_response import format_public_usage_info
from api.services.reports import generate_workflow_report_csv
from api.services.storage import storage_fs
from api.services.workflow.dto import ReactFlowDTO, sanitize_workflow_definition
@ -1186,6 +1187,7 @@ async def get_workflow_run(
}
if run.cost_info
else None,
"usage_info": format_public_usage_info(run.usage_info),
"created_at": run.created_at,
"definition_id": run.definition_id,
"initial_context": run.initial_context,

1
api/schemas/workflow.py
View file

@ -19,6 +19,7 @@ class WorkflowRunResponseSchema(BaseModel):
recording_public_url: str | None = None
public_access_token: str | None = None
cost_info: Dict[str, Any] | None
usage_info: Dict[str, Any] | None = None
definition_id: int | None # This is for backward compatibility
initial_context: dict | None = None
gathered_context: dict | None = None

6
api/services/configuration/options/__init__.py
View file

@ -16,6 +16,9 @@ from .google import (
)
from .sarvam import (
SARVAM_LANGUAGES,
SARVAM_LLM_MODELS,
SARVAM_STT_LANGUAGES_V25,
SARVAM_STT_LANGUAGES_V3,
SARVAM_STT_MODELS,
SARVAM_TTS_MODELS,
SARVAM_V2_VOICES,
@ -41,6 +44,9 @@ __all__ = [
"GOOGLE_VERTEX_REALTIME_MODELS",
"GOOGLE_VERTEX_REALTIME_VOICES",
"SARVAM_LANGUAGES",
"SARVAM_LLM_MODELS",
"SARVAM_STT_LANGUAGES_V25",
"SARVAM_STT_LANGUAGES_V3",
"SARVAM_STT_MODELS",
"SARVAM_TTS_MODELS",
"SARVAM_V2_VOICES",

36
api/services/configuration/options/sarvam.py
View file

@ -63,4 +63,38 @@ SARVAM_LANGUAGES = (
"te-IN",
"as-IN",
)
SARVAM_STT_MODELS = ("saarika:v2.5", "saaras:v2")
SARVAM_STT_MODELS = ("saarika:v2.5", "saaras:v3")
# saarika:v2.5 language codes (unknown = auto-detect)
SARVAM_STT_LANGUAGES_V25 = (
"unknown",
"hi-IN",
"bn-IN",
"gu-IN",
"kn-IN",
"ml-IN",
"mr-IN",
"od-IN",
"pa-IN",
"ta-IN",
"te-IN",
"en-IN",
)
# saaras:v3 adds these regional languages on top of the v2.5 set. Full list: https://docs.sarvam.ai/api-reference-docs/speech-to-text/transcribe
SARVAM_STT_LANGUAGES_V3 = SARVAM_STT_LANGUAGES_V25 + (
"as-IN",
"ur-IN",
"ne-IN",
"kok-IN",
"ks-IN",
"sd-IN",
"sa-IN",
"sat-IN",
"mni-IN",
"brx-IN",
"mai-IN",
"doi-IN",
)
SARVAM_LLM_MODELS = (
"sarvam-30b",
"sarvam-105b",
)

48
api/services/configuration/registry.py
View file

@ -22,6 +22,9 @@ from api.services.configuration.options import (
GOOGLE_VERTEX_REALTIME_MODELS,
GOOGLE_VERTEX_REALTIME_VOICES,
SARVAM_LANGUAGES,
SARVAM_LLM_MODELS,
SARVAM_STT_LANGUAGES_V25,
SARVAM_STT_LANGUAGES_V3,
SARVAM_STT_MODELS,
SARVAM_TTS_MODELS,
SARVAM_V2_VOICES,
@ -89,7 +92,7 @@ class BaseServiceConfiguration(BaseModel):
ServiceProviders.ULTRAVOX_REALTIME,
ServiceProviders.GOOGLE_REALTIME,
ServiceProviders.GOOGLE_VERTEX_REALTIME,
# ServiceProviders.SARVAM,
ServiceProviders.SARVAM,
]
api_key: str | list[str]
@ -472,6 +475,29 @@ class MiniMaxLLMConfiguration(BaseLLMConfiguration):
)
@register_llm
class SarvamLLMConfiguration(BaseLLMConfiguration):
model_config = SARVAM_PROVIDER_MODEL_CONFIG
provider: Literal[ServiceProviders.SARVAM] = ServiceProviders.SARVAM
model: str = Field(
default="sarvam-30b",
description=(
"Sarvam chat model. Use sarvam-30b for low-latency voice agents; "
"sarvam-105b for complex multi-step reasoning."
),
json_schema_extra={"examples": SARVAM_LLM_MODELS, "allow_custom_input": True},
)
temperature: float = Field(
default=0.5,
ge=0.0,
le=2.0,
description=(
"Sampling temperature. Sarvam recommends 0.5 for balanced "
"conversational responses."
),
)
OPENAI_REALTIME_MODELS = ["gpt-realtime-2"]
OPENAI_REALTIME_VOICES = [
"alloy",
@ -661,6 +687,7 @@ LLMConfig = Annotated[
AWSBedrockLLMConfiguration,
SpeachesLLMConfiguration,
MiniMaxLLMConfiguration,
SarvamLLMConfiguration,
],
Field(discriminator="provider"),
]
@ -1129,13 +1156,24 @@ class SarvamSTTConfiguration(BaseSTTConfiguration):
provider: Literal[ServiceProviders.SARVAM] = ServiceProviders.SARVAM
model: str = Field(
default="saarika:v2.5",
description="Sarvam STT model.",
description=(
"Sarvam STT model. saarika:v2.5 transcribes in the spoken language; "
"saaras:v3 is the recommended model with flexible output modes."
),
json_schema_extra={"examples": SARVAM_STT_MODELS},
)
language: str = Field(
default="hi-IN",
description="BCP-47 Indian-language code.",
json_schema_extra={"examples": SARVAM_LANGUAGES},
default="unknown",
description=(
"BCP-47 language code. Use unknown for automatic language detection."
),
json_schema_extra={
"examples": SARVAM_STT_LANGUAGES_V25,
"model_options": {
"saarika:v2.5": SARVAM_STT_LANGUAGES_V25,
"saaras:v3": SARVAM_STT_LANGUAGES_V3,
},
},
)

26
api/services/pipecat/service_factory.py
View file

@ -47,6 +47,7 @@ from pipecat.services.openai.stt import (
from pipecat.services.openai.tts import OpenAITTSService, OpenAITTSSettings
from pipecat.services.openrouter.llm import OpenRouterLLMService, OpenRouterLLMSettings
from pipecat.services.rime.tts import RimeTTSService, RimeTTSSettings
from pipecat.services.sarvam.llm import SarvamLLMService, SarvamLLMSettings
from pipecat.services.sarvam.stt import SarvamSTTService, SarvamSTTSettings
from pipecat.services.sarvam.tts import SarvamTTSService, SarvamTTSSettings
from pipecat.services.speaches.llm import SpeachesLLMService, SpeachesLLMSettings
@ -158,7 +159,7 @@ def create_stt_service(
sample_rate=audio_config.transport_in_sample_rate,
)
elif user_config.stt.provider == ServiceProviders.SARVAM.value:
# Map Sarvam language code to pipecat Language enum
language = getattr(user_config.stt, "language", None)
language_mapping = {
"bn-IN": Language.BN_IN,
"gu-IN": Language.GU_IN,
@ -172,9 +173,18 @@ def create_stt_service(
"od-IN": Language.OR_IN,
"en-IN": Language.EN_IN,
"as-IN": Language.AS_IN,
"ur-IN": Language.UR_IN,
"kok-IN": Language.KOK_IN,
"mai-IN": Language.MAI_IN,
"sd-IN": Language.SD_IN,
}
language = getattr(user_config.stt, "language", None)
pipecat_language = language_mapping.get(language, Language.HI_IN)
if not language or language == "unknown":
pipecat_language = None
elif language in language_mapping:
pipecat_language = language_mapping[language]
else:
# Unmapped BCP-47 codes pass through; Sarvam accepts them per https://docs.sarvam.ai/api-reference-docs/speech-to-text/transcribe
pipecat_language = language
return SarvamSTTService(
api_key=user_config.stt.api_key,
settings=SarvamSTTSettings(
@ -604,6 +614,14 @@ def create_llm_service_from_provider(
temperature=temperature if temperature is not None else 1.0,
),
)
elif provider == ServiceProviders.SARVAM.value:
return SarvamLLMService(
api_key=api_key,
settings=SarvamLLMSettings(
model=model,
temperature=temperature if temperature is not None else 0.5,
),
)
else:
raise HTTPException(status_code=400, detail=f"Invalid LLM provider {provider}")
@ -756,5 +774,7 @@ def create_llm_service(user_config):
elif provider == ServiceProviders.MINIMAX.value:
kwargs["base_url"] = user_config.llm.base_url
kwargs["temperature"] = user_config.llm.temperature
elif provider == ServiceProviders.SARVAM.value:
kwargs["temperature"] = user_config.llm.temperature
return create_llm_service_from_provider(provider, model, api_key, **kwargs)

13
api/services/pricing/run_usage_response.py Normal file
View file

@ -0,0 +1,13 @@
"""Format workflow run usage for public API responses."""
def format_public_usage_info(usage_info: dict | None) -> dict | None:
if not usage_info:
return None
return {
"llm": usage_info.get("llm") or {},
"tts": usage_info.get("tts") or {},
"stt": usage_info.get("stt") or {},
"call_duration_seconds": usage_info.get("call_duration_seconds"),
}

23
api/tests/test_run_usage_response.py Normal file
View file

@ -0,0 +1,23 @@
from api.services.pricing.run_usage_response import format_public_usage_info
def test_format_public_usage_info():
usage_info = {
"llm": {
"SarvamLLMService#0|||sarvam-30b": {
"prompt_tokens": 100,
"completion_tokens": 50,
"total_tokens": 150,
}
},
"tts": {"ElevenLabsTTSService#0|||eleven_flash_v2_5": 42},
"stt": {},
"call_duration_seconds": 12.4,
}
result = format_public_usage_info(usage_info)
assert result["llm"]["SarvamLLMService#0|||sarvam-30b"]["prompt_tokens"] == 100
assert result["tts"]["ElevenLabsTTSService#0|||eleven_flash_v2_5"] == 42
assert result["stt"] == {}
assert result["call_duration_seconds"] == 12.4

114
api/tests/test_sarvam_service_factory.py Normal file
View file

@ -0,0 +1,114 @@
from types import SimpleNamespace
from unittest.mock import patch
import pytest
from pipecat.services.sarvam.llm import SarvamLLMService as RealSarvamLLMService
from pipecat.transcriptions.language import Language
from api.services.configuration.registry import (
SarvamLLMConfiguration,
ServiceProviders,
)
from api.services.pipecat.audio_config import AudioConfig
from api.services.pipecat.service_factory import (
create_llm_service,
create_llm_service_from_provider,
create_stt_service,
)
class TestSarvamLLMConfiguration:
def test_default_values(self):
config = SarvamLLMConfiguration(api_key="test-key")
assert config.provider == ServiceProviders.SARVAM
assert config.model == "sarvam-30b"
assert config.temperature == 0.5
def test_custom_model(self):
config = SarvamLLMConfiguration(api_key="test-key", model="sarvam-105b")
assert config.model == "sarvam-105b"
class TestSarvamLLMServiceFactory:
def test_create_sarvam_llm_service(self):
with patch(
"api.services.pipecat.service_factory.SarvamLLMService"
) as mock_service:
mock_service.Settings = RealSarvamLLMService.Settings
create_llm_service_from_provider(
provider=ServiceProviders.SARVAM.value,
model="sarvam-30b",
api_key="test-key",
)
assert mock_service.call_count == 1
kwargs = mock_service.call_args.kwargs
assert kwargs["api_key"] == "test-key"
assert kwargs["settings"].model == "sarvam-30b"
assert kwargs["settings"].temperature == 0.5
def test_create_sarvam_llm_service_passes_user_temperature(self):
with patch(
"api.services.pipecat.service_factory.SarvamLLMService"
) as mock_service:
mock_service.Settings = RealSarvamLLMService.Settings
create_llm_service_from_provider(
provider=ServiceProviders.SARVAM.value,
model="sarvam-30b",
api_key="test-key",
temperature=0.8,
)
kwargs = mock_service.call_args.kwargs
assert kwargs["settings"].temperature == 0.8
def test_create_llm_service_extracts_sarvam_temperature(self):
user_config = SimpleNamespace(
llm=SimpleNamespace(
provider=ServiceProviders.SARVAM.value,
model="sarvam-30b",
api_key="test-key",
temperature=0.7,
)
)
with patch(
"api.services.pipecat.service_factory.SarvamLLMService"
) as mock_service:
mock_service.Settings = RealSarvamLLMService.Settings
create_llm_service(user_config)
kwargs = mock_service.call_args.kwargs
assert kwargs["settings"].temperature == 0.7
class TestSarvamSTTServiceFactory:
@pytest.mark.parametrize(
"input_language,expected_language",
[
("unknown", None),
(None, None),
("hi-IN", Language.HI_IN),
("ne-IN", "ne-IN"),
],
)
def test_stt_language_mapping(self, input_language, expected_language):
user_config = SimpleNamespace(
stt=SimpleNamespace(
provider=ServiceProviders.SARVAM.value,
model="saaras:v3",
api_key="test-key",
language=input_language,
)
)
audio_config = AudioConfig(
transport_in_sample_rate=16000, transport_out_sample_rate=16000
)
with patch(
"api.services.pipecat.service_factory.SarvamSTTService"
) as mock_service:
create_stt_service(user_config, audio_config)
kwargs = mock_service.call_args.kwargs
assert kwargs["settings"].language == expected_language

12
ui/src/constants/languages.ts
View file

@ -84,6 +84,7 @@ export const LANGUAGE_DISPLAY_NAMES: Record<string, string> = {
"zh-CN": "Chinese (Simplified)",
"zh-TW": "Chinese (Traditional)",
// Sarvam Indian languages
"unknown": "Auto-detect",
"bn-IN": "Bengali",
"gu-IN": "Gujarati",
"hi-IN": "Hindi",
@ -95,4 +96,15 @@ export const LANGUAGE_DISPLAY_NAMES: Record<string, string> = {
"ta-IN": "Tamil",
"te-IN": "Telugu",
"as-IN": "Assamese",
"ur-IN": "Urdu",
"ne-IN": "Nepali",
"kok-IN": "Konkani",
"ks-IN": "Kashmiri",
"sd-IN": "Sindhi",
"sa-IN": "Sanskrit",
"sat-IN": "Santali",
"mni-IN": "Manipuri",
"brx-IN": "Bodo",
"mai-IN": "Maithili",
"doi-IN": "Dogri",
};