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Remove unused env variables (#2299)

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Chris Weaver 2024-09-02 13:29:14 -07:00 committed by GitHub
parent 14a9fecc64
commit 033ec0b6b1
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11 changed files with 9 additions and 173 deletions
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28
backend/danswer/configs/model_configs.py
View File

@ -51,33 +51,9 @@ CROSS_ENCODER_RANGE_MIN = 0
# Generative AI Model Configs
#####
# If changing GEN_AI_MODEL_PROVIDER or GEN_AI_MODEL_VERSION from the default,
# be sure to use one that is LiteLLM compatible:
# https://litellm.vercel.app/docs/providers/azure#completion---using-env-variables
# The provider is the prefix before / in the model argument
# NOTE: settings like `GEN_AI_MODEL_PROVIDER`, `GEN_AI_MODEL_VERSION`, etc. which
# used to be here are now solely configured via the UI and stored in Postgres.
# Additionally Danswer supports GPT4All and custom request library based models
# Set GEN_AI_MODEL_PROVIDER to "custom" to use the custom requests approach
# Set GEN_AI_MODEL_PROVIDER to "gpt4all" to use gpt4all models running locally
GEN_AI_MODEL_PROVIDER = os.environ.get("GEN_AI_MODEL_PROVIDER") or "openai"
# If using Azure, it's the engine name, for example: Danswer
GEN_AI_MODEL_VERSION = os.environ.get("GEN_AI_MODEL_VERSION")
# For secondary flows like extracting filters or deciding if a chunk is useful, we don't need
# as powerful of a model as say GPT-4 so we can use an alternative that is faster and cheaper
FAST_GEN_AI_MODEL_VERSION = os.environ.get("FAST_GEN_AI_MODEL_VERSION")
# If the Generative AI model requires an API key for access, otherwise can leave blank
GEN_AI_API_KEY = (
os.environ.get("GEN_AI_API_KEY", os.environ.get("OPENAI_API_KEY")) or None
)
# API Base, such as (for Azure): https://danswer.openai.azure.com/
GEN_AI_API_ENDPOINT = os.environ.get("GEN_AI_API_ENDPOINT") or None
# API Version, such as (for Azure): 2023-09-15-preview
GEN_AI_API_VERSION = os.environ.get("GEN_AI_API_VERSION") or None
# LiteLLM custom_llm_provider
GEN_AI_LLM_PROVIDER_TYPE = os.environ.get("GEN_AI_LLM_PROVIDER_TYPE") or None
# Override the auto-detection of LLM max context length
GEN_AI_MAX_TOKENS = int(os.environ.get("GEN_AI_MAX_TOKENS") or 0) or None

9
backend/danswer/llm/chat_llm.py
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@ -25,9 +25,6 @@ from langchain_core.messages.tool import ToolMessage
from danswer.configs.app_configs import LOG_ALL_MODEL_INTERACTIONS
from danswer.configs.app_configs import LOG_DANSWER_MODEL_INTERACTIONS
from danswer.configs.model_configs import DISABLE_LITELLM_STREAMING
from danswer.configs.model_configs import GEN_AI_API_ENDPOINT
from danswer.configs.model_configs import GEN_AI_API_VERSION
from danswer.configs.model_configs import GEN_AI_LLM_PROVIDER_TYPE
from danswer.configs.model_configs import GEN_AI_TEMPERATURE
from danswer.llm.interfaces import LLM
from danswer.llm.interfaces import LLMConfig
@ -192,10 +189,10 @@ class DefaultMultiLLM(LLM):
timeout: int,
model_provider: str,
model_name: str,
api_base: str | None = None,
api_version: str | None = None,
max_output_tokens: int | None = None,
api_base: str | None = GEN_AI_API_ENDPOINT,
api_version: str | None = GEN_AI_API_VERSION,
custom_llm_provider: str | None = GEN_AI_LLM_PROVIDER_TYPE,
custom_llm_provider: str | None = None,
temperature: float = GEN_AI_TEMPERATURE,
custom_config: dict[str, str] | None = None,
extra_headers: dict[str, str] | None = None,

3
backend/danswer/llm/custom_llm.py
View File

@ -7,7 +7,6 @@ from langchain_core.messages import AIMessage
from langchain_core.messages import BaseMessage
from requests import Timeout
from danswer.configs.model_configs import GEN_AI_API_ENDPOINT
from danswer.configs.model_configs import GEN_AI_NUM_RESERVED_OUTPUT_TOKENS
from danswer.llm.interfaces import LLM
from danswer.llm.interfaces import ToolChoiceOptions
@ -37,7 +36,7 @@ class CustomModelServer(LLM):
# Not used here but you probably want a model server that isn't completely open
api_key: str | None,
timeout: int,
endpoint: str | None = GEN_AI_API_ENDPOINT,
endpoint: str,
max_output_tokens: int = GEN_AI_NUM_RESERVED_OUTPUT_TOKENS,
):
if not endpoint:

80
backend/danswer/llm/llm_initialization.py
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@ -1,80 +0,0 @@
from sqlalchemy.orm import Session
from danswer.configs.app_configs import DISABLE_GENERATIVE_AI
from danswer.configs.model_configs import FAST_GEN_AI_MODEL_VERSION
from danswer.configs.model_configs import GEN_AI_API_ENDPOINT
from danswer.configs.model_configs import GEN_AI_API_KEY
from danswer.configs.model_configs import GEN_AI_API_VERSION
from danswer.configs.model_configs import GEN_AI_MODEL_PROVIDER
from danswer.configs.model_configs import GEN_AI_MODEL_VERSION
from danswer.db.llm import fetch_existing_llm_providers
from danswer.db.llm import update_default_provider
from danswer.db.llm import upsert_llm_provider
from danswer.llm.llm_provider_options import AZURE_PROVIDER_NAME
from danswer.llm.llm_provider_options import BEDROCK_PROVIDER_NAME
from danswer.llm.llm_provider_options import fetch_available_well_known_llms
from danswer.server.manage.llm.models import LLMProviderUpsertRequest
from danswer.utils.logger import setup_logger
logger = setup_logger()
def load_llm_providers(db_session: Session) -> None:
existing_providers = fetch_existing_llm_providers(db_session)
if existing_providers:
return
if not GEN_AI_API_KEY or DISABLE_GENERATIVE_AI:
return
well_known_provider_name_to_provider = {
provider.name: provider
for provider in fetch_available_well_known_llms()
if provider.name != BEDROCK_PROVIDER_NAME
}
if GEN_AI_MODEL_PROVIDER not in well_known_provider_name_to_provider:
logger.error(f"Cannot auto-transition LLM provider: {GEN_AI_MODEL_PROVIDER}")
return None
# Azure provider requires custom model names,
# OpenAI / anthropic can just use the defaults
model_names = (
[
name
for name in [
GEN_AI_MODEL_VERSION,
FAST_GEN_AI_MODEL_VERSION,
]
if name
]
if GEN_AI_MODEL_PROVIDER == AZURE_PROVIDER_NAME
else None
)
well_known_provider = well_known_provider_name_to_provider[GEN_AI_MODEL_PROVIDER]
llm_provider_request = LLMProviderUpsertRequest(
name=well_known_provider.display_name,
provider=GEN_AI_MODEL_PROVIDER,
api_key=GEN_AI_API_KEY,
api_base=GEN_AI_API_ENDPOINT,
api_version=GEN_AI_API_VERSION,
custom_config={},
default_model_name=(
GEN_AI_MODEL_VERSION
or well_known_provider.default_model
or well_known_provider.llm_names[0]
),
fast_default_model_name=(
FAST_GEN_AI_MODEL_VERSION or well_known_provider.default_fast_model
),
model_names=model_names,
is_public=True,
display_model_names=[],
)
llm_provider = upsert_llm_provider(db_session, llm_provider_request)
update_default_provider(db_session, llm_provider.id)
logger.notice(
f"Migrated LLM provider from env variables for provider '{GEN_AI_MODEL_PROVIDER}'"
)

5
backend/danswer/llm/utils.py
View File

@ -32,7 +32,6 @@ from litellm.exceptions import UnprocessableEntityError # type: ignore
from danswer.configs.constants import MessageType
from danswer.configs.model_configs import GEN_AI_MAX_TOKENS
from danswer.configs.model_configs import GEN_AI_MODEL_FALLBACK_MAX_TOKENS
from danswer.configs.model_configs import GEN_AI_MODEL_PROVIDER
from danswer.configs.model_configs import GEN_AI_NUM_RESERVED_OUTPUT_TOKENS
from danswer.db.models import ChatMessage
from danswer.file_store.models import ChatFileType
@ -331,7 +330,7 @@ def test_llm(llm: LLM) -> str | None:
def get_llm_max_tokens(
model_map: dict,
model_name: str,
model_provider: str = GEN_AI_MODEL_PROVIDER,
model_provider: str,
) -> int:
"""Best effort attempt to get the max tokens for the LLM"""
if GEN_AI_MAX_TOKENS:
@ -371,7 +370,7 @@ def get_llm_max_tokens(
def get_llm_max_output_tokens(
model_map: dict,
model_name: str,
model_provider: str = GEN_AI_MODEL_PROVIDER,
model_provider: str,
) -> int:
"""Best effort attempt to get the max output tokens for the LLM"""
try:

4
backend/danswer/main.py
View File

@ -62,7 +62,6 @@ from danswer.document_index.interfaces import DocumentIndex
from danswer.dynamic_configs.factory import get_dynamic_config_store
from danswer.dynamic_configs.interface import ConfigNotFoundError
from danswer.indexing.models import IndexingSetting
from danswer.llm.llm_initialization import load_llm_providers
from danswer.natural_language_processing.search_nlp_models import EmbeddingModel
from danswer.natural_language_processing.search_nlp_models import warm_up_bi_encoder
from danswer.natural_language_processing.search_nlp_models import warm_up_cross_encoder
@ -182,9 +181,6 @@ def setup_postgres(db_session: Session) -> None:
logger.notice("Verifying default standard answer category exists.")
create_initial_default_standard_answer_category(db_session)
logger.notice("Loading LLM providers from env variables")
load_llm_providers(db_session)
logger.notice("Loading default Prompts and Personas")
delete_old_default_personas(db_session)
load_chat_yamls()

14
deployment/docker_compose/docker-compose.dev.yml
View File

@ -35,13 +35,6 @@ services:
- OPENID_CONFIG_URL=${OPENID_CONFIG_URL:-}
- TRACK_EXTERNAL_IDP_EXPIRY=${TRACK_EXTERNAL_IDP_EXPIRY:-}
# Gen AI Settings
- GEN_AI_MODEL_PROVIDER=${GEN_AI_MODEL_PROVIDER:-}
- GEN_AI_MODEL_VERSION=${GEN_AI_MODEL_VERSION:-}
- FAST_GEN_AI_MODEL_VERSION=${FAST_GEN_AI_MODEL_VERSION:-}
- GEN_AI_API_KEY=${GEN_AI_API_KEY:-}
- GEN_AI_API_ENDPOINT=${GEN_AI_API_ENDPOINT:-}
- GEN_AI_API_VERSION=${GEN_AI_API_VERSION:-}
- GEN_AI_LLM_PROVIDER_TYPE=${GEN_AI_LLM_PROVIDER_TYPE:-}
- GEN_AI_MAX_TOKENS=${GEN_AI_MAX_TOKENS:-}
- QA_TIMEOUT=${QA_TIMEOUT:-}
- MAX_CHUNKS_FED_TO_CHAT=${MAX_CHUNKS_FED_TO_CHAT:-}
@ -120,13 +113,6 @@ services:
environment:
- ENCRYPTION_KEY_SECRET=${ENCRYPTION_KEY_SECRET:-}
# Gen AI Settings (Needed by DanswerBot)
- GEN_AI_MODEL_PROVIDER=${GEN_AI_MODEL_PROVIDER:-}
- GEN_AI_MODEL_VERSION=${GEN_AI_MODEL_VERSION:-}
- FAST_GEN_AI_MODEL_VERSION=${FAST_GEN_AI_MODEL_VERSION:-}
- GEN_AI_API_KEY=${GEN_AI_API_KEY:-}
- GEN_AI_API_ENDPOINT=${GEN_AI_API_ENDPOINT:-}
- GEN_AI_API_VERSION=${GEN_AI_API_VERSION:-}
- GEN_AI_LLM_PROVIDER_TYPE=${GEN_AI_LLM_PROVIDER_TYPE:-}
- GEN_AI_MAX_TOKENS=${GEN_AI_MAX_TOKENS:-}
- QA_TIMEOUT=${QA_TIMEOUT:-}
- MAX_CHUNKS_FED_TO_CHAT=${MAX_CHUNKS_FED_TO_CHAT:-}

14
deployment/docker_compose/docker-compose.gpu-dev.yml
View File

@ -32,13 +32,6 @@ services:
- EMAIL_FROM=${EMAIL_FROM:-}
- TRACK_EXTERNAL_IDP_EXPIRY=${TRACK_EXTERNAL_IDP_EXPIRY:-}
# Gen AI Settings
- GEN_AI_MODEL_PROVIDER=${GEN_AI_MODEL_PROVIDER:-}
- GEN_AI_MODEL_VERSION=${GEN_AI_MODEL_VERSION:-}
- FAST_GEN_AI_MODEL_VERSION=${FAST_GEN_AI_MODEL_VERSION:-}
- GEN_AI_API_KEY=${GEN_AI_API_KEY:-}
- GEN_AI_API_ENDPOINT=${GEN_AI_API_ENDPOINT:-}
- GEN_AI_API_VERSION=${GEN_AI_API_VERSION:-}
- GEN_AI_LLM_PROVIDER_TYPE=${GEN_AI_LLM_PROVIDER_TYPE:-}
- GEN_AI_MAX_TOKENS=${GEN_AI_MAX_TOKENS:-}
- QA_TIMEOUT=${QA_TIMEOUT:-}
- MAX_CHUNKS_FED_TO_CHAT=${MAX_CHUNKS_FED_TO_CHAT:-}
@ -112,13 +105,6 @@ services:
environment:
- ENCRYPTION_KEY_SECRET=${ENCRYPTION_KEY_SECRET:-}
# Gen AI Settings (Needed by DanswerBot)
- GEN_AI_MODEL_PROVIDER=${GEN_AI_MODEL_PROVIDER:-}
- GEN_AI_MODEL_VERSION=${GEN_AI_MODEL_VERSION:-}
- FAST_GEN_AI_MODEL_VERSION=${FAST_GEN_AI_MODEL_VERSION:-}
- GEN_AI_API_KEY=${GEN_AI_API_KEY:-}
- GEN_AI_API_ENDPOINT=${GEN_AI_API_ENDPOINT:-}
- GEN_AI_API_VERSION=${GEN_AI_API_VERSION:-}
- GEN_AI_LLM_PROVIDER_TYPE=${GEN_AI_LLM_PROVIDER_TYPE:-}
- GEN_AI_MAX_TOKENS=${GEN_AI_MAX_TOKENS:-}
- QA_TIMEOUT=${QA_TIMEOUT:-}
- MAX_CHUNKS_FED_TO_CHAT=${MAX_CHUNKS_FED_TO_CHAT:-}

11
deployment/docker_compose/env.prod.template
View File

@ -7,16 +7,7 @@
WEB_DOMAIN=http://localhost:3000
# Generative AI settings, uncomment as needed, will work with defaults
GEN_AI_MODEL_PROVIDER=openai
GEN_AI_MODEL_VERSION=gpt-4
# Provide this as a global default/backup, this can also be set via the UI
#GEN_AI_API_KEY=
# Set to use Azure OpenAI or other services, such as https://danswer.openai.azure.com/
#GEN_AI_API_ENDPOINT=
# Set up to use a specific API version, such as 2023-09-15-preview (example taken from Azure)
#GEN_AI_API_VERSION=
# NOTE: Generative AI configurations are done via the UI now
# If you want to setup a slack bot to answer questions automatically in Slack
# channels it is added to, you must specify the two below.

7
deployment/helm/values.yaml
View File

@ -392,13 +392,6 @@ configMap:
# SMTP_PASS: "" # 'your-gmail-password'
EMAIL_FROM: "" # 'your-email@company.com' SMTP_USER missing used instead
# Gen AI Settings
GEN_AI_MODEL_PROVIDER: ""
GEN_AI_MODEL_VERSION: ""
FAST_GEN_AI_MODEL_VERSION: ""
# GEN_AI_API_KEY: ""
GEN_AI_API_ENDPOINT: ""
GEN_AI_API_VERSION: ""
GEN_AI_LLM_PROVIDER_TYPE: ""
GEN_AI_MAX_TOKENS: ""
QA_TIMEOUT: "60"
MAX_CHUNKS_FED_TO_CHAT: ""

7
deployment/kubernetes/env-configmap.yaml
View File

@ -14,13 +14,6 @@ data:
SMTP_PASS: "" # 'your-gmail-password'
EMAIL_FROM: "" # 'your-email@company.com' SMTP_USER missing used instead
# Gen AI Settings
GEN_AI_MODEL_PROVIDER: ""
GEN_AI_MODEL_VERSION: ""
FAST_GEN_AI_MODEL_VERSION: ""
GEN_AI_API_KEY: ""
GEN_AI_API_ENDPOINT: ""
GEN_AI_API_VERSION: ""
GEN_AI_LLM_PROVIDER_TYPE: ""
GEN_AI_MAX_TOKENS: ""
QA_TIMEOUT: "60"
MAX_CHUNKS_FED_TO_CHAT: ""