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Support image indexing customization (#4261)

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* working well

* k

* ready to go

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* minor nits

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* quick fix

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pablonyx 2025-03-12 13:03:45 -07:00 committed by GitHub
parent 0153ff6b51
commit 5883336d5e
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18 changed files with 482 additions and 45 deletions
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45
backend/alembic/versions/df46c75b714e_add_default_vision_provider_to_llm_.py Normal file
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@ -0,0 +1,45 @@
"""add_default_vision_provider_to_llm_provider
Revision ID: df46c75b714e
Revises: 3934b1bc7b62
Create Date: 2025-03-11 16:20:19.038945
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision = "df46c75b714e"
down_revision = "3934b1bc7b62"
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"llm_provider",
sa.Column(
"is_default_vision_provider",
sa.Boolean(),
nullable=True,
server_default=sa.false(),
),
)
op.add_column(
"llm_provider", sa.Column("default_vision_model", sa.String(), nullable=True)
)
# Add unique constraint for is_default_vision_provider
op.create_unique_constraint(
"uq_llm_provider_is_default_vision_provider",
"llm_provider",
["is_default_vision_provider"],
)
def downgrade() -> None:
op.drop_constraint(
"uq_llm_provider_is_default_vision_provider", "llm_provider", type_="unique"
)
op.drop_column("llm_provider", "default_vision_model")
op.drop_column("llm_provider", "is_default_vision_provider")

21
backend/onyx/configs/app_configs.py
View File

@ -8,6 +8,9 @@ from onyx.configs.constants import AuthType
from onyx.configs.constants import DocumentIndexType
from onyx.configs.constants import QueryHistoryType
from onyx.file_processing.enums import HtmlBasedConnectorTransformLinksStrategy
from onyx.prompts.image_analysis import DEFAULT_IMAGE_ANALYSIS_SYSTEM_PROMPT
from onyx.prompts.image_analysis import DEFAULT_IMAGE_SUMMARIZATION_SYSTEM_PROMPT
from onyx.prompts.image_analysis import DEFAULT_IMAGE_SUMMARIZATION_USER_PROMPT
#####
# App Configs
@ -646,3 +649,21 @@ DEFAULT_IMAGE_ANALYSIS_MAX_SIZE_MB = 20
# Number of pre-provisioned tenants to maintain
TARGET_AVAILABLE_TENANTS = int(os.environ.get("TARGET_AVAILABLE_TENANTS", "5"))
# Image summarization configuration
IMAGE_SUMMARIZATION_SYSTEM_PROMPT = os.environ.get(
"IMAGE_SUMMARIZATION_SYSTEM_PROMPT",
DEFAULT_IMAGE_SUMMARIZATION_SYSTEM_PROMPT,
)
# The user prompt for image summarization - the image filename will be automatically prepended
IMAGE_SUMMARIZATION_USER_PROMPT = os.environ.get(
"IMAGE_SUMMARIZATION_USER_PROMPT",
DEFAULT_IMAGE_SUMMARIZATION_USER_PROMPT,
)
IMAGE_ANALYSIS_SYSTEM_PROMPT = os.environ.get(
"IMAGE_ANALYSIS_SYSTEM_PROMPT",
DEFAULT_IMAGE_ANALYSIS_SYSTEM_PROMPT,
)

1
backend/onyx/connectors/vision_enabled_connector.py
View File

@ -30,6 +30,7 @@ class VisionEnabledConnector:
Sets self.image_analysis_llm to the LLM instance or None if disabled.
"""
self.image_analysis_llm: LLM | None = None
if get_image_extraction_and_analysis_enabled():
try:
self.image_analysis_llm = get_default_llm_with_vision()

2
backend/onyx/context/search/postprocessing/postprocessing.py
View File

@ -10,6 +10,7 @@ from langchain_core.messages import SystemMessage
from onyx.chat.models import SectionRelevancePiece
from onyx.configs.app_configs import BLURB_SIZE
from onyx.configs.app_configs import IMAGE_ANALYSIS_SYSTEM_PROMPT
from onyx.configs.constants import RETURN_SEPARATOR
from onyx.configs.llm_configs import get_search_time_image_analysis_enabled
from onyx.configs.model_configs import CROSS_ENCODER_RANGE_MAX
@ -31,7 +32,6 @@ from onyx.file_store.file_store import get_default_file_store
from onyx.llm.interfaces import LLM
from onyx.llm.utils import message_to_string
from onyx.natural_language_processing.search_nlp_models import RerankingModel
from onyx.prompts.image_analysis import IMAGE_ANALYSIS_SYSTEM_PROMPT
from onyx.secondary_llm_flows.chunk_usefulness import llm_batch_eval_sections
from onyx.utils.logger import setup_logger
from onyx.utils.threadpool_concurrency import FunctionCall

48
backend/onyx/db/llm.py
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@ -13,6 +13,7 @@ from onyx.db.models import SearchSettings
from onyx.db.models import Tool as ToolModel
from onyx.db.models import User
from onyx.db.models import User__UserGroup
from onyx.llm.utils import model_supports_image_input
from onyx.server.manage.embedding.models import CloudEmbeddingProvider
from onyx.server.manage.embedding.models import CloudEmbeddingProviderCreationRequest
from onyx.server.manage.llm.models import FullLLMProvider
@ -187,6 +188,17 @@ def fetch_default_provider(db_session: Session) -> FullLLMProvider | None:
return FullLLMProvider.from_model(provider_model)
def fetch_default_vision_provider(db_session: Session) -> FullLLMProvider | None:
provider_model = db_session.scalar(
select(LLMProviderModel).where(
LLMProviderModel.is_default_vision_provider == True # noqa: E712
)
)
if not provider_model:
return None
return FullLLMProvider.from_model(provider_model)
def fetch_provider(db_session: Session, provider_name: str) -> FullLLMProvider | None:
provider_model = db_session.scalar(
select(LLMProviderModel).where(LLMProviderModel.name == provider_name)
@ -246,3 +258,39 @@ def update_default_provider(provider_id: int, db_session: Session) -> None:
new_default.is_default_provider = True
db_session.commit()
def update_default_vision_provider(
provider_id: int, vision_model: str | None, db_session: Session
) -> None:
new_default = db_session.scalar(
select(LLMProviderModel).where(LLMProviderModel.id == provider_id)
)
if not new_default:
raise ValueError(f"LLM Provider with id {provider_id} does not exist")
# Validate that the specified vision model supports image input
model_to_validate = vision_model or new_default.default_model_name
if model_to_validate:
if not model_supports_image_input(model_to_validate, new_default.provider):
raise ValueError(
f"Model '{model_to_validate}' for provider '{new_default.provider}' does not support image input"
)
else:
raise ValueError(
f"Model '{vision_model}' is not a valid model for provider '{new_default.provider}'"
)
existing_default = db_session.scalar(
select(LLMProviderModel).where(
LLMProviderModel.is_default_vision_provider == True # noqa: E712
)
)
if existing_default:
existing_default.is_default_vision_provider = None
# required to ensure that the below does not cause a unique constraint violation
db_session.flush()
new_default.is_default_vision_provider = True
new_default.default_vision_model = vision_model
db_session.commit()

4
backend/onyx/db/models.py
View File

@ -1489,6 +1489,10 @@ class LLMProvider(Base):
# should only be set for a single provider
is_default_provider: Mapped[bool | None] = mapped_column(Boolean, unique=True)
is_default_vision_provider: Mapped[bool | None] = mapped_column(
Boolean, unique=True
)
default_vision_model: Mapped[str | None] = mapped_column(String, nullable=True)
# EE only
is_public: Mapped[bool] = mapped_column(Boolean, nullable=False, default=True)
groups: Mapped[list["UserGroup"]] = relationship(

11
backend/onyx/file_processing/image_summarization.py
View File

@ -6,10 +6,10 @@ from langchain_core.messages import HumanMessage
from langchain_core.messages import SystemMessage
from PIL import Image
from onyx.configs.app_configs import IMAGE_SUMMARIZATION_SYSTEM_PROMPT
from onyx.configs.app_configs import IMAGE_SUMMARIZATION_USER_PROMPT
from onyx.llm.interfaces import LLM
from onyx.llm.utils import message_to_string
from onyx.prompts.image_analysis import IMAGE_SUMMARIZATION_SYSTEM_PROMPT
from onyx.prompts.image_analysis import IMAGE_SUMMARIZATION_USER_PROMPT
from onyx.utils.logger import setup_logger
logger = setup_logger()
@ -62,7 +62,7 @@ def summarize_image_with_error_handling(
image_data: The raw image bytes
context_name: Name or title of the image for context
system_prompt: System prompt to use for the LLM
user_prompt_template: Template for the user prompt, should contain {title} placeholder
user_prompt_template: User prompt to use (without title)
Returns:
The image summary text, or None if summarization failed or is disabled
@ -70,7 +70,10 @@ def summarize_image_with_error_handling(
if llm is None:
return None
user_prompt = user_prompt_template.format(title=context_name)
# Prepend the image filename to the user prompt
user_prompt = (
f"The image has the file name '{context_name}'.\n{user_prompt_template}"
)
return summarize_image_pipeline(llm, image_data, user_prompt, system_prompt)

78
backend/onyx/llm/factory.py
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@ -5,7 +5,9 @@ from onyx.configs.app_configs import DISABLE_GENERATIVE_AI
from onyx.configs.model_configs import GEN_AI_MODEL_FALLBACK_MAX_TOKENS
from onyx.configs.model_configs import GEN_AI_TEMPERATURE
from onyx.db.engine import get_session_context_manager
from onyx.db.engine import get_session_with_current_tenant
from onyx.db.llm import fetch_default_provider
from onyx.db.llm import fetch_default_vision_provider
from onyx.db.llm import fetch_existing_llm_providers
from onyx.db.llm import fetch_provider
from onyx.db.models import Persona
@ -14,6 +16,7 @@ from onyx.llm.exceptions import GenAIDisabledException
from onyx.llm.interfaces import LLM
from onyx.llm.override_models import LLMOverride
from onyx.llm.utils import model_supports_image_input
from onyx.server.manage.llm.models import FullLLMProvider
from onyx.utils.headers import build_llm_extra_headers
from onyx.utils.logger import setup_logger
from onyx.utils.long_term_log import LongTermLogger
@ -94,40 +97,61 @@ def get_default_llm_with_vision(
additional_headers: dict[str, str] | None = None,
long_term_logger: LongTermLogger | None = None,
) -> LLM | None:
"""Get an LLM that supports image input, with the following priority:
1. Use the designated default vision provider if it exists and supports image input
2. Fall back to the first LLM provider that supports image input
Returns None if no providers exist or if no provider supports images.
"""
if DISABLE_GENERATIVE_AI:
raise GenAIDisabledException()
with get_session_context_manager() as db_session:
llm_providers = fetch_existing_llm_providers(db_session)
if not llm_providers:
return None
for provider in llm_providers:
model_name = provider.default_model_name
fast_model_name = (
provider.fast_default_model_name or provider.default_model_name
def create_vision_llm(provider: FullLLMProvider, model: str) -> LLM:
"""Helper to create an LLM if the provider supports image input."""
return get_llm(
provider=provider.provider,
model=model,
deployment_name=provider.deployment_name,
api_key=provider.api_key,
api_base=provider.api_base,
api_version=provider.api_version,
custom_config=provider.custom_config,
timeout=timeout,
temperature=temperature,
additional_headers=additional_headers,
long_term_logger=long_term_logger,
)
if not model_name or not fast_model_name:
continue
if model_supports_image_input(model_name, provider.provider):
return get_llm(
provider=provider.provider,
model=model_name,
deployment_name=provider.deployment_name,
api_key=provider.api_key,
api_base=provider.api_base,
api_version=provider.api_version,
custom_config=provider.custom_config,
timeout=timeout,
temperature=temperature,
additional_headers=additional_headers,
long_term_logger=long_term_logger,
with get_session_with_current_tenant() as db_session:
# Try the default vision provider first
default_provider = fetch_default_vision_provider(db_session)
if (
default_provider
and default_provider.default_vision_model
and model_supports_image_input(
default_provider.default_vision_model, default_provider.provider
)
):
return create_vision_llm(
default_provider, default_provider.default_vision_model
)
raise ValueError("No LLM provider found that supports image input")
# Fall back to searching all providers
providers = fetch_existing_llm_providers(db_session)
if not providers:
return None
# Find the first provider that supports image input
for provider in providers:
if provider.default_vision_model and model_supports_image_input(
provider.default_vision_model, provider.provider
):
return create_vision_llm(
FullLLMProvider.from_model(provider), provider.default_vision_model
)
return None
def get_default_llms(

7
backend/onyx/prompts/image_analysis.py
View File

@ -1,5 +1,5 @@
# Used for creating embeddings of images for vector search
IMAGE_SUMMARIZATION_SYSTEM_PROMPT = """
DEFAULT_IMAGE_SUMMARIZATION_SYSTEM_PROMPT = """
You are an assistant for summarizing images for retrieval.
Summarize the content of the following image and be as precise as possible.
The summary will be embedded and used to retrieve the original image.
@ -7,14 +7,13 @@ Therefore, write a concise summary of the image that is optimized for retrieval.
"""
# Prompt for generating image descriptions with filename context
IMAGE_SUMMARIZATION_USER_PROMPT = """
The image has the file name '{title}'.
DEFAULT_IMAGE_SUMMARIZATION_USER_PROMPT = """
Describe precisely and concisely what the image shows.
"""
# Used for analyzing images in response to user queries at search time
IMAGE_ANALYSIS_SYSTEM_PROMPT = (
DEFAULT_IMAGE_ANALYSIS_SYSTEM_PROMPT = (
"You are an AI assistant specialized in describing images.\n"
"You will receive a user question plus an image URL. Provide a concise textual answer.\n"
"Focus on aspects of the image that are relevant to the user's question.\n"

59
backend/onyx/server/manage/llm/api.py
View File

@ -14,6 +14,7 @@ from onyx.db.llm import fetch_existing_llm_providers_for_user
from onyx.db.llm import fetch_provider
from onyx.db.llm import remove_llm_provider
from onyx.db.llm import update_default_provider
from onyx.db.llm import update_default_vision_provider
from onyx.db.llm import upsert_llm_provider
from onyx.db.models import User
from onyx.llm.factory import get_default_llms
@ -21,11 +22,13 @@ from onyx.llm.factory import get_llm
from onyx.llm.llm_provider_options import fetch_available_well_known_llms
from onyx.llm.llm_provider_options import WellKnownLLMProviderDescriptor
from onyx.llm.utils import litellm_exception_to_error_msg
from onyx.llm.utils import model_supports_image_input
from onyx.llm.utils import test_llm
from onyx.server.manage.llm.models import FullLLMProvider
from onyx.server.manage.llm.models import LLMProviderDescriptor
from onyx.server.manage.llm.models import LLMProviderUpsertRequest
from onyx.server.manage.llm.models import TestLLMRequest
from onyx.server.manage.llm.models import VisionProviderResponse
from onyx.utils.logger import setup_logger
from onyx.utils.threadpool_concurrency import run_functions_tuples_in_parallel
@ -186,6 +189,62 @@ def set_provider_as_default(
update_default_provider(provider_id=provider_id, db_session=db_session)
@admin_router.post("/provider/{provider_id}/default-vision")
def set_provider_as_default_vision(
provider_id: int,
vision_model: str
| None = Query(None, description="The default vision model to use"),
_: User | None = Depends(current_admin_user),
db_session: Session = Depends(get_session),
) -> None:
update_default_vision_provider(
provider_id=provider_id, vision_model=vision_model, db_session=db_session
)
@admin_router.get("/vision-providers")
def get_vision_capable_providers(
_: User | None = Depends(current_admin_user),
db_session: Session = Depends(get_session),
) -> list[VisionProviderResponse]:
"""Return a list of LLM providers and their models that support image input"""
providers = fetch_existing_llm_providers(db_session)
vision_providers = []
logger.info("Fetching vision-capable providers")
for provider in providers:
vision_models = []
# Check model names in priority order
model_names_to_check = []
if provider.model_names:
model_names_to_check = provider.model_names
elif provider.display_model_names:
model_names_to_check = provider.display_model_names
elif provider.default_model_name:
model_names_to_check = [provider.default_model_name]
# Check each model for vision capability
for model_name in model_names_to_check:
if model_supports_image_input(model_name, provider.provider):
vision_models.append(model_name)
logger.debug(f"Vision model found: {provider.provider}/{model_name}")
# Only include providers with at least one vision-capable model
if vision_models:
provider_dict = FullLLMProvider.from_model(provider).model_dump()
provider_dict["vision_models"] = vision_models
logger.info(
f"Vision provider: {provider.provider} with models: {vision_models}"
)
vision_providers.append(VisionProviderResponse(**provider_dict))
logger.info(f"Found {len(vision_providers)} vision-capable providers")
return vision_providers
"""Endpoints for all"""

21
backend/onyx/server/manage/llm/models.py
View File

@ -34,6 +34,8 @@ class LLMProviderDescriptor(BaseModel):
default_model_name: str
fast_default_model_name: str | None
is_default_provider: bool | None
is_default_vision_provider: bool | None
default_vision_model: str | None
display_model_names: list[str] | None
@classmethod
@ -46,11 +48,10 @@ class LLMProviderDescriptor(BaseModel):
default_model_name=llm_provider_model.default_model_name,
fast_default_model_name=llm_provider_model.fast_default_model_name,
is_default_provider=llm_provider_model.is_default_provider,
model_names=(
llm_provider_model.model_names
or fetch_models_for_provider(llm_provider_model.provider)
or [llm_provider_model.default_model_name]
),
is_default_vision_provider=llm_provider_model.is_default_vision_provider,
default_vision_model=llm_provider_model.default_vision_model,
model_names=llm_provider_model.model_names
or fetch_models_for_provider(llm_provider_model.provider),
display_model_names=llm_provider_model.display_model_names,
)
@ -68,6 +69,7 @@ class LLMProvider(BaseModel):
groups: list[int] = Field(default_factory=list)
display_model_names: list[str] | None = None
deployment_name: str | None = None
default_vision_model: str | None = None
class LLMProviderUpsertRequest(LLMProvider):
@ -79,6 +81,7 @@ class LLMProviderUpsertRequest(LLMProvider):
class FullLLMProvider(LLMProvider):
id: int
is_default_provider: bool | None = None
is_default_vision_provider: bool | None = None
model_names: list[str]
@classmethod
@ -94,6 +97,8 @@ class FullLLMProvider(LLMProvider):
default_model_name=llm_provider_model.default_model_name,
fast_default_model_name=llm_provider_model.fast_default_model_name,
is_default_provider=llm_provider_model.is_default_provider,
is_default_vision_provider=llm_provider_model.is_default_vision_provider,
default_vision_model=llm_provider_model.default_vision_model,
display_model_names=llm_provider_model.display_model_names,
model_names=(
llm_provider_model.model_names
@ -104,3 +109,9 @@ class FullLLMProvider(LLMProvider):
groups=[group.id for group in llm_provider_model.groups],
deployment_name=llm_provider_model.deployment_name,
)
class VisionProviderResponse(FullLLMProvider):
"""Response model for vision providers endpoint, including vision-specific fields."""
vision_models: list[str]

6
web/src/app/admin/configuration/llm/interfaces.ts
View File

@ -49,6 +49,8 @@ export interface LLMProvider {
groups: number[];
display_model_names: string[] | null;
deployment_name: string | null;
default_vision_model: string | null;
is_default_vision_provider: boolean | null;
}
export interface FullLLMProvider extends LLMProvider {
@ -58,6 +60,10 @@ export interface FullLLMProvider extends LLMProvider {
icon?: React.FC<{ size?: number; className?: string }>;
}
export interface VisionProvider extends FullLLMProvider {
vision_models: string[];
}
export interface LLMProviderDescriptor {
name: string;
provider: string;

55
web/src/app/admin/settings/SettingsForm.tsx
View File

@ -13,6 +13,9 @@ import { usePaidEnterpriseFeaturesEnabled } from "@/components/settings/usePaidE
import { Modal } from "@/components/Modal";
import { NEXT_PUBLIC_CLOUD_ENABLED } from "@/lib/constants";
import { AnonymousUserPath } from "./AnonymousUserPath";
import { useChatContext } from "@/components/context/ChatContext";
import { LLMSelector } from "@/components/llm/LLMSelector";
import { useVisionProviders } from "./hooks/useVisionProviders";
export function Checkbox({
label,
@ -111,6 +114,14 @@ export function SettingsForm() {
const { popup, setPopup } = usePopup();
const isEnterpriseEnabled = usePaidEnterpriseFeaturesEnabled();
// Pass setPopup to the hook
const {
visionProviders,
visionLLM,
setVisionLLM,
updateDefaultVisionProvider,
} = useVisionProviders(setPopup);
const combinedSettings = useContext(SettingsContext);
useEffect(() => {
@ -120,6 +131,7 @@ export function SettingsForm() {
combinedSettings.settings.maximum_chat_retention_days?.toString() || ""
);
}
// We don't need to fetch vision providers here anymore as the hook handles it
}, []);
if (!settings) {
@ -354,6 +366,49 @@ export function SettingsForm() {
id="image-analysis-max-size"
placeholder="Enter maximum size in MB"
/>
{/* Default Vision LLM Section */}
<div className="mt-4">
<Label>Default Vision LLM</Label>
<SubLabel>
Select the default LLM to use for image analysis. This model will be
utilized during image indexing and at query time for search results,
if the above settings are enabled.
</SubLabel>
<div className="mt-2 max-w-xs">
{!visionProviders || visionProviders.length === 0 ? (
<div className="text-sm text-gray-500">
No vision providers found. Please add a vision provider.
</div>
) : visionProviders.length > 0 ? (
<>
<LLMSelector
userSettings={false}
llmProviders={visionProviders.map((provider) => ({
...provider,
model_names: provider.vision_models,
display_model_names: provider.vision_models,
}))}
currentLlm={visionLLM}
onSelect={(value) => setVisionLLM(value)}
/>
<Button
onClick={() => updateDefaultVisionProvider(visionLLM)}
className="mt-2"
variant="default"
size="sm"
>
Set Default Vision LLM
</Button>
</>
) : (
<div className="text-sm text-gray-500">
No vision-capable LLMs found. Please add an LLM provider that
supports image input.
</div>
)}
</div>
</div>
</div>
</div>
);

123
web/src/app/admin/settings/hooks/useVisionProviders.ts Normal file
View File

@ -0,0 +1,123 @@
import { useState, useEffect, useCallback } from "react";
import { VisionProvider } from "@/app/admin/configuration/llm/interfaces";
import {
fetchVisionProviders,
setDefaultVisionProvider,
} from "@/lib/llm/visionLLM";
import { destructureValue, structureValue } from "@/lib/llm/utils";
// Define a type for the popup setter function
type SetPopup = (popup: {
message: string;
type: "success" | "error" | "info";
}) => void;
// Accept the setPopup function as a parameter
export function useVisionProviders(setPopup: SetPopup) {
const [visionProviders, setVisionProviders] = useState<VisionProvider[]>([]);
const [visionLLM, setVisionLLM] = useState<string | null>(null);
const [isLoading, setIsLoading] = useState(false);
const [error, setError] = useState<string | null>(null);
const loadVisionProviders = useCallback(async () => {
setIsLoading(true);
setError(null);
try {
const data = await fetchVisionProviders();
setVisionProviders(data);
// Find the default vision provider and set it
const defaultProvider = data.find(
(provider) => provider.is_default_vision_provider
);
if (defaultProvider) {
const modelToUse =
defaultProvider.default_vision_model ||
defaultProvider.default_model_name;
if (modelToUse && defaultProvider.vision_models.includes(modelToUse)) {
setVisionLLM(
structureValue(
defaultProvider.name,
defaultProvider.provider,
modelToUse
)
);
}
}
} catch (error) {
console.error("Error fetching vision providers:", error);
setError(
error instanceof Error ? error.message : "Unknown error occurred"
);
setPopup({
message: `Failed to load vision providers: ${
error instanceof Error ? error.message : "Unknown error"
}`,
type: "error",
});
} finally {
setIsLoading(false);
}
}, []);
const updateDefaultVisionProvider = useCallback(
async (llmValue: string | null) => {
if (!llmValue) {
setPopup({
message: "Please select a valid vision model",
type: "error",
});
return false;
}
try {
const { name, modelName } = destructureValue(llmValue);
// Find the provider ID
const providerObj = visionProviders.find((p) => p.name === name);
if (!providerObj) {
throw new Error("Provider not found");
}
await setDefaultVisionProvider(providerObj.id, modelName);
setPopup({
message: "Default vision provider updated successfully!",
type: "success",
});
setVisionLLM(llmValue);
// Refresh the list to reflect the change
await loadVisionProviders();
return true;
} catch (error: unknown) {
console.error("Error setting default vision provider:", error);
const errorMessage =
error instanceof Error ? error.message : "Unknown error occurred";
setPopup({
message: `Failed to update default vision provider: ${errorMessage}`,
type: "error",
});
return false;
}
},
[visionProviders, setPopup, loadVisionProviders]
);
// Load providers on mount
useEffect(() => {
loadVisionProviders();
}, [loadVisionProviders]);
return {
visionProviders,
visionLLM,
isLoading,
error,
setVisionLLM,
updateDefaultVisionProvider,
refreshVisionProviders: loadVisionProviders,
};
}

7
web/src/app/admin/settings/interfaces.ts
View File

@ -12,11 +12,12 @@ export enum QueryHistoryType {
export interface Settings {
anonymous_user_enabled: boolean;
maximum_chat_retention_days: number | null;
anonymous_user_path?: string;
maximum_chat_retention_days?: number | null;
notifications: Notification[];
needs_reindexing: boolean;
gpu_enabled: boolean;
pro_search_enabled: boolean | null;
pro_search_enabled?: boolean;
application_status: ApplicationStatus;
auto_scroll: boolean;
temperature_override_enabled: boolean;
@ -25,7 +26,7 @@ export interface Settings {
// Image processing settings
image_extraction_and_analysis_enabled?: boolean;
search_time_image_analysis_enabled?: boolean;
image_analysis_max_size_mb?: number;
image_analysis_max_size_mb?: number | null;
}
export enum NotificationType {

1
web/src/app/chat/message/Messages.tsx
View File

@ -243,6 +243,7 @@ export const AIMessage = ({
return preprocessLaTeX(content);
}
}
// return content;
return (
preprocessLaTeX(content) +

1
web/src/components/llm/LLMSelector.tsx
View File

@ -103,7 +103,6 @@ export const LLMSelector: React.FC<LLMSelectorProps> = ({
</SelectItem>
);
}
return null;
})}
</SelectContent>
</Select>

37
web/src/lib/llm/visionLLM.ts Normal file
View File

@ -0,0 +1,37 @@
import { VisionProvider } from "@/app/admin/configuration/llm/interfaces";
export async function fetchVisionProviders(): Promise<VisionProvider[]> {
const response = await fetch("/api/admin/llm/vision-providers", {
headers: {
"Content-Type": "application/json",
},
});
if (!response.ok) {
throw new Error(
`Failed to fetch vision providers: ${await response.text()}`
);
}
return response.json();
}
export async function setDefaultVisionProvider(
providerId: number,
visionModel: string
): Promise<void> {
const response = await fetch(
`/api/admin/llm/provider/${providerId}/default-vision?vision_model=${encodeURIComponent(
visionModel
)}`,
{
method: "POST",
headers: {
"Content-Type": "application/json",
},
}
);
if (!response.ok) {
const errorMsg = await response.text();
throw new Error(errorMsg);
}
}