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feat(database-migrations): add migration to remove legacy model config tables and remove stale model connection code

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This commit is contained in:
Anish Sarkar 2026-06-13 12:45:43 +05:30
parent 50668775f8
commit bd4a04f2e7
93 changed files with 956 additions and 11442 deletions
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2
surfsense_backend/app/agents/chat/multi_agent_chat/subagents/builtins/deliverables/tools/generate_image.py
View file

@ -215,7 +215,7 @@ def create_generate_image_tool(
prompt=prompt,
model=getattr(response, "_hidden_params", {}).get("model"),
n=n,
image_generation_config_id=config_id,
image_gen_model_id=config_id,
response_data=response_dict,
search_space_id=search_space_id,
access_token=access_token,

132
surfsense_backend/app/agents/chat/runtime/llm_config.py
View file

@ -24,8 +24,6 @@ from langchain_core.messages import AIMessage, BaseMessage
from langchain_core.outputs import ChatGenerationChunk, ChatResult
from langchain_litellm import ChatLiteLLM
from litellm import get_model_info
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
from app.agents.chat.runtime.prompt_caching import (
apply_litellm_prompt_caching,
@ -34,7 +32,6 @@ from app.services.llm_router_service import (
AUTO_MODE_ID,
ChatLiteLLMRouter,
_sanitize_content,
is_auto_mode,
)
@ -130,7 +127,7 @@ class AgentConfig:
"""
Complete configuration for the SurfSense agent.
This combines LLM settings with prompt configuration from NewLLMConfig.
This combines resolved model settings with prompt configuration.
Supports Auto mode metadata (ID 0). Runtime callers must resolve Auto to
a concrete global or BYOK model before constructing ChatLiteLLM.
"""
@ -180,7 +177,7 @@ class AgentConfig:
use_default_system_instructions=True,
citations_enabled=True,
config_id=AUTO_MODE_ID,
config_name="Auto (Fastest)",
config_name="Auto",
is_auto_mode=True,
billing_tier="free",
is_premium=False,
@ -191,57 +188,12 @@ class AgentConfig:
supports_image_input=True,
)
@classmethod
def from_new_llm_config(cls, config) -> "AgentConfig":
"""Build an AgentConfig from a NewLLMConfig database model."""
# Lazy import: keeps provider_capabilities (and litellm) out of init order.
from app.services.provider_capabilities import derive_supports_image_input
provider_value = (
config.provider.value
if hasattr(config.provider, "value")
else str(config.provider)
)
litellm_params = config.litellm_params or {}
base_model = (
litellm_params.get("base_model")
if isinstance(litellm_params, dict)
else None
)
return cls(
provider=provider_value,
model_name=config.model_name,
api_key=config.api_key,
api_base=config.api_base,
custom_provider=config.custom_provider,
litellm_params=config.litellm_params,
system_instructions=config.system_instructions,
use_default_system_instructions=config.use_default_system_instructions,
citations_enabled=config.citations_enabled,
config_id=config.id,
config_name=config.name,
is_auto_mode=False,
billing_tier="free",
is_premium=False,
anonymous_enabled=False,
quota_reserve_tokens=None,
# BYOK rows have no curated flag; ask LiteLLM (default-allow on
# unknown). The streaming safety net still blocks explicit text-only.
supports_image_input=derive_supports_image_input(
provider=provider_value.lower(),
model_name=config.model_name,
base_model=base_model,
custom_provider=config.custom_provider,
),
)
@classmethod
def from_yaml_config(cls, yaml_config: dict) -> "AgentConfig":
"""Build an AgentConfig from a YAML configuration dictionary.
Supports the same prompt fields as NewLLMConfig (system_instructions,
use_default_system_instructions, citations_enabled).
Supports prompt fields such as system_instructions,
use_default_system_instructions, and citations_enabled.
"""
# Lazy import: keeps provider_capabilities (and litellm) out of init order.
from app.services.provider_capabilities import derive_supports_image_input
@ -334,82 +286,6 @@ def load_global_llm_config_by_id(llm_config_id: int) -> dict | None:
return load_llm_config_from_yaml(llm_config_id)
async def load_new_llm_config_from_db(
session: AsyncSession,
config_id: int,
) -> "AgentConfig | None":
"""Load a NewLLMConfig from the database by ID."""
from app.db import NewLLMConfig
try:
result = await session.execute(
select(NewLLMConfig).filter(NewLLMConfig.id == config_id)
)
config = result.scalars().first()
if not config:
print(f"Error: NewLLMConfig with id {config_id} not found")
return None
return AgentConfig.from_new_llm_config(config)
except Exception as e:
print(f"Error loading NewLLMConfig from database: {e}")
return None
async def load_agent_llm_config_for_search_space(
session: AsyncSession,
search_space_id: int,
) -> "AgentConfig | None":
"""Load the chat model config for a search space via its agent_llm_id.
Positive id -> DB; negative -> YAML; None -> first global config (-1).
"""
from app.db import SearchSpace
try:
result = await session.execute(
select(SearchSpace).filter(SearchSpace.id == search_space_id)
)
search_space = result.scalars().first()
if not search_space:
print(f"Error: SearchSpace with id {search_space_id} not found")
return None
config_id = (
search_space.agent_llm_id if search_space.agent_llm_id is not None else -1
)
return await load_agent_config(session, config_id, search_space_id)
except Exception as e:
print(f"Error loading chat model config for search space {search_space_id}: {e}")
return None
async def load_agent_config(
session: AsyncSession,
config_id: int,
search_space_id: int | None = None,
) -> "AgentConfig | None":
"""Main config loader: id 0 -> Auto mode; negative -> YAML; positive -> DB."""
if is_auto_mode(config_id):
return AgentConfig.from_auto_mode()
if config_id < 0:
# In-memory covers static YAML + dynamic OpenRouter configs.
from app.config import config as app_config
for cfg in app_config.GLOBAL_LLM_CONFIGS:
if cfg.get("id") == config_id:
return AgentConfig.from_yaml_config(cfg)
yaml_config = load_llm_config_from_yaml(config_id)
if yaml_config:
return AgentConfig.from_yaml_config(yaml_config)
return None
else:
return await load_new_llm_config_from_db(session, config_id)
def create_chat_litellm_from_config(llm_config: dict) -> ChatLiteLLM | None:
"""Create a ChatLiteLLM instance from a global LLM config dictionary."""
if llm_config.get("custom_provider"):