When updating a compute without providing a password field,
compute_update.password is None and calling .get_secret_value()
on it causes a 500 Internal Server Error. Only set the password
in update_values when a password is actually provided.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
remove unused reserved_jsonb fields
Remove the three reserved JSONB fields (reserved_jsonb_1, reserved_jsonb_2, reserved_jsonb_3) from the llm_model_configs
table. These fields were planned for future use but are no longer needed.
Security Enhancement:
- API keys are now always filtered to null in all LLM config API responses
- Created LLMModelConfigDataWithoutSecret schema for response validation
- Added _filter_api_key_from_config() helper in API routes
- Modified repository to always hide api_key in get_user_effective_configs()
- Update/create operations still accept and store api_key securely
Documentation Updates:
- Updated API key visibility section to reflect new security policy
- Updated all response examples to show api_key as null
- Marked max_tokens field as reserved for future use
- Added "Reserved Fields" section explaining unused fields
This defense-in-depth approach prevents API keys from being leaked through
logs, browser devtools, or network monitoring.
- Replace separate user_id and jwt_token parameters with unified llm_config dict
- Simplify model factory to accept llm_config directly instead of fetching from API
- Update llm_call and generate_title nodes to extract llm_config from LangGraph config
- Remove deprecated API fetching logic from model factory
- Maintain backward compatibility for existing tool usage patterns
This change centralizes LLM configuration management, reducing API calls and improving performance by passing configuration directly from the API layer rather than fetching it repeatedly.
Updated documentation and implementation to clearly define the priority order for selecting default LLM model configurations. The logic now explicitly states:
1. User's config marked with `is_default: true` (highest priority)
2. Group's config marked with `is_default: true`
3. First config in the list (user configs come before group configs)
This ensures consistent behavior between the API documentation and the actual implementation in the repository code.
Update API documentation to reflect new nested `config` object structure in LLM model configurations endpoints. The response format now encapsulates provider-specific fields (provider, base_url, model, temperature, api_key, max_tokens) within a `config` object, while moving ownership metadata (user_id, group_id, is_default, version, created_at, updated_at) to the top level. This aligns the user-facing endpoints with the group configuration structure and improves API consistency.
- Update API documentation to explicitly describe default configuration selection logic
- Add fallback behavior in repository to use first config when no default is marked
- Clarify difference between `/default` endpoint and `default_config` field
- Document that `default_config` is never null when configs list is not empty
- Add `/default` endpoints for users and groups to retrieve default LLM model configurations
- Update documentation to clarify that users receive both own and inherited configurations
- Improve response examples to show combined configs with source field
- Add 404 response example for missing default configurations
- Fix optimistic locking documentation formatting
Add explicit datetime.utcnow() assignments for created_at and updated_at fields in LLMModelConfigsRepository to ensure proper timestamp handling with SQLite. This addresses issues where SQLite may not automatically populate these timestamp fields during create and update operations. Changes applied to both user and group configuration methods for consistency.
- Change `JSONB` columns to generic `JSON` in LLMModelConfig model for database compatibility
- Update migration to use `sa.String(32)` for UUID and `sa.JSON()` for config fields
- Remove PostgreSQL dialect imports to support multiple database backends
- Keep existing constraints and indexes with PostgreSQL-specific annotations where needed
Replace deferred UniqueConstraints with partial unique indexes for user and group default configurations in the LLM model configs table. This change improves performance and ensures at most one default config per user/group while maintaining data integrity. The migration script has been updated accordingly to create and drop the new indexes.
- Add `model_type` field to database schema with supported values (text, vision, stt, tts, multimodal, embedding, reranking, other)
- Add `name` field as table-level column for indexing and filtering
- Add reserved JSONB fields for future extensibility
- Update API request/response schemas to include `model_type` and `name` fields
- Add new `LLMModelConfigWithSource` schema for detailed configuration responses
- Update usage examples to reflect new required fields
- Improve database constraints and indexing documentation
- Include `version` field in all LLM model config response schemas
- Add `expected_version` parameter to update endpoints for optimistic locking
- Handle concurrent modification errors with HTTP 409 Conflict status
- Update both user and group config endpoints consistently
- Add smarter database state detection during initialization to handle new databases, existing databases with new features, and old databases needing migration
- Make migration for llm_model_configs table idempotent to prevent conflicts when table already exists from code
- Add detailed logging for different database initialization scenarios
- Import sqlalchemy module for database inspection capabilities
- Introduce new API route `/access` for managing LLM model configurations
- Add LLMModelConfig model to database models
- Include comprehensive schemas for LLM model config CRUD operations
- Register new router with tags for LLM Model Configurations
- Add optional `tags` query parameter to `/nodes` and `/templates` endpoints
- Support filtering by tags in format "key:value" with multiple tags ANDed together
- Example: `?tags=vendor:cisco&tags=model:7200` filters nodes/templates with both tags
- Maintain backward compatibility for existing API usage without tags parameter
Add three new optional fields to the template schema:
- vendor: Device vendor (e.g., Cisco, Juniper, Huawei)
- model: Device model (e.g., ISR4451-X, MX204, NE40E)
- netmiko_device_type: Netmiko device type for automation (e.g., cisco_ios, juniper_junos, huawei)
These fields enable AI/LLM integration to determine the appropriate
Netmiko device type when automating network device configuration.
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
As described in #2568 when multiple clients connect simultaneously, an excessive number of database pool connections are created. This leads to resource exhaustion and connection management issues.
We have introduced the pool_size and max_overflow parameters to better control the database connection pool.
These parameters ensure the database can handle a sufficient number of concurrent connections without over-allocating resources.
Added pool_size and max_overflow arguments to the database initialization.
This change overrides the default initialization configuration where the temporary fix was applied.
Co-Authored-By: Ufi <86113085+ufiking@users.noreply.github.com>
