feat: Get live provider and model data from model.dev #11007
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WalkthroughThis PR adds live model data fetching from the models.dev API with caching support, controlled by the Changes
Sequence Diagram(s)sequenceDiagram
participant Client as Client Code
participant UM as unified_models
participant MDC as models_dev_client
participant Cache as Local Cache File
participant API as models.dev API
Client->>UM: get_models_detailed()
alt USE_LIVE_MODEL_DATA enabled
UM->>MDC: get_live_models_detailed()
MDC->>Cache: _load_cache()
alt Cache valid (within 1h TTL)
Cache-->>MDC: cached data
else Cache missing or expired
MDC->>API: fetch https://models.dev/api.json
API-->>MDC: provider & model data
MDC->>Cache: _save_cache(data)
end
loop For each provider & model
MDC->>MDC: transform_api_model_to_metadata()
Note over MDC: Map provider IDs,<br/>determine model type,<br/>structure cost/limits
end
MDC-->>UM: list[ModelMetadata]
else Live data unavailable
UM->>UM: get_static_models_detailed()
Note over UM: Fallback to static<br/>model definitions
end
UM-->>Client: list[ModelMetadata]
Estimated code review effort🎯 4 (Complex) | ⏱️ ~45 minutes
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Actionable comments posted: 4
🧹 Nitpick comments (4)
src/lfx/src/lfx/base/models/unified_models.py (2)
100-113: Consider narrowing the exception type (static analysis warning).The blind
Exceptioncatch at line 109 triggers Ruff BLE001. While the fallback behavior is correct for resilience, consider either:
- Catching more specific exceptions (e.g.,
OSError,ValueError,TimeoutError)- Adding
# noqa: BLE001with a comment explaining why broad catching is intentional here- except Exception as e: + except Exception as e: # noqa: BLE001 - Intentional broad catch for graceful fallback logger.debug(f"Failed to get live provider metadata: {e}")
133-155: Same BLE001 warning applies here.Line 153 has the same blind exception catch. Add
# noqa: BLE001with justification for consistency.- except Exception as e: + except Exception as e: # noqa: BLE001 - Intentional broad catch for graceful fallback logger.debug(f"Failed to fetch live models: {e}") return []src/lfx/src/lfx/base/models/models_dev_client.py (2)
174-189: Use idiomatic string containment check.Line 186 uses
.find() != -1which is not idiomatic Python. Use theinoperator instead.Apply this diff:
- if model_data.get("id", "").lower().find("embed") != -1: + if "embed" in model_data.get("id", "").lower():
191-227: Consider omitting None values from TypedDict construction.The transform functions explicitly include optional fields with
Nonevalues (e.g., lines 199-203). Since these TypedDicts havetotal=False, it's cleaner to omitNonevalues rather than include them, which also prevents potential serialization issues.Example for
_transform_cost:def _transform_cost(cost_data: dict[str, Any] | None) -> ModelCost | None: """Transform API cost data to ModelCost format.""" if not cost_data: return None - return ModelCost( - input=cost_data.get("input", 0), - output=cost_data.get("output", 0), - reasoning=cost_data.get("reasoning"), - cache_read=cost_data.get("cache_read"), - cache_write=cost_data.get("cache_write"), - input_audio=cost_data.get("input_audio"), - output_audio=cost_data.get("output_audio"), - ) + result = ModelCost( + input=cost_data.get("input", 0), + output=cost_data.get("output", 0), + ) + # Only add optional fields if present + for key in ["reasoning", "cache_read", "cache_write", "input_audio", "output_audio"]: + if key in cost_data: + result[key] = cost_data[key] + return resultApply similar logic to
_transform_limitsand_transform_modalities.
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📒 Files selected for processing (7)
.env.example(2 hunks)src/frontend/src/controllers/API/queries/models/use-get-model-providers.ts(1 hunks)src/frontend/src/modals/modelProviderModal/index.tsx(1 hunks)src/lfx/src/lfx/base/models/__init__.py(1 hunks)src/lfx/src/lfx/base/models/model_metadata.py(1 hunks)src/lfx/src/lfx/base/models/models_dev_client.py(1 hunks)src/lfx/src/lfx/base/models/unified_models.py(5 hunks)
🧰 Additional context used
📓 Path-based instructions (3)
src/frontend/src/**/*.{ts,tsx}
📄 CodeRabbit inference engine (.cursor/rules/frontend_development.mdc)
src/frontend/src/**/*.{ts,tsx}: Use React 18 with TypeScript for frontend development
Use Zustand for state management
Files:
src/frontend/src/modals/modelProviderModal/index.tsxsrc/frontend/src/controllers/API/queries/models/use-get-model-providers.ts
src/frontend/src/**/*.{tsx,jsx,css,scss}
📄 CodeRabbit inference engine (.cursor/rules/frontend_development.mdc)
Use Tailwind CSS for styling
Files:
src/frontend/src/modals/modelProviderModal/index.tsx
src/frontend/src/**/*.{tsx,jsx}
📄 CodeRabbit inference engine (.cursor/rules/frontend_development.mdc)
src/frontend/src/**/*.{tsx,jsx}: Implement dark mode support using the useDarkMode hook and dark store
Use Lucide React for icon components in the application
Files:
src/frontend/src/modals/modelProviderModal/index.tsx
🧠 Learnings (5)
📚 Learning: 2025-07-11T22:12:46.255Z
Learnt from: namastex888
Repo: langflow-ai/langflow PR: 9018
File: src/frontend/src/modals/apiModal/codeTabs/code-tabs.tsx:244-244
Timestamp: 2025-07-11T22:12:46.255Z
Learning: In src/frontend/src/modals/apiModal/codeTabs/code-tabs.tsx, the inconsistent showLineNumbers setting between Step 1 (false) and Step 2 (true) in the API modal is intentional to prevent breaking the modal height. Step 1 uses showLineNumbers={false} to save vertical space while Step 2 uses showLineNumbers={true} for better readability of longer code.
Applied to files:
src/frontend/src/modals/modelProviderModal/index.tsx
📚 Learning: 2025-07-23T21:19:22.567Z
Learnt from: deon-sanchez
Repo: langflow-ai/langflow PR: 9158
File: src/backend/base/langflow/api/v1/mcp_projects.py:404-404
Timestamp: 2025-07-23T21:19:22.567Z
Learning: In langflow MCP projects configuration, prefer using dynamically computed URLs (like the `sse_url` variable) over hardcoded localhost URLs to ensure compatibility across different deployment environments.
Applied to files:
.env.example
📚 Learning: 2025-11-24T19:46:57.920Z
Learnt from: CR
Repo: langflow-ai/langflow PR: 0
File: .cursor/rules/icons.mdc:0-0
Timestamp: 2025-11-24T19:46:57.920Z
Learning: Applies to src/frontend/src/icons/lazyIconImports.ts : Add icon entries to the `lazyIconsMapping` object in `src/frontend/src/icons/lazyIconImports.ts`. The key must match the backend icon name exactly (case-sensitive) and use dynamic imports: `IconName: () => import("@/icons/IconName").then((mod) => ({ default: mod.IconNameIcon }))`.
Applied to files:
src/frontend/src/controllers/API/queries/models/use-get-model-providers.ts
📚 Learning: 2025-11-24T19:46:57.920Z
Learnt from: CR
Repo: langflow-ai/langflow PR: 0
File: .cursor/rules/icons.mdc:0-0
Timestamp: 2025-11-24T19:46:57.920Z
Learning: Use clear, recognizable icon names (e.g., `"AstraDB"`, `"Postgres"`, `"OpenAI"`). Always use the same icon name for the same service across backend and frontend.
Applied to files:
src/frontend/src/controllers/API/queries/models/use-get-model-providers.ts
📚 Learning: 2025-06-23T12:46:52.420Z
Learnt from: CR
Repo: langflow-ai/langflow PR: 0
File: .cursor/rules/icons.mdc:0-0
Timestamp: 2025-06-23T12:46:52.420Z
Learning: The frontend icon mapping key (in 'lazyIconsMapping') must match the backend 'icon' attribute string exactly, including case sensitivity, to ensure correct icon rendering.
Applied to files:
src/frontend/src/controllers/API/queries/models/use-get-model-providers.ts
🧬 Code graph analysis (2)
src/lfx/src/lfx/base/models/models_dev_client.py (1)
src/lfx/src/lfx/base/models/model_metadata.py (4)
ModelCost(4-13)ModelLimits(16-20)ModelMetadata(30-69)ModelModalities(23-27)
src/lfx/src/lfx/base/models/unified_models.py (1)
src/lfx/src/lfx/base/models/models_dev_client.py (3)
clear_cache(386-394)get_live_models_detailed(307-350)get_provider_metadata_from_api(354-383)
🪛 GitHub Actions: Ruff Style Check
src/lfx/src/lfx/base/models/__init__.py
[error] 20-20: RUF022 __all__ is not sorted.
🪛 GitHub Check: Ruff Style Check (3.13)
src/lfx/src/lfx/base/models/models_dev_client.py
[failure] 169-169: Ruff (BLE001)
src/lfx/src/lfx/base/models/models_dev_client.py:169:12: BLE001 Do not catch blind exception: Exception
[failure] 159-159: Ruff (TRY300)
src/lfx/src/lfx/base/models/models_dev_client.py:159:9: TRY300 Consider moving this statement to an else block
src/lfx/src/lfx/base/models/unified_models.py
[failure] 109-109: Ruff (BLE001)
src/lfx/src/lfx/base/models/unified_models.py:109:12: BLE001 Do not catch blind exception: Exception
[failure] 189-189: Ruff (PLW0602)
src/lfx/src/lfx/base/models/unified_models.py:189:12: PLW0602 Using global for MODELS_DETAILED but no assignment is done
[failure] 153-153: Ruff (BLE001)
src/lfx/src/lfx/base/models/unified_models.py:153:12: BLE001 Do not catch blind exception: Exception
⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (7)
- GitHub Check: Test Docker Images / Test docker images
- GitHub Check: Run Frontend Tests / Determine Test Suites and Shard Distribution
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- GitHub Check: Run Ruff Check and Format
- GitHub Check: Update Starter Projects
🔇 Additional comments (13)
src/frontend/src/modals/modelProviderModal/index.tsx (1)
255-255: LGTM! Enables scrolling for overflowing provider list.The addition of
overflow-y-autocorrectly handles scenarios where the provider list exceeds the fixed height of 513px, allowing users to scroll through all available providers..env.example (1)
143-148: Documentation looks good.The environment variable documentation is clear and follows the established pattern in this file. It properly documents the purpose, allowed values, default, and fallback behavior.
src/lfx/src/lfx/base/models/model_metadata.py (2)
4-28: Well-structured type definitions.The new
ModelCost,ModelLimits, andModelModalitiesTypedDicts are well-designed withtotal=Falsefor optional fields and clear inline documentation of units and purposes.
72-144: Clean implementation of the factory function.The conditional assignment pattern (only adding fields when not
None) is a good approach to keep the metadata dictionaries lean. The function signature is getting long but remains manageable for a configuration factory.src/lfx/src/lfx/base/models/unified_models.py (3)
33-35: Environment variable parsing looks good.The pattern of parsing the env var with a lowercase comparison and default to
"false"is correct and defensive.
158-175: Good fallback pattern with appropriate logging.The live-to-static fallback with a warning log is a solid resilience pattern. The function cleanly encapsulates the toggle behavior.
181-200: > Likely an incorrect or invalid review comment.src/frontend/src/controllers/API/queries/models/use-get-model-providers.ts (1)
78-100: Verify icon keys matchlazyIconImports.tsbefore merging.The provider-to-icon mappings reference several custom icons (GoogleGenerativeAI, VertexAI, Mistral, DeepSeek, xAI, WatsonxAI, SambaNova, AWS, Azure, NVIDIA, Ollama) that must be registered in
src/frontend/src/icons/lazyIconImports.ts. Icon keys are case-sensitive and must match exactly. Ensure each referenced icon key has a corresponding dynamic import entry inlazyIconImports.ts. The "Bot" fallback is acceptable for unsupported providers (Together AI, Fireworks AI, Alibaba, Cerebras).src/lfx/src/lfx/base/models/models_dev_client.py (5)
1-93: LGTM: Well-structured module with comprehensive provider mappings.The imports, constants, and provider mappings are well-organized and comprehensive.
96-120: LGTM: Cache loading logic is sound.The cache path construction and loading with TTL validation are implemented correctly.
122-131: LGTM: Cache saving is implemented correctly.Directory creation and error handling are appropriate.
307-351: LGTM: Query function is well-implemented.The filtering logic and parameter handling are correct.
397-439: LGTM: Convenience and search functions are well-implemented.The wrapper and search functions provide a clean API surface.
| __all__ = [ | ||
| # Core components | ||
| "LCModelComponent", | ||
| # Unified models API | ||
| "get_model_provider_variable_mapping", | ||
| "get_model_providers", | ||
| "get_unified_models_detailed", | ||
| "refresh_live_model_data", | ||
| # Model metadata types | ||
| "ModelCost", | ||
| "ModelLimits", | ||
| "ModelMetadata", | ||
| "ModelModalities", | ||
| "create_model_metadata", | ||
| # Live models API (models.dev) | ||
| "clear_live_models_cache", | ||
| "fetch_models_dev_data", | ||
| "get_live_models_detailed", | ||
| "get_models_by_provider", | ||
| "get_provider_metadata_from_api", | ||
| "search_models", | ||
| ] |
There was a problem hiding this comment.
Fix: __all__ is not sorted (pipeline failure).
The static analysis is failing because __all__ entries are not sorted alphabetically. While the grouping comments are helpful for organization, Ruff's RUF022 rule requires sorted exports.
Apply this diff to fix the pipeline failure:
__all__ = [
- # Core components
"LCModelComponent",
- # Unified models API
- "get_model_provider_variable_mapping",
- "get_model_providers",
- "get_unified_models_detailed",
- "refresh_live_model_data",
- # Model metadata types
"ModelCost",
"ModelLimits",
"ModelMetadata",
"ModelModalities",
+ "clear_live_models_cache",
"create_model_metadata",
- # Live models API (models.dev)
- "clear_live_models_cache",
"fetch_models_dev_data",
"get_live_models_detailed",
+ "get_model_provider_variable_mapping",
+ "get_model_providers",
"get_models_by_provider",
"get_provider_metadata_from_api",
+ "get_unified_models_detailed",
+ "refresh_live_model_data",
"search_models",
]📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| __all__ = [ | |
| # Core components | |
| "LCModelComponent", | |
| # Unified models API | |
| "get_model_provider_variable_mapping", | |
| "get_model_providers", | |
| "get_unified_models_detailed", | |
| "refresh_live_model_data", | |
| # Model metadata types | |
| "ModelCost", | |
| "ModelLimits", | |
| "ModelMetadata", | |
| "ModelModalities", | |
| "create_model_metadata", | |
| # Live models API (models.dev) | |
| "clear_live_models_cache", | |
| "fetch_models_dev_data", | |
| "get_live_models_detailed", | |
| "get_models_by_provider", | |
| "get_provider_metadata_from_api", | |
| "search_models", | |
| ] | |
| __all__ = [ | |
| "LCModelComponent", | |
| "ModelCost", | |
| "ModelLimits", | |
| "ModelMetadata", | |
| "ModelModalities", | |
| "clear_live_models_cache", | |
| "create_model_metadata", | |
| "fetch_models_dev_data", | |
| "get_live_models_detailed", | |
| "get_model_provider_variable_mapping", | |
| "get_model_providers", | |
| "get_models_by_provider", | |
| "get_provider_metadata_from_api", | |
| "get_unified_models_detailed", | |
| "refresh_live_model_data", | |
| "search_models", | |
| ] |
🧰 Tools
🪛 GitHub Actions: Ruff Style Check
[error] 20-20: RUF022 __all__ is not sorted.
🪛 GitHub Check: Ruff Style Check (3.13)
[failure] 20-41: Ruff (RUF022)
src/lfx/src/lfx/base/models/init.py:20:11: RUF022 __all__ is not sorted
🤖 Prompt for AI Agents
In src/lfx/src/lfx/base/models/__init__.py around lines 20 to 41, the __all__
list is failing RUF022 because its string entries are not alphabetically sorted;
update the list so all exported names (ignore the inline grouping comments) are
sorted in ascending alphabetical order, keeping each entry as a quoted string
with trailing commas and preserving overall formatting/line breaks.
| def fetch_models_dev_data(*, force_refresh: bool = False) -> dict[str, Any]: | ||
| """Fetch model data from models.dev API. | ||
| Args: | ||
| force_refresh: If True, bypass cache and fetch fresh data. | ||
| Returns: | ||
| Dictionary containing all provider and model data from the API. | ||
| """ | ||
| # Try cache first | ||
| if not force_refresh: | ||
| cached = _load_cache() | ||
| if cached is not None: | ||
| logger.debug("Using cached models.dev data") | ||
| return cached | ||
|
|
||
| # Fetch from API | ||
| try: | ||
| with httpx.Client(timeout=30.0) as client: | ||
| response = client.get(MODELS_DEV_API_URL) | ||
| response.raise_for_status() | ||
| data = response.json() | ||
|
|
||
| # Cache the result | ||
| _save_cache(data) | ||
| logger.info("Successfully fetched models.dev data") | ||
| return data | ||
|
|
||
| except httpx.HTTPError as e: | ||
| logger.warning(f"Failed to fetch models.dev data: {e}") | ||
| # Try to return stale cache if available | ||
| cached = _load_cache() | ||
| if cached is not None: | ||
| logger.info("Using stale cache due to API error") | ||
| return cached | ||
| return {} | ||
| except Exception as e: | ||
| logger.error(f"Unexpected error fetching models.dev data: {e}") | ||
| return {} | ||
|
|
There was a problem hiding this comment.
Fix stale cache fallback logic and exception handling.
There are several issues in this function:
-
Line 164: The stale cache fallback won't work as intended because
_load_cache()checks TTL and returnsNonefor expired cache. To retrieve stale cache, you need to read the file directly without TTL validation. -
Line 169: Catching bare
Exceptionis too broad and can mask unexpected errors. Be more specific or remove this catch block to let unexpected exceptions propagate. -
Line 151: The timeout value
30.0should be defined as a module-level constant alongside other configuration values.
Apply this diff to fix the stale cache logic:
except httpx.HTTPError as e:
logger.warning(f"Failed to fetch models.dev data: {e}")
- # Try to return stale cache if available
- cached = _load_cache()
- if cached is not None:
+ # Try to return stale cache (bypass TTL check)
+ cache_path = _get_cache_path()
+ if cache_path.exists():
+ try:
+ with cache_path.open() as f:
+ cache_data = json.load(f)
+ cached = cache_data.get("data")
+ if cached:
+ logger.info("Using stale cache due to API error")
+ return cached
+ except (OSError, json.JSONDecodeError):
+ pass
- logger.info("Using stale cache due to API error")
- return cached
return {}
- except Exception as e:
- logger.error(f"Unexpected error fetching models.dev data: {e}")
- return {}For the timeout constant:
# API Configuration
MODELS_DEV_API_URL = "https://models.dev/api.json"
CACHE_TTL_SECONDS = 3600 # 1 hour cache TTL
+HTTP_TIMEOUT_SECONDS = 30.0 # HTTP request timeout
CACHE_FILE_NAME = ".models_dev_cache.json"- with httpx.Client(timeout=30.0) as client:
+ with httpx.Client(timeout=HTTP_TIMEOUT_SECONDS) as client:Committable suggestion skipped: line range outside the PR's diff.
🧰 Tools
🪛 GitHub Check: Ruff Style Check (3.13)
[failure] 169-169: Ruff (BLE001)
src/lfx/src/lfx/base/models/models_dev_client.py:169:12: BLE001 Do not catch blind exception: Exception
[failure] 159-159: Ruff (TRY300)
src/lfx/src/lfx/base/models/models_dev_client.py:159:9: TRY300 Consider moving this statement to an else block
| def transform_api_model_to_metadata( | ||
| provider_id: str, | ||
| provider_data: dict[str, Any], | ||
| model_id: str, | ||
| model_data: dict[str, Any], | ||
| ) -> ModelMetadata: | ||
| """Transform API model data to ModelMetadata format. | ||
| Args: | ||
| provider_id: The provider ID from the API (e.g., "openai") | ||
| provider_data: The provider data from the API | ||
| model_id: The model ID from the API | ||
| model_data: The model data from the API | ||
| Returns: | ||
| ModelMetadata object with transformed data | ||
| """ | ||
| provider_name = PROVIDER_NAME_MAP.get(provider_id, provider_data.get("name", provider_id.title())) | ||
| icon = PROVIDER_ICON_MAP.get(provider_id, "bot") # Default to "bot" if no custom icon | ||
|
|
||
| # Determine model type | ||
| model_type = _determine_model_type(model_data) | ||
|
|
||
| # Build metadata | ||
| metadata = ModelMetadata( | ||
| # Core identification | ||
| provider=provider_name, | ||
| provider_id=provider_id, | ||
| name=model_id, | ||
| display_name=model_data.get("name", model_id), | ||
| icon=icon, | ||
| # Capabilities | ||
| tool_calling=model_data.get("tool_call", False), | ||
| reasoning=model_data.get("reasoning", False), | ||
| structured_output=model_data.get("structured_output", False), | ||
| temperature=model_data.get("temperature", True), | ||
| attachment=model_data.get("attachment", False), | ||
| # Status flags | ||
| preview="-preview" in model_id.lower() or "beta" in model_id.lower(), | ||
| not_supported=provider_id not in SUPPORTED_PROVIDERS, | ||
| deprecated=False, | ||
| default=False, | ||
| open_weights=model_data.get("open_weights", False), | ||
| # Model classification | ||
| model_type=model_type, | ||
| ) | ||
|
|
||
| # Add extended metadata | ||
| cost = _transform_cost(model_data.get("cost")) | ||
| if cost: | ||
| metadata["cost"] = cost | ||
|
|
||
| limits = _transform_limits(model_data.get("limit")) | ||
| if limits: | ||
| metadata["limits"] = limits | ||
|
|
||
| modalities = _transform_modalities(model_data.get("modalities")) | ||
| if modalities: | ||
| metadata["modalities"] = modalities | ||
|
|
||
| if model_data.get("knowledge"): | ||
| metadata["knowledge_cutoff"] = model_data["knowledge"] | ||
| if model_data.get("release_date"): | ||
| metadata["release_date"] = model_data["release_date"] | ||
| if model_data.get("last_updated"): | ||
| metadata["last_updated"] = model_data["last_updated"] | ||
|
|
||
| # Provider metadata | ||
| if provider_data.get("api"): | ||
| metadata["api_base"] = provider_data["api"] | ||
| if provider_data.get("env"): | ||
| metadata["env_vars"] = provider_data["env"] | ||
| if provider_data.get("doc"): | ||
| metadata["documentation_url"] = provider_data["doc"] | ||
|
|
||
| return metadata |
There was a problem hiding this comment.
Fix icon name inconsistency.
Line 247 uses lowercase "bot" as the default icon, but line 370 uses "Bot" with a capital B, and the PROVIDER_ICON_MAP consistently uses "Bot". This inconsistency could cause icon lookup failures in the frontend.
Apply this diff:
- icon = PROVIDER_ICON_MAP.get(provider_id, "bot") # Default to "bot" if no custom icon
+ icon = PROVIDER_ICON_MAP.get(provider_id, "Bot") # Default to "Bot" if no custom icon📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| def transform_api_model_to_metadata( | |
| provider_id: str, | |
| provider_data: dict[str, Any], | |
| model_id: str, | |
| model_data: dict[str, Any], | |
| ) -> ModelMetadata: | |
| """Transform API model data to ModelMetadata format. | |
| Args: | |
| provider_id: The provider ID from the API (e.g., "openai") | |
| provider_data: The provider data from the API | |
| model_id: The model ID from the API | |
| model_data: The model data from the API | |
| Returns: | |
| ModelMetadata object with transformed data | |
| """ | |
| provider_name = PROVIDER_NAME_MAP.get(provider_id, provider_data.get("name", provider_id.title())) | |
| icon = PROVIDER_ICON_MAP.get(provider_id, "bot") # Default to "bot" if no custom icon | |
| # Determine model type | |
| model_type = _determine_model_type(model_data) | |
| # Build metadata | |
| metadata = ModelMetadata( | |
| # Core identification | |
| provider=provider_name, | |
| provider_id=provider_id, | |
| name=model_id, | |
| display_name=model_data.get("name", model_id), | |
| icon=icon, | |
| # Capabilities | |
| tool_calling=model_data.get("tool_call", False), | |
| reasoning=model_data.get("reasoning", False), | |
| structured_output=model_data.get("structured_output", False), | |
| temperature=model_data.get("temperature", True), | |
| attachment=model_data.get("attachment", False), | |
| # Status flags | |
| preview="-preview" in model_id.lower() or "beta" in model_id.lower(), | |
| not_supported=provider_id not in SUPPORTED_PROVIDERS, | |
| deprecated=False, | |
| default=False, | |
| open_weights=model_data.get("open_weights", False), | |
| # Model classification | |
| model_type=model_type, | |
| ) | |
| # Add extended metadata | |
| cost = _transform_cost(model_data.get("cost")) | |
| if cost: | |
| metadata["cost"] = cost | |
| limits = _transform_limits(model_data.get("limit")) | |
| if limits: | |
| metadata["limits"] = limits | |
| modalities = _transform_modalities(model_data.get("modalities")) | |
| if modalities: | |
| metadata["modalities"] = modalities | |
| if model_data.get("knowledge"): | |
| metadata["knowledge_cutoff"] = model_data["knowledge"] | |
| if model_data.get("release_date"): | |
| metadata["release_date"] = model_data["release_date"] | |
| if model_data.get("last_updated"): | |
| metadata["last_updated"] = model_data["last_updated"] | |
| # Provider metadata | |
| if provider_data.get("api"): | |
| metadata["api_base"] = provider_data["api"] | |
| if provider_data.get("env"): | |
| metadata["env_vars"] = provider_data["env"] | |
| if provider_data.get("doc"): | |
| metadata["documentation_url"] = provider_data["doc"] | |
| return metadata | |
| def transform_api_model_to_metadata( | |
| provider_id: str, | |
| provider_data: dict[str, Any], | |
| model_id: str, | |
| model_data: dict[str, Any], | |
| ) -> ModelMetadata: | |
| """Transform API model data to ModelMetadata format. | |
| Args: | |
| provider_id: The provider ID from the API (e.g., "openai") | |
| provider_data: The provider data from the API | |
| model_id: The model ID from the API | |
| model_data: The model data from the API | |
| Returns: | |
| ModelMetadata object with transformed data | |
| """ | |
| provider_name = PROVIDER_NAME_MAP.get(provider_id, provider_data.get("name", provider_id.title())) | |
| icon = PROVIDER_ICON_MAP.get(provider_id, "Bot") # Default to "Bot" if no custom icon | |
| # Determine model type | |
| model_type = _determine_model_type(model_data) | |
| # Build metadata | |
| metadata = ModelMetadata( | |
| # Core identification | |
| provider=provider_name, | |
| provider_id=provider_id, | |
| name=model_id, | |
| display_name=model_data.get("name", model_id), | |
| icon=icon, | |
| # Capabilities | |
| tool_calling=model_data.get("tool_call", False), | |
| reasoning=model_data.get("reasoning", False), | |
| structured_output=model_data.get("structured_output", False), | |
| temperature=model_data.get("temperature", True), | |
| attachment=model_data.get("attachment", False), | |
| # Status flags | |
| preview="-preview" in model_id.lower() or "beta" in model_id.lower(), | |
| not_supported=provider_id not in SUPPORTED_PROVIDERS, | |
| deprecated=False, | |
| default=False, | |
| open_weights=model_data.get("open_weights", False), | |
| # Model classification | |
| model_type=model_type, | |
| ) | |
| # Add extended metadata | |
| cost = _transform_cost(model_data.get("cost")) | |
| if cost: | |
| metadata["cost"] = cost | |
| limits = _transform_limits(model_data.get("limit")) | |
| if limits: | |
| metadata["limits"] = limits | |
| modalities = _transform_modalities(model_data.get("modalities")) | |
| if modalities: | |
| metadata["modalities"] = modalities | |
| if model_data.get("knowledge"): | |
| metadata["knowledge_cutoff"] = model_data["knowledge"] | |
| if model_data.get("release_date"): | |
| metadata["release_date"] = model_data["release_date"] | |
| if model_data.get("last_updated"): | |
| metadata["last_updated"] = model_data["last_updated"] | |
| # Provider metadata | |
| if provider_data.get("api"): | |
| metadata["api_base"] = provider_data["api"] | |
| if provider_data.get("env"): | |
| metadata["env_vars"] = provider_data["env"] | |
| if provider_data.get("doc"): | |
| metadata["documentation_url"] = provider_data["doc"] | |
| return metadata |
🤖 Prompt for AI Agents
In src/lfx/src/lfx/base/models/models_dev_client.py around lines 229 to 304, the
default icon is set to the lowercase string "bot" which is inconsistent with
PROVIDER_ICON_MAP and elsewhere using "Bot"; change the default icon value to
"Bot" (capital B) so the fallback matches the map and frontend lookups—update
the icon assignment to use "Bot" instead of "bot".
| @lru_cache(maxsize=1) | ||
| def get_provider_metadata_from_api() -> dict[str, dict[str, Any]]: | ||
| """Get provider metadata from the API for all supported providers. | ||
| Returns: | ||
| Dictionary mapping provider names to their metadata | ||
| """ | ||
| api_data = fetch_models_dev_data() | ||
| if not api_data: | ||
| return {} | ||
|
|
||
| provider_metadata = {} | ||
| for provider_id, provider_data in api_data.items(): | ||
| if provider_id not in SUPPORTED_PROVIDERS: | ||
| continue | ||
|
|
||
| provider_name = PROVIDER_NAME_MAP.get(provider_id, provider_data.get("name", provider_id.title())) | ||
| icon = PROVIDER_ICON_MAP.get(provider_id, "Bot") | ||
|
|
||
| env_vars = provider_data.get("env", []) | ||
| variable_name = env_vars[0] if env_vars else f"{provider_id.upper()}_API_KEY" | ||
|
|
||
| provider_metadata[provider_name] = { | ||
| "icon": icon, | ||
| "variable_name": variable_name, | ||
| "api_base": provider_data.get("api"), | ||
| "documentation_url": provider_data.get("doc"), | ||
| "provider_id": provider_id, | ||
| } | ||
|
|
||
| return provider_metadata | ||
|
|
There was a problem hiding this comment.
Address cache coherence issue with lru_cache.
The @lru_cache decorator creates a memory cache that won't be invalidated when clear_cache() is called. This could lead to stale provider metadata being returned from memory even after the disk cache is cleared.
Apply this diff to clear the lru_cache when clearing disk cache:
def clear_cache() -> None:
"""Clear the models.dev cache."""
cache_path = _get_cache_path()
try:
if cache_path.exists():
cache_path.unlink()
+ get_provider_metadata_from_api.cache_clear()
logger.info("Cleared models.dev cache")
except OSError as e:
logger.warning(f"Failed to clear cache: {e}")Committable suggestion skipped: line range outside the PR's diff.
🤖 Prompt for AI Agents
In src/lfx/src/lfx/base/models/models_dev_client.py around lines 353-384, the
get_provider_metadata_from_api function is decorated with @lru_cache which
causes stale in-memory data after clearing the disk cache; update the code that
clears the disk cache (where clear_cache() or similar is implemented) to also
call get_provider_metadata_from_api.cache_clear() so the lru_cache is
invalidated when disk cache is cleared; if clear_cache() lives in another
module, import get_provider_metadata_from_api there and invoke .cache_clear() as
part of the cache-clearing routine.
Summary by CodeRabbit
New Features
Improvements
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