PR Summary: Unified Model Providers Configuration

Overview

This PR introduces a centralized system for managing AI model providers and configurations across Langflow, moving from provider-specific implementations to a unified, dynamic approach.

Key Features Added

1. New API Endpoints (`/models` and `/model_options`)

Model Catalog Management:
- List available model providers
- Filter models by provider, type, and metadata (tool_calling, reasoning, deprecated, etc.)
- Retrieve provider-to-credential mappings
User-Specific Model Management:
- Get enabled providers for current user
- Get/update enabled/disabled models per user
- Set/get/clear default models for language and embedding types
Model Options:
- Language model options endpoint
- Embedding model options endpoint

2. Variable Management

Variable validation for model provider keys
Filter internal variables (names with __prefix__) from API responses
Enhanced variable creation/retrieval/deletion

3. Component Refactoring (20+ Starter Projects)

Unified all language model components from provider-specific implementations to a generic approach:

Before:

inputs = [
    DropdownInput(name="provider", options=["OpenAI", "Anthropic", ...]),
    DropdownInput(name="model_name", options=[...]),
    SecretStrInput(name="api_key"),
    # ... provider-specific fields
]

After:

inputs = [
    ModelInput(name="model", providers=[...], dynamic_options=True),
    SecretStrInput(name="api_key"),
    # ... unified fields
]

Affected Projects:

Basic Prompt Chaining, Basic Prompting, Blog Writer
Custom Component Generator, Financial Report Parser, Invoice Summarizer
Memory Chatbot, News Aggregator, Nvidia Remix, Pokédex Agent
Price Deal Finder, Research Translation Loop, SEO Keyword Generator
SaaS Pricing, Search Agent, Social Media Agent, Text Sentiment Analysis
And more...

4. Cleanup

Removed unused forward imports from openai_constants.py
Added docstring to Alembic versions module

Technical Highlights

Backend Service Integration: Uses DatabaseVariableService for user-scoped variable storage (disabled models, default models)
Dynamic Configuration: Components now use get_llm() and update_model_options_in_build_config() helpers for runtime model resolution
Provider Prioritization: Default model provider appears first, followed by enabled providers, then alphabetical
Metadata-Driven: Model enablement considers provider status, deprecation flags, and user preferences

Impact

Simplifies model provider integration
Enables runtime model discovery and configuration
Provides consistent UX across all language model components
Centralizes model credential management
Supports future provider additions without component changes

This is a significant architectural improvement that standardizes model handling across the entire Langflow platform.

Nov 11 '25 18:11 HimavarshaVS

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Walkthrough

Introduces new v1 API endpoints for model management and provider discovery, integrating with a DatabaseVariableService to track user-specific model enablement and defaults. Concurrently, updates 17 starter project JSON templates to replace provider-specific language model inputs with a unified, dynamic ModelInput-based configuration, and removes re-exported OpenAI model constants.

Changes

Cohort / File(s)	Summary
New Model Management API `src/backend/base/langflow/api/router.py`, `src/backend/base/langflow/api/v1/__init__.py`	Registered two new routers (`models_router` and `model_options_router`) in the v1 API module; exposed routers in public API exports.
Model Providers & Listing Endpoints `src/backend/base/langflow/api/v1/models.py`	Added 8 new endpoints: `list_model_providers()`, `list_models()`, `get_model_provider_mapping()`, `get_enabled_providers()`, `get_enabled_models()`, `update_enabled_models()`, `get_default_model()`, `set_default_model()`, `clear_default_model()`. Integrates DatabaseVariableService for persistence of user-scoped disabled/default models. Introduced `ModelStatusUpdate` and `DefaultModelRequest` data models.
Model Options Endpoints `src/backend/base/langflow/api/v1/model_options.py`	Added two GET endpoints under `/model_options`: `get_language_model_options_endpoint()` and `get_embedding_model_options_endpoint()` for returning user-specific model options.
Variable API Updates & Validation `src/backend/base/langflow/api/v1/variable.py`	Added reserved-variable validation for model provider keys via `validate_model_provider_key()`. Implemented filtering to exclude internal variables (names starting and ending with `__`) from read responses. Imported model provider mapping utilities.
OpenAI Constants Cleanup `src/backend/base/langflow/base/models/openai_constants.py`	Removed forward re-exports of `OPENAI_EMBEDDING_MODEL_NAMES` and `OPENAI_MODEL_NAMES` and their `__all__` entries.
Starter Project Refactoring `src/backend/base/langflow/initial_setup/starter_projects/{Basic Prompt Chaining, Basic Prompting, Blog Writer, Custom Component Generator, Financial Report Parser, Invoice Summarizer, Memory Chatbot, News Aggregator, Nvidia Remix, Pokédex Agent, Price Deal Finder, Research Translation Loop, SEO Keyword Generator, SaaS Pricing, Search agent, Social Media Agent, Text Sentiment Analysis}.json`	Replaced provider-specific LanguageModelComponent/AgentComponent inputs (DropdownInput for provider/model_name, static inputs per provider) with unified ModelInput-based configuration. Updated node/edge IDs, removed legacy provider-specific fields (e.g., `openai_api_base`, `base_url`, `project_id`, `max_output_tokens`), renamed API key display labels, and regenerated graph positions. Migrated component build logic from explicit per-provider branches to centralized `get_llm` pathway.

Sequence Diagram(s)

sequenceDiagram
    actor User
    participant Client
    participant ModelsAPI as /api/v1/models
    participant VariableService as DatabaseVariableService
    participant UnifiedModels as Unified Models Catalog

    User->>Client: Request list of enabled models for language type
    Client->>ModelsAPI: GET /models/enabled?model_names=...
    ModelsAPI->>UnifiedModels: get_unified_models_detailed()
    UnifiedModels-->>ModelsAPI: Model metadata (provider, deprecated, etc.)
    ModelsAPI->>VariableService: Fetch user disabled-models list
    VariableService-->>ModelsAPI: Disabled model IDs
    ModelsAPI->>ModelsAPI: Filter by provider status + disabled list
    ModelsAPI-->>Client: {provider: {model_id: enabled}}
    
    User->>Client: Enable/disable specific model
    Client->>ModelsAPI: POST /models/enabled (ModelStatusUpdate[])
    ModelsAPI->>VariableService: Update disabled-models variable
    VariableService-->>ModelsAPI: ✓ Persisted
    ModelsAPI-->>Client: Success
    
    User->>Client: Set default language model
    Client->>ModelsAPI: POST /models/default (DefaultModelRequest)
    ModelsAPI->>VariableService: Store default-model JSON
    VariableService-->>ModelsAPI: ✓ Persisted
    ModelsAPI-->>Client: {provider, model_name, model_type}

Estimated code review effort

🎯 4 (Complex) | ⏱️ ~75 minutes

Areas requiring extra attention:

src/backend/base/langflow/api/v1/models.py — Dense logic with provider aggregation, per-provider model enablement computation combining provider status, model metadata (deprecated/not_supported flags), and user-disabled lists; DatabaseVariableService integration for persistence; sorting prioritizing default provider first.
Model default and disabled-model persistence — JSON parsing, variable store key naming, and fallback handling for missing/malformed variables require careful verification of edge cases (e.g., missing default-model variable should not error).
Variable API reserved-key validation — The new validate_model_provider_key() check in create_variable() endpoint blocks creation of variables matching provider keys; verify it integrates correctly with existing tests and does not block legitimate variable creation.
Starter project refactoring scope — 17 files with similar but distinct structural changes (node ID regeneration, field renaming, input model conversion). While the pattern is consistent, verify a sample of each project type (Agent-based, Component-based, Chat-based) to ensure component signatures are correctly translated and that the new ModelInput-based configuration is applied uniformly.
Backward compatibility — Verify that existing stored disabled-models and default-model variables are correctly parsed and migrated (or handled gracefully if missing/malformed).

Possibly related PRs

langflow-ai/langflow#8268 — Introduced unified/detailed model metadata catalog (get_unified_models_detailed) and provider-variable mappings that are directly consumed by the new /models endpoints.
langflow-ai/langflow#8708 — Refactored LanguageModelComponent and starter-project templates to use unified provider-agnostic ModelInput, directly overlapping with the starter-project JSON updates in this PR.
langflow-ai/langflow#10471 — Adds provider-specific model fetch helpers (fetch_ibm_models/fetch_ollama_models) for IBM watsonx.ai/Ollama; this PR removes in-method per-provider logic in favor of centralized option-fetching, so the two refactor the same code paths in opposite directions.

Suggested labels

enhancement, size:L, lgtm

Suggested reviewers

ogabrielluiz
edwinjosechittilappilly
jordanrfrazier

Pre-merge checks and finishing touches

❌ Failed checks (1 error, 2 warnings)

Check name	Status	Explanation	Resolution
Test Coverage For New Implementations	❌ Error	PR adds 8+ new API endpoints in models.py, new model_options.py router with 2 endpoints, variable.py modifications for model provider validation, and database migrations, but includes no accompanying test files or test coverage for the new functionality.	Add comprehensive tests for new endpoints (models.py, model_options.py), model provider validation in variable.py, database migrations, and DatabaseVariableService operations with category field.
Test Quality And Coverage	⚠️ Warning	No test files found for new implementations in models.py, model_options.py, and variable.py modifications covering 8+ endpoints with async operations and complex validation logic.	Add comprehensive pytest test coverage for all new endpoints including async tests, error handling, user isolation, and blocking call validation in variable.py endpoints.
Test File Naming And Structure	⚠️ Warning	PR adds two new API files with 10+ endpoints and modifies critical validation logic but includes no corresponding test files despite established repository test patterns.	Add test files: test_models.py for 8+ model endpoints, test_model_options.py for 2 new endpoints, and extend test_variable.py for reserved-variable validation logic, following async/pytest patterns established in repository.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Title check	✅ Passed	The PR title accurately describes the main objective: introducing unified model provider configuration via new API endpoints and variable management improvements.
Docstring Coverage	✅ Passed	Docstring coverage is 86.67% which is sufficient. The required threshold is 80.00%.
Excessive Mock Usage Warning	✅ Passed	The custom check for excessive mock usage is not applicable to this pull request. The PR introduces new production code for API endpoints and updates starter project JSON configurations, but does not include or modify any test files. Since no test files were added or modified, there is no test code to evaluate for mock usage patterns.
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.

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Nov 11 '25 18:11 coderabbitai[bot]

Frontend Unit Test Coverage Report

Coverage Summary

Lines	Statements	Branches	Functions
	16.37% (4586/28003)	9.65% (2087/21610)	10.68% (659/6165)

Unit Test Results

Tests	Skipped	Failures	Errors	Time
1777	0 :zzz:	0 :x:	0 :fire:	24.245s :stopwatch:

Nov 11 '25 19:11 github-actions[bot]

Codecov Report

:x: Patch coverage is 27.03412% with 278 lines in your changes missing coverage. Please review. :white_check_mark: Project coverage is 30.18%. Comparing base (b0bae86) to head (bd3a45c). :warning: Report is 1 commits behind head on main.

Files with missing lines	Patch %	Lines
src/backend/base/langflow/api/v1/models.py	24.60%	236 Missing :warning:
src/backend/base/langflow/api/v1/variable.py	27.27%	40 Missing :warning:
src/backend/base/langflow/api/v1/model_options.py	80.00%	2 Missing :warning:

:x: Your patch status has failed because the patch coverage (27.03%) is below the target coverage (40.00%). You can increase the patch coverage or adjust the target coverage. :x: Your project status has failed because the head coverage (39.27%) is below the target coverage (60.00%). You can increase the head coverage or adjust the target coverage.

Additional details and impacted files

@@            Coverage Diff             @@
##             main   #10565      +/-   ##
==========================================
- Coverage   32.96%   30.18%   -2.79%     
==========================================
  Files        1372     1387      +15     
  Lines       63889    65334    +1445     
  Branches     9404     9653     +249     
==========================================
- Hits        21062    19719    -1343     
- Misses      41782    44522    +2740     
- Partials     1045     1093      +48

Flag	Coverage Δ
backend	`41.76% <27.03%> (-10.95%)`	:arrow_down:

Flags with carried forward coverage won't be shown. Click here to find out more.

Files with missing lines	Coverage Δ
src/backend/base/langflow/api/router.py	`100.00% <100.00%> (ø)`
src/backend/base/langflow/api/v1/mcp.py	`58.70% <100.00%> (-8.39%)`	:arrow_down:
src/backend/base/langflow/api/v1/mcp_projects.py	`29.10% <ø> (-11.80%)`	:arrow_down:
src/backend/base/langflow/inputs/inputs.py	`0.00% <ø> (ø)`
...angflow/services/database/models/variable/model.py	`100.00% <ø> (ø)`
...rc/backend/base/langflow/services/variable/base.py	`100.00% <ø> (ø)`
...kend/base/langflow/services/variable/kubernetes.py	`0.00% <ø> (ø)`
...backend/base/langflow/services/variable/service.py	`47.46% <ø> (-40.24%)`	:arrow_down:
...es/GenericNode/components/NodeInputField/index.tsx	`0.00% <ø> (ø)`
...nents/common/modelProviderCountComponent/index.tsx	`95.00% <ø> (ø)`
... and 38 more

... and 103 files with indirect coverage changes

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Nov 11 '25 19:11 codecov[bot]

@coderabbitai Can you do an assessment of the (1) quality, (2) security robustness, and (3) merge worthiness of this PR? and please ensure you're using the LATEST commit hash: 03183dfc6a5bd15aad2925026d639729037ed7ee

Dec 09 '25 16:12 erichare

[!TIP] For best results, initiate chat on the files or code changes.

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@erichare I've completed a comprehensive assessment of PR #10565. Here are my findings:

⚠️ Important: Commit Hash Discrepancy

The branch is currently at commit bd3a45c10fd (autofix attempt 2/3), but you requested 03183dfc6a5b (autofix attempt 3/3). The requested commit exists in the history but isn't the current HEAD. Please verify which commit should be reviewed.

1️⃣ QUALITY ASSESSMENT: GOOD (7/10)

✅ Strengths:

Well-structured code: Clear separation of concerns with dedicated routers, models, and helper functions
Comprehensive input validation: Pydantic models with custom validators (@field_validator) enforcing length limits and non-empty strings
Robust error handling: Consistent try/except patterns with appropriate HTTPException responses
Audit logging: Sensitive operations (model updates, default changes) are logged with user IDs
Security constants: MAX_STRING_LENGTH=200, MAX_BATCH_UPDATE_SIZE=100 prevent abuse
Test coverage: Multiple test files exist (test_models_api.py, test_models_enabled_providers.py)
Type safety: Comprehensive type hints throughout
API key validation: Calls validate_model_provider_key asynchronously when creating/updating provider credentials

⚠️ Issues:

Missing database migration: PR description mentions "adds a category column to the variable table" but no such Alembic migration exists
Broad exception catching: Several except Exception as e blocks (lines 151, 250, 425 in models.py)
Heavy JSON serialization: Storing model lists as JSON strings in variables could impact performance at scale
Inconsistent variable cleanup: Internal variables (e.g., __disabled_models__) are filtered from read_variables but created alongside user variables

2️⃣ SECURITY ROBUSTNESS: MODERATE (6/10)

✅ Strengths:

Authentication enforced: All endpoints require CurrentActiveUser dependency
Input validation: String length limits (200 chars), batch size limits (100 items), Pydantic validators
SQL injection protection: Uses SQLAlchemy ORM with parameterized queries
User isolation: Operations scoped to current_user.id prevent unauthorized access
Audit trails: Logs user actions for model configuration changes
API key validation: External validation (validate_model_provider_key) before storing credentials
Internal variable filtering: Variables starting/ending with __ hidden from public listing

🚨 Critical Security Gaps:

NO RATE LIMITING: Endpoints like /models/enabled_models (POST) lack rate limiting, enabling:
- Brute force attacks on API key validation
- DoS via repeated large batch updates
- Resource exhaustion through repeated JSON parsing
Batch size concerns: MAX_BATCH_UPDATE_SIZE=100 is high; a malicious actor could repeatedly update 100 models to exhaust resources
No timeout on external calls: validate_model_provider_key has no visible timeout, risking hanging requests
Exception suppression: Line 151 in models.py silences exceptions when fetching default models (# noqa: BLE001)
Dependency on external validation: Security relies on lfx.base.models.unified_models.validate_model_provider_key whose implementation isn't visible

Recommendations:

# Add rate limiting (example using slowapi)
from slowapi import Limiter
from slowapi.util import get_remote_address

limiter = Limiter(key_func=get_remote_address)

@router.post("/enabled_models", status_code=200)
@limiter.limit("10/minute")  # Limit to 10 updates per minute
async def update_enabled_models(...):
    ...

3️⃣ MERGE WORTHINESS: CONDITIONAL APPROVAL (⚠️ Requires Fixes)

🚫 Blocking Issues:

Missing database migration: PR description claims category column addition but no migration found. This could cause:
- Runtime errors if code expects the column
- Data integrity issues
- Failed deployments
Commit hash mismatch: Current HEAD ≠ requested commit for review

⚠️ High-Risk Areas:

Large surface area: Updates to 19 starter project JSON files with substantial LanguageModelComponent refactoring
- Risk: Breaking existing user flows
- Mitigation: Requires thorough integration testing
No rate limiting: Production deployment could be vulnerable immediately
Variable service assumptions: Code assumes DatabaseVariableService with isinstance checks but no fallback logic

✅ Positive Signals:

Non-breaking API changes: Only adds new endpoints
Clean router integration: Simple 2-line additions to router.py
Test coverage: Tests exist for core functionality
Follows conventions: Consistent with existing codebase patterns
User isolation: Proper scoping prevents cross-user data leakage

📋 Recommendations Before Merge:

Must-Have:

✅ Resolve commit discrepancy - checkout 03183dfc6a5b or clarify intent
✅ Add/verify category migration - Check if it was accidentally excluded or if PR description is incorrect
✅ Implement rate limiting - At minimum on POST endpoints
✅ Integration tests - Verify starter projects load correctly with new component structure

Should-Have:

Add timeout to validate_model_provider_key calls
Lower MAX_BATCH_UPDATE_SIZE to 50 or add exponential backoff
Add API documentation (OpenAPI/Swagger annotations)
Consider caching for get_model_provider_variable_mapping() (called frequently)

Nice-to-Have:

Add metrics/monitoring for model configuration changes
Consider pagination for /models endpoint if catalog grows large
Add validation that model_name/provider exist before setting as default

🎯 Final Verdict:

Conditional Merge - Code quality is good and architecture is sound, but blocking issues must be resolved:

Clarify missing category migration
Add rate limiting
Verify commit hash

Once addressed, this PR provides a solid foundation for unified model provider management with proper security boundaries.

Dec 09 '25 16:12 coderabbitai[bot]

feat: Add a Unified Model Providers configuration

PR Summary: Unified Model Providers Configuration

Overview

Key Features Added

1. New API Endpoints (/models and /model_options)

2. Variable Management

3. Component Refactoring (20+ Starter Projects)

4. Cleanup

Technical Highlights

Impact

Review skipped

Walkthrough

Changes

Sequence Diagram(s)

Estimated code review effort

Possibly related PRs

Suggested labels

Suggested reviewers

Pre-merge checks and finishing touches

Frontend Unit Test Coverage Report

Coverage Summary

Unit Test Results

Codecov Report

⚠️ Important: Commit Hash Discrepancy

1️⃣ QUALITY ASSESSMENT: GOOD (7/10)

✅ Strengths:

⚠️ Issues:

2️⃣ SECURITY ROBUSTNESS: MODERATE (6/10)

✅ Strengths:

🚨 Critical Security Gaps:

Recommendations:

3️⃣ MERGE WORTHINESS: CONDITIONAL APPROVAL (⚠️ Requires Fixes)

🚫 Blocking Issues:

⚠️ High-Risk Areas:

✅ Positive Signals:

📋 Recommendations Before Merge:

Must-Have:

Should-Have:

Nice-to-Have:

🎯 Final Verdict:

1. New API Endpoints (`/models` and `/model_options`)