feat(llm): expand LLM provider options and improve model selection UI

- Added new LLM providers including Google, Azure OpenAI, Bedrock, and others to the backend.
- Updated the model selection UI to dynamically display available models based on the selected provider.
- Enhanced the provider change handling to reset the model selection when the provider is changed.
- Improved the overall user experience by providing contextual information for model selection.
This commit is contained in:
DESKTOP-RTLN3BA\$punk 2025-11-13 02:41:30 -08:00
parent c1e8753567
commit 38dffaffa3
10 changed files with 2197 additions and 126 deletions

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@ -0,0 +1,199 @@
"""Update LiteLLMProvider enum with comprehensive provider support
This migration adds support for all major LiteLLM providers including:
- Fast inference platforms (XAI, Cerebras, SambaNova, Fireworks AI)
- Cloud platforms (Cloudflare, Databricks)
- Renames AWS_BEDROCK to BEDROCK for consistency
- Adds CUSTOM for custom OpenAI-compatible endpoints
Revision ID: 35
Revises: 34
"""
from collections.abc import Sequence
from alembic import op
# revision identifiers, used by Alembic.
revision: str = "35"
down_revision: str | None = "34"
branch_labels: str | Sequence[str] | None = None
depends_on: str | Sequence[str] | None = None
def upgrade() -> None:
"""
Add new LLM providers to LiteLLMProvider enum and migrate existing data.
New providers added:
- XAI: xAI's Grok models
- FIREWORKS_AI: Fireworks AI platform
- CEREBRAS: Cerebras inference platform (fastest)
- SAMBANOVA: SambaNova inference platform
- CLOUDFLARE: Cloudflare Workers AI
- DATABRICKS: Databricks Model Serving
- BEDROCK: AWS Bedrock (replaces AWS_BEDROCK)
- CUSTOM: Custom OpenAI-compatible endpoints
"""
# Add XAI (xAI Grok models)
op.execute(
"""
DO $$
BEGIN
IF NOT EXISTS (
SELECT 1 FROM pg_enum
WHERE enumtypid = 'litellmprovider'::regtype
AND enumlabel = 'XAI'
) THEN
ALTER TYPE litellmprovider ADD VALUE 'XAI';
END IF;
END$$;
"""
)
# Add FIREWORKS_AI
op.execute(
"""
DO $$
BEGIN
IF NOT EXISTS (
SELECT 1 FROM pg_enum
WHERE enumtypid = 'litellmprovider'::regtype
AND enumlabel = 'FIREWORKS_AI'
) THEN
ALTER TYPE litellmprovider ADD VALUE 'FIREWORKS_AI';
END IF;
END$$;
"""
)
# Add CEREBRAS (fastest inference platform)
op.execute(
"""
DO $$
BEGIN
IF NOT EXISTS (
SELECT 1 FROM pg_enum
WHERE enumtypid = 'litellmprovider'::regtype
AND enumlabel = 'CEREBRAS'
) THEN
ALTER TYPE litellmprovider ADD VALUE 'CEREBRAS';
END IF;
END$$;
"""
)
# Add SAMBANOVA
op.execute(
"""
DO $$
BEGIN
IF NOT EXISTS (
SELECT 1 FROM pg_enum
WHERE enumtypid = 'litellmprovider'::regtype
AND enumlabel = 'SAMBANOVA'
) THEN
ALTER TYPE litellmprovider ADD VALUE 'SAMBANOVA';
END IF;
END$$;
"""
)
# Add CLOUDFLARE (Cloudflare Workers AI)
op.execute(
"""
DO $$
BEGIN
IF NOT EXISTS (
SELECT 1 FROM pg_enum
WHERE enumtypid = 'litellmprovider'::regtype
AND enumlabel = 'CLOUDFLARE'
) THEN
ALTER TYPE litellmprovider ADD VALUE 'CLOUDFLARE';
END IF;
END$$;
"""
)
# Add DATABRICKS
op.execute(
"""
DO $$
BEGIN
IF NOT EXISTS (
SELECT 1 FROM pg_enum
WHERE enumtypid = 'litellmprovider'::regtype
AND enumlabel = 'DATABRICKS'
) THEN
ALTER TYPE litellmprovider ADD VALUE 'DATABRICKS';
END IF;
END$$;
"""
)
# Add BEDROCK (new standardized name)
op.execute(
"""
DO $$
BEGIN
IF NOT EXISTS (
SELECT 1 FROM pg_enum
WHERE enumtypid = 'litellmprovider'::regtype
AND enumlabel = 'BEDROCK'
) THEN
ALTER TYPE litellmprovider ADD VALUE 'BEDROCK';
END IF;
END$$;
"""
)
# Add CUSTOM for custom OpenAI-compatible endpoints
op.execute(
"""
DO $$
BEGIN
IF NOT EXISTS (
SELECT 1 FROM pg_enum
WHERE enumtypid = 'litellmprovider'::regtype
AND enumlabel = 'CUSTOM'
) THEN
ALTER TYPE litellmprovider ADD VALUE 'CUSTOM';
END IF;
END$$;
"""
)
# Note: Both AWS_BEDROCK and BEDROCK will coexist in the enum for backward compatibility.
# - New configurations will use BEDROCK (via the frontend)
# - Existing AWS_BEDROCK configurations will continue to work
# - The backend service handles both values correctly
#
# Legacy enum values (PALM, NLPCLOUD, ALEPH_ALPHA, PETALS, etc.) also remain in the enum.
# PostgreSQL doesn't support removing enum values without recreating the entire type.
#
# Data migration from AWS_BEDROCK -> BEDROCK is NOT performed because:
# 1. PostgreSQL doesn't allow using new enum values in the same transaction
# 2. Both values work correctly with the backend service
# 3. Users can manually update old configs if desired (not required)
def downgrade() -> None:
"""
Downgrade migration.
Note: PostgreSQL doesn't support removing enum values directly.
This would require recreating the entire enum type and updating all dependent objects.
For safety and data preservation, this downgrade is a no-op.
If you need to downgrade, you should:
1. Ensure no llm_configs are using the new providers
2. Manually remove enum values (requires enum recreation - complex operation)
This is not automated to prevent accidental data loss.
New enum values (XAI, FIREWORKS_AI, CEREBRAS, BEDROCK, etc.) will remain
in the database but won't be selectable in the application after downgrade.
"""
# PostgreSQL doesn't support removing enum values directly
# This is a no-op for safety
pass

View file

@ -86,32 +86,33 @@ class LiteLLMProvider(str, Enum):
OPENAI = "OPENAI"
ANTHROPIC = "ANTHROPIC"
GOOGLE = "GOOGLE"
AZURE_OPENAI = "AZURE_OPENAI"
BEDROCK = "BEDROCK"
VERTEX_AI = "VERTEX_AI"
GROQ = "GROQ"
COHERE = "COHERE"
HUGGINGFACE = "HUGGINGFACE"
AZURE_OPENAI = "AZURE_OPENAI"
GOOGLE = "GOOGLE"
AWS_BEDROCK = "AWS_BEDROCK"
OLLAMA = "OLLAMA"
MISTRAL = "MISTRAL"
TOGETHER_AI = "TOGETHER_AI"
OPENROUTER = "OPENROUTER"
REPLICATE = "REPLICATE"
PALM = "PALM"
VERTEX_AI = "VERTEX_AI"
ANYSCALE = "ANYSCALE"
PERPLEXITY = "PERPLEXITY"
DEEPINFRA = "DEEPINFRA"
AI21 = "AI21"
NLPCLOUD = "NLPCLOUD"
ALEPH_ALPHA = "ALEPH_ALPHA"
PETALS = "PETALS"
COMETAPI = "COMETAPI"
# Chinese LLM Providers (OpenAI-compatible)
DEEPSEEK = "DEEPSEEK"
XAI = "XAI"
OPENROUTER = "OPENROUTER"
TOGETHER_AI = "TOGETHER_AI"
FIREWORKS_AI = "FIREWORKS_AI"
REPLICATE = "REPLICATE"
PERPLEXITY = "PERPLEXITY"
OLLAMA = "OLLAMA"
ALIBABA_QWEN = "ALIBABA_QWEN"
MOONSHOT = "MOONSHOT"
ZHIPU = "ZHIPU"
ANYSCALE = "ANYSCALE"
DEEPINFRA = "DEEPINFRA"
CEREBRAS = "CEREBRAS"
SAMBANOVA = "SAMBANOVA"
AI21 = "AI21"
CLOUDFLARE = "CLOUDFLARE"
DATABRICKS = "DATABRICKS"
COMETAPI = "COMETAPI"
HUGGINGFACE = "HUGGINGFACE"
CUSTOM = "CUSTOM"

View file

@ -61,11 +61,26 @@ async def validate_llm_config(
"AZURE_OPENAI": "azure",
"OPENROUTER": "openrouter",
"COMETAPI": "cometapi",
# Chinese LLM providers (OpenAI-compatible)
"XAI": "xai",
"BEDROCK": "bedrock",
"AWS_BEDROCK": "bedrock", # Legacy support (backward compatibility)
"VERTEX_AI": "vertex_ai",
"TOGETHER_AI": "together_ai",
"FIREWORKS_AI": "fireworks_ai",
"REPLICATE": "replicate",
"PERPLEXITY": "perplexity",
"ANYSCALE": "anyscale",
"DEEPINFRA": "deepinfra",
"CEREBRAS": "cerebras",
"SAMBANOVA": "sambanova",
"AI21": "ai21",
"CLOUDFLARE": "cloudflare",
"DATABRICKS": "databricks",
# Chinese LLM providers
"DEEPSEEK": "openai",
"ALIBABA_QWEN": "openai",
"MOONSHOT": "openai",
"ZHIPU": "openai",
"ZHIPU": "openai", # GLM needs special handling
}
provider_prefix = provider_map.get(provider, provider.lower())
model_string = f"{provider_prefix}/{model_name}"
@ -187,12 +202,26 @@ async def get_user_llm_instance(
"AZURE_OPENAI": "azure",
"OPENROUTER": "openrouter",
"COMETAPI": "cometapi",
# Chinese LLM providers (OpenAI-compatible)
"DEEPSEEK": "openai", # DeepSeek uses OpenAI-compatible API
"ALIBABA_QWEN": "openai", # Qwen uses OpenAI-compatible API
"MOONSHOT": "openai", # Moonshot (Kimi) uses OpenAI-compatible API
"ZHIPU": "openai", # Zhipu (GLM) uses OpenAI-compatible API
# Add more mappings as needed
"XAI": "xai",
"BEDROCK": "bedrock",
"AWS_BEDROCK": "bedrock", # Legacy support (backward compatibility)
"VERTEX_AI": "vertex_ai",
"TOGETHER_AI": "together_ai",
"FIREWORKS_AI": "fireworks_ai",
"REPLICATE": "replicate",
"PERPLEXITY": "perplexity",
"ANYSCALE": "anyscale",
"DEEPINFRA": "deepinfra",
"CEREBRAS": "cerebras",
"SAMBANOVA": "sambanova",
"AI21": "ai21",
"CLOUDFLARE": "cloudflare",
"DATABRICKS": "databricks",
# Chinese LLM providers
"DEEPSEEK": "openai",
"ALIBABA_QWEN": "openai",
"MOONSHOT": "openai",
"ZHIPU": "openai",
}
provider_prefix = provider_map.get(
llm_config.provider.value, llm_config.provider.value.lower()