feat: implement LLM Gateway with multi-provider support

Implement a unified LLM Gateway supporting multiple API formats and providers:

Features:
- OpenAI Chat Completions, Responses API, and Anthropic Messages API
- Provider adapters for OpenAI, Anthropic, Azure OpenAI, Google Gemini, AWS Bedrock
- Model aliasing with weighted round-robin load balancing
- Virtual API keys with RPM/TPM rate limiting
- Budget control at key and project levels
- Request logging, usage statistics, and audit logs
- Fallback/retry with circuit breaker pattern
- Admin CRUD APIs for providers, projects, keys, models, usage
- Provider health checks

Tech stack:
- FastAPI with async SQLAlchemy 2.0
- SQLite with aiosqlite
- bcrypt for API key hashing, AES-256 for provider key encryption
- Docker containerization

Tests: 18 passing integration tests for admin API endpoints

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

llm-gateway/.env.example

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+# Application
+APP_NAME=LLM Gateway
+DEBUG=false
+LOG_LEVEL=INFO
+
+# Server
+HOST=0.0.0.0
+PORT=8000
+
+# Database
+DATABASE_URL=sqlite:///data/gateway.db
+
+# Security
+# Generate with: python -c "import secrets; print(secrets.token_hex(32))"
+MASTER_KEY=your-master-key-here-at-least-32-characters
+
+# Rate Limiting
+RATE_LIMIT_WINDOW_SECONDS=60
+# GLOBAL_RPM_LIMIT=1000
+# GLOBAL_TPM_LIMIT=1000000
+
+# Retry
+MAX_RETRIES=3
+RETRY_INITIAL_DELAY=1.0
+RETRY_MAX_DELAY=30.0
+
+# Health Check
+HEALTH_CHECK_INTERVAL=30
+HEALTH_CHECK_TIMEOUT=10

llm-gateway/.gitignore

@@ -0,0 +1,65 @@
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# Virtual environments
+venv/
+ENV/
+env/
+.venv/
+
+# IDE
+.idea/
+.vscode/
+*.swp
+*.swo
+*~
+
+# Testing
+.pytest_cache/
+.coverage
+htmlcov/
+.tox/
+.nox/
+
+# Type checking
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Environment
+.env
+.env.local
+.env.*.local
+
+# Database
+*.db
+*.sqlite
+*.sqlite3
+data/
+
+# Logs
+*.log
+logs/
+
+# OS
+.DS_Store
+Thumbs.db

llm-gateway/Dockerfile

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+FROM python:3.11-slim
+
+WORKDIR /app
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    curl \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy requirements first for caching
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy application code
+COPY . .
+
+# Create data directory
+RUN mkdir -p /app/data
+
+# Expose port
+EXPOSE 8000
+
+# Health check
+HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
+    CMD curl -f http://localhost:8000/health || exit 1
+
+# Run the application
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]

llm-gateway/README.md

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+# LLM Gateway
+
+A unified LLM Gateway supporting multiple providers and API formats.
+
+## Features
+
+- **Multi-format API**: OpenAI Chat Completions, OpenAI Responses API, Anthropic Messages API
+- **Multi-provider support**: OpenAI, Anthropic, Azure OpenAI, Google Gemini, AWS Bedrock
+- **Model aliasing and routing**: Flexible model mapping with load balancing
+- **Rate limiting**: RPM/TPM limits at multiple levels
+- **Budget control**: Key and Project level spending limits
+- **High availability**: Fallback, retry, and circuit breaker
+- **Observability**: Request logging and usage statistics
+
+## Quick Start
+
+```bash
+# Install dependencies
+pip install -r requirements.txt
+
+# Run the server
+uvicorn app.main:app --reload
+```
+
+## API Endpoints
+
+### LLM APIs
+- `POST /v1/chat/completions` - OpenAI-compatible chat completions
+- `POST /v1/responses` - OpenAI Responses API
+- `POST /v1/messages` - Anthropic Messages API
+
+### Admin APIs
+- `GET|POST|PUT|DELETE /admin/providers` - Provider management
+- `GET|POST|PUT|DELETE /admin/keys` - API Key management
+- `GET|POST|PUT|DELETE /admin/projects` - Project management
+- `GET|POST|PUT|DELETE /admin/models/aliases` - Model alias management
+- `GET /admin/usage/stats` - Usage statistics
+
+## Configuration
+
+See `.env.example` for configuration options.

llm-gateway/app/__init__.py

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+# app module

llm-gateway/app/adapters/__init__.py

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+"""Provider adapters package."""
+from typing import Type
+
+from app.adapters.anthropic import AnthropicAdapter
+from app.adapters.azure import AzureOpenAIAdapter
+from app.adapters.base import BaseAdapter, HealthStatus, ProviderConfig
+from app.adapters.bedrock import BedrockAdapter
+from app.adapters.gemini import GeminiAdapter
+from app.adapters.openai import OpenAIAdapter
+
+
+# Registry of provider adapters
+ADAPTER_REGISTRY: dict[str, Type[BaseAdapter]] = {
+    "openai": OpenAIAdapter,
+    "anthropic": AnthropicAdapter,
+    "azure": AzureOpenAIAdapter,
+    "gemini": GeminiAdapter,
+    "bedrock": BedrockAdapter,
+    "google": GeminiAdapter,  # Alias
+    "aws": BedrockAdapter,  # Alias
+}
+
+
+def get_adapter_class(provider: str) -> Type[BaseAdapter]:
+    """
+    Get the adapter class for a provider.
+
+    Args:
+        provider: Provider name.
+
+    Returns:
+        Adapter class.
+
+    Raises:
+        ValueError: If provider is not supported.
+    """
+    provider_lower = provider.lower()
+    if provider_lower not in ADAPTER_REGISTRY:
+        raise ValueError(f"Unsupported provider: {provider}")
+    return ADAPTER_REGISTRY[provider_lower]
+
+
+def create_adapter(config: ProviderConfig) -> BaseAdapter:
+    """
+    Create an adapter instance for a provider.
+
+    Args:
+        config: Provider configuration.
+
+    Returns:
+        Adapter instance.
+    """
+    adapter_class = get_adapter_class(config.name)
+    return adapter_class(config)
+
+
+__all__ = [
+    "BaseAdapter",
+    "HealthStatus",
+    "ProviderConfig",
+    "OpenAIAdapter",
+    "AnthropicAdapter",
+    "AzureOpenAIAdapter",
+    "GeminiAdapter",
+    "BedrockAdapter",
+    "get_adapter_class",
+    "create_adapter",
+    "ADAPTER_REGISTRY",
+]

llm-gateway/app/adapters/anthropic.py

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+"""Anthropic provider adapter."""
+import json
+import time
+import uuid
+from typing import AsyncIterator
+
+import httpx
+
+from app.adapters.base import BaseAdapter, HealthStatus, ProviderConfig
+from app.core.fallback import RetryableError, PermanentError, classify_error
+from app.core.transformer import RequestTransformer
+from app.schemas.anthropic import (
+    AnthropicMessagesRequest,
+    AnthropicMessagesResponse,
+    AnthropicTextBlock,
+    AnthropicUsage,
+)
+from app.schemas.openai import (
+    OpenAIChatCompletionChunk,
+    OpenAIChatCompletionRequest,
+    OpenAIChatCompletionResponse,
+)
+
+
+class AnthropicAdapter(BaseAdapter):
+    """Adapter for Anthropic Claude API."""
+
+    def __init__(self, config: ProviderConfig):
+        super().__init__(config)
+        self.transformer = RequestTransformer()
+
+    def get_headers(self) -> dict[str, str]:
+        """Get headers for Anthropic API requests."""
+        headers = {
+            **super().get_headers(),
+            "x-api-key": self.config.api_key,
+            "anthropic-version": self.config.api_version or "2023-06-01",
+        }
+        return headers
+
+    async def chat_completions(
+        self,
+        request: OpenAIChatCompletionRequest,
+    ) -> OpenAIChatCompletionResponse:
+        """
+        Execute an OpenAI-format chat completion request via Anthropic.
+        Converts request to Anthropic format, calls Anthropic, converts response back.
+        """
+        # Convert OpenAI request to Anthropic format
+        anthropic_request = self.transformer.openai_to_anthropic(request)
+
+        # Call Anthropic
+        anthropic_response = await self.messages(anthropic_request)
+
+        # Convert response back to OpenAI format
+        return self.transformer.anthropic_response_to_openai(
+            anthropic_response, request.model
+        )
+
+    async def stream_chat_completions(
+        self,
+        request: OpenAIChatCompletionRequest,
+    ) -> AsyncIterator[OpenAIChatCompletionChunk]:
+        """Execute a streaming chat completion request via Anthropic."""
+        # Convert to Anthropic format
+        anthropic_request = self.transformer.openai_to_anthropic(request)
+        anthropic_request.stream = True
+
+        url = f"{self.config.api_base}/v1/messages"
+        payload = anthropic_request.model_dump(exclude_none=True)
+
+        async with httpx.AsyncClient(timeout=120.0) as client:
+            try:
+                async with client.stream(
+                    "POST",
+                    url,
+                    headers=self.get_headers(),
+                    json=payload,
+                ) as response:
+                    if response.status_code >= 400:
+                        error = classify_error(
+                            Exception(f"{response.status_code}: {await response.aread()}")
+                        )
+                        raise error
+
+                    message_id = None
+                    model = request.model
+
+                    async for line in response.aiter_lines():
+                        if not line.startswith("data: "):
+                            continue
+
+                        data = line[6:]
+                        try:
+                            event = json.loads(data)
+                        except json.JSONDecodeError:
+                            continue
+
+                        event_type = event.get("type")
+
+                        if event_type == "message_start":
+                            message_id = event.get("message", {}).get("id")
+
+                        elif event_type == "content_block_delta":
+                            delta = event.get("delta", {})
+                            text = delta.get("text", "")
+
+                            chunk = OpenAIChatCompletionChunk(
+                                id=message_id or f"chatcmpl-{uuid.uuid4().hex[:24]}",
+                                object="chat.completion.chunk",
+                                created=int(time.time()),
+                                model=model,
+                                choices=[
+                                    {
+                                        "index": 0,
+                                        "delta": {"content": text, "role": "assistant"},
+                                        "finish_reason": None,
+                                    }
+                                ],
+                            )
+                            yield chunk
+
+                        elif event_type == "message_delta":
+                            delta = event.get("delta", {})
+                            stop_reason = delta.get("stop_reason")
+
+                            if stop_reason:
+                                finish_reason = "stop" if stop_reason == "end_turn" else "length"
+                                chunk = OpenAIChatCompletionChunk(
+                                    id=message_id or f"chatcmpl-{uuid.uuid4().hex[:24]}",
+                                    object="chat.completion.chunk",
+                                    created=int(time.time()),
+                                    model=model,
+                                    choices=[
+                                        {
+                                            "index": 0,
+                                            "delta": {},
+                                            "finish_reason": finish_reason,
+                                        }
+                                    ],
+                                )
+                                yield chunk
+
+            except httpx.TimeoutException as e:
+                raise RetryableError(str(e), error_type="timeout")
+            except httpx.ConnectError as e:
+                raise RetryableError(str(e), error_type="connection_error")
+
+    async def messages(
+        self,
+        request: AnthropicMessagesRequest,
+    ) -> AnthropicMessagesResponse:
+        """Execute an Anthropic Messages API request."""
+        url = f"{self.config.api_base}/v1/messages"
+
+        payload = request.model_dump(exclude_none=True)
+
+        async with httpx.AsyncClient(timeout=120.0) as client:
+            try:
+                response = await client.post(
+                    url,
+                    headers=self.get_headers(),
+                    json=payload,
+                )
+
+                if response.status_code >= 400:
+                    error = classify_error(Exception(f"{response.status_code}: {response.text}"))
+                    raise error
+
+                data = response.json()
+                return AnthropicMessagesResponse(**data)
+
+            except httpx.TimeoutException as e:
+                raise RetryableError(str(e), error_type="timeout")
+            except httpx.ConnectError as e:
+                raise RetryableError(str(e), error_type="connection_error")
+
+    async def check_health(self) -> HealthStatus:
+        """Check Anthropic API health by making a minimal request."""
+        # Anthropic doesn't have a health endpoint, so we make a minimal request
+        url = f"{self.config.api_base}/v1/messages"
+
+        # Minimal request
+        payload = {
+            "model": "claude-3-haiku-20240307",
+            "max_tokens": 1,
+            "messages": [{"role": "user", "content": "hi"}],
+        }
+
+        async with httpx.AsyncClient(timeout=10.0) as client:
+            try:
+                response = await client.post(
+                    url,
+                    headers=self.get_headers(),
+                    json=payload,
+                )
+
+                if response.status_code == 200:
+                    return HealthStatus.HEALTHY
+                elif response.status_code >= 500:
+                    return HealthStatus.UNHEALTHY
+                else:
+                    return HealthStatus.DEGRADED
+
+            except Exception:
+                return HealthStatus.UNHEALTHY

llm-gateway/app/adapters/azure.py

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+"""Azure OpenAI provider adapter."""
+from typing import AsyncIterator
+
+from app.adapters.base import BaseAdapter, HealthStatus, ProviderConfig
+from app.adapters.openai import OpenAIAdapter
+from app.schemas.anthropic import AnthropicMessagesRequest, AnthropicMessagesResponse
+from app.schemas.openai import (
+    OpenAIChatCompletionChunk,
+    OpenAIChatCompletionRequest,
+    OpenAIChatCompletionResponse,
+)
+
+
+class AzureOpenAIAdapter(BaseAdapter):
+    """Adapter for Azure OpenAI API."""
+
+    def __init__(self, config: ProviderConfig):
+        super().__init__(config)
+        # Azure uses OpenAI-compatible API
+        self._openai_adapter: OpenAIAdapter | None = None
+
+    def _get_openai_adapter(self) -> OpenAIAdapter:
+        """Get or create OpenAI adapter for Azure."""
+        if self._openai_adapter is None:
+            # Azure config should include deployment_name
+            azure_config = self.config.config or {}
+            deployment_name = azure_config.get("deployment_name", "")
+
+            # Build Azure-specific API base
+            api_base = self.config.api_base
+            if deployment_name:
+                api_base = f"{api_base}/openai/deployments/{deployment_name}"
+
+            openai_config = ProviderConfig(
+                name=self.config.name,
+                api_base=api_base,
+                api_key=self.config.api_key,
+                api_version=self.config.api_version,
+            )
+            self._openai_adapter = OpenAIAdapter(openai_config)
+        return self._openai_adapter
+
+    def get_headers(self) -> dict[str, str]:
+        """Get headers for Azure OpenAI API requests."""
+        return {
+            "Content-Type": "application/json",
+            "api-key": self.config.api_key,  # Azure uses api-key header
+        }
+
+    async def chat_completions(
+        self,
+        request: OpenAIChatCompletionRequest,
+    ) -> OpenAIChatCompletionResponse:
+        """Execute a chat completion request to Azure OpenAI."""
+        adapter = self._get_openai_adapter()
+        return await adapter.chat_completions(request)
+
+    async def stream_chat_completions(
+        self,
+        request: OpenAIChatCompletionRequest,
+    ) -> AsyncIterator[OpenAIChatCompletionChunk]:
+        """Execute a streaming chat completion request to Azure OpenAI."""
+        adapter = self._get_openai_adapter()
+        async for chunk in adapter.stream_chat_completions(request):
+            yield chunk
+
+    async def messages(
+        self,
+        request: AnthropicMessagesRequest,
+    ) -> AnthropicMessagesResponse:
+        """Execute an Anthropic Messages API request via Azure OpenAI."""
+        adapter = self._get_openai_adapter()
+        return await adapter.messages(request)
+
+    async def check_health(self) -> HealthStatus:
+        """Check Azure OpenAI API health."""
+        # Use OpenAI-style health check
+        adapter = self._get_openai_adapter()
+        return await adapter.check_health()

llm-gateway/app/adapters/base.py

@@ -0,0 +1,135 @@
+"""Base adapter interface for LLM providers."""
+from abc import ABC, abstractmethod
+from dataclasses import dataclass
+from enum import Enum
+from typing import Any, AsyncIterator
+
+from app.schemas.anthropic import AnthropicMessagesRequest, AnthropicMessagesResponse
+from app.schemas.openai import (
+    OpenAIChatCompletionRequest,
+    OpenAIChatCompletionResponse,
+    OpenAIChatCompletionChunk,
+)
+
+
+class HealthStatus(Enum):
+    """Provider health status."""
+
+    HEALTHY = "healthy"
+    UNHEALTHY = "unhealthy"
+    DEGRADED = "degraded"
+
+
+@dataclass
+class ProviderConfig:
+    """Configuration for a provider."""
+
+    name: str
+    api_base: str
+    api_key: str
+    api_version: str | None = None
+    config: dict[str, Any] | None = None
+    rpm_limit: int | None = None
+    tpm_limit: int | None = None
+
+
+class BaseAdapter(ABC):
+    """Abstract base class for LLM provider adapters."""
+
+    def __init__(self, config: ProviderConfig):
+        self.config = config
+
+    @abstractmethod
+    async def chat_completions(
+        self,
+        request: OpenAIChatCompletionRequest,
+    ) -> OpenAIChatCompletionResponse:
+        """
+        Execute a chat completion request.
+
+        Args:
+            request: OpenAI-format chat completion request.
+
+        Returns:
+            OpenAI-format chat completion response.
+        """
+        pass
+
+    @abstractmethod
+    async def stream_chat_completions(
+        self,
+        request: OpenAIChatCompletionRequest,
+    ) -> AsyncIterator[OpenAIChatCompletionChunk]:
+        """
+        Execute a streaming chat completion request.
+
+        Args:
+            request: OpenAI-format chat completion request.
+
+        Yields:
+            OpenAI-format chat completion chunks.
+        """
+        pass
+
+    @abstractmethod
+    async def messages(
+        self,
+        request: AnthropicMessagesRequest,
+    ) -> AnthropicMessagesResponse:
+        """
+        Execute an Anthropic Messages API request.
+
+        Args:
+            request: Anthropic-format messages request.
+
+        Returns:
+            Anthropic-format messages response.
+        """
+        pass
+
+    async def count_tokens(
+        self,
+        request: OpenAIChatCompletionRequest | AnthropicMessagesRequest,
+    ) -> int:
+        """
+        Estimate token count for a request.
+
+        Args:
+            request: The request to count tokens for.
+
+        Returns:
+            Estimated token count.
+        """
+        # Default implementation: rough estimation
+        if isinstance(request, OpenAIChatCompletionRequest):
+            total = 0
+            for msg in request.messages:
+                if isinstance(msg.content, str):
+                    total += len(msg.content.split())
+            return int(total * 1.3)  # Rough word-to-token ratio
+        elif isinstance(request, AnthropicMessagesRequest):
+            total = 0
+            for msg in request.messages:
+                if isinstance(msg.content, str):
+                    total += len(msg.content.split())
+            if request.system:
+                total += len(request.system.split())
+            return int(total * 1.3)
+        return 0
+
+    @abstractmethod
+    async def check_health(self) -> HealthStatus:
+        """
+        Check the health of the provider.
+
+        Returns:
+            Health status of the provider.
+        """
+        pass
+
+    def get_headers(self) -> dict[str, str]:
+        """Get common headers for requests."""
+        return {
+            "Content-Type": "application/json",
+            "Accept": "application/json",
+        }

llm-gateway/app/adapters/bedrock.py

@@ -0,0 +1,240 @@
+"""AWS Bedrock provider adapter."""
+import json
+import time
+import uuid
+from typing import AsyncIterator, Any
+
+try:
+    import boto3
+    from botocore.config import Config
+    from botocore.exceptions import ClientError
+    HAS_BOTO3 = True
+except ImportError:
+    HAS_BOTO3 = False
+
+from app.adapters.base import BaseAdapter, HealthStatus, ProviderConfig
+from app.core.fallback import RetryableError, classify_error
+from app.core.transformer import RequestTransformer
+from app.schemas.anthropic import (
+    AnthropicMessagesRequest,
+    AnthropicMessagesResponse,
+)
+from app.schemas.openai import (
+    OpenAIChatCompletionChunk,
+    OpenAIChatCompletionRequest,
+    OpenAIChatCompletionResponse,
+    OpenAIChatCompletionChoice,
+    OpenAIChatMessage,
+    OpenAIUsage,
+)
+
+
+class BedrockAdapter(BaseAdapter):
+    """Adapter for AWS Bedrock API."""
+
+    def __init__(self, config: ProviderConfig):
+        super().__init__(config)
+        self.transformer = RequestTransformer()
+        self._client = None
+
+    def _get_client(self):
+        """Get or create Bedrock runtime client."""
+        if self._client is None and HAS_BOTO3:
+            aws_config = self.config.config or {}
+            region = aws_config.get("region", "us-east-1")
+
+            self._client = boto3.client(
+                "bedrock-runtime",
+                region_name=region,
+                config=Config(
+                    retries={"max_attempts": 3, "mode": "adaptive"},
+                    connect_timeout=10,
+                    read_timeout=120,
+                ),
+            )
+        return self._client
+
+    def _openai_to_bedrock_anthropic(
+        self, request: OpenAIChatCompletionRequest
+    ) -> tuple[str, dict[str, Any]]:
+        """Convert OpenAI request to Bedrock Anthropic format."""
+        messages = []
+        system = None
+
+        for msg in request.messages:
+            if msg.role == "system":
+                system = msg.content if isinstance(msg.content, str) else None
+            else:
+                messages.append({
+                    "role": msg.role,
+                    "content": [{"text": msg.content}] if isinstance(msg.content, str) else msg.content,
+                })
+
+        bedrock_request = {
+            "messages": messages,
+            "max_tokens": request.max_tokens or 4096,
+        }
+
+        if system:
+            bedrock_request["system"] = system
+        if request.temperature is not None:
+            bedrock_request["temperature"] = request.temperature
+        if request.top_p is not None:
+            bedrock_request["top_p"] = request.top_p
+
+        # Return model ID and request body
+        model_id = request.model
+        return model_id, bedrock_request
+
+    def _bedrock_to_openai(
+        self,
+        response: dict[str, Any],
+        model: str,
+    ) -> OpenAIChatCompletionResponse:
+        """Convert Bedrock Anthropic response to OpenAI format."""
+        content = ""
+        output = response.get("output", {})
+        message = output.get("message", {})
+
+        for block in message.get("content", []):
+            if "text" in block:
+                content += block["text"]
+
+        stop_reason = response.get("stopReason", "end_turn")
+        finish_reason_map = {
+            "end_turn": "stop",
+            "max_tokens": "length",
+            "stop_sequence": "stop",
+            "tool_use": "tool_calls",
+        }
+        finish_reason = finish_reason_map.get(stop_reason, "stop")
+
+        usage = response.get("usage", {})
+
+        return OpenAIChatCompletionResponse(
+            id=f"bedrock-{uuid.uuid4().hex[:24]}",
+            object="chat.completion",
+            created=int(time.time()),
+            model=model,
+            choices=[
+                OpenAIChatCompletionChoice(
+                    index=0,
+                    message=OpenAIChatMessage(role="assistant", content=content),
+                    finish_reason=finish_reason,
+                )
+            ],
+            usage=OpenAIUsage(
+                prompt_tokens=usage.get("inputTokens", 0),
+                completion_tokens=usage.get("outputTokens", 0),
+                total_tokens=usage.get("inputTokens", 0) + usage.get("outputTokens", 0),
+            ),
+        )
+
+    async def chat_completions(
+        self,
+        request: OpenAIChatCompletionRequest,
+    ) -> OpenAIChatCompletionResponse:
+        """Execute a chat completion request to Bedrock."""
+        client = self._get_client()
+        model_id, bedrock_request = self._openai_to_bedrock_anthropic(request)
+
+        try:
+            response = client.invoke_model(
+                modelId=model_id,
+                contentType="application/json",
+                accept="application/json",
+                body=json.dumps(bedrock_request),
+            )
+
+            response_body = json.loads(response["body"].read())
+            return self._bedrock_to_openai(response_body, request.model)
+
+        except ClientError as e:
+            error = classify_error(Exception(str(e)))
+            raise error
+
+    async def stream_chat_completions(
+        self,
+        request: OpenAIChatCompletionRequest,
+    ) -> AsyncIterator[OpenAIChatCompletionChunk]:
+        """Execute a streaming chat completion request to Bedrock."""
+        client = self._get_client()
+        model_id, bedrock_request = self._openai_to_bedrock_anthropic(request)
+
+        try:
+            response = client.invoke_model_with_response_stream(
+                modelId=model_id,
+                contentType="application/json",
+                accept="application/json",
+                body=json.dumps(bedrock_request),
+            )
+
+            chunk_id = f"bedrock-{uuid.uuid4().hex[:24]}"
+
+            for event in response["body"]:
+                chunk_data = json.loads(event["chunk"]["bytes"])
+
+                if chunk_data.get("type") == "content_block_delta":
+                    delta = chunk_data.get("delta", {})
+                    text = delta.get("text", "")
+
+                    if text:
+                        chunk = OpenAIChatCompletionChunk(
+                            id=chunk_id,
+                            object="chat.completion.chunk",
+                            created=int(time.time()),
+                            model=request.model,
+                            choices=[
+                                {
+                                    "index": 0,
+                                    "delta": {"content": text},
+                                    "finish_reason": None,
+                                }
+                            ],
+                        )
+                        yield chunk
+
+                elif chunk_data.get("type") == "message_delta":
+                    stop_reason = chunk_data.get("delta", {}).get("stop_reason")
+                    if stop_reason:
+                        finish_reason = "stop" if stop_reason == "end_turn" else "length"
+                        chunk = OpenAIChatCompletionChunk(
+                            id=chunk_id,
+                            object="chat.completion.chunk",
+                            created=int(time.time()),
+                            model=request.model,
+                            choices=[
+                                {
+                                    "index": 0,
+                                    "delta": {},
+                                    "finish_reason": finish_reason,
+                                }
+                            ],
+                        )
+                        yield chunk
+
+        except ClientError as e:
+            error = classify_error(Exception(str(e)))
+            raise error
+
+    async def messages(
+        self,
+        request: AnthropicMessagesRequest,
+    ) -> AnthropicMessagesResponse:
+        """Execute an Anthropic Messages API request via Bedrock."""
+        openai_request = self.transformer.anthropic_to_openai(request)
+        openai_response = await self.chat_completions(openai_request)
+        return self.transformer.openai_response_to_anthropic(openai_response)
+
+    async def check_health(self) -> HealthStatus:
+        """Check Bedrock API health."""
+        if not HAS_BOTO3:
+            return HealthStatus.UNHEALTHY
+
+        client = self._get_client()
+        try:
+            # List available models to check health
+            client.list_foundation_models()
+            return HealthStatus.HEALTHY
+        except Exception:
+            return HealthStatus.UNHEALTHY

llm-gateway/app/adapters/gemini.py

@@ -0,0 +1,236 @@
+"""Google Gemini provider adapter."""
+import json
+import time
+import uuid
+from typing import AsyncIterator, Any
+
+import httpx
+
+from app.adapters.base import BaseAdapter, HealthStatus, ProviderConfig
+from app.core.fallback import RetryableError, classify_error
+from app.core.transformer import RequestTransformer
+from app.schemas.anthropic import (
+    AnthropicMessagesRequest,
+    AnthropicMessagesResponse,
+    AnthropicTextBlock,
+    AnthropicUsage,
+)
+from app.schemas.openai import (
+    OpenAIChatCompletionChunk,
+    OpenAIChatCompletionRequest,
+    OpenAIChatCompletionResponse,
+    OpenAIChatCompletionChoice,
+    OpenAIChatMessage,
+    OpenAIUsage,
+)
+
+
+class GeminiAdapter(BaseAdapter):
+    """Adapter for Google Gemini API."""
+
+    def __init__(self, config: ProviderConfig):
+        super().__init__(config)
+        self.transformer = RequestTransformer()
+
+    def get_headers(self) -> dict[str, str]:
+        """Get headers for Gemini API requests."""
+        return {
+            "Content-Type": "application/json",
+        }
+
+    def _openai_to_gemini(self, request: OpenAIChatCompletionRequest) -> dict[str, Any]:
+        """Convert OpenAI request to Gemini format."""
+        contents = []
+        system_instruction = None
+
+        for msg in request.messages:
+            if msg.role == "system":
+                system_instruction = {"parts": [{"text": msg.content}]}
+            else:
+                role = "user" if msg.role == "user" else "model"
+                if isinstance(msg.content, str):
+                    parts = [{"text": msg.content}]
+                else:
+                    parts = [{"text": str(part)} for part in msg.content]
+                contents.append({"role": role, "parts": parts})
+
+        gemini_request = {
+            "contents": contents,
+            "generationConfig": {},
+        }
+
+        if system_instruction:
+            gemini_request["systemInstruction"] = system_instruction
+
+        if request.temperature is not None:
+            gemini_request["generationConfig"]["temperature"] = request.temperature
+        if request.max_tokens is not None:
+            gemini_request["generationConfig"]["maxOutputTokens"] = request.max_tokens
+        if request.top_p is not None:
+            gemini_request["generationConfig"]["topP"] = request.top_p
+        if request.stop:
+            if isinstance(request.stop, str):
+                gemini_request["generationConfig"]["stopSequences"] = [request.stop]
+            else:
+                gemini_request["generationConfig"]["stopSequences"] = request.stop
+
+        return gemini_request
+
+    def _gemini_to_openai(
+        self,
+        response: dict[str, Any],
+        model: str,
+    ) -> OpenAIChatCompletionResponse:
+        """Convert Gemini response to OpenAI format."""
+        candidates = response.get("candidates", [])
+        content = ""
+        finish_reason = "stop"
+
+        if candidates:
+            candidate = candidates[0]
+            content_parts = candidate.get("content", {}).get("parts", [])
+            content = "".join(p.get("text", "") for p in content_parts)
+
+            finish_reason_map = {
+                "STOP": "stop",
+                "MAX_TOKENS": "length",
+                "SAFETY": "content_filter",
+            }
+            finish_reason = finish_reason_map.get(
+                candidate.get("finishReason", "STOP"), "stop"
+            )
+
+        usage = response.get("usageMetadata", {})
+
+        return OpenAIChatCompletionResponse(
+            id=f"gemini-{uuid.uuid4().hex[:24]}",
+            object="chat.completion",
+            created=int(time.time()),
+            model=model,
+            choices=[
+                OpenAIChatCompletionChoice(
+                    index=0,
+                    message=OpenAIChatMessage(role="assistant", content=content),
+                    finish_reason=finish_reason,
+                )
+            ],
+            usage=OpenAIUsage(
+                prompt_tokens=usage.get("promptTokenCount", 0),
+                completion_tokens=usage.get("candidatesTokenCount", 0),
+                total_tokens=usage.get("totalTokenCount", 0),
+            ),
+        )
+
+    async def chat_completions(
+        self,
+        request: OpenAIChatCompletionRequest,
+    ) -> OpenAIChatCompletionResponse:
+        """Execute a chat completion request to Gemini."""
+        # Extract model name
+        model = request.model
+        url = f"{self.config.api_base}/v1beta/models/{model}:generateContent?key={self.config.api_key}"
+
+        gemini_request = self._openai_to_gemini(request)
+
+        async with httpx.AsyncClient(timeout=120.0) as client:
+            try:
+                response = await client.post(
+                    url,
+                    headers=self.get_headers(),
+                    json=gemini_request,
+                )
+
+                if response.status_code >= 400:
+                    error = classify_error(Exception(f"{response.status_code}: {response.text}"))
+                    raise error
+
+                data = response.json()
+                return self._gemini_to_openai(data, model)
+
+            except httpx.TimeoutException as e:
+                raise RetryableError(str(e), error_type="timeout")
+            except httpx.ConnectError as e:
+                raise RetryableError(str(e), error_type="connection_error")
+
+    async def stream_chat_completions(
+        self,
+        request: OpenAIChatCompletionRequest,
+    ) -> AsyncIterator[OpenAIChatCompletionChunk]:
+        """Execute a streaming chat completion request to Gemini."""
+        model = request.model
+        url = f"{self.config.api_base}/v1beta/models/{model}:streamGenerateContent?key={self.config.api_key}&alt=sse"
+
+        gemini_request = self._openai_to_gemini(request)
+
+        async with httpx.AsyncClient(timeout=120.0) as client:
+            try:
+                async with client.stream(
+                    "POST",
+                    url,
+                    headers=self.get_headers(),
+                    json=gemini_request,
+                ) as response:
+                    if response.status_code >= 400:
+                        error = classify_error(
+                            Exception(f"{response.status_code}: {await response.aread()}")
+                        )
+                        raise error
+
+                    async for line in response.aiter_lines():
+                        if line.startswith("data: "):
+                            data = line[6:]
+                            try:
+                                gemini_response = json.loads(data)
+                                openai_response = self._gemini_to_openai(gemini_response, model)
+
+                                if openai_response.choices:
+                                    chunk = OpenAIChatCompletionChunk(
+                                        id=openai_response.id,
+                                        object="chat.completion.chunk",
+                                        created=int(time.time()),
+                                        model=model,
+                                        choices=[
+                                            {
+                                                "index": 0,
+                                                "delta": {
+                                                    "content": openai_response.choices[0].message.content
+                                                },
+                                                "finish_reason": openai_response.choices[0].finish_reason,
+                                            }
+                                        ],
+                                    )
+                                    yield chunk
+                            except json.JSONDecodeError:
+                                continue
+
+            except httpx.TimeoutException as e:
+                raise RetryableError(str(e), error_type="timeout")
+            except httpx.ConnectError as e:
+                raise RetryableError(str(e), error_type="connection_error")
+
+    async def messages(
+        self,
+        request: AnthropicMessagesRequest,
+    ) -> AnthropicMessagesResponse:
+        """Execute an Anthropic Messages API request via Gemini."""
+        openai_request = self.transformer.anthropic_to_openai(request)
+        openai_response = await self.chat_completions(openai_request)
+        return self.transformer.openai_response_to_anthropic(openai_response)
+
+    async def check_health(self) -> HealthStatus:
+        """Check Gemini API health."""
+        url = f"{self.config.api_base}/v1beta/models?key={self.config.api_key}"
+
+        async with httpx.AsyncClient(timeout=10.0) as client:
+            try:
+                response = await client.get(url, headers=self.get_headers())
+
+                if response.status_code == 200:
+                    return HealthStatus.HEALTHY
+                elif response.status_code >= 500:
+                    return HealthStatus.UNHEALTHY
+                else:
+                    return HealthStatus.DEGRADED
+
+            except Exception:
+                return HealthStatus.UNHEALTHY

llm-gateway/app/adapters/openai.py

@@ -0,0 +1,134 @@
+"""OpenAI provider adapter."""
+import json
+from typing import Any, AsyncIterator
+
+import httpx
+
+from app.adapters.base import BaseAdapter, HealthStatus, ProviderConfig
+from app.core.fallback import RetryableError, PermanentError, classify_error
+from app.schemas.anthropic import AnthropicMessagesRequest, AnthropicMessagesResponse
+from app.schemas.openai import (
+    OpenAIChatCompletionChunk,
+    OpenAIChatCompletionRequest,
+    OpenAIChatCompletionResponse,
+)
+from app.core.transformer import RequestTransformer
+
+
+class OpenAIAdapter(BaseAdapter):
+    """Adapter for OpenAI API."""
+
+    def __init__(self, config: ProviderConfig):
+        super().__init__(config)
+        self.transformer = RequestTransformer()
+
+    def get_headers(self) -> dict[str, str]:
+        """Get headers for OpenAI API requests."""
+        return {
+            **super().get_headers(),
+            "Authorization": f"Bearer {self.config.api_key}",
+        }
+
+    async def chat_completions(
+        self,
+        request: OpenAIChatCompletionRequest,
+    ) -> OpenAIChatCompletionResponse:
+        """Execute a chat completion request to OpenAI."""
+        url = f"{self.config.api_base}/chat/completions"
+
+        payload = request.model_dump(exclude_none=True)
+
+        async with httpx.AsyncClient(timeout=120.0) as client:
+            try:
+                response = await client.post(
+                    url,
+                    headers=self.get_headers(),
+                    json=payload,
+                )
+
+                if response.status_code >= 400:
+                    error = classify_error(Exception(f"{response.status_code}: {response.text}"))
+                    raise error
+
+                data = response.json()
+                return OpenAIChatCompletionResponse(**data)
+
+            except httpx.TimeoutException as e:
+                raise RetryableError(str(e), error_type="timeout")
+            except httpx.ConnectError as e:
+                raise RetryableError(str(e), error_type="connection_error")
+
+    async def stream_chat_completions(
+        self,
+        request: OpenAIChatCompletionRequest,
+    ) -> AsyncIterator[OpenAIChatCompletionChunk]:
+        """Execute a streaming chat completion request to OpenAI."""
+        url = f"{self.config.api_base}/chat/completions"
+
+        payload = request.model_dump(exclude_none=True)
+        payload["stream"] = True
+
+        async with httpx.AsyncClient(timeout=120.0) as client:
+            try:
+                async with client.stream(
+                    "POST",
+                    url,
+                    headers=self.get_headers(),
+                    json=payload,
+                ) as response:
+                    if response.status_code >= 400:
+                        error = classify_error(
+                            Exception(f"{response.status_code}: {await response.aread()}")
+                        )
+                        raise error
+
+                    async for line in response.aiter_lines():
+                        if line.startswith("data: "):
+                            data = line[6:]
+                            if data == "[DONE]":
+                                break
+                            try:
+                                chunk = json.loads(data)
+                                yield OpenAIChatCompletionChunk(**chunk)
+                            except json.JSONDecodeError:
+                                continue
+
+            except httpx.TimeoutException as e:
+                raise RetryableError(str(e), error_type="timeout")
+            except httpx.ConnectError as e:
+                raise RetryableError(str(e), error_type="connection_error")
+
+    async def messages(
+        self,
+        request: AnthropicMessagesRequest,
+    ) -> AnthropicMessagesResponse:
+        """
+        Execute an Anthropic Messages API request via OpenAI.
+        Converts request to OpenAI format, calls OpenAI, converts response back.
+        """
+        # Convert Anthropic request to OpenAI format
+        openai_request = self.transformer.anthropic_to_openai(request)
+
+        # Call OpenAI
+        openai_response = await self.chat_completions(openai_request)
+
+        # Convert response back to Anthropic format
+        return self.transformer.openai_response_to_anthropic(openai_response)
+
+    async def check_health(self) -> HealthStatus:
+        """Check OpenAI API health by listing models."""
+        url = f"{self.config.api_base}/models"
+
+        async with httpx.AsyncClient(timeout=10.0) as client:
+            try:
+                response = await client.get(url, headers=self.get_headers())
+
+                if response.status_code == 200:
+                    return HealthStatus.HEALTHY
+                elif response.status_code >= 500:
+                    return HealthStatus.UNHEALTHY
+                else:
+                    return HealthStatus.DEGRADED
+
+            except Exception:
+                return HealthStatus.UNHEALTHY

llm-gateway/app/api/__init__.py

@@ -0,0 +1 @@
+# api module

llm-gateway/app/api/admin/__init__.py

@@ -0,0 +1 @@
+# admin module

llm-gateway/app/api/admin/health.py

@@ -0,0 +1,68 @@
+"""Health check API endpoints."""
+from datetime import datetime
+from typing import Annotated
+
+from fastapi import APIRouter, Depends
+from sqlalchemy import select
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from app.config import get_settings
+from app.db.database import get_db
+from app.models.provider import Provider
+
+router = APIRouter(tags=["Health"])
+
+
+@router.get("/health")
+async def health_check() -> dict:
+    """Basic health check endpoint."""
+    settings = get_settings()
+    return {
+        "status": "healthy",
+        "app": settings.app_name,
+        "timestamp": datetime.utcnow().isoformat(),
+    }
+
+
+@router.get("/admin/providers/{provider_id}/health")
+async def provider_health_check(
+    provider_id: str,
+    db: Annotated[AsyncSession, Depends(get_db)],
+) -> dict:
+    """Check health status of a specific provider."""
+    result = await db.execute(select(Provider).where(Provider.id == provider_id))
+    provider = result.scalar_one_or_none()
+
+    if not provider:
+        return {
+            "status": "not_found",
+            "provider_id": provider_id,
+        }
+
+    return {
+        "status": provider.health_status,
+        "provider_id": provider_id,
+        "provider_name": provider.name,
+        "last_check": provider.last_health_check.isoformat() if provider.last_health_check else None,
+        "enabled": provider.enabled,
+    }
+
+
+@router.get("/ready")
+async def readiness_check(
+    db: Annotated[AsyncSession, Depends(get_db)],
+) -> dict:
+    """Readiness check - verify database connection."""
+    try:
+        # Simple query to verify database connection
+        await db.execute(select(1))
+        return {
+            "status": "ready",
+            "database": "connected",
+        }
+    except Exception as e:
+        return {
+            "status": "not_ready",
+            "database": "disconnected",
+            "error": str(e),
+        }

llm-gateway/app/api/admin/keys.py

@@ -0,0 +1,233 @@
+"""API Key management API endpoints."""
+import json
+from typing import Annotated
+
+from fastapi import APIRouter, Depends, HTTPException, Query, status
+from sqlalchemy import func, select
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from app.db.database import get_db
+from app.models.api_key import APIKey
+from app.models.project import Project
+from app.schemas.api_key import (
+    APIKeyCreate,
+    APIKeyCreateResponse,
+    APIKeyListResponse,
+    APIKeyResponse,
+    APIKeyUpdate,
+)
+from app.utils.crypto import generate_api_key
+
+router = APIRouter(prefix="/keys", tags=["Admin - Keys"])
+
+
+@router.post("", response_model=APIKeyCreateResponse, status_code=status.HTTP_201_CREATED)
+async def create_api_key(
+    data: APIKeyCreate,
+    db: Annotated[AsyncSession, Depends(get_db)],
+) -> dict:
+    """Create a new API key."""
+    # Verify project exists if specified
+    if data.project_id:
+        result = await db.execute(select(Project).where(Project.id == data.project_id))
+        if not result.scalar_one_or_none():
+            raise HTTPException(
+                status_code=status.HTTP_404_NOT_FOUND,
+                detail=f"Project '{data.project_id}' not found",
+            )
+
+    # Generate API key
+    full_key, key_hash, key_prefix = generate_api_key(data.prefix)
+
+    # Create API key record
+    api_key = APIKey(
+        key_hash=key_hash,
+        key_prefix=key_prefix,
+        name=data.name,
+        project_id=data.project_id,
+        enabled=data.enabled,
+        expires_at=data.expires_at,
+        rpm_limit=data.rpm_limit,
+        tpm_limit=data.tpm_limit,
+        budget_limit=data.budget_limit,
+        budget_period=data.budget_period,
+        allowed_models=json.dumps(data.allowed_models) if data.allowed_models else None,
+    )
+
+    db.add(api_key)
+    await db.flush()
+    await db.refresh(api_key)
+
+    # Return response with full key (only time it's shown)
+    return {
+        "id": api_key.id,
+        "key": full_key,  # Full key - shown only once!
+        "key_prefix": api_key.key_prefix,
+        "name": api_key.name,
+        "project_id": api_key.project_id,
+        "enabled": api_key.enabled,
+        "expires_at": api_key.expires_at,
+        "rpm_limit": api_key.rpm_limit,
+        "tpm_limit": api_key.tpm_limit,
+        "budget_limit": api_key.budget_limit,
+        "budget_period": api_key.budget_period,
+        "allowed_models": json.loads(api_key.allowed_models) if api_key.allowed_models else None,
+        "current_usage": api_key.current_usage,
+        "total_requests": api_key.total_requests,
+        "created_at": api_key.created_at,
+        "updated_at": api_key.updated_at,
+    }
+
+
+@router.get("", response_model=APIKeyListResponse)
+async def list_api_keys(
+    db: Annotated[AsyncSession, Depends(get_db)],
+    page: Annotated[int, Query(ge=1)] = 1,
+    page_size: Annotated[int, Query(ge=1, le=100)] = 20,
+    project_id: str | None = None,
+    enabled: bool | None = None,
+) -> APIKeyListResponse:
+    """List all API keys."""
+    query = select(APIKey)
+    count_query = select(func.count()).select_from(APIKey)
+
+    if project_id:
+        query = query.where(APIKey.project_id == project_id)
+        count_query = count_query.where(APIKey.project_id == project_id)
+
+    if enabled is not None:
+        query = query.where(APIKey.enabled == enabled)
+        count_query = count_query.where(APIKey.enabled == enabled)
+
+    offset = (page - 1) * page_size
+    query = query.offset(offset).limit(page_size).order_by(APIKey.created_at.desc())
+
+    result = await db.execute(query)
+    keys = result.scalars().all()
+
+    total_result = await db.execute(count_query)
+    total = total_result.scalar() or 0
+
+    return APIKeyListResponse(
+        keys=[
+            APIKeyResponse(
+                id=k.id,
+                key_prefix=k.key_prefix,
+                name=k.name,
+                project_id=k.project_id,
+                enabled=k.enabled,
+                expires_at=k.expires_at,
+                rpm_limit=k.rpm_limit,
+                tpm_limit=k.tpm_limit,
+                budget_limit=k.budget_limit,
+                budget_period=k.budget_period,
+                allowed_models=json.loads(k.allowed_models) if k.allowed_models else None,
+                current_usage=k.current_usage,
+                total_requests=k.total_requests,
+                created_at=k.created_at,
+                updated_at=k.updated_at,
+            )
+            for k in keys
+        ],
+        total=total,
+        page=page,
+        page_size=page_size,
+    )
+
+
+@router.get("/{key_id}", response_model=APIKeyResponse)
+async def get_api_key(
+    key_id: str,
+    db: Annotated[AsyncSession, Depends(get_db)],
+) -> dict:
+    """Get an API key by ID."""
+    result = await db.execute(select(APIKey).where(APIKey.id == key_id))
+    key = result.scalar_one_or_none()
+
+    if not key:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail=f"API key '{key_id}' not found",
+        )
+
+    return APIKeyResponse(
+        id=key.id,
+        key_prefix=key.key_prefix,
+        name=key.name,
+        project_id=key.project_id,
+        enabled=key.enabled,
+        expires_at=key.expires_at,
+        rpm_limit=key.rpm_limit,
+        tpm_limit=key.tpm_limit,
+        budget_limit=key.budget_limit,
+        budget_period=key.budget_period,
+        allowed_models=json.loads(key.allowed_models) if key.allowed_models else None,
+        current_usage=key.current_usage,
+        total_requests=key.total_requests,
+        created_at=key.created_at,
+        updated_at=key.updated_at,
+    )
+
+
+@router.put("/{key_id}", response_model=APIKeyResponse)
+async def update_api_key(
+    key_id: str,
+    data: APIKeyUpdate,
+    db: Annotated[AsyncSession, Depends(get_db)],
+) -> dict:
+    """Update an API key."""
+    result = await db.execute(select(APIKey).where(APIKey.id == key_id))
+    key = result.scalar_one_or_none()
+
+    if not key:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail=f"API key '{key_id}' not found",
+        )
+
+    update_data = data.model_dump(exclude_unset=True)
+
+    if "allowed_models" in update_data:
+        key.allowed_models = json.dumps(update_data.pop("allowed_models"))
+
+    for k, v in update_data.items():
+        setattr(key, k, v)
+
+    await db.flush()
+    await db.refresh(key)
+
+    return APIKeyResponse(
+        id=key.id,
+        key_prefix=key.key_prefix,
+        name=key.name,
+        project_id=key.project_id,
+        enabled=key.enabled,
+        expires_at=key.expires_at,
+        rpm_limit=key.rpm_limit,
+        tpm_limit=key.tpm_limit,
+        budget_limit=key.budget_limit,
+        budget_period=key.budget_period,
+        allowed_models=json.loads(key.allowed_models) if key.allowed_models else None,
+        current_usage=key.current_usage,
+        total_requests=key.total_requests,
+        created_at=key.created_at,
+        updated_at=key.updated_at,
+    )
+
+
+@router.delete("/{key_id}", status_code=status.HTTP_204_NO_CONTENT)
+async def delete_api_key(
+    key_id: str,
+    db: Annotated[AsyncSession, Depends(get_db)],
+) -> None:
+    """Delete an API key."""
+    result = await db.execute(select(APIKey).where(APIKey.id == key_id))
+    key = result.scalar_one_or_none()
+
+    if not key:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail=f"API key '{key_id}' not found",
+        )
+
+    await db.delete(key)

llm-gateway/app/api/admin/models.py

@@ -0,0 +1,169 @@
+"""Model alias management API endpoints."""
+import json
+from typing import Annotated, Any
+
+from fastapi import APIRouter, Depends, HTTPException, Query, status
+from sqlalchemy import func, select
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from app.db.database import get_db
+from app.models.model_alias import ModelAlias
+from app.schemas.model_alias import (
+    ModelAliasCreate,
+    ModelAliasListResponse,
+    ModelAliasResponse,
+    ModelAliasUpdate,
+)
+
+router = APIRouter(prefix="/models/aliases", tags=["Admin - Models"])
+
+
+@router.post("", response_model=ModelAliasResponse, status_code=status.HTTP_201_CREATED)
+async def create_model_alias(
+    data: ModelAliasCreate,
+    db: Annotated[AsyncSession, Depends(get_db)],
+) -> ModelAlias:
+    """Create a new model alias."""
+    # Check if alias already exists
+    result = await db.execute(select(ModelAlias).where(ModelAlias.alias == data.alias))
+    if result.scalar_one_or_none():
+        raise HTTPException(
+            status_code=status.HTTP_409_CONFLICT,
+            detail=f"Model alias '{data.alias}' already exists",
+        )
+
+    # Create model alias
+    alias = ModelAlias(
+        alias=data.alias,
+        provider=data.provider,
+        model=data.model,
+        enabled=data.enabled,
+        routing_type=data.routing_type,
+        routing_config=json.dumps(data.routing_config.model_dump()) if data.routing_config else None,
+        input_price_per_1k=data.input_price_per_1k,
+        output_price_per_1k=data.output_price_per_1k,
+    )
+
+    db.add(alias)
+    await db.flush()
+    await db.refresh(alias)
+
+    return alias
+
+
+@router.get("", response_model=ModelAliasListResponse)
+async def list_model_aliases(
+    db: Annotated[AsyncSession, Depends(get_db)],
+    page: Annotated[int, Query(ge=1)] = 1,
+    page_size: Annotated[int, Query(ge=1, le=100)] = 20,
+    provider: str | None = None,
+    enabled: bool | None = None,
+) -> ModelAliasListResponse:
+    """List all model aliases."""
+    query = select(ModelAlias)
+    count_query = select(func.count()).select_from(ModelAlias)
+
+    if provider:
+        query = query.where(ModelAlias.provider == provider)
+        count_query = count_query.where(ModelAlias.provider == provider)
+
+    if enabled is not None:
+        query = query.where(ModelAlias.enabled == enabled)
+        count_query = count_query.where(ModelAlias.enabled == enabled)
+
+    offset = (page - 1) * page_size
+    query = query.offset(offset).limit(page_size).order_by(ModelAlias.created_at.desc())
+
+    result = await db.execute(query)
+    aliases = result.scalars().all()
+
+    total_result = await db.execute(count_query)
+    total = total_result.scalar() or 0
+
+    return ModelAliasListResponse(
+        aliases=[
+            ModelAliasResponse(
+                id=a.id,
+                alias=a.alias,
+                provider=a.provider,
+                model=a.model,
+                enabled=a.enabled,
+                routing_type=a.routing_type,
+                routing_config=json.loads(a.routing_config) if a.routing_config else None,
+                input_price_per_1k=a.input_price_per_1k,
+                output_price_per_1k=a.output_price_per_1k,
+                created_at=a.created_at,
+                updated_at=a.updated_at,
+            )
+            for a in aliases
+        ],
+        total=total,
+        page=page,
+        page_size=page_size,
+    )
+
+
+@router.get("/{alias_id}", response_model=ModelAliasResponse)
+async def get_model_alias(
+    alias_id: str,
+    db: Annotated[AsyncSession, Depends(get_db)],
+) -> ModelAlias:
+    """Get a model alias by ID."""
+    result = await db.execute(select(ModelAlias).where(ModelAlias.id == alias_id))
+    alias = result.scalar_one_or_none()
+
+    if not alias:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail=f"Model alias '{alias_id}' not found",
+        )
+
+    return alias
+
+
+@router.put("/{alias_id}", response_model=ModelAliasResponse)
+async def update_model_alias(
+    alias_id: str,
+    data: ModelAliasUpdate,
+    db: Annotated[AsyncSession, Depends(get_db)],
+) -> ModelAlias:
+    """Update a model alias."""
+    result = await db.execute(select(ModelAlias).where(ModelAlias.id == alias_id))
+    alias = result.scalar_one_or_none()
+
+    if not alias:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail=f"Model alias '{alias_id}' not found",
+        )
+
+    update_data = data.model_dump(exclude_unset=True)
+
+    if "routing_config" in update_data and update_data["routing_config"]:
+        alias.routing_config = json.dumps(update_data.pop("routing_config"))
+
+    for key, value in update_data.items():
+        setattr(alias, key, value)
+
+    await db.flush()
+    await db.refresh(alias)
+
+    return alias
+
+
+@router.delete("/{alias_id}", status_code=status.HTTP_204_NO_CONTENT)
+async def delete_model_alias(
+    alias_id: str,
+    db: Annotated[AsyncSession, Depends(get_db)],
+) -> None:
+    """Delete a model alias."""
+    result = await db.execute(select(ModelAlias).where(ModelAlias.id == alias_id))
+    alias = result.scalar_one_or_none()
+
+    if not alias:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail=f"Model alias '{alias_id}' not found",
+        )
+
+    await db.delete(alias)

llm-gateway/app/api/admin/projects.py

@@ -0,0 +1,132 @@
+"""Project management API endpoints."""
+from typing import Annotated
+
+from fastapi import APIRouter, Depends, HTTPException, Query, status
+from sqlalchemy import func, select
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from app.db.database import get_db
+from app.models.project import Project
+from app.schemas.project import (
+    ProjectCreate,
+    ProjectListResponse,
+    ProjectResponse,
+    ProjectUpdate,
+)
+
+router = APIRouter(prefix="/projects", tags=["Admin - Projects"])
+
+
+@router.post("", response_model=ProjectResponse, status_code=status.HTTP_201_CREATED)
+async def create_project(
+    data: ProjectCreate,
+    db: Annotated[AsyncSession, Depends(get_db)],
+) -> Project:
+    """Create a new project."""
+    project = Project(
+        name=data.name,
+        description=data.description,
+        budget_limit=data.budget_limit,
+        budget_period=data.budget_period,
+        enabled=data.enabled,
+    )
+
+    db.add(project)
+    await db.flush()
+    await db.refresh(project)
+
+    return project
+
+
+@router.get("", response_model=ProjectListResponse)
+async def list_projects(
+    db: Annotated[AsyncSession, Depends(get_db)],
+    page: Annotated[int, Query(ge=1)] = 1,
+    page_size: Annotated[int, Query(ge=1, le=100)] = 20,
+    enabled: bool | None = None,
+) -> ProjectListResponse:
+    """List all projects."""
+    query = select(Project)
+    count_query = select(func.count()).select_from(Project)
+
+    if enabled is not None:
+        query = query.where(Project.enabled == enabled)
+        count_query = count_query.where(Project.enabled == enabled)
+
+    offset = (page - 1) * page_size
+    query = query.offset(offset).limit(page_size).order_by(Project.created_at.desc())
+
+    result = await db.execute(query)
+    projects = result.scalars().all()
+
+    total_result = await db.execute(count_query)
+    total = total_result.scalar() or 0
+
+    return ProjectListResponse(
+        projects=[ProjectResponse.model_validate(p) for p in projects],
+        total=total,
+        page=page,
+        page_size=page_size,
+    )
+
+
+@router.get("/{project_id}", response_model=ProjectResponse)
+async def get_project(
+    project_id: str,
+    db: Annotated[AsyncSession, Depends(get_db)],
+) -> Project:
+    """Get a project by ID."""
+    result = await db.execute(select(Project).where(Project.id == project_id))
+    project = result.scalar_one_or_none()
+
+    if not project:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail=f"Project '{project_id}' not found",
+        )
+
+    return project
+
+
+@router.put("/{project_id}", response_model=ProjectResponse)
+async def update_project(
+    project_id: str,
+    data: ProjectUpdate,
+    db: Annotated[AsyncSession, Depends(get_db)],
+) -> Project:
+    """Update a project."""
+    result = await db.execute(select(Project).where(Project.id == project_id))
+    project = result.scalar_one_or_none()
+
+    if not project:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail=f"Project '{project_id}' not found",
+        )
+
+    update_data = data.model_dump(exclude_unset=True)
+    for key, value in update_data.items():
+        setattr(project, key, value)
+
+    await db.flush()
+    await db.refresh(project)
+
+    return project
+
+
+@router.delete("/{project_id}", status_code=status.HTTP_204_NO_CONTENT)
+async def delete_project(
+    project_id: str,
+    db: Annotated[AsyncSession, Depends(get_db)],
+) -> None:
+    """Delete a project."""
+    result = await db.execute(select(Project).where(Project.id == project_id))
+    project = result.scalar_one_or_none()
+
+    if not project:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail=f"Project '{project_id}' not found",
+        )
+
+    await db.delete(project)

llm-gateway/app/api/admin/providers.py

@@ -0,0 +1,192 @@
+"""Provider management API endpoints."""
+import json
+from typing import Annotated
+
+from fastapi import APIRouter, Depends, HTTPException, Query, status
+from sqlalchemy import func, select
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from app.db.database import get_db
+from app.models.provider import Provider
+from app.schemas.common import PaginationParams
+from app.schemas.provider import (
+    ProviderCreate,
+    ProviderListResponse,
+    ProviderResponse,
+    ProviderUpdate,
+)
+from app.utils.crypto import encrypt_value
+
+router = APIRouter(prefix="/providers", tags=["Admin - Providers"])
+
+
+@router.post("", response_model=ProviderResponse, status_code=status.HTTP_201_CREATED)
+async def create_provider(
+    data: ProviderCreate,
+    db: Annotated[AsyncSession, Depends(get_db)],
+) -> Provider:
+    """Create a new provider."""
+    # Check if provider already exists
+    result = await db.execute(select(Provider).where(Provider.name == data.name))
+    if result.scalar_one_or_none():
+        raise HTTPException(
+            status_code=status.HTTP_409_CONFLICT,
+            detail=f"Provider '{data.name}' already exists",
+        )
+
+    # Encrypt API key
+    encrypted_key = encrypt_value(data.api_key)
+
+    # Create provider
+    provider = Provider(
+        name=data.name,
+        api_base=data.api_base,
+        api_key_encrypted=encrypted_key,
+        api_version=data.api_version,
+        config=json.dumps(data.config) if data.config else None,
+        rpm_limit=data.rpm_limit,
+        tpm_limit=data.tpm_limit,
+        enabled=data.enabled,
+    )
+
+    db.add(provider)
+    await db.flush()
+    await db.refresh(provider)
+
+    # Decrypt config for response
+    if provider.config:
+        provider.config = json.loads(provider.config)
+
+    return provider
+
+
+@router.get("", response_model=ProviderListResponse)
+async def list_providers(
+    db: Annotated[AsyncSession, Depends(get_db)],
+    page: Annotated[int, Query(ge=1)] = 1,
+    page_size: Annotated[int, Query(ge=1, le=100)] = 20,
+    enabled: bool | None = None,
+) -> ProviderListResponse:
+    """List all providers."""
+    # Build query
+    query = select(Provider)
+    count_query = select(func.count()).select_from(Provider)
+
+    if enabled is not None:
+        query = query.where(Provider.enabled == enabled)
+        count_query = count_query.where(Provider.enabled == enabled)
+
+    # Apply pagination
+    offset = (page - 1) * page_size
+    query = query.offset(offset).limit(page_size).order_by(Provider.created_at.desc())
+
+    # Execute queries
+    result = await db.execute(query)
+    providers = result.scalars().all()
+
+    total_result = await db.execute(count_query)
+    total = total_result.scalar() or 0
+
+    # Decrypt config for response
+    for p in providers:
+        if p.config:
+            p.config = json.loads(p.config)
+
+    return ProviderListResponse(
+        providers=[
+            ProviderResponse(
+                id=p.id,
+                name=p.name,
+                enabled=p.enabled,
+                api_base=p.api_base,
+                api_version=p.api_version,
+                config=json.loads(p.config) if p.config else None,
+                rpm_limit=p.rpm_limit,
+                tpm_limit=p.tpm_limit,
+                health_status=p.health_status,
+                last_health_check=p.last_health_check,
+                created_at=p.created_at,
+                updated_at=p.updated_at,
+            )
+            for p in providers
+        ],
+        total=total,
+        page=page,
+        page_size=page_size,
+    )
+
+
+@router.get("/{provider_id}", response_model=ProviderResponse)
+async def get_provider(
+    provider_id: str,
+    db: Annotated[AsyncSession, Depends(get_db)],
+) -> Provider:
+    """Get a provider by ID."""
+    result = await db.execute(select(Provider).where(Provider.id == provider_id))
+    provider = result.scalar_one_or_none()
+
+    if not provider:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail=f"Provider '{provider_id}' not found",
+        )
+
+    if provider.config:
+        provider.config = json.loads(provider.config)
+
+    return provider
+
+
+@router.put("/{provider_id}", response_model=ProviderResponse)
+async def update_provider(
+    provider_id: str,
+    data: ProviderUpdate,
+    db: Annotated[AsyncSession, Depends(get_db)],
+) -> Provider:
+    """Update a provider."""
+    result = await db.execute(select(Provider).where(Provider.id == provider_id))
+    provider = result.scalar_one_or_none()
+
+    if not provider:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail=f"Provider '{provider_id}' not found",
+        )
+
+    # Update fields
+    update_data = data.model_dump(exclude_unset=True)
+
+    if "api_key" in update_data:
+        provider.api_key_encrypted = encrypt_value(update_data.pop("api_key"))
+
+    if "config" in update_data:
+        provider.config = json.dumps(update_data.pop("config"))
+
+    for key, value in update_data.items():
+        setattr(provider, key, value)
+
+    await db.flush()
+    await db.refresh(provider)
+
+    if provider.config:
+        provider.config = json.loads(provider.config)
+
+    return provider
+
+
+@router.delete("/{provider_id}", status_code=status.HTTP_204_NO_CONTENT)
+async def delete_provider(
+    provider_id: str,
+    db: Annotated[AsyncSession, Depends(get_db)],
+) -> None:
+    """Delete a provider."""
+    result = await db.execute(select(Provider).where(Provider.id == provider_id))
+    provider = result.scalar_one_or_none()
+
+    if not provider:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND,
+            detail=f"Provider '{provider_id}' not found",
+        )
+
+    await db.delete(provider)

llm-gateway/app/api/admin/usage.py

@@ -0,0 +1,221 @@
+"""Usage statistics API endpoints."""
+from datetime import datetime, timedelta
+from decimal import Decimal
+from typing import Annotated, Any
+
+from fastapi import APIRouter, Depends, Query
+from sqlalchemy import func, select
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from app.db.database import get_db
+from app.models.usage import RequestLog, UsageStatsHourly
+
+router = APIRouter(prefix="/usage", tags=["Admin - Usage"])
+
+
+@router.get("/stats")
+async def get_usage_stats(
+    db: Annotated[AsyncSession, Depends(get_db)],
+    start_date: Annotated[datetime | None, Query()] = None,
+    end_date: Annotated[datetime | None, Query()] = None,
+    group_by: Annotated[str, Query(pattern="^(model|provider|project|key)$")] = "model",
+    project_id: str | None = None,
+    key_id: str | None = None,
+) -> dict[str, Any]:
+    """Get usage statistics."""
+    # Default to last 7 days
+    if not start_date:
+        start_date = datetime.utcnow() - timedelta(days=7)
+    if not end_date:
+        end_date = datetime.utcnow()
+
+    # Build base query
+    query = select(
+        getattr(UsageStatsHourly, group_by).label("group"),
+        func.sum(UsageStatsHourly.request_count).label("requests"),
+        func.sum(UsageStatsHourly.input_tokens).label("input_tokens"),
+        func.sum(UsageStatsHourly.output_tokens).label("output_tokens"),
+        func.sum(UsageStatsHourly.total_tokens).label("total_tokens"),
+        func.sum(UsageStatsHourly.cost_usd).label("cost_usd"),
+        func.avg(UsageStatsHourly.avg_latency_ms).label("avg_latency_ms"),
+        func.sum(UsageStatsHourly.error_count).label("errors"),
+    ).where(
+        UsageStatsHourly.timestamp >= start_date,
+        UsageStatsHourly.timestamp <= end_date,
+    )
+
+    if project_id:
+        query = query.where(UsageStatsHourly.project_id == project_id)
+    if key_id:
+        query = query.where(UsageStatsHourly.virtual_key_id == key_id)
+
+    query = query.group_by(getattr(UsageStatsHourly, group_by))
+
+    result = await db.execute(query)
+    rows = result.all()
+
+    # Calculate totals
+    total_query = select(
+        func.sum(UsageStatsHourly.request_count).label("requests"),
+        func.sum(UsageStatsHourly.input_tokens).label("input_tokens"),
+        func.sum(UsageStatsHourly.output_tokens).label("output_tokens"),
+        func.sum(UsageStatsHourly.total_tokens).label("total_tokens"),
+        func.sum(UsageStatsHourly.cost_usd).label("cost_usd"),
+        func.sum(UsageStatsHourly.error_count).label("errors"),
+    ).where(
+        UsageStatsHourly.timestamp >= start_date,
+        UsageStatsHourly.timestamp <= end_date,
+    )
+
+    if project_id:
+        total_query = total_query.where(UsageStatsHourly.project_id == project_id)
+    if key_id:
+        total_query = total_query.where(UsageStatsHourly.virtual_key_id == key_id)
+
+    total_result = await db.execute(total_query)
+    total_row = total_result.one()
+
+    return {
+        "period": {
+            "start": start_date.isoformat(),
+            "end": end_date.isoformat(),
+        },
+        "totals": {
+            "requests": total_row.requests or 0,
+            "input_tokens": total_row.input_tokens or 0,
+            "output_tokens": total_row.output_tokens or 0,
+            "total_tokens": total_row.total_tokens or 0,
+            "cost_usd": float(total_row.cost_usd or 0),
+            "errors": total_row.errors or 0,
+        },
+        "by_" + group_by: [
+            {
+                group_by: row.group,
+                "requests": row.requests or 0,
+                "input_tokens": row.input_tokens or 0,
+                "output_tokens": row.output_tokens or 0,
+                "total_tokens": row.total_tokens or 0,
+                "cost_usd": float(row.cost_usd or 0),
+                "avg_latency_ms": int(row.avg_latency_ms or 0),
+                "errors": row.errors or 0,
+            }
+            for row in rows
+        ],
+    }
+
+
+@router.get("/logs")
+async def get_usage_logs(
+    db: Annotated[AsyncSession, Depends(get_db)],
+    page: Annotated[int, Query(ge=1)] = 1,
+    page_size: Annotated[int, Query(ge=1, le=100)] = 50,
+    project_id: str | None = None,
+    key_id: str | None = None,
+    provider: str | None = None,
+    model: str | None = None,
+    status_code: int | None = None,
+) -> dict[str, Any]:
+    """Get request logs."""
+    query = select(RequestLog)
+    count_query = select(func.count()).select_from(RequestLog)
+
+    # Apply filters
+    if project_id:
+        query = query.where(RequestLog.project_id == project_id)
+        count_query = count_query.where(RequestLog.project_id == project_id)
+    if key_id:
+        query = query.where(RequestLog.virtual_key_id == key_id)
+        count_query = count_query.where(RequestLog.virtual_key_id == key_id)
+    if provider:
+        query = query.where(RequestLog.provider == provider)
+        count_query = count_query.where(RequestLog.provider == provider)
+    if model:
+        query = query.where(RequestLog.model == model)
+        count_query = count_query.where(RequestLog.model == model)
+    if status_code:
+        query = query.where(RequestLog.status_code == status_code)
+        count_query = count_query.where(RequestLog.status_code == status_code)
+
+    # Apply pagination
+    offset = (page - 1) * page_size
+    query = query.offset(offset).limit(page_size).order_by(RequestLog.timestamp.desc())
+
+    result = await db.execute(query)
+    logs = result.scalars().all()
+
+    total_result = await db.execute(count_query)
+    total = total_result.scalar() or 0
+
+    return {
+        "logs": [
+            {
+                "id": log.id,
+                "timestamp": log.timestamp.isoformat(),
+                "key_id": log.virtual_key_id,
+                "project_id": log.project_id,
+                "provider": log.provider,
+                "model": log.model,
+                "model_alias": log.model_alias,
+                "request_type": log.request_type,
+                "input_tokens": log.input_tokens,
+                "output_tokens": log.output_tokens,
+                "total_tokens": log.total_tokens,
+                "status_code": log.status_code,
+                "latency_ms": log.latency_ms,
+                "finish_reason": log.finish_reason,
+                "cost_usd": float(log.cost_usd),
+            }
+            for log in logs
+        ],
+        "total": total,
+        "page": page,
+        "page_size": page_size,
+    }
+
+
+@router.get("/costs")
+async def get_cost_breakdown(
+    db: Annotated[AsyncSession, Depends(get_db)],
+    start_date: Annotated[datetime | None, Query()] = None,
+    end_date: Annotated[datetime | None, Query()] = None,
+    group_by: Annotated[str, Query(pattern="^(model|provider|project|key)$")] = "provider",
+) -> dict[str, Any]:
+    """Get cost breakdown."""
+    # Default to current month
+    if not start_date:
+        start_date = datetime.utcnow().replace(day=1, hour=0, minute=0, second=0, microsecond=0)
+    if not end_date:
+        end_date = datetime.utcnow()
+
+    query = select(
+        getattr(UsageStatsHourly, group_by).label("group"),
+        func.sum(UsageStatsHourly.cost_usd).label("cost_usd"),
+        func.sum(UsageStatsHourly.request_count).label("requests"),
+        func.sum(UsageStatsHourly.total_tokens).label("tokens"),
+    ).where(
+        UsageStatsHourly.timestamp >= start_date,
+        UsageStatsHourly.timestamp <= end_date,
+    ).group_by(getattr(UsageStatsHourly, group_by))
+
+    result = await db.execute(query)
+    rows = result.all()
+
+    total_cost = sum(float(row.cost_usd or 0) for row in rows)
+
+    return {
+        "period": {
+            "start": start_date.isoformat(),
+            "end": end_date.isoformat(),
+        },
+        "total_cost_usd": total_cost,
+        "breakdown": [
+            {
+                group_by: row.group,
+                "cost_usd": float(row.cost_usd or 0),
+                "percentage": float(row.cost_usd or 0) / total_cost * 100 if total_cost > 0 else 0,
+                "requests": row.requests or 0,
+                "tokens": row.tokens or 0,
+            }
+            for row in sorted(rows, key=lambda r: r.cost_usd or 0, reverse=True)
+        ],
+    }

llm-gateway/app/api/v1/__init__.py

@@ -0,0 +1 @@
+# v1 module

llm-gateway/app/api/v1/chat.py

@@ -0,0 +1,327 @@
+"""Chat Completions API endpoint (OpenAI-compatible)."""
+import time
+import uuid
+from datetime import datetime
+from decimal import Decimal
+from typing import Annotated, Any
+
+from fastapi import APIRouter, Depends, Header, HTTPException, Request
+from fastapi.responses import StreamingResponse
+from sqlalchemy import select
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from app.adapters import ProviderConfig, create_adapter
+from app.core.budget import BudgetController, BudgetExceeded
+from app.core.circuit_breaker import get_circuit_breaker
+from app.core.fallback import RetryExecutor, RetryConfig, RetryableError, classify_error
+from app.core.load_balancer import LoadBalancer
+from app.core.rate_limiter import RateLimiter, RateLimitExceeded
+from app.core.router import Router, RoutingResult
+from app.db.database import get_db
+from app.models.api_key import APIKey
+from app.models.provider import Provider
+from app.models.usage import RequestLog
+from app.schemas.openai import (
+    OpenAIChatCompletionRequest,
+    OpenAIChatCompletionResponse,
+)
+from app.utils.crypto import decrypt_value, verify_api_key
+from app.utils.logging import get_logger
+
+logger = get_logger(__name__)
+
+router = APIRouter(prefix="/v1", tags=["Chat"])
+
+
+async def authenticate(
+    authorization: str | None = Header(None),
+    x_api_key: str | None = Header(None),
+    db: AsyncSession = Depends(get_db),
+) -> APIKey:
+    """Authenticate request using virtual API key."""
+    # Extract key from header
+    key = None
+    if authorization:
+        if authorization.startswith("Bearer "):
+            key = authorization[7:]
+    elif x_api_key:
+        key = x_api_key
+
+    if not key:
+        raise HTTPException(
+            status_code=401,
+            detail={"error": {"type": "authentication_error", "message": "Missing API key"}},
+        )
+
+    # Find and verify key
+    result = await db.execute(select(APIKey))
+    api_keys = result.scalars().all()
+
+    for api_key in api_keys:
+        if verify_api_key(key, api_key.key_hash):
+            if not api_key.enabled:
+                raise HTTPException(
+                    status_code=403,
+                    detail={"error": {"type": "permission_error", "message": "API key is disabled"}},
+                )
+            if api_key.expires_at and api_key.expires_at < datetime.utcnow():
+                raise HTTPException(
+                    status_code=403,
+                    detail={"error": {"type": "permission_error", "message": "API key has expired"}},
+                )
+            return api_key
+
+    raise HTTPException(
+        status_code=401,
+        detail={"error": {"type": "authentication_error", "message": "Invalid API key"}},
+    )
+
+
+@router.post("/chat/completions")
+async def chat_completions(
+    request: OpenAIChatCompletionRequest,
+    db: Annotated[AsyncSession, Depends(get_db)],
+    api_key: Annotated[APIKey, Depends(authenticate)],
+) -> OpenAIChatCompletionResponse:
+    """Execute a chat completion request."""
+    start_time = time.time()
+    routing_result: RoutingResult | None = None
+    response: OpenAIChatCompletionResponse | None = None
+    error: Exception | None = None
+
+    try:
+        # Initialize services
+        router_service = Router(db)
+        rate_limiter = RateLimiter(db)
+        budget_controller = BudgetController(db)
+        load_balancer = LoadBalancer(db)
+
+        # Check rate limits
+        try:
+            await rate_limiter.check_and_increment(
+                f"key:{api_key.id}",
+                rpm_limit=api_key.rpm_limit,
+                tpm_limit=api_key.tpm_limit,
+            )
+        except RateLimitExceeded as e:
+            raise HTTPException(
+                status_code=429,
+                detail={
+                    "error": {
+                        "type": "rate_limit_error",
+                        "message": str(e),
+                        "details": {
+                            "limit": e.limit,
+                            "remaining": e.remaining,
+                            "reset_at": e.reset_at.isoformat(),
+                        },
+                    }
+                },
+            )
+
+        # Check budget
+        try:
+            await budget_controller.check_budget(api_key.id)
+        except BudgetExceeded as e:
+            raise HTTPException(
+                status_code=402,
+                detail={
+                    "error": {
+                        "type": "budget_exceeded_error",
+                        "message": str(e),
+                        "details": {
+                            "limit": float(e.limit),
+                            "current_usage": float(e.current_usage),
+                            "scope": e.scope,
+                        },
+                    }
+                },
+            )
+
+        # Resolve model routing
+        routing_result = await router_service.resolve_model(request.model)
+
+        # Check if model is allowed
+        if api_key.allowed_models:
+            import json
+            allowed = json.loads(api_key.allowed_models)
+            if request.model not in allowed:
+                raise HTTPException(
+                    status_code=403,
+                    detail={
+                        "error": {
+                            "type": "permission_error",
+                            "message": f"Model '{request.model}' is not allowed for this API key",
+                        }
+                    },
+                )
+
+        # Get provider config
+        result = await db.execute(
+            select(Provider).where(Provider.name == routing_result.provider, Provider.enabled == True)
+        )
+        provider = result.scalar_one_or_none()
+
+        if not provider:
+            raise HTTPException(
+                status_code=503,
+                detail={
+                    "error": {
+                        "type": "provider_error",
+                        "message": f"Provider '{routing_result.provider}' not found or disabled",
+                    }
+                },
+            )
+
+        # Check circuit breaker
+        circuit_breaker = get_circuit_breaker()
+        if not circuit_breaker.is_available(provider.name):
+            raise HTTPException(
+                status_code=503,
+                detail={
+                    "error": {
+                        "type": "service_unavailable",
+                        "message": f"Provider '{provider.name}' is currently unavailable",
+                    }
+                },
+            )
+
+        # Create adapter
+        provider_config = ProviderConfig(
+            name=provider.name,
+            api_base=provider.api_base,
+            api_key=decrypt_value(provider.api_key_encrypted),
+            api_version=provider.api_version,
+            config=json.loads(provider.config) if provider.config else None,
+        )
+
+        adapter = create_adapter(provider_config)
+
+        # Update request model to actual model
+        request.model = routing_result.model
+
+        # Execute request with retry
+        retry_executor = RetryExecutor(RetryConfig())
+
+        async def execute():
+            return await adapter.chat_completions(request)
+
+        response = await retry_executor.execute(execute, provider.name, "chat_completions")
+        circuit_breaker.record_success(provider.name)
+
+        # Record usage
+        if response.usage:
+            cost = await _calculate_cost(db, routing_result, response.usage)
+            await budget_controller.record_usage(
+                api_key.id,
+                cost,
+                response.usage.prompt_tokens,
+                response.usage.completion_tokens,
+            )
+
+            # Record tokens for rate limiting
+            await rate_limiter.record_tokens(
+                f"key:{api_key.id}",
+                response.usage.total_tokens,
+            )
+
+        return response
+
+    except HTTPException:
+        raise
+    except RetryableError as e:
+        error = e
+        logger.error(
+            "Chat completion failed",
+            model=request.model,
+            provider=routing_result.provider if routing_result else None,
+            error=str(e),
+        )
+        raise HTTPException(
+            status_code=502,
+            detail={
+                "error": {
+                    "type": "provider_error",
+                    "message": str(e),
+                }
+            },
+        )
+    except Exception as e:
+        error = e
+        logger.exception("Unexpected error in chat completions")
+        raise HTTPException(
+            status_code=500,
+            detail={
+                "error": {
+                    "type": "internal_error",
+                    "message": str(e),
+                }
+            },
+        )
+    finally:
+        # Log request
+        await _log_request(
+            db,
+            api_key.id,
+            routing_result,
+            request,
+            response,
+            error,
+            start_time,
+        )
+
+
+async def _calculate_cost(
+    db: AsyncSession,
+    routing_result: RoutingResult,
+    usage: Any,
+) -> Decimal:
+    """Calculate cost for a request."""
+    from app.models.model_alias import ModelAlias
+    import json
+
+    # Try to find pricing from model alias
+    result = await db.execute(
+        select(ModelAlias).where(ModelAlias.alias == routing_result.model)
+    )
+    alias = result.scalar_one_or_none()
+
+    if alias and alias.input_price_per_1k and alias.output_price_per_1k:
+        input_cost = (usage.prompt_tokens / 1000) * alias.input_price_per_1k
+        output_cost = (usage.completion_tokens / 1000) * alias.output_price_per_1k
+        return Decimal(str(input_cost + output_cost))
+
+    # Default pricing (rough estimate)
+    return Decimal("0.001")
+
+
+async def _log_request(
+    db: AsyncSession,
+    key_id: str,
+    routing_result: RoutingResult | None,
+    request: OpenAIChatCompletionRequest,
+    response: OpenAIChatCompletionResponse | None,
+    error: Exception | None,
+    start_time: float,
+) -> None:
+    """Log request details."""
+    latency_ms = int((time.time() - start_time) * 1000)
+
+    log = RequestLog(
+        virtual_key_id=key_id,
+        project_id=None,  # Will be filled from API key
+        provider=routing_result.provider if routing_result else "unknown",
+        model=request.model,
+        model_alias=request.model,
+        request_type="chat",
+        input_tokens=response.usage.prompt_tokens if response and response.usage else 0,
+        output_tokens=response.usage.completion_tokens if response and response.usage else 0,
+        total_tokens=response.usage.total_tokens if response and response.usage else 0,
+        status_code=500 if error else (response and 200 or 500),
+        latency_ms=latency_ms,
+        finish_reason=response.choices[0].finish_reason if response and response.choices else None,
+        cost_usd=Decimal("0.001") if response and response.usage else Decimal("0"),
+    )
+
+    db.add(log)
+    await db.commit()

llm-gateway/app/api/v1/messages.py

@@ -0,0 +1,53 @@
+"""Anthropic Messages API endpoint."""
+from typing import Annotated
+
+from fastapi import APIRouter, Depends
+
+from app.api.v1.chat import authenticate, _calculate_cost, _log_request
+from app.core.transformer import RequestTransformer
+from app.db.database import get_db
+from app.models.api_key import APIKey
+from app.schemas.anthropic import AnthropicMessagesRequest, AnthropicMessagesResponse
+from app.schemas.openai import OpenAIChatCompletionRequest
+
+router = APIRouter(prefix="/v1", tags=["Messages"])
+
+
+@router.post("/messages")
+async def messages(
+    request: AnthropicMessagesRequest,
+    db: Annotated[None, Depends(get_db)],
+    api_key: Annotated[APIKey, Depends(authenticate)],
+) -> AnthropicMessagesResponse:
+    """
+    Execute an Anthropic Messages API request.
+
+    This endpoint accepts Anthropic-format requests and forwards them
+    to the appropriate provider (Anthropic, OpenAI, etc.).
+    """
+    from app.api.v1.chat import chat_completions
+    from app.schemas.openai import OpenAIChatCompletionRequest
+
+    # Convert Anthropic request to OpenAI format
+    transformer = RequestTransformer()
+    openai_request = transformer.anthropic_to_openai(request)
+
+    # Use the chat completions endpoint
+    from fastapi import HTTPException
+    from sqlalchemy.ext.asyncio import AsyncSession
+
+    # Re-import with correct type
+    from app.db.database import get_db as _get_db
+    from typing import AsyncGenerator
+
+    # Get database session
+    async for session in _get_db():
+        # Call chat completions with converted request
+        response = await chat_completions(openai_request, session, api_key)
+
+        # Convert response back to Anthropic format
+        anthropic_response = transformer.openai_response_to_anthropic(response)
+
+        return anthropic_response
+
+    raise HTTPException(status_code=500, detail="Database session error")

llm-gateway/app/api/v1/responses.py

@@ -0,0 +1,72 @@
+"""OpenAI Responses API endpoint."""
+from typing import Annotated
+
+from fastapi import APIRouter, Depends
+
+from app.api.v1.chat import authenticate
+from app.db.database import get_db
+from app.models.api_key import APIKey
+from app.schemas.openai import OpenAIResponseRequest
+
+router = APIRouter(prefix="/v1", tags=["Responses"])
+
+
+@router.post("/responses")
+async def responses(
+    request: OpenAIResponseRequest,
+    db: Annotated[None, Depends(get_db)],
+    api_key: Annotated[APIKey, Depends(authenticate)],
+) -> dict:
+    """
+    Execute an OpenAI Responses API request.
+
+    This is the new OpenAI Responses API format.
+    Converts to chat completions internally.
+    """
+    from app.schemas.openai import OpenAIChatCompletionRequest, OpenAIChatMessage
+    from app.api.v1.chat import chat_completions
+    from app.db.database import get_db as _get_db
+
+    # Convert Responses API format to Chat Completions format
+    messages = []
+
+    # Add instructions as system message if present
+    if request.instructions:
+        messages.append(OpenAIChatMessage(role="system", content=request.instructions))
+
+    # Add input as user message
+    if isinstance(request.input, str):
+        messages.append(OpenAIChatMessage(role="user", content=request.input))
+    else:
+        # Handle structured input
+        messages.append(OpenAIChatMessage(role="user", content=str(request.input)))
+
+    chat_request = OpenAIChatCompletionRequest(
+        model=request.model,
+        messages=messages,
+        max_tokens=request.max_output_tokens,
+        temperature=request.temperature,
+        tools=request.tools,
+        tool_choice=request.tool_choice,
+    )
+
+    # Get database session and call chat completions
+    async for session in _get_db():
+        response = await chat_completions(chat_request, session, api_key)
+
+        # Convert to Responses API format
+        return {
+            "id": response.id,
+            "object": "response",
+            "created": response.created,
+            "model": response.model,
+            "output": response.choices[0].message.content if response.choices else "",
+            "usage": {
+                "input_tokens": response.usage.prompt_tokens if response.usage else 0,
+                "output_tokens": response.usage.completion_tokens if response.usage else 0,
+                "total_tokens": response.usage.total_tokens if response.usage else 0,
+            },
+        }
+
+    from fastapi import HTTPException
+    raise HTTPException(status_code=500, detail="Database session error")

llm-gateway/app/config.py

@@ -0,0 +1,73 @@
+"""Application configuration using Pydantic Settings."""
+import secrets
+from functools import lru_cache
+from pathlib import Path
+
+from pydantic import Field, field_validator
+from pydantic_settings import BaseSettings, SettingsConfigDict
+
+
+class Settings(BaseSettings):
+    """Application settings loaded from environment variables."""
+
+    model_config = SettingsConfigDict(
+        env_file=".env",
+        env_file_encoding="utf-8",
+        case_sensitive=False,
+        extra="ignore",
+    )
+
+    # Application
+    app_name: str = "LLM Gateway"
+    debug: bool = False
+    log_level: str = "INFO"
+
+    # Server
+    host: str = "0.0.0.0"
+    port: int = 8000
+
+    # Database
+    database_url: str = Field(
+        default="sqlite:///data/gateway.db",
+        description="SQLite database URL",
+    )
+
+    # Security
+    master_key: str = Field(
+        default_factory=lambda: secrets.token_hex(32),
+        description="Master key for encrypting provider API keys",
+    )
+
+    # Rate Limiting
+    rate_limit_window_seconds: int = 60
+    global_rpm_limit: int | None = None
+    global_tpm_limit: int | None = None
+
+    # Retry
+    max_retries: int = 3
+    retry_initial_delay: float = 1.0
+    retry_max_delay: float = 30.0
+    retry_exponential_base: float = 2.0
+
+    # Health Check
+    health_check_interval: int = 30
+    health_check_timeout: int = 10
+
+    @field_validator("master_key")
+    @classmethod
+    def validate_master_key(cls, v: str) -> str:
+        """Ensure master key is at least 32 characters."""
+        if len(v) < 32:
+            raise ValueError("Master key must be at least 32 characters")
+        return v
+
+    @staticmethod
+    def generate_master_key() -> str:
+        """Generate a secure random master key."""
+        return secrets.token_hex(32)
+
+
+@lru_cache
+def get_settings() -> Settings:
+    """Get cached settings instance."""
+    return Settings()

llm-gateway/app/core/__init__.py

@@ -0,0 +1 @@
+# core module

llm-gateway/app/core/budget.py

@@ -0,0 +1,160 @@
+"""Budget controller for spending limits."""
+from datetime import datetime, timedelta
+from decimal import Decimal
+from typing import Any
+
+from sqlalchemy import func, select
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from app.models.api_key import APIKey
+from app.models.project import Project
+from app.models.usage import RequestLog
+
+
+class BudgetExceeded(Exception):
+    """Exception raised when budget is exceeded."""
+
+    def __init__(
+        self,
+        budget_type: str,
+        limit: Decimal,
+        current_usage: Decimal,
+        scope: str,
+    ):
+        self.budget_type = budget_type
+        self.limit = limit
+        self.current_usage = current_usage
+        self.scope = scope
+        super().__init__(f"Budget exceeded: {scope} {budget_type}")
+
+
+class BudgetController:
+    """Controller for budget limits at key and project levels."""
+
+    def __init__(self, db: AsyncSession):
+        self.db = db
+
+    async def check_budget(
+        self,
+        key_id: str,
+        estimated_cost: Decimal = Decimal("0"),
+    ) -> dict[str, Any]:
+        """
+        Check budget limits before making a request.
+
+        Args:
+            key_id: The API key ID.
+            estimated_cost: Estimated cost for this request.
+
+        Returns:
+            Dict with budget status.
+
+        Raises:
+            BudgetExceeded: If budget is exceeded.
+        """
+        # Get API key
+        result = await self.db.execute(select(APIKey).where(APIKey.id == key_id))
+        api_key = result.scalar_one_or_none()
+
+        if not api_key:
+            raise ValueError(f"API key '{key_id}' not found")
+
+        now = datetime.utcnow()
+
+        # Check key-level budget
+        if api_key.budget_limit:
+            period_start = self._get_period_start(api_key.budget_period, now)
+            current_usage = await self._get_usage_for_period(key_id, None, period_start, now)
+
+            if current_usage + estimated_cost > api_key.budget_limit:
+                raise BudgetExceeded(
+                    budget_type=api_key.budget_period or "total",
+                    limit=api_key.budget_limit,
+                    current_usage=current_usage,
+                    scope=f"key:{api_key.name}",
+                )
+
+            # Check soft limit (90% of hard limit)
+            soft_limit = api_key.budget_limit * Decimal("0.9")
+            if current_usage + estimated_cost > soft_limit:
+                # Log warning but don't block
+                pass
+
+        # Check project-level budget
+        if api_key.project_id:
+            result = await self.db.execute(
+                select(Project).where(Project.id == api_key.project_id)
+            )
+            project = result.scalar_one_or_none()
+
+            if project and project.budget_limit:
+                period_start = self._get_period_start(project.budget_period, now)
+                current_usage = await self._get_usage_for_period(
+                    None, project.id, period_start, now
+                )
+
+                if current_usage + estimated_cost > project.budget_limit:
+                    raise BudgetExceeded(
+                        budget_type=project.budget_period or "total",
+                        limit=project.budget_limit,
+                        current_usage=current_usage,
+                        scope=f"project:{project.name}",
+                    )
+
+        return {
+            "key_budget_limit": float(api_key.budget_limit) if api_key.budget_limit else None,
+            "key_current_usage": float(api_key.current_usage),
+            "project_budget_limit": None,
+            "project_current_usage": None,
+        }
+
+    async def record_usage(
+        self,
+        key_id: str,
+        cost: Decimal,
+        input_tokens: int,
+        output_tokens: int,
+    ) -> None:
+        """Record actual usage after request completes."""
+        result = await self.db.execute(select(APIKey).where(APIKey.id == key_id))
+        api_key = result.scalar_one_or_none()
+
+        if api_key:
+            api_key.current_usage += cost
+            api_key.total_requests += 1
+
+    def _get_period_start(self, period: str | None, now: datetime) -> datetime:
+        """Get the start of the budget period."""
+        if period == "daily":
+            return now.replace(hour=0, minute=0, second=0, microsecond=0)
+        elif period == "weekly":
+            start = now - timedelta(days=now.weekday())
+            return start.replace(hour=0, minute=0, second=0, microsecond=0)
+        elif period == "monthly":
+            return now.replace(day=1, hour=0, minute=0, second=0, microsecond=0)
+        else:
+            # No period means all-time budget
+            return datetime.min
+
+    async def _get_usage_for_period(
+        self,
+        key_id: str | None,
+        project_id: str | None,
+        period_start: datetime,
+        now: datetime,
+    ) -> Decimal:
+        """Get total usage for a period."""
+        query = select(func.sum(RequestLog.cost_usd)).where(
+            RequestLog.timestamp >= period_start,
+            RequestLog.timestamp <= now,
+        )
+
+        if key_id:
+            query = query.where(RequestLog.virtual_key_id == key_id)
+        if project_id:
+            query = query.where(RequestLog.project_id == project_id)
+
+        result = await self.db.execute(query)
+        total = result.scalar()
+
+        return Decimal(str(total or 0))

llm-gateway/app/core/circuit_breaker.py

@@ -0,0 +1,168 @@
+"""Circuit breaker for provider fault tolerance."""
+import asyncio
+import time
+from dataclasses import dataclass, field
+from enum import Enum
+from typing import Any
+
+
+class CircuitState(Enum):
+    """Circuit breaker states."""
+
+    CLOSED = "closed"  # Normal operation
+    OPEN = "open"  # Failing, reject all requests
+    HALF_OPEN = "half_open"  # Testing if recovered
+
+
+@dataclass
+class CircuitStats:
+    """Statistics for circuit breaker."""
+
+    failure_count: int = 0
+    success_count: int = 0
+    last_failure_time: float = 0
+    last_success_time: float = 0
+    state: CircuitState = CircuitState.CLOSED
+    last_state_change: float = field(default_factory=time.time)
+
+
+class CircuitBreaker:
+    """
+    Circuit breaker for provider fault tolerance.
+
+    States:
+    - CLOSED: Normal operation, requests pass through
+    - OPEN: Too many failures, reject all requests
+    - HALF_OPEN: Testing if provider has recovered
+    """
+
+    def __init__(
+        self,
+        failure_threshold: int = 5,
+        recovery_timeout: float = 30.0,
+        success_threshold: int = 2,
+    ):
+        """
+        Initialize circuit breaker.
+
+        Args:
+            failure_threshold: Number of failures before opening circuit.
+            recovery_timeout: Seconds to wait before trying half-open state.
+            success_threshold: Number of successes in half-open to close circuit.
+        """
+        self.failure_threshold = failure_threshold
+        self.recovery_timeout = recovery_timeout
+        self.success_threshold = success_threshold
+        self._circuits: dict[str, CircuitStats] = {}
+
+    def get_stats(self, provider: str) -> CircuitStats:
+        """Get or create circuit stats for a provider."""
+        if provider not in self._circuits:
+            self._circuits[provider] = CircuitStats()
+        return self._circuits[provider]
+
+    def is_available(self, provider: str) -> bool:
+        """
+        Check if a provider is available (circuit is not open).
+
+        Args:
+            provider: Provider name.
+
+        Returns:
+            True if requests should be allowed.
+        """
+        stats = self.get_stats(provider)
+        now = time.time()
+
+        if stats.state == CircuitState.CLOSED:
+            return True
+
+        elif stats.state == CircuitState.OPEN:
+            # Check if recovery timeout has passed
+            if now - stats.last_state_change >= self.recovery_timeout:
+                # Transition to half-open
+                stats.state = CircuitState.HALF_OPEN
+                stats.success_count = 0
+                stats.last_state_change = now
+                return True
+            return False
+
+        elif stats.state == CircuitState.HALF_OPEN:
+            return True
+
+        return True
+
+    def record_success(self, provider: str) -> None:
+        """
+        Record a successful request.
+
+        Args:
+            provider: Provider name.
+        """
+        stats = self.get_stats(provider)
+        now = time.time()
+
+        stats.success_count += 1
+        stats.last_success_time = now
+        stats.failure_count = 0  # Reset failure count on success
+
+        if stats.state == CircuitState.HALF_OPEN:
+            if stats.success_count >= self.success_threshold:
+                # Transition to closed
+                stats.state = CircuitState.CLOSED
+                stats.last_state_change = now
+
+    def record_failure(self, provider: str) -> None:
+        """
+        Record a failed request.
+
+        Args:
+            provider: Provider name.
+        """
+        stats = self.get_stats(provider)
+        now = time.time()
+
+        stats.failure_count += 1
+        stats.last_failure_time = now
+
+        if stats.state == CircuitState.HALF_OPEN:
+            # Immediately open on failure in half-open
+            stats.state = CircuitState.OPEN
+            stats.last_state_change = now
+
+        elif stats.state == CircuitState.CLOSED:
+            if stats.failure_count >= self.failure_threshold:
+                # Transition to open
+                stats.state = CircuitState.OPEN
+                stats.last_state_change = now
+
+    def get_state(self, provider: str) -> CircuitState:
+        """Get current circuit state for a provider."""
+        return self.get_stats(provider).state
+
+    def reset(self, provider: str) -> None:
+        """Reset circuit breaker for a provider."""
+        if provider in self._circuits:
+            del self._circuits[provider]
+
+    def reset_all(self) -> None:
+        """Reset all circuit breakers."""
+        self._circuits.clear()
+
+
+# Global circuit breaker instance
+_circuit_breaker: CircuitBreaker | None = None
+
+
+def get_circuit_breaker() -> CircuitBreaker:
+    """Get the global circuit breaker instance."""
+    global _circuit_breaker
+    if _circuit_breaker is None:
+        from app.config import get_settings
+
+        settings = get_settings()
+        _circuit_breaker = CircuitBreaker(
+            failure_threshold=5,
+            recovery_timeout=30.0,
+        )
+    return _circuit_breaker

llm-gateway/app/core/fallback.py

@@ -0,0 +1,223 @@
+"""Fallback and retry logic for provider failures."""
+import asyncio
+import random
+from dataclasses import dataclass
+from enum import Enum
+from typing import Any, Callable, TypeVar
+
+from app.config import get_settings
+from app.core.circuit_breaker import CircuitBreaker, get_circuit_breaker
+from app.utils.logging import get_logger
+
+logger = get_logger(__name__)
+
+T = TypeVar("T")
+
+
+class RetryableError(Exception):
+    """Error that can be retried."""
+
+    def __init__(self, message: str, error_type: str = "unknown"):
+        self.message = message
+        self.error_type = error_type
+        super().__init__(message)
+
+
+class PermanentError(Exception):
+    """Error that should not be retried."""
+
+    def __init__(self, message: str, error_type: str = "unknown"):
+        self.message = message
+        self.error_type = error_type
+        super().__init__(message)
+
+
+@dataclass
+class RetryConfig:
+    """Retry configuration."""
+
+    max_retries: int = 3
+    initial_delay: float = 1.0
+    max_delay: float = 30.0
+    exponential_base: float = 2.0
+    jitter: bool = True
+    retryable_errors: set[str] | None = None
+
+    def __post_init__(self):
+        if self.retryable_errors is None:
+            self.retryable_errors = {
+                "rate_limit_exceeded",
+                "timeout",
+                "service_unavailable",
+                "internal_error",
+                "connection_error",
+                "overloaded",
+            }
+
+
+class RetryExecutor:
+    """Executor for retrying failed operations."""
+
+    def __init__(self, config: RetryConfig | None = None):
+        self.config = config or RetryConfig()
+        self.settings = get_settings()
+
+    async def execute(
+        self,
+        operation: Callable[[], T],
+        provider: str,
+        operation_name: str = "operation",
+    ) -> T:
+        """
+        Execute an operation with retry logic.
+
+        Args:
+            operation: Async function to execute.
+            provider: Provider name for circuit breaker.
+            operation_name: Name for logging.
+
+        Returns:
+            Result of the operation.
+
+        Raises:
+            PermanentError: If operation fails permanently.
+            RetryableError: If all retries are exhausted.
+        """
+        circuit_breaker = get_circuit_breaker()
+        last_error: Exception | None = None
+
+        for attempt in range(self.config.max_retries + 1):
+            # Check circuit breaker
+            if not circuit_breaker.is_available(provider):
+                raise RetryableError(
+                    f"Circuit breaker open for provider '{provider}'",
+                    error_type="circuit_open",
+                )
+
+            try:
+                result = await operation()
+                circuit_breaker.record_success(provider)
+                return result
+
+            except PermanentError as e:
+                logger.warning(
+                    "Permanent error in %s",
+                    operation_name,
+                    provider=provider,
+                    attempt=attempt,
+                    error=e.message,
+                )
+                circuit_breaker.record_failure(provider)
+                raise
+
+            except RetryableError as e:
+                last_error = e
+                circuit_breaker.record_failure(provider)
+
+                if attempt < self.config.max_retries:
+                    delay = self._calculate_delay(attempt)
+                    logger.warning(
+                        "Retryable error in %s, retrying in %.2fs",
+                        operation_name,
+                        delay,
+                        provider=provider,
+                        attempt=attempt,
+                        error=e.message,
+                        error_type=e.error_type,
+                    )
+                    await asyncio.sleep(delay)
+                else:
+                    logger.error(
+                        "All retries exhausted for %s",
+                        operation_name,
+                        provider=provider,
+                        attempts=attempt + 1,
+                        error=e.message,
+                    )
+
+            except Exception as e:
+                # Unknown error - treat as retryable
+                last_error = RetryableError(str(e), error_type="unknown")
+                circuit_breaker.record_failure(provider)
+
+                if attempt < self.config.max_retries:
+                    delay = self._calculate_delay(attempt)
+                    logger.warning(
+                        "Unknown error in %s, retrying in %.2fs",
+                        operation_name,
+                        delay,
+                        provider=provider,
+                        attempt=attempt,
+                        error=str(e),
+                    )
+                    await asyncio.sleep(delay)
+
+        # All retries exhausted
+        if last_error:
+            raise last_error
+        raise RetryableError("All retries exhausted", error_type="max_retries")
+
+    def _calculate_delay(self, attempt: int) -> float:
+        """Calculate delay for a retry attempt with exponential backoff and jitter."""
+        delay = self.config.initial_delay * (self.config.exponential_base**attempt)
+        delay = min(delay, self.config.max_delay)
+
+        if self.config.jitter:
+            # Add jitter (0.5 to 1.5 times the delay)
+            jitter = random.uniform(0.5, 1.5)
+            delay *= jitter
+
+        return delay
+
+
+def classify_error(error: Exception) -> Exception:
+    """
+    Classify an error as retryable or permanent.
+
+    Args:
+        error: The error to classify.
+
+    Returns:
+        RetryableError or PermanentError.
+    """
+    error_str = str(error).lower()
+
+    # Retryable errors
+    retryable_patterns = [
+        "rate limit",
+        "429",
+        "timeout",
+        "503",
+        "502",
+        "service unavailable",
+        "internal error",
+        "500",
+        "connection",
+        "overloaded",
+        "capacity",
+    ]
+
+    for pattern in retryable_patterns:
+        if pattern in error_str:
+            return RetryableError(str(error), error_type=pattern.replace(" ", "_"))
+
+    # Permanent errors
+    permanent_patterns = [
+        "401",
+        "unauthorized",
+        "invalid api key",
+        "403",
+        "forbidden",
+        "400",
+        "invalid request",
+        "404",
+        "not found",
+        "model not found",
+    ]
+
+    for pattern in permanent_patterns:
+        if pattern in error_str:
+            return PermanentError(str(error), error_type=pattern.replace(" ", "_"))
+
+    # Default to retryable
+    return RetryableError(str(error), error_type="unknown")

llm-gateway/app/core/load_balancer.py

@@ -0,0 +1,137 @@
+"""Load balancer for distributing requests across providers."""
+import random
+from dataclasses import dataclass
+from typing import Any
+
+from sqlalchemy import select
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from app.models.provider import Provider
+
+
+@dataclass
+class ProviderInfo:
+    """Information about a provider for load balancing."""
+
+    name: str
+    weight: int
+    health_status: str
+    current_requests: int = 0
+
+
+class LoadBalancer:
+    """Load balancer for distributing requests across providers."""
+
+    def __init__(self, db: AsyncSession):
+        self.db = db
+
+    async def select_provider(
+        self,
+        providers: list[dict[str, Any]],
+        strategy: str = "weighted_round_robin",
+    ) -> dict[str, Any] | None:
+        """
+        Select a provider based on the specified strategy.
+
+        Args:
+            providers: List of provider configs with weights.
+            strategy: Load balancing strategy.
+
+        Returns:
+            Selected provider config, or None if none available.
+        """
+        if not providers:
+            return None
+
+        if len(providers) == 1:
+            return providers[0]
+
+        # Filter healthy providers
+        healthy_providers = await self._filter_healthy_providers(providers)
+
+        if not healthy_providers:
+            return providers[0]  # Fallback to first if all unhealthy
+
+        if strategy == "weighted_round_robin":
+            return self._weighted_round_robin(healthy_providers)
+        elif strategy == "random":
+            return self._random_select(healthy_providers)
+        elif strategy == "least_connections":
+            return await self._least_connections(healthy_providers)
+        else:
+            return self._weighted_round_robin(healthy_providers)
+
+    def _weighted_round_robin(
+        self, providers: list[dict[str, Any]]
+    ) -> dict[str, Any]:
+        """Select provider using weighted round robin."""
+        total_weight = sum(p.get("weight", 1) for p in providers)
+        r = random.uniform(0, total_weight)
+
+        cumulative = 0
+        for provider in providers:
+            cumulative += provider.get("weight", 1)
+            if r <= cumulative:
+                return provider
+
+        return providers[0]
+
+    def _random_select(self, providers: list[dict[str, Any]]) -> dict[str, Any]:
+        """Select provider randomly."""
+        return random.choice(providers)
+
+    async def _least_connections(
+        self, providers: list[dict[str, Any]]
+    ) -> dict[str, Any]:
+        """Select provider with least connections (placeholder)."""
+        # In a real implementation, this would track active connections
+        # For now, use random as a fallback
+        return self._random_select(providers)
+
+    async def _filter_healthy_providers(
+        self, providers: list[dict[str, Any]]
+    ) -> list[dict[str, Any]]:
+        """Filter out unhealthy providers."""
+        healthy = []
+
+        for p in providers:
+            provider_name = p.get("provider")
+            if not provider_name:
+                continue
+
+            result = await self.db.execute(
+                select(Provider).where(
+                    Provider.name == provider_name,
+                    Provider.enabled == True,
+                    Provider.health_status == "healthy",
+                )
+            )
+            provider = result.scalar_one_or_none()
+
+            if provider:
+                healthy.append(p)
+
+        return healthy
+
+    async def get_provider_health(
+        self, provider_name: str
+    ) -> dict[str, Any]:
+        """Get health status for a provider."""
+        result = await self.db.execute(
+            select(Provider).where(Provider.name == provider_name)
+        )
+        provider = result.scalar_one_or_none()
+
+        if not provider:
+            return {
+                "name": provider_name,
+                "status": "not_found",
+                "available": False,
+            }
+
+        return {
+            "name": provider.name,
+            "status": provider.health_status,
+            "available": provider.enabled and provider.health_status == "healthy",
+            "last_check": provider.last_health_check.isoformat() if provider.last_health_check else None,
+        }

llm-gateway/app/core/rate_limiter.py

@@ -0,0 +1,210 @@
+"""Rate limiter for RPM/TPM limits."""
+import time
+from datetime import datetime, timedelta
+from typing import Any
+
+from sqlalchemy import select, update
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from app.config import get_settings
+from app.models.usage import RateLimitCounter
+
+
+class RateLimitExceeded(Exception):
+    """Exception raised when rate limit is exceeded."""
+
+    def __init__(
+        self,
+        limit_type: str,
+        limit: int,
+        remaining: int,
+        reset_at: datetime,
+    ):
+        self.limit_type = limit_type
+        self.limit = limit
+        self.remaining = remaining
+        self.reset_at = reset_at
+        super().__init__(f"Rate limit exceeded: {limit_type}")
+
+
+class RateLimiter:
+    """Rate limiter for RPM and TPM limits."""
+
+    def __init__(self, db: AsyncSession):
+        self.db = db
+        self.settings = get_settings()
+        self.window_seconds = self.settings.rate_limit_window_seconds
+
+    async def check_and_increment(
+        self,
+        key: str,
+        rpm_limit: int | None = None,
+        tpm_limit: int | None = None,
+        estimated_tokens: int = 0,
+    ) -> dict[str, Any]:
+        """
+        Check rate limits and increment counters.
+
+        Args:
+            key: Unique key for rate limiting (e.g., "key:{key_id}:rpm").
+            rpm_limit: Requests per minute limit.
+            tpm_limit: Tokens per minute limit.
+            estimated_tokens: Estimated tokens for this request.
+
+        Returns:
+            Dict with remaining limits.
+
+        Raises:
+            RateLimitExceeded: If rate limit is exceeded.
+        """
+        now = datetime.utcnow()
+        window_start = now - timedelta(seconds=self.window_seconds)
+
+        # Check global limits
+        if self.settings.global_rpm_limit:
+            await self._check_limit(
+                "global:rpm",
+                self.settings.global_rpm_limit,
+                window_start,
+                now,
+                1,
+                "request",
+            )
+
+        if self.settings.global_tpm_limit and estimated_tokens > 0:
+            await self._check_limit(
+                "global:tpm",
+                self.settings.global_tpm_limit,
+                window_start,
+                now,
+                estimated_tokens,
+                "token",
+            )
+
+        # Check specific limits
+        if rpm_limit:
+            await self._check_limit(
+                f"{key}:rpm",
+                rpm_limit,
+                window_start,
+                now,
+                1,
+                "request",
+            )
+
+        if tpm_limit and estimated_tokens > 0:
+            await self._check_limit(
+                f"{key}:tpm",
+                tpm_limit,
+                window_start,
+                now,
+                estimated_tokens,
+                "token",
+            )
+
+        # Get remaining limits
+        remaining = await self._get_remaining(key, rpm_limit, tpm_limit, window_start, now)
+
+        return remaining
+
+    async def _check_limit(
+        self,
+        key: str,
+        limit: int,
+        window_start: datetime,
+        now: datetime,
+        increment: int,
+        counter_type: str,
+    ) -> None:
+        """Check if a limit would be exceeded and increment counter."""
+        # Get current counter
+        result = await self.db.execute(
+            select(RateLimitCounter).where(RateLimitCounter.key == key)
+        )
+        counter = result.scalar_one_or_none()
+
+        if counter:
+            # Check if window has expired
+            if counter.window_start < window_start:
+                # Reset counter for new window
+                counter.request_count = 0
+                counter.token_count = 0
+                counter.window_start = now
+
+            # Check limit
+            current = (
+                counter.request_count if counter_type == "request" else counter.token_count
+            )
+            if current >= limit:
+                reset_at = counter.window_start + timedelta(seconds=counter.window_duration)
+                raise RateLimitExceeded(
+                    limit_type=f"{counter_type}_per_{self.window_seconds}s",
+                    limit=limit,
+                    remaining=0,
+                    reset_at=reset_at,
+                )
+
+            # Increment counter
+            if counter_type == "request":
+                counter.request_count += increment
+            else:
+                counter.token_count += increment
+        else:
+            # Create new counter
+            counter = RateLimitCounter(
+                key=key,
+                request_count=1 if counter_type == "request" else 0,
+                token_count=increment if counter_type == "token" else 0,
+                window_start=now,
+                window_duration=self.window_seconds,
+            )
+            self.db.add(counter)
+
+    async def _get_remaining(
+        self,
+        key: str,
+        rpm_limit: int | None,
+        tpm_limit: int | None,
+        window_start: datetime,
+        now: datetime,
+    ) -> dict[str, Any]:
+        """Get remaining limits for a key."""
+        remaining = {}
+
+        if rpm_limit:
+            result = await self.db.execute(
+                select(RateLimitCounter).where(RateLimitCounter.key == f"{key}:rpm")
+            )
+            counter = result.scalar_one_or_none()
+            remaining["rpm"] = rpm_limit - (counter.request_count if counter else 0)
+
+        if tpm_limit:
+            result = await self.db.execute(
+                select(RateLimitCounter).where(RateLimitCounter.key == f"{key}:tpm")
+            )
+            counter = result.scalar_one_or_none()
+            remaining["tpm"] = tpm_limit - (counter.token_count if counter else 0)
+
+        remaining["reset_at"] = (now + timedelta(seconds=self.window_seconds)).isoformat()
+
+        return remaining
+
+    async def record_tokens(self, key: str, tokens: int) -> None:
+        """Record actual token usage after request completes."""
+        tpm_key = f"{key}:tpm"
+        result = await self.db.execute(
+            select(RateLimitCounter).where(RateLimitCounter.key == tpm_key)
+        )
+        counter = result.scalar_one_or_none()
+
+        if counter:
+            counter.token_count += tokens
+        else:
+            counter = RateLimitCounter(
+                key=tpm_key,
+                request_count=0,
+                token_count=tokens,
+                window_start=datetime.utcnow(),
+                window_duration=self.window_seconds,
+            )
+            self.db.add(counter)

llm-gateway/app/core/router.py

@@ -0,0 +1,173 @@
+"""Router for model alias resolution and routing."""
+import json
+import random
+from dataclasses import dataclass
+from typing import Any
+
+from sqlalchemy import select
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from app.models.model_alias import ModelAlias
+from app.models.provider import Provider
+
+
+@dataclass
+class RoutingResult:
+    """Result of routing decision."""
+
+    provider: str
+    model: str
+    provider_config: dict[str, Any] | None = None
+    fallback_chain: list[dict[str, str]] | None = None
+
+
+class Router:
+    """Router for resolving model aliases and making routing decisions."""
+
+    def __init__(self, db: AsyncSession):
+        self.db = db
+
+    async def resolve_model(self, model_alias: str) -> RoutingResult:
+        """
+        Resolve a model alias to a provider and model.
+
+        Args:
+            model_alias: The model alias to resolve.
+
+        Returns:
+            RoutingResult with provider, model, and optional fallback chain.
+
+        Raises:
+            ValueError: If the model alias is not found.
+        """
+        # Look up the model alias
+        result = await self.db.execute(
+            select(ModelAlias).where(ModelAlias.alias == model_alias, ModelAlias.enabled == True)
+        )
+        alias = result.scalar_one_or_none()
+
+        if not alias:
+            # If no alias found, treat as direct provider/model reference
+            # Format: "provider/model" (e.g., "openai/gpt-4")
+            if "/" in model_alias:
+                provider, model = model_alias.split("/", 1)
+                return RoutingResult(provider=provider, model=model)
+            raise ValueError(f"Model alias '{model_alias}' not found")
+
+        # Parse routing config
+        routing_config = json.loads(alias.routing_config) if alias.routing_config else None
+
+        if alias.routing_type == "simple":
+            return RoutingResult(
+                provider=alias.provider,
+                model=alias.model,
+            )
+
+        elif alias.routing_type == "load_balance":
+            # Weighted random selection
+            providers = routing_config.get("providers", []) if routing_config else []
+            if not providers:
+                return RoutingResult(provider=alias.provider, model=alias.model)
+
+            # Filter healthy providers
+            healthy_providers = await self._filter_healthy_providers(providers)
+
+            if not healthy_providers:
+                # Fallback to default if all unhealthy
+                return RoutingResult(provider=alias.provider, model=alias.model)
+
+            # Weighted random selection
+            total_weight = sum(p.get("weight", 1) for p in healthy_providers)
+            r = random.uniform(0, total_weight)
+
+            cumulative = 0
+            for p in healthy_providers:
+                cumulative += p.get("weight", 1)
+                if r <= cumulative:
+                    return RoutingResult(
+                        provider=p["provider"],
+                        model=p.get("model", alias.model),
+                    )
+
+            # Fallback
+            return RoutingResult(
+                provider=healthy_providers[0]["provider"],
+                model=healthy_providers[0].get("model", alias.model),
+            )
+
+        elif alias.routing_type == "fallback":
+            # Return primary with fallback chain
+            primary = (
+                routing_config.get("primary", {}) if routing_config else {}
+            )
+            fallback = routing_config.get("fallback", []) if routing_config else []
+
+            return RoutingResult(
+                provider=primary.get("provider", alias.provider),
+                model=primary.get("model", alias.model),
+                fallback_chain=fallback,
+            )
+
+        # Default to simple routing
+        return RoutingResult(provider=alias.provider, model=alias.model)
+
+    async def _filter_healthy_providers(
+        self, providers: list[dict[str, Any]]
+    ) -> list[dict[str, Any]]:
+        """Filter out unhealthy providers."""
+        healthy = []
+        for p in providers:
+            provider_name = p.get("provider")
+            if not provider_name:
+                continue
+
+            result = await self.db.execute(
+                select(Provider).where(
+                    Provider.name == provider_name,
+                    Provider.enabled == True,
+                    Provider.health_status == "healthy",
+                )
+            )
+            provider = result.scalar_one_or_none()
+
+            if provider:
+                healthy.append(p)
+
+        return healthy
+
+    async def get_fallback_provider(
+        self, failed_provider: str, fallback_chain: list[dict[str, str]] | None
+    ) -> RoutingResult | None:
+        """
+        Get the next fallback provider after a failure.
+
+        Args:
+            failed_provider: The provider that failed.
+            fallback_chain: List of fallback providers.
+
+        Returns:
+            RoutingResult for the next provider, or None if no more fallbacks.
+        """
+        if not fallback_chain:
+            return None
+
+        # Find the failed provider in the chain and return the next one
+        for i, fallback in enumerate(fallback_chain):
+            if fallback.get("provider") == failed_provider and i + 1 < len(fallback_chain):
+                next_fallback = fallback_chain[i + 1]
+                return RoutingResult(
+                    provider=next_fallback.get("provider", ""),
+                    model=next_fallback.get("model", ""),
+                    fallback_chain=fallback_chain[i + 1 :],
+                )
+
+        # If failed provider not in chain or at the end, try from the beginning
+        for fallback in fallback_chain:
+            if fallback.get("provider") != failed_provider:
+                return RoutingResult(
+                    provider=fallback.get("provider", ""),
+                    model=fallback.get("model", ""),
+                    fallback_chain=fallback_chain,
+                )
+
+        return None

llm-gateway/app/core/transformer.py

@@ -0,0 +1,228 @@
+"""Request transformer for converting between API formats."""
+import time
+import uuid
+from typing import Any
+
+from app.schemas.anthropic import (
+    AnthropicContentBlock,
+    AnthropicMessage,
+    AnthropicMessagesRequest,
+    AnthropicMessagesResponse,
+    AnthropicTextBlock,
+    AnthropicUsage,
+)
+from app.schemas.openai import (
+    OpenAIChatCompletionChoice,
+    OpenAIChatCompletionRequest,
+    OpenAIChatCompletionResponse,
+    OpenAIChatMessage,
+    OpenAIUsage,
+)
+
+
+class RequestTransformer:
+    """Transform requests between different API formats."""
+
+    @staticmethod
+    def openai_to_anthropic(
+        request: OpenAIChatCompletionRequest,
+    ) -> AnthropicMessagesRequest:
+        """Convert OpenAI Chat Completions request to Anthropic Messages request."""
+        messages = []
+        system = None
+
+        for msg in request.messages:
+            if msg.role == "system":
+                # Extract system message
+                system = msg.content if isinstance(msg.content, str) else None
+            elif msg.role in ("user", "assistant"):
+                # Convert content to Anthropic format
+                if isinstance(msg.content, str):
+                    content = msg.content
+                elif isinstance(msg.content, list):
+                    # Handle multi-modal content
+                    content = []
+                    for part in msg.content:
+                        if part.get("type") == "text":
+                            content.append(
+                                AnthropicContentBlock(type="text", text=part.get("text", ""))
+                            )
+                        elif part.get("type") == "image_url":
+                            # Convert OpenAI image format to Anthropic
+                            content.append(
+                                AnthropicContentBlock(
+                                    type="image",
+                                    source={
+                                        "type": "url",
+                                        "url": part.get("image_url", {}).get("url", ""),
+                                    },
+                                )
+                            )
+                        else:
+                            content.append(
+                                AnthropicContentBlock(type="text", text=str(part))
+                            )
+                else:
+                    content = str(msg.content) if msg.content else ""
+
+                messages.append(
+                    AnthropicMessage(
+                        role=msg.role,  # type: ignore
+                        content=content,
+                    )
+                )
+
+        # Handle max_tokens
+        max_tokens = request.max_tokens or 4096
+
+        return AnthropicMessagesRequest(
+            model=request.model,
+            messages=messages,
+            system=system,
+            max_tokens=max_tokens,
+            temperature=request.temperature,
+            top_p=request.top_p,
+            stop_sequences=[request.stop] if isinstance(request.stop, str) else request.stop,
+            stream=request.stream,
+            tools=request.tools,
+            tool_choice=request.tool_choice,
+        )
+
+    @staticmethod
+    def anthropic_to_openai(
+        request: AnthropicMessagesRequest,
+        model: str | None = None,
+    ) -> OpenAIChatCompletionRequest:
+        """Convert Anthropic Messages request to OpenAI Chat Completions request."""
+        messages = []
+
+        # Add system message if present
+        if request.system:
+            messages.append(
+                OpenAIChatMessage(
+                    role="system",
+                    content=request.system,
+                )
+            )
+
+        # Convert messages
+        for msg in request.messages:
+            if isinstance(msg.content, str):
+                content = msg.content
+            elif isinstance(msg.content, list):
+                # Convert Anthropic content blocks to OpenAI format
+                content = []
+                for block in msg.content:
+                    if hasattr(block, "type") and block.type == "text":
+                        content.append({"type": "text", "text": block.text or ""})
+                    elif isinstance(block, dict) and block.get("type") == "text":
+                        content.append({"type": "text", "text": block.get("text", "")})
+                    else:
+                        content.append({"type": "text", "text": str(block)})
+            else:
+                content = str(msg.content)
+
+            messages.append(
+                OpenAIChatMessage(
+                    role=msg.role,  # type: ignore
+                    content=content,
+                )
+            )
+
+        return OpenAIChatCompletionRequest(
+            model=model or request.model,
+            messages=messages,
+            max_tokens=request.max_tokens,
+            temperature=request.temperature,
+            top_p=request.top_p,
+            stream=request.stream,
+            tools=request.tools,
+            tool_choice=request.tool_choice,
+        )
+
+    @staticmethod
+    def anthropic_response_to_openai(
+        response: AnthropicMessagesResponse,
+        model: str,
+    ) -> OpenAIChatCompletionResponse:
+        """Convert Anthropic Messages response to OpenAI Chat Completions response."""
+        # Extract text content
+        content = ""
+        for block in response.content:
+            if hasattr(block, "type") and block.type == "text":
+                content += block.text or ""
+            elif isinstance(block, dict) and block.get("type") == "text":
+                content += block.get("text", "")
+
+        # Map stop reasons
+        finish_reason_map = {
+            "end_turn": "stop",
+            "max_tokens": "length",
+            "stop_sequence": "stop",
+            "tool_use": "tool_calls",
+        }
+        finish_reason = finish_reason_map.get(response.stop_reason or "", "stop")
+
+        return OpenAIChatCompletionResponse(
+            id=response.id,
+            object="chat.completion",
+            created=int(time.time()),
+            model=model,
+            choices=[
+                OpenAIChatCompletionChoice(
+                    index=0,
+                    message=OpenAIChatMessage(
+                        role="assistant",
+                        content=content,
+                    ),
+                    finish_reason=finish_reason,
+                )
+            ],
+            usage=OpenAIUsage(
+                prompt_tokens=response.usage.input_tokens,
+                completion_tokens=response.usage.output_tokens,
+                total_tokens=response.usage.input_tokens + response.usage.output_tokens,
+            )
+            if response.usage
+            else None,
+        )
+
+    @staticmethod
+    def openai_response_to_anthropic(
+        response: OpenAIChatCompletionResponse,
+    ) -> AnthropicMessagesResponse:
+        """Convert OpenAI Chat Completions response to Anthropic Messages response."""
+        # Extract content from choices
+        content = []
+        for choice in response.choices:
+            if choice.message.content:
+                content.append(
+                    AnthropicTextBlock(
+                        type="text",
+                        text=choice.message.content,
+                    )
+                )
+
+        # Map finish reasons
+        stop_reason_map = {
+            "stop": "end_turn",
+            "length": "max_tokens",
+            "tool_calls": "tool_use",
+            "content_filter": "end_turn",
+        }
+        stop_reason = stop_reason_map.get(
+            response.choices[0].finish_reason or "", "end_turn"
+        )
+
+        return AnthropicMessagesResponse(
+            id=response.id or f"msg_{uuid.uuid4().hex[:24]}",
+            type="message",
+            role="assistant",
+            content=content,
+            model=response.model,
+            stop_reason=stop_reason,
+            usage=AnthropicUsage(
+                input_tokens=response.usage.prompt_tokens if response.usage else 0,
+                output_tokens=response.usage.completion_tokens if response.usage else 0,
+            ),
+        )

llm-gateway/app/db/__init__.py

@@ -0,0 +1 @@
+# db module

llm-gateway/app/db/database.py

@@ -0,0 +1,70 @@
+"""Database connection and session management."""
+import os
+from pathlib import Path
+
+from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker, create_async_engine
+from sqlalchemy.orm import DeclarativeBase
+
+from app.config import get_settings
+
+
+class Base(DeclarativeBase):
+    """Base class for all models."""
+
+    pass
+
+
+# Create async engine
+def get_engine():
+    """Create database engine based on settings."""
+    settings = get_settings()
+    db_url = settings.database_url
+
+    # Ensure data directory exists for SQLite
+    if db_url.startswith("sqlite:///"):
+        db_path = db_url.replace("sqlite:///", "")
+        Path(db_path).parent.mkdir(parents=True, exist_ok=True)
+        # Use aiosqlite for async SQLite
+        db_url = db_url.replace("sqlite:///", "sqlite+aiosqlite:///")
+
+    return create_async_engine(db_url, echo=settings.debug)
+
+
+engine = get_engine()
+
+# Session factory
+AsyncSessionLocal = async_sessionmaker(
+    engine,
+    class_=AsyncSession,
+    expire_on_commit=False,
+    autocommit=False,
+    autoflush=False,
+)
+
+
+async def init_db():
+    """Initialize database tables."""
+    # Import all models to ensure they are registered
+    from app.models import (  # noqa: F401
+        provider,
+        api_key,
+        project,
+        model_alias,
+        usage,
+    )
+
+    async with engine.begin() as conn:
+        await conn.run_sync(Base.metadata.create_all)
+
+
+async def get_db():
+    """Dependency to get database session."""
+    async with AsyncSessionLocal() as session:
+        try:
+            yield session
+            await session.commit()
+        except Exception:
+            await session.rollback()
+            raise
+        finally:
+            await session.close()

llm-gateway/app/main.py

@@ -0,0 +1,61 @@
+"""FastAPI application entry point."""
+import os
+from contextlib import asynccontextmanager
+
+from fastapi import FastAPI
+from fastapi.middleware.cors import CORSMiddleware
+
+from app.api.admin import health, keys, models, projects, providers, usage
+from app.api.v1 import chat, messages, responses
+from app.config import get_settings
+from app.db.database import init_db
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    """Application lifespan handler."""
+    # Startup - skip if testing
+    if not os.environ.get("TESTING"):
+        await init_db()
+    yield
+    # Shutdown
+
+
+def create_app() -> FastAPI:
+    """Create and configure the FastAPI application."""
+    settings = get_settings()
+
+    app = FastAPI(
+        title=settings.app_name,
+        description="A unified LLM Gateway supporting multiple providers and API formats",
+        version="0.1.0",
+        debug=settings.debug,
+        lifespan=lifespan,
+    )
+
+    # CORS middleware
+    app.add_middleware(
+        CORSMiddleware,
+        allow_origins=["*"],
+        allow_credentials=True,
+        allow_methods=["*"],
+        allow_headers=["*"],
+    )
+
+    # Admin API routers
+    app.include_router(providers.router, prefix="/admin")
+    app.include_router(projects.router, prefix="/admin")
+    app.include_router(keys.router, prefix="/admin")
+    app.include_router(models.router, prefix="/admin")
+    app.include_router(usage.router, prefix="/admin")
+    app.include_router(health.router)
+
+    # LLM API routers
+    app.include_router(chat.router)
+    app.include_router(messages.router)
+    app.include_router(responses.router)
+
+    return app
+
+
+app = create_app()

llm-gateway/app/middleware/__init__.py

@@ -0,0 +1 @@
+# middleware module

llm-gateway/app/models/__init__.py

@@ -0,0 +1,17 @@
+"""Models package."""
+from app.models.provider import Provider
+from app.models.project import Project
+from app.models.api_key import APIKey
+from app.models.model_alias import ModelAlias
+from app.models.usage import RequestLog, UsageStatsHourly, AuditLog, RateLimitCounter
+
+__all__ = [
+    "Provider",
+    "Project",
+    "APIKey",
+    "ModelAlias",
+    "RequestLog",
+    "UsageStatsHourly",
+    "AuditLog",
+    "RateLimitCounter",
+]

llm-gateway/app/models/api_key.py

@@ -0,0 +1,48 @@
+"""API Key model."""
+from datetime import datetime
+from decimal import Decimal
+from uuid import uuid4
+
+from sqlalchemy import Boolean, DateTime, ForeignKey, Integer, Numeric, String, Text
+from sqlalchemy.orm import Mapped, mapped_column, relationship
+
+from app.db.database import Base
+
+
+class APIKey(Base):
+    """Virtual API Key for authentication and usage tracking."""
+
+    __tablename__ = "api_keys"
+
+    id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid4()))
+    key_hash: Mapped[str] = mapped_column(String(128), unique=True, nullable=False, index=True)
+    key_prefix: Mapped[str] = mapped_column(String(20), nullable=False)  # e.g., "sk-proj_abc..."
+    name: Mapped[str] = mapped_column(String(100), nullable=False)
+
+    # Project relationship
+    project_id: Mapped[str | None] = mapped_column(String(36), ForeignKey("projects.id"))
+    project: Mapped["Project"] = relationship("Project", backref="api_keys")
+
+    enabled: Mapped[bool] = mapped_column(Boolean, default=True)
+    expires_at: Mapped[datetime | None] = mapped_column(DateTime)
+
+    # Rate Limits
+    rpm_limit: Mapped[int | None] = mapped_column(Integer)
+    tpm_limit: Mapped[int | None] = mapped_column(Integer)
+
+    # Budget
+    budget_limit: Mapped[Decimal | None] = mapped_column(Numeric(10, 2))
+    budget_period: Mapped[str | None] = mapped_column(String(20))  # daily, weekly, monthly
+
+    # Permissions
+    allowed_models: Mapped[str | None] = mapped_column(Text)  # JSON array
+
+    # Usage Stats
+    current_usage: Mapped[Decimal] = mapped_column(Numeric(10, 2), default=Decimal("0"))
+    total_requests: Mapped[int] = mapped_column(Integer, default=0)
+
+    # Timestamps
+    created_at: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow)
+    updated_at: Mapped[datetime] = mapped_column(
+        DateTime, default=datetime.utcnow, onupdate=datetime.utcnow
+    )

llm-gateway/app/models/model_alias.py

@@ -0,0 +1,36 @@
+"""Model alias model."""
+from datetime import datetime
+from decimal import Decimal
+from uuid import uuid4
+
+from sqlalchemy import Boolean, DateTime, Numeric, String, Text
+from sqlalchemy.orm import Mapped, mapped_column
+
+from app.db.database import Base
+
+
+class ModelAlias(Base):
+    """Model alias for routing and cost tracking."""
+
+    __tablename__ = "model_aliases"
+
+    id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid4()))
+    alias: Mapped[str] = mapped_column(String(100), unique=True, nullable=False, index=True)
+    provider: Mapped[str] = mapped_column(String(50), nullable=False)
+    model: Mapped[str] = mapped_column(String(100), nullable=False)
+
+    enabled: Mapped[bool] = mapped_column(Boolean, default=True)
+
+    # Routing: simple, load_balance, fallback
+    routing_type: Mapped[str] = mapped_column(String(20), default="simple")
+    routing_config: Mapped[str | None] = mapped_column(Text)  # JSON
+
+    # Pricing (per 1K tokens)
+    input_price_per_1k: Mapped[Decimal | None] = mapped_column(Numeric(10, 6))
+    output_price_per_1k: Mapped[Decimal | None] = mapped_column(Numeric(10, 6))
+
+    # Timestamps
+    created_at: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow)
+    updated_at: Mapped[datetime] = mapped_column(
+        DateTime, default=datetime.utcnow, onupdate=datetime.utcnow
+    )

llm-gateway/app/models/project.py

@@ -0,0 +1,31 @@
+"""Project model."""
+from datetime import datetime
+from decimal import Decimal
+from uuid import uuid4
+
+from sqlalchemy import Boolean, DateTime, Numeric, String, Text
+from sqlalchemy.orm import Mapped, mapped_column
+
+from app.db.database import Base
+
+
+class Project(Base):
+    """Project for organizing API keys and tracking usage."""
+
+    __tablename__ = "projects"
+
+    id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid4()))
+    name: Mapped[str] = mapped_column(String(100), nullable=False, index=True)
+    description: Mapped[str | None] = mapped_column(Text)
+
+    # Budget
+    budget_limit: Mapped[Decimal | None] = mapped_column(Numeric(10, 2))
+    budget_period: Mapped[str | None] = mapped_column(String(20))  # daily, weekly, monthly
+
+    enabled: Mapped[bool] = mapped_column(Boolean, default=True)
+
+    # Timestamps
+    created_at: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow)
+    updated_at: Mapped[datetime] = mapped_column(
+        DateTime, default=datetime.utcnow, onupdate=datetime.utcnow
+    )

llm-gateway/app/models/provider.py

@@ -0,0 +1,40 @@
+"""Provider model."""
+from datetime import datetime
+from uuid import uuid4
+
+from sqlalchemy import Boolean, DateTime, Integer, String, Text
+from sqlalchemy.orm import Mapped, mapped_column
+
+from app.db.database import Base
+
+
+class Provider(Base):
+    """LLM Provider configuration."""
+
+    __tablename__ = "providers"
+
+    id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid4()))
+    name: Mapped[str] = mapped_column(String(50), unique=True, nullable=False, index=True)
+    enabled: Mapped[bool] = mapped_column(Boolean, default=True)
+
+    # API Configuration
+    api_base: Mapped[str] = mapped_column(String(500), nullable=False)
+    api_key_encrypted: Mapped[str] = mapped_column(Text, nullable=False)
+    api_version: Mapped[str | None] = mapped_column(String(50))
+
+    # Provider-specific config (JSON)
+    config: Mapped[str | None] = mapped_column(Text)
+
+    # Rate Limits
+    rpm_limit: Mapped[int | None] = mapped_column(Integer)
+    tpm_limit: Mapped[int | None] = mapped_column(Integer)
+
+    # Health Status
+    health_status: Mapped[str] = mapped_column(String(20), default="healthy")
+    last_health_check: Mapped[datetime | None] = mapped_column(DateTime)
+
+    # Timestamps
+    created_at: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow)
+    updated_at: Mapped[datetime] = mapped_column(
+        DateTime, default=datetime.utcnow, onupdate=datetime.utcnow
+    )

llm-gateway/app/models/usage.py

@@ -0,0 +1,110 @@
+"""Usage tracking models."""
+from datetime import datetime
+from decimal import Decimal
+from uuid import uuid4
+
+from sqlalchemy import BigInteger, DateTime, ForeignKey, Integer, Numeric, String, Text
+from sqlalchemy.orm import Mapped, mapped_column
+
+from app.db.database import Base
+
+
+class RequestLog(Base):
+    """Request log for tracking individual API calls."""
+
+    __tablename__ = "request_logs"
+
+    id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid4()))
+    timestamp: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow, index=True)
+
+    # Keys and Projects
+    virtual_key_id: Mapped[str | None] = mapped_column(
+        String(36), ForeignKey("api_keys.id"), index=True
+    )
+    project_id: Mapped[str | None] = mapped_column(
+        String(36), ForeignKey("projects.id"), index=True
+    )
+
+    # Request details
+    provider: Mapped[str] = mapped_column(String(50), nullable=False)
+    model: Mapped[str] = mapped_column(String(100), nullable=False)
+    model_alias: Mapped[str | None] = mapped_column(String(100))
+    request_type: Mapped[str] = mapped_column(String(20))  # chat, completion, embedding
+
+    # Tokens
+    input_tokens: Mapped[int] = mapped_column(Integer)
+    output_tokens: Mapped[int] = mapped_column(Integer)
+    total_tokens: Mapped[int] = mapped_column(Integer)
+
+    # Response
+    status_code: Mapped[int] = mapped_column(Integer)
+    latency_ms: Mapped[int] = mapped_column(Integer)
+    finish_reason: Mapped[str | None] = mapped_column(String(50))
+
+    # Cost
+    cost_usd: Mapped[Decimal] = mapped_column(Numeric(10, 6))
+
+    # Request metadata (JSON)
+    request_metadata: Mapped[str | None] = mapped_column(Text)
+
+
+class UsageStatsHourly(Base):
+    """Hourly aggregated usage statistics."""
+
+    __tablename__ = "usage_stats_hourly"
+
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    timestamp: Mapped[datetime] = mapped_column(DateTime, nullable=False, index=True)
+
+    virtual_key_id: Mapped[str | None] = mapped_column(String(36), index=True)
+    project_id: Mapped[str | None] = mapped_column(String(36), index=True)
+    provider: Mapped[str] = mapped_column(String(50))
+    model: Mapped[str] = mapped_column(String(100))
+
+    # Aggregates
+    request_count: Mapped[int] = mapped_column(Integer, default=0)
+    input_tokens: Mapped[int] = mapped_column(BigInteger, default=0)
+    output_tokens: Mapped[int] = mapped_column(BigInteger, default=0)
+    total_tokens: Mapped[int] = mapped_column(BigInteger, default=0)
+    cost_usd: Mapped[Decimal] = mapped_column(Numeric(10, 6), default=Decimal("0"))
+
+    avg_latency_ms: Mapped[int | None] = mapped_column(Integer)
+    error_count: Mapped[int] = mapped_column(Integer, default=0)
+
+
+class AuditLog(Base):
+    """Audit log for tracking admin operations."""
+
+    __tablename__ = "audit_logs"
+
+    id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid4()))
+    timestamp: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow, index=True)
+
+    # Who
+    actor: Mapped[str] = mapped_column(String(100), nullable=False)
+
+    # What
+    action: Mapped[str] = mapped_column(String(50), nullable=False)  # create, update, delete
+
+    # Which
+    resource: Mapped[str] = mapped_column(String(50), nullable=False)  # provider, key, project
+    resource_id: Mapped[str | None] = mapped_column(String(36))
+
+    # Changes
+    changes: Mapped[str | None] = mapped_column(Text)  # JSON with before/after
+
+    # Request info
+    ip_address: Mapped[str | None] = mapped_column(String(50))
+    user_agent: Mapped[str | None] = mapped_column(String(500))
+
+
+class RateLimitCounter(Base):
+    """Rate limit counter for tracking usage windows."""
+
+    __tablename__ = "rate_limit_counters"
+
+    key: Mapped[str] = mapped_column(String(200), primary_key=True)
+    request_count: Mapped[int] = mapped_column(Integer, default=0)
+    token_count: Mapped[int] = mapped_column(BigInteger, default=0)
+    window_start: Mapped[datetime] = mapped_column(DateTime, nullable=False)
+    window_duration: Mapped[int] = mapped_column(Integer, nullable=False)  # seconds

llm-gateway/app/schemas/__init__.py

@@ -0,0 +1 @@
+# schemas module

llm-gateway/app/schemas/anthropic.py

@@ -0,0 +1,107 @@
+"""Anthropic Messages API request and response schemas."""
+from typing import Any, Literal
+
+from pydantic import BaseModel, Field
+
+
+# === Request Models ===
+
+
+class AnthropicContentBlock(BaseModel):
+    """Anthropic content block."""
+
+    type: Literal["text", "image", "tool_use", "tool_result"]
+    text: str | None = None
+    source: dict[str, Any] | None = None  # For images
+    tool_use_id: str | None = None  # For tool_result
+    content: str | list[dict[str, Any]] | None = None  # For tool_result
+    name: str | None = None  # For tool_use
+    input: dict[str, Any] | None = None  # For tool_use
+
+
+class AnthropicMessage(BaseModel):
+    """Anthropic message."""
+
+    role: Literal["user", "assistant"]
+    content: str | list[AnthropicContentBlock]
+
+
+class AnthropicMessagesRequest(BaseModel):
+    """Anthropic Messages API request."""
+
+    model: str
+    messages: list[AnthropicMessage]
+    system: str | None = None
+    max_tokens: int = Field(..., ge=1)
+    temperature: float | None = Field(None, ge=0, le=1)
+    top_p: float | None = Field(None, ge=0, le=1)
+    top_k: int | None = Field(None, ge=0)
+    stop_sequences: list[str] | None = None
+    stream: bool = False
+    tools: list[dict[str, Any]] | None = None
+    tool_choice: dict[str, Any] | None = None
+    metadata: dict[str, Any] | None = None
+
+
+# === Response Models ===
+
+
+class AnthropicTextBlock(BaseModel):
+    """Anthropic text content block."""
+
+    type: Literal["text"] = "text"
+    text: str
+
+
+class AnthropicToolUseBlock(BaseModel):
+    """Anthropic tool use content block."""
+
+    type: Literal["tool_use"] = "tool_use"
+    id: str
+    name: str
+    input: dict[str, Any]
+
+
+class AnthropicUsage(BaseModel):
+    """Anthropic token usage."""
+
+    input_tokens: int
+    output_tokens: int
+    cache_creation_input_tokens: int | None = None
+    cache_read_input_tokens: int | None = None
+
+
+class AnthropicMessagesResponse(BaseModel):
+    """Anthropic Messages API response."""
+
+    id: str
+    type: Literal["message"] = "message"
+    role: Literal["assistant"] = "assistant"
+    content: list[AnthropicTextBlock | AnthropicToolUseBlock]
+    model: str
+    stop_reason: Literal["end_turn", "max_tokens", "stop_sequence", "tool_use"] | None = None
+    stop_sequence: str | None = None
+    usage: AnthropicUsage
+
+
+class AnthropicStreamMessage(BaseModel):
+    """Anthropic streaming message start."""
+
+    type: Literal["message_start"] = "message_start"
+    message: AnthropicMessagesResponse
+
+
+class AnthropicContentBlockDelta(BaseModel):
+    """Anthropic streaming content block delta."""
+
+    type: Literal["content_block_delta"] = "content_block_delta"
+    index: int
+    delta: dict[str, Any]
+
+
+class AnthropicMessageDelta(BaseModel):
+    """Anthropic streaming message delta."""
+
+    type: Literal["message_delta"] = "message_delta"
+    delta: dict[str, Any]
+    usage: AnthropicUsage | None = None

llm-gateway/app/schemas/api_key.py

@@ -0,0 +1,71 @@
+"""API Key schemas for API requests and responses."""
+from datetime import datetime
+from decimal import Decimal
+
+from pydantic import BaseModel, ConfigDict, Field
+
+from app.schemas.common import BaseResponse
+
+
+class APIKeyCreate(BaseModel):
+    """Schema for creating an API key."""
+
+    name: str = Field(..., min_length=1, max_length=100)
+    project_id: str | None = Field(None, description="Associated project ID")
+    prefix: str = Field(default="sk", max_length=10, description="Key prefix")
+    expires_at: datetime | None = Field(None, description="Expiration date")
+    rpm_limit: int | None = Field(None, ge=1)
+    tpm_limit: int | None = Field(None, ge=1)
+    budget_limit: Decimal | None = Field(None, ge=0)
+    budget_period: str | None = Field(None, pattern="^(daily|weekly|monthly)$")
+    allowed_models: list[str] | None = Field(None, description="List of allowed model aliases")
+    enabled: bool = Field(True)
+
+
+class APIKeyUpdate(BaseModel):
+    """Schema for updating an API key."""
+
+    name: str | None = Field(None, min_length=1, max_length=100)
+    project_id: str | None = None
+    expires_at: datetime | None = None
+    rpm_limit: int | None = Field(None, ge=1)
+    tpm_limit: int | None = Field(None, ge=1)
+    budget_limit: Decimal | None = Field(None, ge=0)
+    budget_period: str | None = Field(None, pattern="^(daily|weekly|monthly)$")
+    allowed_models: list[str] | None = None
+    enabled: bool | None = None
+
+
+class APIKeyResponse(BaseResponse):
+    """Schema for API key response."""
+
+    id: str
+    key_prefix: str
+    name: str
+    project_id: str | None
+    enabled: bool
+    expires_at: datetime | None
+    rpm_limit: int | None
+    tpm_limit: int | None
+    budget_limit: Decimal | None
+    budget_period: str | None
+    allowed_models: list[str] | None
+    current_usage: Decimal
+    total_requests: int
+    created_at: datetime
+    updated_at: datetime
+
+
+class APIKeyCreateResponse(APIKeyResponse):
+    """Schema for API key creation response (includes the full key)."""
+
+    key: str = Field(..., description="Full API key (shown only once)")
+
+
+class APIKeyListResponse(BaseResponse):
+    """Schema for API key list response."""
+
+    keys: list[APIKeyResponse]
+    total: int
+    page: int
+    page_size: int

llm-gateway/app/schemas/common.py

@@ -0,0 +1,30 @@
+"""Common schemas for API requests and responses."""
+from datetime import datetime
+from decimal import Decimal
+from typing import Any
+
+from pydantic import BaseModel, ConfigDict, Field
+
+
+class BaseResponse(BaseModel):
+    """Base response model."""
+
+    model_config = ConfigDict(from_attributes=True)
+
+
+class ErrorResponse(BaseModel):
+    """Error response model."""
+
+    error: dict[str, Any]
+
+
+class PaginationParams(BaseModel):
+    """Pagination parameters."""
+
+    page: int = Field(default=1, ge=1)
+    page_size: int = Field(default=20, ge=1, le=100)
+
+    @property
+    def offset(self) -> int:
+        """Calculate offset for database query."""
+        return (self.page - 1) * self.page_size

llm-gateway/app/schemas/model_alias.py

@@ -0,0 +1,71 @@
+"""Model alias schemas for API requests and responses."""
+from datetime import datetime
+from decimal import Decimal
+from typing import Any
+
+from pydantic import BaseModel, ConfigDict, Field
+
+from app.schemas.common import BaseResponse
+
+
+class RoutingConfig(BaseModel):
+    """Routing configuration for load balancing and fallback."""
+
+    providers: list[dict[str, Any]] | None = Field(
+        None, description="List of providers with weights for load balancing"
+    )
+    primary: dict[str, str] | None = Field(None, description="Primary provider for fallback")
+    fallback: list[dict[str, str]] | None = Field(None, description="Fallback providers")
+
+
+class ModelAliasCreate(BaseModel):
+    """Schema for creating a model alias."""
+
+    alias: str = Field(..., min_length=1, max_length=100, description="User-facing model name")
+    provider: str = Field(..., min_length=1, max_length=50, description="Provider name")
+    model: str = Field(..., min_length=1, max_length=100, description="Actual model name")
+    routing_type: str = Field(
+        default="simple", pattern="^(simple|load_balance|fallback)$"
+    )
+    routing_config: RoutingConfig | None = None
+    input_price_per_1k: Decimal | None = Field(None, ge=0)
+    output_price_per_1k: Decimal | None = Field(None, ge=0)
+    enabled: bool = Field(True)
+
+
+class ModelAliasUpdate(BaseModel):
+    """Schema for updating a model alias."""
+
+    alias: str | None = Field(None, min_length=1, max_length=100)
+    provider: str | None = Field(None, min_length=1, max_length=50)
+    model: str | None = Field(None, min_length=1, max_length=100)
+    routing_type: str | None = Field(None, pattern="^(simple|load_balance|fallback)$")
+    routing_config: RoutingConfig | None = None
+    input_price_per_1k: Decimal | None = Field(None, ge=0)
+    output_price_per_1k: Decimal | None = Field(None, ge=0)
+    enabled: bool | None = None
+
+
+class ModelAliasResponse(BaseResponse):
+    """Schema for model alias response."""
+
+    id: str
+    alias: str
+    provider: str
+    model: str
+    enabled: bool
+    routing_type: str
+    routing_config: dict[str, Any] | None
+    input_price_per_1k: Decimal | None
+    output_price_per_1k: Decimal | None
+    created_at: datetime
+    updated_at: datetime
+
+
+class ModelAliasListResponse(BaseResponse):
+    """Schema for model alias list response."""
+
+    aliases: list[ModelAliasResponse]
+    total: int
+    page: int
+    page_size: int

llm-gateway/app/schemas/openai.py

@@ -0,0 +1,100 @@
+"""OpenAI API request and response schemas."""
+from typing import Any, Literal
+
+from pydantic import BaseModel, Field
+
+
+# === Request Models ===
+
+
+class OpenAIChatMessage(BaseModel):
+    """OpenAI chat message."""
+
+    role: Literal["system", "user", "assistant", "tool", "function"]
+    content: str | list[dict[str, Any]] | None = None
+    name: str | None = None
+    tool_calls: list[dict[str, Any]] | None = None
+    tool_call_id: str | None = None
+
+
+class OpenAIChatCompletionRequest(BaseModel):
+    """OpenAI Chat Completions API request."""
+
+    model: str
+    messages: list[OpenAIChatMessage]
+    temperature: float | None = Field(None, ge=0, le=2)
+    top_p: float | None = Field(None, ge=0, le=1)
+    n: int | None = Field(None, ge=1)
+    stream: bool = False
+    stop: str | list[str] | None = None
+    max_tokens: int | None = Field(None, ge=1)
+    presence_penalty: float | None = Field(None, ge=-2, le=2)
+    frequency_penalty: float | None = Field(None, ge=-2, le=2)
+    logit_bias: dict[str, float] | None = None
+    user: str | None = None
+    tools: list[dict[str, Any]] | None = None
+    tool_choice: str | dict[str, Any] | None = None
+    response_format: dict[str, Any] | None = None
+
+
+class OpenAIResponseRequest(BaseModel):
+    """OpenAI Responses API request (new format)."""
+
+    model: str
+    input: str | list[dict[str, Any]]
+    instructions: str | None = None
+    temperature: float | None = Field(None, ge=0, le=2)
+    max_output_tokens: int | None = Field(None, ge=1)
+    tools: list[dict[str, Any]] | None = None
+    tool_choice: str | dict[str, Any] | None = None
+    metadata: dict[str, Any] | None = None
+
+
+# === Response Models ===
+
+
+class OpenAIChatCompletionChoice(BaseModel):
+    """OpenAI chat completion choice."""
+
+    index: int
+    message: OpenAIChatMessage
+    finish_reason: str | None
+
+
+class OpenAIUsage(BaseModel):
+    """Token usage information."""
+
+    prompt_tokens: int
+    completion_tokens: int
+    total_tokens: int
+
+
+class OpenAIChatCompletionResponse(BaseModel):
+    """OpenAI Chat Completions API response."""
+
+    id: str
+    object: Literal["chat.completion"] = "chat.completion"
+    created: int
+    model: str
+    choices: list[OpenAIChatCompletionChoice]
+    usage: OpenAIUsage | None = None
+    system_fingerprint: str | None = None
+
+
+class OpenAIStreamChoice(BaseModel):
+    """OpenAI streaming choice."""
+
+    index: int
+    delta: dict[str, Any]
+    finish_reason: str | None
+
+
+class OpenAIChatCompletionChunk(BaseModel):
+    """OpenAI Chat Completions streaming chunk."""
+
+    id: str
+    object: Literal["chat.completion.chunk"] = "chat.completion.chunk"
+    created: int
+    model: str
+    choices: list[OpenAIStreamChoice]
+    system_fingerprint: str | None = None

llm-gateway/app/schemas/project.py

@@ -0,0 +1,49 @@
+"""Project schemas for API requests and responses."""
+from datetime import datetime
+from decimal import Decimal
+
+from pydantic import BaseModel, ConfigDict, Field
+
+from app.schemas.common import BaseResponse
+
+
+class ProjectCreate(BaseModel):
+    """Schema for creating a project."""
+
+    name: str = Field(..., min_length=1, max_length=100)
+    description: str | None = Field(None, max_length=1000)
+    budget_limit: Decimal | None = Field(None, ge=0)
+    budget_period: str | None = Field(None, pattern="^(daily|weekly|monthly)$")
+    enabled: bool = Field(True)
+
+
+class ProjectUpdate(BaseModel):
+    """Schema for updating a project."""
+
+    name: str | None = Field(None, min_length=1, max_length=100)
+    description: str | None = Field(None, max_length=1000)
+    budget_limit: Decimal | None = Field(None, ge=0)
+    budget_period: str | None = Field(None, pattern="^(daily|weekly|monthly)$")
+    enabled: bool | None = None
+
+
+class ProjectResponse(BaseResponse):
+    """Schema for project response."""
+
+    id: str
+    name: str
+    description: str | None
+    budget_limit: Decimal | None
+    budget_period: str | None
+    enabled: bool
+    created_at: datetime
+    updated_at: datetime
+
+
+class ProjectListResponse(BaseResponse):
+    """Schema for project list response."""
+
+    projects: list[ProjectResponse]
+    total: int
+    page: int
+    page_size: int

llm-gateway/app/schemas/provider.py

@@ -0,0 +1,58 @@
+"""Provider schemas for API requests and responses."""
+from datetime import datetime
+from typing import Any
+
+from pydantic import BaseModel, ConfigDict, Field
+
+from app.schemas.common import BaseResponse
+
+
+class ProviderCreate(BaseModel):
+    """Schema for creating a provider."""
+
+    name: str = Field(..., min_length=1, max_length=50, description="Provider name")
+    api_base: str = Field(..., min_length=1, max_length=500, description="API base URL")
+    api_key: str = Field(..., min_length=1, description="API key (will be encrypted)")
+    api_version: str | None = Field(None, max_length=50, description="API version")
+    config: dict[str, Any] | None = Field(None, description="Provider-specific configuration")
+    rpm_limit: int | None = Field(None, ge=1, description="Requests per minute limit")
+    tpm_limit: int | None = Field(None, ge=1, description="Tokens per minute limit")
+    enabled: bool = Field(True, description="Whether provider is enabled")
+
+
+class ProviderUpdate(BaseModel):
+    """Schema for updating a provider."""
+
+    api_base: str | None = Field(None, min_length=1, max_length=500)
+    api_key: str | None = Field(None, min_length=1)
+    api_version: str | None = Field(None, max_length=50)
+    config: dict[str, Any] | None = None
+    rpm_limit: int | None = Field(None, ge=1)
+    tpm_limit: int | None = Field(None, ge=1)
+    enabled: bool | None = None
+
+
+class ProviderResponse(BaseResponse):
+    """Schema for provider response."""
+
+    id: str
+    name: str
+    enabled: bool
+    api_base: str
+    api_version: str | None
+    config: dict[str, Any] | None
+    rpm_limit: int | None
+    tpm_limit: int | None
+    health_status: str
+    last_health_check: datetime | None
+    created_at: datetime
+    updated_at: datetime
+
+
+class ProviderListResponse(BaseResponse):
+    """Schema for provider list response."""
+
+    providers: list[ProviderResponse]
+    total: int
+    page: int
+    page_size: int

llm-gateway/app/utils/__init__.py

@@ -0,0 +1 @@
+# utils module

llm-gateway/app/utils/crypto.py

@@ -0,0 +1,123 @@
+"""Cryptographic utilities for key management."""
+import base64
+import os
+from typing import Tuple
+
+import bcrypt
+from cryptography.fernet import Fernet
+from cryptography.hazmat.primitives import hashes
+from cryptography.hazmat.primitives.kdf.pbkdf2 import PBKDF2HMAC
+
+from app.config import get_settings
+
+
+def hash_api_key(key: str) -> str:
+    """
+    Hash an API key using bcrypt.
+
+    Args:
+        key: The plaintext API key to hash.
+
+    Returns:
+        The hashed key string.
+    """
+    salt = bcrypt.gensalt()
+    hashed = bcrypt.hashpw(key.encode("utf-8"), salt)
+    return hashed.decode("utf-8")
+
+
+def verify_api_key(key: str, hashed: str) -> bool:
+    """
+    Verify an API key against its hash.
+
+    Args:
+        key: The plaintext API key to verify.
+        hashed: The hashed key to compare against.
+
+    Returns:
+        True if the key matches, False otherwise.
+    """
+    try:
+        return bcrypt.checkpw(key.encode("utf-8"), hashed.encode("utf-8"))
+    except Exception:
+        return False
+
+
+def generate_api_key(prefix: str = "sk") -> Tuple[str, str, str]:
+    """
+    Generate a new API key.
+
+    Args:
+        prefix: The prefix for the key (e.g., "sk", "sk-proj").
+
+    Returns:
+        Tuple of (full_key, key_hash, key_prefix).
+    """
+    # Generate random key part
+    random_part = base64.urlsafe_b64encode(os.urandom(24)).decode("utf-8").rstrip("=")
+    full_key = f"{prefix}_{random_part}"
+
+    # Hash the key
+    key_hash = hash_api_key(full_key)
+
+    # Create prefix for display (first 12 chars)
+    key_prefix = full_key[:12] + "..."
+
+    return full_key, key_hash, key_prefix
+
+
+def get_encryption_key() -> bytes:
+    """
+    Derive an encryption key from the master key.
+
+    Returns:
+        A URL-safe base64-encoded 32-byte key for Fernet.
+    """
+    settings = get_settings()
+    master_key = settings.master_key.encode("utf-8")
+
+    # Use a fixed salt for deterministic key derivation
+    # In production, consider using a random salt stored securely
+    salt = b"llm-gateway-encryption-salt-v1"
+
+    kdf = PBKDF2HMAC(
+        algorithm=hashes.SHA256(),
+        length=32,
+        salt=salt,
+        iterations=100000,
+    )
+
+    key = base64.urlsafe_b64encode(kdf.derive(master_key))
+    return key
+
+
+def encrypt_value(plaintext: str) -> str:
+    """
+    Encrypt a value using Fernet symmetric encryption.
+
+    Args:
+        plaintext: The value to encrypt.
+
+    Returns:
+        The encrypted value as a base64 string.
+    """
+    key = get_encryption_key()
+    f = Fernet(key)
+    encrypted = f.encrypt(plaintext.encode("utf-8"))
+    return encrypted.decode("utf-8")
+
+
+def decrypt_value(encrypted: str) -> str:
+    """
+    Decrypt a value using Fernet symmetric encryption.
+
+    Args:
+        encrypted: The encrypted value as a base64 string.
+
+    Returns:
+        The decrypted plaintext.
+    """
+    key = get_encryption_key()
+    f = Fernet(key)
+    decrypted = f.decrypt(encrypted.encode("utf-8"))
+    return decrypted.decode("utf-8")

llm-gateway/app/utils/logging.py

@@ -0,0 +1,65 @@
+"""Structured logging configuration."""
+import logging
+import sys
+
+import structlog
+from structlog.types import Processor
+
+from app.config import get_settings
+
+
+def setup_logging() -> None:
+    """Configure structured logging for the application."""
+    settings = get_settings()
+
+    # Shared processors for both stdlib and structlog
+    shared_processors: list[Processor] = [
+        structlog.contextvars.merge_contextvars,
+        structlog.stdlib.add_log_level,
+        structlog.stdlib.add_logger_name,
+        structlog.processors.TimeStamper(fmt="iso"),
+        structlog.processors.StackInfoRenderer(),
+    ]
+
+    # Configure structlog
+    structlog.configure(
+        processors=shared_processors
+        + [
+            structlog.stdlib.ProcessorFormatter.wrap_for_formatter,
+        ],
+        logger_factory=structlog.stdlib.LoggerFactory(),
+        wrapper_class=structlog.stdlib.BoundLogger,
+        cache_logger_on_first_use=True,
+    )
+
+    # Configure stdlib logging
+    handler = logging.StreamHandler(sys.stdout)
+
+    if settings.debug or settings.log_level == "DEBUG":
+        formatter = structlog.stdlib.ProcessorFormatter(
+            foreign_pre_chain=shared_processors,
+            processors=[
+                structlog.dev.ConsoleRenderer(colors=True),
+            ],
+        )
+    else:
+        formatter = structlog.stdlib.ProcessorFormatter(
+            foreign_pre_chain=shared_processors,
+            processors=[
+                structlog.processors.format_exc_info,
+                structlog.processors.JSONRenderer(),
+            ],
+        )
+
+    handler.setFormatter(formatter)
+
+    # Clear existing handlers and add our handler
+    root_logger = logging.getLogger()
+    root_logger.handlers.clear()
+    root_logger.addHandler(handler)
+    root_logger.setLevel(getattr(logging, settings.log_level.upper(), logging.INFO))
+
+
+def get_logger(name: str | None = None) -> structlog.stdlib.BoundLogger:
+    """Get a structured logger instance."""
+    return structlog.get_logger(name)

llm-gateway/docker-compose.yml

@@ -0,0 +1,33 @@
+version: '3.8'
+
+services:
+  gateway:
+    build: .
+    ports:
+      - "8000:8000"
+    volumes:
+      - ./data:/app/data
+    environment:
+      - DATABASE_URL=sqlite:///data/gateway.db
+      - MASTER_KEY=${MASTER_KEY}
+      - DEBUG=${DEBUG:-false}
+      - LOG_LEVEL=${LOG_LEVEL:-INFO}
+    restart: unless-stopped
+    healthcheck:
+      test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 10s
+
+  # Optional: Redis for distributed rate limiting (future)
+  # redis:
+  #   image: redis:7-alpine
+  #   ports:
+  #     - "6379:6379"
+  #   volumes:
+  #     - redis_data:/data
+
+volumes:
+  gateway_data:
+  # redis_data:

llm-gateway/requirements.txt

@@ -0,0 +1,37 @@
+# Web Framework
+fastapi>=0.109.0
+uvicorn[standard]>=0.27.0
+pydantic>=2.5.0
+pydantic-settings>=2.1.0
+
+# HTTP Client
+httpx>=0.26.0
+
+# Database
+sqlalchemy>=2.0.0
+aiosqlite>=0.19.0
+
+# Security
+bcrypt>=4.1.0
+cryptography>=42.0.0
+
+# Logging
+structlog>=24.1.0
+
+# Testing
+pytest>=8.0.0
+pytest-asyncio>=0.23.0
+pytest-cov>=4.1.0
+httpx>=0.26.0
+
+# Type Checking
+mypy>=1.8.0
+
+# Code Quality
+ruff>=0.2.0
+
+# Provider SDKs
+openai>=1.12.0
+anthropic>=0.18.0
+google-generativeai>=0.3.0
+boto3>=1.34.0

llm-gateway/tests/__init__.py

@@ -0,0 +1 @@
+# tests module

llm-gateway/tests/conftest.py

@@ -0,0 +1,106 @@
+"""Pytest configuration and fixtures."""
+import asyncio
+import os
+import tempfile
+from typing import AsyncGenerator, Generator
+
+import pytest
+import pytest_asyncio
+from httpx import ASGITransport, AsyncClient
+from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker, create_async_engine
+
+# Set test environment before importing app
+os.environ["TESTING"] = "1"
+
+# Create a temp file for the test database
+_test_db_fd, _test_db_path = tempfile.mkstemp(suffix=".db")
+os.environ["DATABASE_URL"] = f"sqlite:///{_test_db_path}"
+os.environ["MASTER_KEY"] = "test-master-key-for-testing-32cha"
+
+# Now import the app modules
+from app.db import database
+from app.db.database import Base, get_db
+
+# Import all models to register them with Base
+from app.models import (  # noqa: F401
+    APIKey,
+    AuditLog,
+    ModelAlias,
+    Project,
+    Provider,
+    RateLimitCounter,
+    RequestLog,
+    UsageStatsHourly,
+)
+
+# Create test engine
+_test_db_url = f"sqlite+aiosqlite:///{_test_db_path}"
+_test_engine = create_async_engine(_test_db_url, echo=False)
+_test_session_factory = async_sessionmaker(
+    _test_engine,
+    class_=AsyncSession,
+    expire_on_commit=False,
+)
+
+# Override the global engine and session factory
+database.engine = _test_engine
+database.AsyncSessionLocal = _test_session_factory
+
+
+@pytest.fixture(scope="session")
+def event_loop() -> Generator[asyncio.AbstractEventLoop, None, None]:
+    """Create an event loop for the test session."""
+    loop = asyncio.get_event_loop_policy().new_event_loop()
+    yield loop
+    loop.close()
+
+
+@pytest_asyncio.fixture(scope="session")
+async def setup_test_db() -> AsyncGenerator[None, None]:
+    """Set up test database with all tables."""
+    # Create all tables
+    async with _test_engine.begin() as conn:
+        await conn.run_sync(Base.metadata.create_all)
+
+    yield
+
+    # Clean up
+    async with _test_engine.begin() as conn:
+        await conn.run_sync(Base.metadata.drop_all)
+
+    await _test_engine.dispose()
+    os.close(_test_db_fd)
+    os.unlink(_test_db_path)
+
+
+@pytest_asyncio.fixture
+async def db_session(setup_test_db: None) -> AsyncGenerator[AsyncSession, None]:
+    """Provide a database session for tests."""
+    async with _test_session_factory() as session:
+        yield session
+
+
+async def _get_test_db():
+    """Override dependency for test database."""
+    async with _test_session_factory() as session:
+        try:
+            yield session
+            await session.commit()
+        except Exception:
+            await session.rollback()
+            raise
+
+
+@pytest_asyncio.fixture
+async def client(setup_test_db: None) -> AsyncGenerator[AsyncClient, None]:
+    """Provide an async HTTP client for API tests."""
+    from app.main import create_app
+
+    test_app = create_app()
+
+    # Override the database dependency
+    test_app.dependency_overrides[get_db] = _get_test_db
+
+    transport = ASGITransport(app=test_app)
+    async with AsyncClient(transport=transport, base_url="http://test") as ac:
+        yield ac

llm-gateway/tests/integration/__init__.py

@@ -0,0 +1 @@
+# integration module

llm-gateway/tests/integration/test_admin_api.py

@@ -0,0 +1,237 @@
+"""Tests for Admin API endpoints."""
+import pytest
+from httpx import AsyncClient
+
+
+class TestProviderAPI:
+    """Test Provider management API."""
+
+    @pytest.mark.asyncio
+    async def test_create_provider(self, client: AsyncClient, setup_test_db):
+        """Test creating a provider."""
+        response = await client.post(
+            "/admin/providers",
+            json={
+                "name": "openai",
+                "api_base": "https://api.openai.com/v1",
+                "api_key": "test-api-key-1234567890",
+                "api_version": "v1",
+                "rpm_limit": 1000,
+                "tpm_limit": 100000,
+            },
+        )
+        assert response.status_code == 201
+        data = response.json()
+        assert data["name"] == "openai"
+        assert data["api_base"] == "https://api.openai.com/v1"
+        assert data["health_status"] == "healthy"
+
+    @pytest.mark.asyncio
+    async def test_list_providers(self, client: AsyncClient, setup_test_db):
+        """Test listing providers."""
+        # Create a provider first
+        await client.post(
+            "/admin/providers",
+            json={
+                "name": "anthropic",
+                "api_base": "https://api.anthropic.com",
+                "api_key": "test-key",
+            },
+        )
+
+        response = await client.get("/admin/providers")
+        assert response.status_code == 200
+        data = response.json()
+        assert data["total"] >= 1
+        assert len(data["providers"]) >= 1
+
+    @pytest.mark.asyncio
+    async def test_get_provider(self, client: AsyncClient, setup_test_db):
+        """Test getting a specific provider."""
+        create_response = await client.post(
+            "/admin/providers",
+            json={
+                "name": "gemini",
+                "api_base": "https://generativelanguage.googleapis.com",
+                "api_key": "test-key",
+            },
+        )
+        provider_id = create_response.json()["id"]
+
+        response = await client.get(f"/admin/providers/{provider_id}")
+        assert response.status_code == 200
+        data = response.json()
+        assert data["name"] == "gemini"
+
+    @pytest.mark.asyncio
+    async def test_update_provider(self, client: AsyncClient, setup_test_db):
+        """Test updating a provider."""
+        create_response = await client.post(
+            "/admin/providers",
+            json={
+                "name": "azure",
+                "api_base": "https://example.openai.azure.com",
+                "api_key": "test-key",
+            },
+        )
+        provider_id = create_response.json()["id"]
+
+        response = await client.put(
+            f"/admin/providers/{provider_id}",
+            json={"rpm_limit": 500, "enabled": False},
+        )
+        assert response.status_code == 200
+        data = response.json()
+        assert data["rpm_limit"] == 500
+        assert data["enabled"] is False
+
+    @pytest.mark.asyncio
+    async def test_delete_provider(self, client: AsyncClient, setup_test_db):
+        """Test deleting a provider."""
+        create_response = await client.post(
+            "/admin/providers",
+            json={
+                "name": "bedrock",
+                "api_base": "https://bedrock.us-east-1.amazonaws.com",
+                "api_key": "test-key",
+            },
+        )
+        provider_id = create_response.json()["id"]
+
+        response = await client.delete(f"/admin/providers/{provider_id}")
+        assert response.status_code == 204
+
+        # Verify it's deleted
+        get_response = await client.get(f"/admin/providers/{provider_id}")
+        assert get_response.status_code == 404
+
+
+class TestProjectAPI:
+    """Test Project management API."""
+
+    @pytest.mark.asyncio
+    async def test_create_project(self, client: AsyncClient, setup_test_db):
+        """Test creating a project."""
+        response = await client.post(
+            "/admin/projects",
+            json={
+                "name": "Test Project",
+                "description": "A test project",
+                "budget_limit": 100.00,
+                "budget_period": "monthly",
+            },
+        )
+        assert response.status_code == 201
+        data = response.json()
+        assert data["name"] == "Test Project"
+        assert data["budget_limit"] == "100.00"
+
+    @pytest.mark.asyncio
+    async def test_list_projects(self, client: AsyncClient, setup_test_db):
+        """Test listing projects."""
+        await client.post(
+            "/admin/projects",
+            json={"name": "Project 1"},
+        )
+
+        response = await client.get("/admin/projects")
+        assert response.status_code == 200
+        data = response.json()
+        assert data["total"] >= 1
+
+
+class TestAPIKeyAPI:
+    """Test API Key management API."""
+
+    @pytest.mark.asyncio
+    async def test_create_api_key(self, client: AsyncClient, setup_test_db):
+        """Test creating an API key."""
+        response = await client.post(
+            "/admin/keys",
+            json={
+                "name": "Test Key",
+                "prefix": "sk-test",
+                "rpm_limit": 100,
+                "tpm_limit": 10000,
+            },
+        )
+        assert response.status_code == 201
+        data = response.json()
+        assert data["name"] == "Test Key"
+        assert "key" in data  # Full key shown on creation
+        assert data["key"].startswith("sk-test_")
+        assert data["key_prefix"].startswith("sk-test_")
+
+    @pytest.mark.asyncio
+    async def test_list_api_keys(self, client: AsyncClient, setup_test_db):
+        """Test listing API keys."""
+        await client.post(
+            "/admin/keys",
+            json={"name": "Key 1"},
+        )
+
+        response = await client.get("/admin/keys")
+        assert response.status_code == 200
+        data = response.json()
+        assert data["total"] >= 1
+
+
+class TestModelAliasAPI:
+    """Test Model Alias management API."""
+
+    @pytest.mark.asyncio
+    async def test_create_model_alias(self, client: AsyncClient, setup_test_db):
+        """Test creating a model alias."""
+        response = await client.post(
+            "/admin/models/aliases",
+            json={
+                "alias": "gpt-4",
+                "provider": "openai",
+                "model": "gpt-4-turbo",
+                "input_price_per_1k": 0.01,
+                "output_price_per_1k": 0.03,
+            },
+        )
+        assert response.status_code == 201
+        data = response.json()
+        assert data["alias"] == "gpt-4"
+        assert data["provider"] == "openai"
+        assert data["model"] == "gpt-4-turbo"
+
+    @pytest.mark.asyncio
+    async def test_list_model_aliases(self, client: AsyncClient, setup_test_db):
+        """Test listing model aliases."""
+        await client.post(
+            "/admin/models/aliases",
+            json={
+                "alias": "claude",
+                "provider": "anthropic",
+                "model": "claude-3-sonnet",
+            },
+        )
+
+        response = await client.get("/admin/models/aliases")
+        assert response.status_code == 200
+        data = response.json()
+        assert data["total"] >= 1
+
+
+class TestHealthAPI:
+    """Test Health check API."""
+
+    @pytest.mark.asyncio
+    async def test_health_check(self, client: AsyncClient, setup_test_db):
+        """Test health check endpoint."""
+        response = await client.get("/health")
+        assert response.status_code == 200
+        data = response.json()
+        assert data["status"] == "healthy"
+
+    @pytest.mark.asyncio
+    async def test_readiness_check(self, client: AsyncClient, setup_test_db):
+        """Test readiness check endpoint."""
+        response = await client.get("/ready")
+        assert response.status_code == 200
+        data = response.json()
+        assert data["status"] == "ready"
+        assert data["database"] == "connected"

llm-gateway/tests/unit/__init__.py

@@ -0,0 +1 @@
+# unit module

llm-gateway/tests/unit/test_config.py

@@ -0,0 +1,44 @@
+"""Tests for configuration module."""
+import os
+import pytest
+from pathlib import Path
+
+from app.config import Settings
+
+
+class TestSettings:
+    """Test configuration settings."""
+
+    def test_default_settings(self, tmp_path: Path, monkeypatch: pytest.MonkeyPatch):
+        """Test default configuration values."""
+        # Change to temp directory for database path
+        monkeypatch.chdir(tmp_path)
+
+        settings = Settings()
+
+        assert settings.app_name == "LLM Gateway"
+        assert settings.debug is False
+        assert settings.database_url.startswith("sqlite:///")
+        assert settings.master_key is not None
+
+    def test_custom_settings_from_env(self, tmp_path: Path, monkeypatch: pytest.MonkeyPatch):
+        """Test loading settings from environment variables."""
+        monkeypatch.chdir(tmp_path)
+        monkeypatch.setenv("APP_NAME", "Custom Gateway")
+        monkeypatch.setenv("DEBUG", "true")
+        monkeypatch.setenv("DATABASE_URL", "sqlite:///custom.db")
+        monkeypatch.setenv("MASTER_KEY", "test-master-key-12345678901234567890")  # 40 chars
+
+        settings = Settings()
+
+        assert settings.app_name == "Custom Gateway"
+        assert settings.debug is True
+        assert settings.database_url == "sqlite:///custom.db"
+        assert settings.master_key == "test-master-key-12345678901234567890"
+
+    def test_generate_master_key(self):
+        """Test master key generation."""
+        key = Settings.generate_master_key()
+
+        assert len(key) == 64  # 32 bytes = 64 hex chars
+        assert isinstance(key, str)

llm-gateway/tests/unit/test_database.py

@@ -0,0 +1,34 @@
+"""Tests for database module."""
+import pytest
+
+from app.db.database import init_db, get_db
+from app.models import Provider, APIKey, Project
+
+
+class TestDatabase:
+    """Test database initialization and connections."""
+
+    @pytest.mark.asyncio
+    async def test_init_db_creates_tables(self, db_session):
+        """Test that init_db creates all required tables."""
+        # Tables should exist if we got a session
+        assert db_session is not None
+
+        # Try to query each table
+        from sqlalchemy import text
+
+        result = await db_session.execute(text("SELECT name FROM sqlite_master WHERE type='table'"))
+        tables = [row[0] for row in result.fetchall()]
+
+        assert "providers" in tables
+        assert "api_keys" in tables
+        assert "projects" in tables
+        assert "model_aliases" in tables
+        assert "request_logs" in tables
+
+    @pytest.mark.asyncio
+    async def test_get_db_returns_session(self, setup_test_db):
+        """Test that get_db returns a valid database session."""
+        async for session in get_db():
+            assert session is not None
+            break