"""
llm-connect — Pluggable LLM adapters.

Provides concrete :class:`LLMAdapter` implementations backed by
OpenRouter (HTTP), Gemini, OpenAI, and Claude Code CLI (subprocess).

Quick start::

    from llm_connect import create_adapter

    adapter = create_adapter("openrouter", model="anthropic/claude-sonnet-4")
    response = adapter.execute_prompt(prompt, run_config)
"""

from llm_connect.adapter import ErrorLLMAdapter, LLMAdapter, MockLLMAdapter
from llm_connect.claude_code import ClaudeCodeAdapter
from llm_connect.config import LLMConfig, load_config
from llm_connect.costs import CostEstimate, CostModel, estimate_cost
from llm_connect.embedding_adapter import EmbeddingAdapter
from llm_connect.embedding_cache import EmbeddingCache
from llm_connect.embedding_factory import create_embedding_adapter
from llm_connect.embedding_openai import OpenAICompatibleEmbeddingAdapter
from llm_connect.exceptions import (
    LLMAPIError,
    LLMBudgetExceededError,
    LLMConfigurationError,
    LLMError,
    LLMRateLimitError,
    LLMSubprocessError,
    LLMTimeoutError,
)
from llm_connect.factory import create_adapter
from llm_connect.gemini import GeminiAdapter
from llm_connect.grading import (
    BaselineGrader,
    EmbeddingSimilarityJudge,
    ExactMatchJudge,
    GradingResult,
    Judge,
    LLMJudge,
    PairedGrader,
)
from llm_connect.models import BudgetTracker, LLMResponse, RunConfig
from llm_connect.openai import OpenAIAdapter
from llm_connect.openrouter import OpenRouterAdapter
from llm_connect.problem_classes import (
    ChunkSummarizationProblemClass,
    EntityExtractionProblemClass,
    JudgeEvalProblemClass,
    Observation,
    ProblemClass,
    ProblemClassRegistry,
    RelationExtractionProblemClass,
    ReportSynthesisProblemClass,
    TokenEstimate,
    default_problem_class_registry,
)
from llm_connect.quality import QualityLedger, QualityObservation, is_stale
from llm_connect.rates import ModelRate, ModelRateRegistry
from llm_connect.routing import AdaptiveRoutingPolicy, RoutingPolicy, RoutingRule
from llm_connect.server import LLMServer
from llm_connect.shadowing import ShadowingAdapter
from llm_connect.similarity import (
    cosine_similarity,
    find_similar_pairs,
    similarity_matrix,
)

__all__ = [
    "RunConfig",
    "LLMResponse",
    "BudgetTracker",
    "LLMAdapter",
    "MockLLMAdapter",
    "ErrorLLMAdapter",
    "create_adapter",
    "OpenRouterAdapter",
    "ClaudeCodeAdapter",
    "GeminiAdapter",
    "OpenAIAdapter",
    "LLMConfig",
    "load_config",
    "LLMError",
    "LLMConfigurationError",
    "LLMAPIError",
    "LLMRateLimitError",
    "LLMTimeoutError",
    "LLMSubprocessError",
    "LLMBudgetExceededError",
    "EmbeddingAdapter",
    "OpenAICompatibleEmbeddingAdapter",
    "EmbeddingCache",
    "create_embedding_adapter",
    "QualityObservation",
    "QualityLedger",
    "is_stale",
    "GradingResult",
    "Judge",
    "BaselineGrader",
    "ExactMatchJudge",
    "EmbeddingSimilarityJudge",
    "LLMJudge",
    "PairedGrader",
    "cosine_similarity",
    "similarity_matrix",
    "find_similar_pairs",
    "RoutingPolicy",
    "RoutingRule",
    "AdaptiveRoutingPolicy",
    "ShadowingAdapter",
    "LLMServer",
    "ModelRate",
    "ModelRateRegistry",
    "CostEstimate",
    "CostModel",
    "estimate_cost",
    "TokenEstimate",
    "Observation",
    "ProblemClass",
    "ProblemClassRegistry",
    "default_problem_class_registry",
    "ChunkSummarizationProblemClass",
    "EntityExtractionProblemClass",
    "RelationExtractionProblemClass",
    "JudgeEvalProblemClass",
    "ReportSynthesisProblemClass",
]