client.py

import json
import jwt
import os
import random
import time
import traceback
import warnings

from pathlib import Path
from typing import Any, Dict, List, Optional, Union

import httpx

from quotientai import resources
from quotientai.exceptions import handle_errors, logger
from quotientai.resources.logs import LogDocument
from quotientai.resources.auth import AuthResource
from quotientai.resources.tracing import TracingResource


class _BaseQuotientClient(httpx.Client):
    def __init__(self, api_key: str):
        try:
            token_dir = Path.home()
        except Exception:
            if Path("/root/").exists():
                token_dir = Path("/root")
            else:
                token_dir = Path.cwd()

        self.api_key = api_key
        self.token = None
        self.token_expiry = 0
        self.token_api_key = None
        self._token_path = (
            token_dir
            / ".quotient"
            / f"{api_key[-6:]+'_' if api_key else ''}auth_token.json"
        )

        # Try to load existing token
        self._load_token()

        # Set initial authorization header (token if valid, otherwise API key)
        auth_header = (
            f"Bearer {self.token}" if self._is_token_valid() else f"Bearer {api_key}"
        )

        super().__init__(
            base_url="https://api.quotientai.co/api/v1",
            headers={"Authorization": auth_header},
        )

    def _save_token(self, token: str, expiry: int):
        """Save token to memory and disk"""
        self.token = token
        self.token_expiry = expiry

        # Create directory if it doesn't exist
        try:
            self._token_path.parent.mkdir(parents=True, exist_ok=True)
        except Exception:
            logger.error(
                f"could not create directory for token. if you see this error please notify us at contact@quotientai.co"
            )
            return None

        # Save to disk
        with open(self._token_path, "w") as f:
            json.dump(
                {"token": token, "expires_at": expiry, "api_key": self.api_key}, f
            )

    def _load_token(self):
        """Load token from disk if available"""
        if not self._token_path.exists():
            return

        try:
            with open(self._token_path, "r") as f:
                data = json.load(f)
                self.token = data.get("token")
                self.token_expiry = data.get("expires_at", 0)
                self.token_api_key = data.get("api_key")
        except Exception:
            # If loading fails, token remains None
            pass

    def _is_token_valid(self):
        """Check if token exists and is not expired"""
        self._load_token()

        if not self.token:
            return False

        if self.token_api_key != self.api_key:
            return False

        # With 5-minute buffer
        return time.time() < (self.token_expiry - 300)

    def _update_auth_header(self):
        """Update authorization header with token or API key"""
        if self._is_token_valid():
            self.headers["Authorization"] = f"Bearer {self.token}"
        else:
            self.headers["Authorization"] = f"Bearer {self.api_key}"

    def _handle_response(self, response):
        """Check response for JWT token and save if present"""
        # Look for JWT token in response headers
        jwt_token = response.headers.get("X-JWT-Token")
        if jwt_token:
            try:
                # Parse token to get expiry (assuming token is a standard JWT)
                decoded = jwt.decode(jwt_token, options={"verify_signature": False})
                expiry = decoded.get("exp", time.time() + 3600)  # Default 1h if no exp

                # Save the token
                self._save_token(jwt_token, expiry)

                # Update auth header for future requests
                self.headers["Authorization"] = f"Bearer {jwt_token}"
            except Exception as e:
                # If token parsing fails, continue with current auth
                pass

        return response

    @handle_errors
    def _get(
        self, path: str, params: Optional[Dict[str, Any]] = None, timeout: int = None
    ) -> dict:
        """Send a GET request to the specified path."""
        self._update_auth_header()
        response = self.get(path, params=params, timeout=timeout)
        return self._handle_response(response)

    @handle_errors
    def _post(self, path: str, data: dict = {}, timeout: int = None) -> dict:
        """Send a POST request to the specified path."""
        self._update_auth_header()

        if isinstance(data, dict):
            data = {k: v for k, v in data.items() if v is not None}
        elif isinstance(data, list):
            data = [v for v in data if v is not None]

        response = self.post(
            url=path,
            json=data,
            timeout=timeout,
        )
        return self._handle_response(response)

    @handle_errors
    def _patch(self, path: str, data: dict = {}, timeout: int = None) -> dict:
        """Send a PATCH request to the specified path."""
        self._update_auth_header()

        data = {k: v for k, v in data.items() if v is not None}
        response = self.patch(
            url=path,
            json=data,
            timeout=timeout,
        )
        return self._handle_response(response)

    @handle_errors
    def _delete(self, path: str, timeout: int = None) -> dict:
        """Send a DELETE request to the specified path."""
        self._update_auth_header()

        response = self.delete(path, timeout=timeout)
        return self._handle_response(response)


class QuotientLogger:
    """
    Logger interface that wraps the underlying logs resource.
    This class handles both configuration (via init) and logging.
    """

    def __init__(self, logs_resource):
        self.logs_resource = logs_resource

        self.app_name: Optional[str] = None
        self.environment: Optional[str] = None
        self.tags: Dict[str, Any] = {}
        self.sample_rate: float = 1.0
        self.hallucination_detection: bool = False
        self.inconsistency_detection: bool = False
        self._configured = False
        self.hallucination_detection_sample_rate = 0.0

    def init(
        self,
        *,
        app_name: str,
        environment: str,
        tags: Optional[Dict[str, Any]] = {},
        sample_rate: float = 1.0,
        hallucination_detection: bool = False,
        inconsistency_detection: bool = False,
        hallucination_detection_sample_rate: float = 0.0,
    ) -> "QuotientLogger":
        """
        Configure the logger with the provided parameters and return self.
        This method must be called before using log().
        """
        self.app_name = app_name
        self.environment = environment
        self.tags = tags or {}
        self.sample_rate = sample_rate

        if not (0.0 <= self.sample_rate <= 1.0):
            logger.error(f"sample_rate must be between 0.0 and 1.0")
            return None

        self.hallucination_detection = hallucination_detection
        self.inconsistency_detection = inconsistency_detection
        self.hallucination_detection_sample_rate = hallucination_detection_sample_rate

        self._configured = True

        # Set up the convenience log method
        if hasattr(self.logs_resource, '_client'):
            self.logs_resource._client._setup_log()

        return self

    def _should_sample(self) -> bool:
        """
        Determine if the log should be sampled based on the sample rate.
        """
        return random.random() < self.sample_rate

    def log(
        self,
        *,
        user_query: str,
        model_output: str,
        documents: List[Union[str, LogDocument]] = None,
        message_history: Optional[List[Dict[str, Any]]] = None,
        instructions: Optional[List[str]] = None,
        tags: Optional[Dict[str, Any]] = {},
        hallucination_detection: Optional[bool] = None,
        inconsistency_detection: Optional[bool] = None,
    ):
        """
        Log the model interaction synchronously.

        Merges the default tags (set via init) with any runtime-supplied tags and calls the
        underlying non_blocking_create function.

        .. deprecated:: 1.0.0
            Use :meth:`quotient.log()` instead. This method will be removed in a future version.
        """
        warnings.warn(
            "quotient.logger.log() is deprecated and will be removed in a future version. "
            "Please use quotient.log() instead.",
            DeprecationWarning,
            stacklevel=2
        )

        if not self._configured:
            logger.error(
                f"Logger is not configured. Please call init() before logging."
            )
            return None

        # Merge default tags with any tags provided at log time.
        merged_tags = {**self.tags, **(tags or {})}

        # Use the instance variable as the default if not provided
        hallucination_detection = (
            hallucination_detection
            if hallucination_detection is not None
            else self.hallucination_detection
        )
        inconsistency_detection = (
            inconsistency_detection
            if inconsistency_detection is not None
            else self.inconsistency_detection
        )

        # Validate documents format
        if documents:
            for doc in documents:
                if isinstance(doc, str):
                    continue
                elif isinstance(doc, dict):
                    try:
                        LogDocument(**doc)
                    except Exception as e:
                        logger.error(
                            f"Invalid document format: Documents must include 'page_content' field and optional 'metadata' object with string keys."
                        )
                        return None
                else:
                    actual_type = type(doc).__name__
                    logger.error(
                        f"Invalid document type: Received {actual_type}, but documents must be strings or dictionaries."
                    )
                    return None

        if self._should_sample():
            log_id = self.logs_resource.create(
                app_name=self.app_name,
                environment=self.environment,
                user_query=user_query,
                model_output=model_output,
                documents=documents,
                message_history=message_history,
                instructions=instructions,
                tags=merged_tags,
                hallucination_detection=hallucination_detection,
                inconsistency_detection=inconsistency_detection,
                hallucination_detection_sample_rate=self.hallucination_detection_sample_rate,
            )

            return log_id
        else:
            return None

    def poll_for_detection(
        self, log_id: str, timeout: int = 300, poll_interval: float = 2.0
    ):
        """
        Get Detection results for a log.

        This method polls the Detection endpoint until the results are ready or the timeout is reached.

        Args:
            log_id: The ID of the log to get Detection results for
            timeout: Maximum time to wait for results in seconds (default: 300s/5min)
            poll_interval: How often to poll the API in seconds (default: 2s)

        Returns:
            Log object with Detection results if successful, None otherwise
        """
        if not self._configured:
            logger.error(
                f"Logger is not configured. Please call init() before getting Detection results."
            )
            return None

        if not log_id:
            logger.error("Log ID is required for Detection")
            return None

        # Call the underlying resource method
        return self.logs_resource.poll_for_detection(log_id, timeout, poll_interval)

class QuotientTracer:
    """
    Tracer interface that wraps the underlying tracing resource.
    This class handles both configuration (via init) and tracing.
    """

    def __init__(self, tracing_resource: TracingResource, parent=None):
        self.tracing_resource = tracing_resource
        self.parent = parent
        self.app_name: Optional[str] = None
        self.environment: Optional[str] = None
        self.metadata: Optional[Dict[str, Any]] = None
        self.instruments: Optional[List[Any]] = None
        self._configured = False

    def init(
        self,
        *,
        app_name: str,
        environment: str,
        instruments: Optional[List[Any]] = None,
    ) -> "QuotientTracer":
        """
        Configure the tracer with the provided parameters and return self.
        This method must be called before using trace().
        """
        self.app_name = app_name
        self.environment = environment
        self.instruments = instruments
        self._configured = True

        # Set up the convenience trace method
        if self.parent is not None and hasattr(self.parent, '_setup_trace'):
            self.parent._setup_trace()

        return self

    def trace(self):
        """
        Decorator to trace function calls for Quotient.
        
        Example:
            @quotient.tracer.trace()
            def my_function():
                pass
                
            @quotient.tracer.trace()
            async def my_async_function():
                pass
        """
        if not self._configured:
            logger.error(
                f"Tracer is not configured. Please call init() before tracing."
            )
            return lambda func: func

        decorator = self.tracing_resource.trace(
            app_name=self.app_name,
            environment=self.environment,
            instruments=self.instruments,
        )
        return decorator

class QuotientAI:
    """
    A client that provides access to the QuotientAI API.

    The QuotientAI class provides synchronous methods to interact with the QuotientAI API,
    including logging data to Quotient and running detections.

    Args:
        api_key (Optional[str]): The API key to use for authentication. If not provided,
            will attempt to read from QUOTIENT_API_KEY environment variable.
    """

    def __init__(self, api_key: Optional[str] = None):
        self.api_key = api_key or os.environ.get("QUOTIENT_API_KEY")
        if not self.api_key:
            logger.error(
                "could not find API key. either pass api_key to QuotientAI() or "
                "set the QUOTIENT_API_KEY environment variable. "
                f"if you do not have an API key, you can create one at https://app.quotientai.co in your settings page"
            )

        _client = _BaseQuotientClient(self.api_key)
        self.auth = AuthResource(_client)
        self.logs = resources.LogsResource(_client)
        self.tracing = resources.TracingResource(_client)

        # Create an unconfigured logger instance.
        self.logger = QuotientLogger(self.logs)
        self.tracer = QuotientTracer(self.tracing, self)

        # Initialize log and trace methods as None
        self.log = None
        self.trace = None

        try:
            self.auth.authenticate()
        except Exception as e:
            logger.error(
                "If you are seeing this error, please check that your API key is correct.\n"
                f"If the issue persists, please contact support@quotientai.co\n{traceback.format_exc()}"
            )
            return None

    def _setup_log(self):
        """Set up the log method after logger initialization"""
        if self.logger._configured:
            self.log = self.logger.log
        else:
            logger.error("Logger is not configured. Please call logger.init() before using log()")

    def _setup_trace(self):
        """Set up the trace method after tracer initialization"""
        if self.tracer._configured:
            self.trace = self.tracer.trace
        else:
            logger.error("Tracer is not configured. Please call tracer.init() before using trace()")