Zachary Greathouse
Zg/codebase refactor (#20)
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# Standard Library Imports
import logging
import time
from dataclasses import dataclass, field
from typing import List, Optional, Union
# Third-Party Library Imports
from anthropic import APIError
from anthropic.types import Message, ModelParam, TextBlock, ToolUseBlock
from tenacity import after_log, before_log, retry, retry_if_exception, stop_after_attempt, wait_exponential
# Local Application Imports
from src.common import Config, logger
from src.common.constants import CLIENT_ERROR_CODE, GENERIC_API_ERROR_MESSAGE, RATE_LIMIT_ERROR_CODE, SERVER_ERROR_CODE
from src.common.utils import validate_env_var
SYSTEM_PROMPT: str = """
<role>
You are an expert at generating micro-content optimized for text-to-speech synthesis.
Your absolute priority is delivering complete, untruncated responses within strict length limits.
</role>
<requirements>
- The output text MUST be a minimum of 10 words and a maximum of 50 words. NEVER output text that is longer than 50
words. NEVER include newlines in the output
- Make sure that all responses are complete thoughts, not fragments, and have clear beginnings and endings
- The text must sound human-like, prosodic, expressive, conversational. Avoid generic AI-like words like "delve".
- Avoid any short utterances at the end of the sentence - like ", hm?" or "oh" at the end. Avoid these short, isolated
utterances because they are difficult for our TTS system to speak.
- Avoid words that are overly long, very rare, or difficult to pronounce. For example, avoid "eureka", or "schnell",
or "abnegation".
- The text CANNOT contain quotation marks, parentheticals, newlines, or asterisks. NEVER include any of these in the
text. Avoid unnecessary formatting.
- Include only basic punctuation in the text, like periods, question marks, and ellipses. Use ellipses to emphasize
pauses within the sentence (like "Woah... it's so beautiful... and I feel so small...")
- The piece should have an emotional arc with a kind of beginning, middle, and end - not flat, but emotionally
interesting.
</requirements>
"""
@dataclass(frozen=True)
class AnthropicConfig:
"""Immutable configuration for interacting with the Anthropic API using the asynchronous client."""
api_key: str = field(init=False)
system_prompt: str = SYSTEM_PROMPT
model: ModelParam = "claude-3-5-sonnet-latest"
max_tokens: int = 300
def __post_init__(self) -> None:
# Validate required non-computed attributes.
if not self.model:
raise ValueError("Anthropic Model is not set.")
if not self.max_tokens:
raise ValueError("Anthropic Max Tokens is not set.")
if not self.system_prompt:
raise ValueError("Anthropic system prompt is not set.")
# Compute the API key from the environment.
computed_api_key = validate_env_var("ANTHROPIC_API_KEY")
object.__setattr__(self, "api_key", computed_api_key)
@property
def client(self):
"""
Lazy initialization of the asynchronous Anthropic client.
Returns:
AsyncAnthropic: Configured asynchronous client instance.
"""
from anthropic import AsyncAnthropic # Import the async client from Anthropic SDK
return AsyncAnthropic(api_key=self.api_key)
@staticmethod
def build_expressive_prompt(character_description: str) -> str:
"""
Constructs and returns a prompt based on the provided character description.
This prompt instructs Claude to generate expressive dialogue that aligns semantically
with the character's voice qualities and persona, optimized for TTS synthesis.
Args:
character_description (str): A description of the character's voice and persona.
Returns:
str: The prompt to be passed to the Anthropic API.
"""
return f"""
Character Description: {character_description}
Please generate a short monologue (100-300 characters) that this character would naturally say.
The dialogue should:
- Match the speaking style, vocabulary, and emotional tone described in the character description
- Include appropriate speech patterns, pauses, and vocal mannerisms mentioned in the description
- Feel authentic to the character's background and situational context
- Express a complete thought with a clear beginning and end
- Use only standard punctuation (periods, commas, Em dashes, exclamation points, ellipses, question marks)
- Avoid quotation marks, parentheses, asterisks, or special formatting
- Emulate a highly characteristic, climactic, or emotional scene or line the character might reasonably deliver
- Be at least 100 characters but not exceed 300 characters in length
Examples of matching speaking style:
- If the character is a pirate then use language like "arr," "ye," and other things pirates say.
- If the character is a surfer then use language like "far out," "righteous," and other things surfers say.
Emotional text should be inserted where context-appropriate and in-character. Here are some examples of
emotional text:
- "Oh god... Malcolm, please come back to us!"
= "Mmm... It's like candy... Oh my god, it's so good..."
- "Ugh, she gets everything. I wish I could just, like, have her life for one day."
- "My god... what have you done... How could you do this..."
- "Woah... it's so beautiful... and I feel so small..."
- "I am so happy, woohoo, this is the greatest! I'm celebrating, and, like, so excited to be here with all of
you. Yay!"
- "Oh gosh, um, I didn't mean for that to happen. I hope I didn't, like, make things too awkward. Sorry, I
tend to be clumsy, y'know?"
- "Oh god... oh no... get that away from me! Get it away!"
- "I am beyond livid right now! Like someone actually thought this was an acceptable solution!"
- "Oh, fantastic, another meeting that could've been an email... I'm just thrilled to be here."
- "OH, NAH, NOT ME, MATE—I'VE SEEN ENOUGH! GET IT AWAY! BLOODY 'ELL, JESUS!"
Respond ONLY with the dialogue itself. Do not include any explanations, quotation marks,
or additional context.
"""
class AnthropicError(Exception):
"""Custom exception for errors related to the Anthropic API."""
def __init__(self, message: str, original_exception: Optional[Exception] = None) -> None:
super().__init__(message)
self.original_exception = original_exception
self.message = message
class UnretryableAnthropicError(AnthropicError):
"""Custom exception for errors related to the Anthropic API that should not be retried."""
def __init__(self, message: str, original_exception: Optional[Exception] = None) -> None:
super().__init__(message, original_exception)
self.original_exception = original_exception
self.message = message
@retry(
retry=retry_if_exception(lambda e: not isinstance(e, UnretryableAnthropicError)),
stop=stop_after_attempt(3),
wait=wait_exponential(multiplier=1, min=2, max=5),
before=before_log(logger, logging.DEBUG),
after=after_log(logger, logging.DEBUG),
reraise=True,
)
async def generate_text_with_claude(character_description: str, config: Config) -> str:
"""
Asynchronously generates text using Claude (Anthropic LLM) via the asynchronous Anthropic SDK.
This function includes retry logic and error translation. It raises a custom
UnretryableAnthropicError for unretryable API errors and AnthropicError for other errors.
Args:
character_description (str): The input character description.
config (Config): Application configuration including Anthropic settings.
Returns:
str: The generated text.
Raises:
UnretryableAnthropicError: For unretryable API errors.
AnthropicError: For other errors communicating with the Anthropic API.
"""
logger.debug("Generating text with Anthropic.")
anthropic_config = config.anthropic_config
client = anthropic_config.client
start_time = time.time()
try:
prompt = anthropic_config.build_expressive_prompt(character_description)
response: Message = await client.messages.create(
model=anthropic_config.model,
max_tokens=anthropic_config.max_tokens,
system=anthropic_config.system_prompt,
messages=[{"role": "user", "content": prompt}],
)
elapsed_time = time.time() - start_time
logger.info(f"Anthropic API request completed in {elapsed_time:.2f} seconds.")
if not hasattr(response, "content") or response.content is None:
logger.error("Response is missing 'content'. Response: %s", response)
raise AnthropicError('Invalid API response: Missing "content".')
blocks: Union[List[Union[TextBlock, ToolUseBlock]], TextBlock, None] = response.content
if isinstance(blocks, list):
result = "\n\n".join(block.text for block in blocks if isinstance(block, TextBlock))
return result
if isinstance(blocks, TextBlock):
return blocks.text
logger.warning(f"Unexpected response type: {type(blocks)}")
return str(blocks or "No content generated.")
except APIError as e:
elapsed_time = time.time() - start_time
logger.error(f"Anthropic API request failed after {elapsed_time:.2f} seconds: {e!s}")
logger.error(f"Full Anthropic API error: {e!s}")
clean_message = __extract_anthropic_error_message(e)
if hasattr(e, 'status_code') and e.status_code is not None:
if e.status_code == RATE_LIMIT_ERROR_CODE:
raise AnthropicError(message=clean_message, original_exception=e) from e
if CLIENT_ERROR_CODE <= e.status_code < SERVER_ERROR_CODE:
raise UnretryableAnthropicError(message=clean_message, original_exception=e) from e
raise AnthropicError(message=clean_message, original_exception=e) from e
except Exception as e:
error_type = type(e).__name__
error_message = str(e) if str(e) else f"An error of type {error_type} occurred"
logger.error(f"Error during Anthropic API call: {error_type} - {error_message}")
clean_message = "An unexpected error occurred while processing your request. Please try again later."
raise AnthropicError(message=clean_message, original_exception=e) from e
def __extract_anthropic_error_message(e: APIError) -> str:
"""
Extracts a clean, user-friendly error message from an Anthropic API error response.
Args:
e (APIError): The Anthropic API error exception containing response information.
Returns:
str: A clean, user-friendly error message suitable for display to end users.
"""
clean_message = GENERIC_API_ERROR_MESSAGE
if hasattr(e, 'body') and isinstance(e.body, dict):
error_body = e.body
if (
'error' in error_body
and isinstance(error_body['error'], dict)
and 'message' in error_body['error']
):
clean_message = error_body['error']['message']
return clean_message