Spaces:
Running
Running
# 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> | |
""" | |
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) | |
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) | |
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 | |
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 | |