A Python package designed to help Cartoon Network fans identify, categorize, and troubleshoot broadcast-related issues (1995–2025). Whether you're dealing with missing episodes, audio glitches, or unexpected interruptions, this tool provides structured solutions based on your input.
- Error Categorization: Identifies common Cartoon Network broadcast issues (e.g., missing episodes, audio cuts, re-airing delays).
- Root Cause Analysis: Explains possible reasons behind the problem (technical failures, scheduling conflicts, etc.).
- Solution Suggestions: Recommends fixes (e.g., checking re-airings, streaming alternatives, or contacting support).
- Flexible LLM Integration: Works with LLM7 (default) or any LangChain-compatible LLM (OpenAI, Anthropic, Google, etc.).
pip install toon_troubleshooterfrom toon_troubleshooter import toon_troubleshooter
# Example: User reports a missing episode
user_input = "My favorite Cartoon Network episode 'SpongeBob: The Camping Episode' was cut short last night."
response = toon_troubleshooter(user_input)
print(response)from langchain_openai import ChatOpenAI
from toon_troubleshooter import toon_troubleshooter
llm = ChatOpenAI(model="gpt-4")
response = toon_troubleshooter(user_input, llm=llm)
print(response)from langchain_anthropic import ChatAnthropic
from toon_troubleshooter import toon_troubleshooter
llm = ChatAnthropic(model="claude-2")
response = toon_troubleshooter(user_input, llm=llm)
print(response)from langchain_google_genai import ChatGoogleGenerativeAI
from toon_troubleshooter import toon_troubleshooter
llm = ChatGoogleGenerativeAI(model="gemini-pro")
response = toon_troubleshooter(user_input, llm=llm)
print(response)| Parameter | Type | Description |
|---|---|---|
user_input |
str |
Required. Description of the issue (e.g., missing episode, audio distortion). |
api_key |
Optional[str] |
Optional. LLM7 API key (defaults to LLM7_API_KEY env var). |
llm |
Optional[BaseChatModel] |
Optional. Custom LangChain LLM (e.g., ChatOpenAI, ChatAnthropic). Uses ChatLLM7 by default. |
- Default LLM: Uses LLM7 (free tier rate limits apply).
- Get a Free API Key: Register at LLM7.
- Pass Key via:
- Environment variable:
export LLM7_API_KEY="your_key" - Direct argument:
toon_troubleshooter(user_input, api_key="your_key")
- Environment variable:
For input:
"The Cartoon Network broadcast of 'Teen Titans Go!' was interrupted by a 5-minute commercial break in the middle of the episode."
Possible response:
[
{
"issue_type": "broadcast_interruption",
"possible_causes": ["technical glitch", "unscheduled ad insertion"],
"suggested_solutions": [
"Check for re-airings later in the day.",
"Try streaming the episode online (e.g., Boomerang app).",
"Report to Cartoon Network support if frequent."
]
}
]llmatch-messages(for structured LLM responses)langchain-core(LLM abstraction)langchain_llm7(default LLM provider)
Install dependencies automatically via pip install toon-troubleshooter.
Report bugs or feature requests: 🔗 GitHub Issues
Eugene Evstafev (@chigwell) 📧 hi@euegne.plus