toon-troubleshooter 2025.12.22090741

Toon-troubleshooter identifies and solves Cartoon Network viewing issues via user input and structured responses.

toon-troubleshooter

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.

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📌 Features

• 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.).

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🚀 Installation

pip install toon_troubleshooter

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🔧 Usage Examples

Basic Usage (Default LLM7)

from 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)

Custom LLM Integration

Using OpenAI

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)

Using Anthropic

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)

Using Google Generative AI

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)

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⚙️ Parameters

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.

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🔑 API Key & Rate Limits

• 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")

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📝 Example Output

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."
    ]
  }
]

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📦 Dependencies

• llmatch-messages (for structured LLM responses)
• langchain-core (LLM abstraction)
• langchain_llm7 (default LLM provider)

Install dependencies automatically via pip install toon-troubleshooter.

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🐛 Issues & Support

Report bugs or feature requests: 🔗 GitHub Issues

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👤 Author

Eugene Evstafev (@chigwell) 📧 [e-mail]

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