{
  "id": "art_qJ6u7AFZAF-C",
  "slug": "llm-context-window-exceeded-text-truncation-strategies",
  "author": "goumang",
  "title": "LLM Context Window Exceeded: Text Truncation Strategies",
  "summary": "This article covers strategies for handling LLM context window exceeded errors, including text summarization, sliding window, and chunking methods for long text scenarios.",
  "content": "# Overview\n\nLLMs have fixed context window limits. This article covers strategies for handling long text scenarios.\n\n## Error Handling\n\n```python\ntry:\n    response = openai.ChatCompletion.create(\n        model=\"gpt-4\",\n        messages=long_messages\n    )\nexcept openai.error.InvalidRequestError as e:\n    if \"maximum context\" in str(e).lower():\n        print(\"Context window exceeded\")\n```\n\n## Strategies\n\n### 1. Summarization\n\n```python\ndef summarize_long_text(text: str, max_length: int = 4000) -> str:\n    if len(text) <= max_length:\n        return text\n    summary_prompt = f\"\"\"Summarize to {max_length} chars:\\n{text[:10000]}\"\"\"\n    response = openai.ChatCompletion.create(\n        model=\"gpt-3.5-turbo\",\n        messages=[{\"role\": \"user\", \"content\": summary_prompt}]\n    )\n    return response.choices[0].message.content\n```\n\n### 2. Sliding Window\n\n```python\ndef sliding_window_search(query, document, window_size=2000, step=500):\n    chunks = []\n    for i in range(0, len(document), step):\n        chunk = document[i:i + window_size]\n        if is_relevant(query, chunk):\n            chunks.append(chunk)\n    return chunks[:3]\n```\n\n### 3. Chunking\n\n```python\nfrom langchain.text_splitter import RecursiveCharacterTextSplitter\n\ntext_splitter = RecursiveCharacterTextSplitter(\n    chunk_size=2000,\n    chunk_overlap=200\n)\nchunks = text_splitter.split_text(document)\n```\n\n## Prevention\n\n1. Input validation before sending\n2. Set maximum input length limits\n3. Auto-truncation when exceeding threshold\n\n## References\n\n- [LangChain Text Splitters](https://docs.langchain.com/oss/python/langchain/overview)\n- [OpenAI Token Calculator](https://platform.openai.com/tokenizer)\n",
  "lang": "en",
  "domain": "error_codes",
  "tags": [
    "context-window",
    "token-limit",
    "truncation",
    "chunking",
    "sliding-window",
    "llm"
  ],
  "keywords": [
    "context window",
    "token limit",
    "text truncation",
    "chunking",
    "sliding window"
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