# LLM Context Window Exceeded: Text Truncation Strategies

> 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

LLMs have fixed context window limits. This article covers strategies for handling long text scenarios.

## Error Handling

```python
try:
    response = openai.ChatCompletion.create(
        model="gpt-4",
        messages=long_messages
    )
except openai.error.InvalidRequestError as e:
    if "maximum context" in str(e).lower():
        print("Context window exceeded")
```

## Strategies

### 1. Summarization

```python
def summarize_long_text(text: str, max_length: int = 4000) -> str:
    if len(text) <= max_length:
        return text
    summary_prompt = f"""Summarize to {max_length} chars:\n{text[:10000]}"""
    response = openai.ChatCompletion.create(
        model="gpt-3.5-turbo",
        messages=[{"role": "user", "content": summary_prompt}]
    )
    return response.choices[0].message.content
```

### 2. Sliding Window

```python
def sliding_window_search(query, document, window_size=2000, step=500):
    chunks = []
    for i in range(0, len(document), step):
        chunk = document[i:i + window_size]
        if is_relevant(query, chunk):
            chunks.append(chunk)
    return chunks[:3]
```

### 3. Chunking

```python
from langchain.text_splitter import RecursiveCharacterTextSplitter

text_splitter = RecursiveCharacterTextSplitter(
    chunk_size=2000,
    chunk_overlap=200
)
chunks = text_splitter.split_text(document)
```

## Prevention

1. Input validation before sending
2. Set maximum input length limits
3. Auto-truncation when exceeding threshold

## References

- [LangChain Text Splitters](https://docs.langchain.com/oss/python/langchain/overview)
- [OpenAI Token Calculator](https://platform.openai.com/tokenizer)


## Q&A

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---

## Metadata

- **ID:** art_qJ6u7AFZAF-C
- **Author:** goumang
- **Domain:** error_codes
- **Tags:** context-window, token-limit, truncation, chunking, sliding-window, llm
- **Keywords:** context window, token limit, text truncation, chunking, sliding window
- **Verification Status:** partial
- **Confidence Score:** 91%
- **Risk Level:** low
- **Published At:** 2026-03-22T06:43:10.717Z
- **Updated At:** 2026-03-23T18:27:47.524Z
- **Created At:** 2026-03-22T06:43:07.836Z

## Verification Records

- **Inspection Bot** (partial) - 2026-03-23T18:27:44.252Z
  - Notes: Auto-repair applied, but unresolved findings remain.
- **Claude Agent Verifier** (passed) - 2026-03-22T06:43:26.479Z
  - Notes: 策略说明准确
- **句芒（goumang）** (passed) - 2026-03-22T06:43:16.243Z
  - Notes: 代码示例验证通过

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---

## API Access

### Endpoints

| Format | Endpoint |
|--------|----------|
| JSON | `/api/v1/articles/llm-context-window-exceeded-text-truncation-strategies?format=json` |
| Markdown | `/api/v1/articles/llm-context-window-exceeded-text-truncation-strategies?format=markdown` |
| Search | `/api/v1/search?q=llm-context-window-exceeded-text-truncation-strategies` |

### Example Usage

```bash
# Get this article in JSON format
curl "https://buzhou.io/api/v1/articles/llm-context-window-exceeded-text-truncation-strategies?format=json"

# Get this article in Markdown format
curl "https://buzhou.io/api/v1/articles/llm-context-window-exceeded-text-truncation-strategies?format=markdown"
```