# format_cortex_search_documents

> **Function** in `langchain_snowflake`

📖 [View in docs](https://reference.langchain.com/python/langchain-snowflake/formatters/format_cortex_search_documents)

Format documents from Snowflake Cortex Search for RAG usage.

This function extracts content from Cortex Search documents and formats them
into a single string suitable for use as context in RAG applications.

## Signature

```python
format_cortex_search_documents(
    docs: List[Document],
    content_field: str = 'TRANSCRIPT_TEXT',
    join_separator: str = '\n\n',
    fallback_to_page_content: bool = True,
) -> str
```

## Description

**Example:**

>>> from langchain_snowflake import SnowflakeCortexSearchRetriever, format_cortex_search_documents
>>> retriever = SnowflakeCortexSearchRetriever(...)
>>> docs = retriever.get_relevant_documents("query")
>>> context = format_cortex_search_documents(docs, content_field="CONTENT")

## Parameters

| Name | Type | Required | Description |
|------|------|----------|-------------|
| `docs` | `List[Document]` | Yes | List of Document objects from Cortex Search |
| `content_field` | `str` | No | Metadata field containing the main content (default: `'TRANSCRIPT_TEXT'`) |
| `join_separator` | `str` | No | String used to join multiple documents (default: `'\n\n'`) |
| `fallback_to_page_content` | `bool` | No | Whether to use page_content if content_field is missing (default: `True`) |

## Returns

`str`

Formatted string containing all document content

---

[View source on GitHub](https://github.com/langchain-ai/langchain-snowflake/blob/c7b3fc040db944acce19c2afb245c1735b9b63a2/libs/snowflake/langchain_snowflake/formatters.py#L17)