---
title: (Deprecated) Query Engines + Pydantic Outputs | Developer Documentation
---

Tip

This guide references a deprecated method of extracting structured outputs in a RAG workflow. Check out our [structured output starter guide](/python/examples/structured_outputs/structured_outputs/index.md) for more details.

Using `index.as_query_engine()` and it’s underlying `RetrieverQueryEngine`, we can support structured pydantic outputs without an additional LLM calls (in contrast to a typical output parser.)

Every query engine has support for integrated structured responses using the following `response_mode`s in `RetrieverQueryEngine`:

- `refine`
- `compact`
- `tree_summarize`
- `accumulate` (beta, requires extra parsing to convert to objects)
- `compact_accumulate` (beta, requires extra parsing to convert to objects)

Under the hood, this uses `OpenAIPydanitcProgam` or `LLMTextCompletionProgram` depending on which LLM you’ve setup. If there are intermediate LLM responses (i.e. during `refine` or `tree_summarize` with multiple LLM calls), the pydantic object is injected into the next LLM prompt as a JSON object.

## Usage Pattern

First, you need to define the object you want to extract.

```
from typing import List
from pydantic import BaseModel




class Biography(BaseModel):
    """Data model for a biography."""


    name: str
    best_known_for: List[str]
    extra_info: str
```

Then, you create your query engine.

```
query_engine = index.as_query_engine(
    response_mode="tree_summarize", output_cls=Biography
)
```

Lastly, you can get a response and inspect the output.

```
response = query_engine.query("Who is Paul Graham?")


print(response.name)
# > 'Paul Graham'
print(response.best_known_for)
# > ['working on Bel', 'co-founding Viaweb', 'creating the programming language Arc']
print(response.extra_info)
# > "Paul Graham is a computer scientist, entrepreneur, and writer. He is best known      for ..."
```

## Modules

Detailed usage is available in the notebooks below:

- [Structured Outputs with a Query Engine](/python/examples/query_engine/pydantic_query_engine/index.md)
- [Structured Outputs with a Tree Summarize](/python/examples/response_synthesizers/pydantic_tree_summarize/index.md)