structured output support

[xdevfaheem]

Does llamafile support response format argument like llamacpp to get structured output based on specified schema? would be very helpful if anyone can help me out, ASAP.

@jart

[aaqib-ahmed-nazir]

The ability of LLMs to produce structured outputs are important for downstream applications that rely on reliably parsing output values. LlamaIndex itself also relies on structured output in the following ways.

Document retrieval: Many data structures within LlamaIndex rely on LLM calls with a specific schema for Document retrieval. For instance, the tree index expects LLM calls to be in the format "ANSWER: (number)".
Response synthesis: Users may expect that the final response contains some degree of structure (e.g. a JSON output, a formatted SQL query, etc.)
LlamaIndex provides a variety of modules enabling LLMs to produce outputs in a structured format. By default, structured output is offered within our LLM classes. We also provide lower-level modules:

Pydantic Programs: These are generic modules that map an input prompt to a structured output, represented by a Pydantic object. They may use function calling APIs or text completion APIs + output parsers. These can also be integrated with query engines.
Pre-defined Pydantic Program: We have pre-defined Pydantic programs that map inputs to specific output types (like dataframes).
Output Parsers: These are modules that operate before and after an LLM text completion endpoint. They are not used with LLM function calling endpoints (since those contain structured outputs out of the box).
See the sections below for an overview of output parsers and Pydantic programs.

[xdevfaheem]

where did you plucked these from?

[aaqib-ahmed-nazir]

Source: https://docs.llamaindex.ai/en/stable/module_guides/querying/structured_outputs/