* Adds support for `NativeOutput` via a new `NativeOutput` dataclass
* Adds support for structured output specification via the following
(pydantic models already supported)
* dataclasses
* typed dicts
* json schemas
* Adds mocking support to support native strategies with
`FakeToolCallingModel`
* Add new default tool message when `tool_message_content` not provided
* Smart "selection" of native vs tool output based on provider support,
necessitates profiles down the line
Considered questions
* do we want to enforce docstrings? -- decided on no for now
* do we want to enforce names (titles) on json schemas? -- decided no
for now, defaulting to `structured_output`
* do we want to validate that json schemas coming in are valid? --
decided no for now
* do we want to validate model results against a given json schema? we
validate against all other types (typed dict, dataclass, etc) w/
pydantic -- decided no for now
TODO in future PRs:
* Figure out retry policy
* Add standard testing (handed off to @casparb)
* Further privatize certain structures (like the bindings) -- this is
low prio
---------
Co-authored-by: Sydney Runkle <sydneymarierunkle@gmail.com>
Co-authored-by: Sydney Runkle <54324534+sydney-runkle@users.noreply.github.com>
* Add support for ToolOutput response format.
* I don't love the name -- it's confusing unless you know that it's parameterizing a strategy.
We should determine if we want to support our old strategy for doing
things -- it has a higher latency (one extra LLM call), but it's a
reasonable built-in strategy as it doesn't do anything awkward with
conversation history. (Wouldn't surprising if it has overall better
performance than tool choice for longer conversations)
