As a LangChain user streaming a tool-calling model, I expect each
streamed chunk to expose structured `tool_call_chunk` content blocks so
I can render or process tool calls live, instead of waiting for the
final aggregated message.
This adds `tool_call_streaming` to `ModelProfile` and uses it in the
standard chat-model tool-calling tests. When a model profile opts in,
`test_tool_calling` and `test_tool_calling_async` now validate that at
least one streamed chunk includes a `tool_call_chunk` block via
`content_blocks`, while preserving the existing final-message
validation.
This keeps the contract profile-gated so providers can opt in once their
streaming chunk shape is verified. This PR opts in the providers
verified by smoke testing with straightforward profile coverage: OpenAI,
Anthropic, Fireworks, HuggingFace, OpenRouter, DeepSeek, and xAI. The
generated profile artifacts are refreshed so runtime profiles expose the
new capability flag.
Perplexity Responses also passed the smoke test, but its current profile
data is for the `sonar` family while the Responses smoke path used a
routed model string. That profile strategy is left as follow-up.
MistralAI currently streams `.tool_call_chunks`, but its content-block
translator exposes a complete `tool_call` block instead of
`tool_call_chunk`, so it also stays out of this flag until that
integration is fixed.
Extract additional fields from models.dev into `_model_data_to_profile`:
`name`, `status`, `release_date`, `last_updated`, `open_weights`,
`attachment`, `temperature`
Move the model profile refresh logic from an inline bash script in the
GitHub Actions workflow into a `make refresh-profiles` target in
`libs/model-profiles/Makefile`. This makes it runnable locally with a
single command and keeps the provider map in one place instead of
duplicated between CI and developer docs.
- Sort model profiles alphabetically by model ID (the top-level
`_PROFILES` dictionary keys, e.g. `claude-3-5-haiku-20241022`,
`gpt-4o-mini`) before writing `_profiles.py`, so that regenerating
profiles only shows actual data changes in diffs — not random reordering
from the models.dev API response order
- Regenerate all 10 partner profile files with the new sorted ordering
- Add `text_inputs` and `text_outputs` fields to `ModelProfile`
- Regenerate `_profiles.py` for all providers
## Why
models.dev data includes `'text'` as both an input and output modality,
but we didn't capture it.
models.dev broadly contains models without text input (Whisper/ASR) and
without text output (image generators, TTS).
Without this, downstream consumers can't filter on model text support
(e.g. preventing users from passing text input to an audio-only model).
---
We'd need to also run for Google, AWS and cut releases for all to
propagate
