Fixes#37912
`ChatPerplexity._convert_message_to_dict` raises `TypeError` on
`ToolMessage` and drops `AIMessage.tool_calls`, which breaks
tool-message round-trips through `ChatPerplexity` — a client-side
tool-calling loop, or a shared message history across providers via
`RunnableWithFallbacks`.
Repro:
```python
from langchain_perplexity import ChatPerplexity
from langchain_core.messages import ToolMessage
ChatPerplexity(model="sonar")._convert_message_to_dict(
ToolMessage(content="result", tool_call_id="call_1")
)
# TypeError: Got unknown type content='result' tool_call_id='call_1'
```
An `AIMessage` carrying `tool_calls` also serializes to `{"role":
"assistant", "content": ...}` with the `tool_calls` silently dropped.
This brings the converter to parity with `langchain-openai`: serialize
`tool_calls` / `invalid_tool_calls`, send `content` as `null` when
tool_calls are present, and add a `tool`-role branch for `ToolMessage`.
How I verified: added unit tests for the `ToolMessage` and
`AIMessage.tool_calls` / `invalid_tool_calls` cases; the perplexity
package unit tests, lint, and format all pass.
Scope: translating these to the Responses (Agent) API's `function_call`
/ `function_call_output` input items is a separate follow-up; this PR is
the Chat Completions serialization parity fix.
---------
Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
Co-authored-by: Mason Daugherty <mason@langchain.dev>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
## Description
Bumps `langchain-perplexity` to require the Perplexity SDK release with
fixed Responses streaming and removes the temporary SSE shim workaround.
## Release Note
`langchain-perplexity` now requires `perplexityai>=0.34.1` for Responses
API streaming.
## Test Plan
- [x] `NO_COLOR=1 uv run --group test pytest
tests/unit_tests/test_chat_models_responses.py --disable-socket
--allow-unix-socket`
_Opened collaboratively by Mason Daugherty and open-swe._
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
Co-authored-by: Mason Daugherty <61371264+mdrxy@users.noreply.github.com>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
Closes#37360
Adds a `use_responses_api` flag to `ChatPerplexity` so requests can be
routed through Perplexity's Agent API (the Perplexity-flavored Responses
API) in addition to the existing Chat Completions endpoint. This mirrors
the `use_responses_api` flag on `ChatOpenAI`.
## Motivation
Perplexity exposes two HTTP surfaces from the same SDK client object:
`client.chat.completions.create()` (Chat Completions) and
`client.responses.create()` (Agent API, OpenAI-compatible Responses
shape). The Agent API supports built-in tools (`web_search`,
`fetch_url`, `finance_search`, `people_search`), `instructions`,
`input`, `previous_response_id`, and `include` — none of which exist on
Chat Completions. Today `ChatPerplexity` only calls Chat Completions, so
users who want the Agent API have to drop down to the raw SDK.
## What this changes
- New field `use_responses_api: bool | None = None` on `ChatPerplexity`.
- New module-level helper `_use_responses_api(payload)` that returns
`True` when the payload contains a built-in tool (any `tools[*]` whose
`type` is not `"function"`) or any of the Responses-only fields
`previous_response_id`, `instructions`, `input`, `include`.
- New instance method `ChatPerplexity._use_responses_api(payload)` that
honors `self.use_responses_api` when it is a `bool`, otherwise delegates
to the module helper.
- New converters `_convert_responses_to_chat_result(response)` and
`_convert_responses_stream_event_to_chunk(event)` that translate Agent
API objects/events into `AIMessage` and `AIMessageChunk` (preserving
`usage_metadata`, `response_metadata`, citations, images, related
questions, search results, and `function_call` tool calls).
- A surgical `_to_responses_payload(...)` helper that renames `messages`
→ `input` and `max_tokens` → `max_output_tokens`, passes through
Responses-supported fields, and parks anything Perplexity-specific under
`extra_body`.
- Each of the four API call sites (`_stream`, `_astream`, `_generate`,
`_agenerate`) now branches on `self._use_responses_api(payload)`. The
Chat Completions path is untouched.
## Auto-detection rules
When `use_responses_api` is unset (the default), routing is decided per
call from the outgoing payload:
- Has a built-in tool? → Responses
- Has `previous_response_id`, `instructions`, `input`, or `include`? →
Responses
- Otherwise → Chat Completions
Explicit `use_responses_api=True` or `=False` always overrides
auto-detection.
## Backwards compatibility
Existing usage is unchanged.
`ChatPerplexity(model="sonar").invoke("hi")` still calls
`client.chat.completions.create()`. No public field was renamed or
removed; the new field is purely additive.
## Tests
Adds `tests/unit_tests/test_chat_models_responses.py` covering the
helper, auto-detect routing, explicit overrides in both directions,
response-to-`AIMessage` conversion (content, `usage_metadata`,
`response_metadata.id`), `function_call` → `tool_calls` conversion, and
sync + async streaming of `response.output_text.delta` and
`response.completed` events. All mocks use `MagicMock`/`AsyncMock`; no
network calls.
## Notes for reviewers
This was implemented with help from an AI agent. The shape mirrors
`langchain-openai`'s `use_responses_api` — same field name, same helper
name, same docstring style — so the diff should be familiar.
Closes nothing — net new feature.
---------
Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
## Description
This PR adds a new `PerplexityEmbeddings` class to the
`langchain-perplexity` partner package, providing first-class support
for the Perplexity Embeddings API alongside the existing
`ChatPerplexity`, `PerplexitySearchRetriever`, and
`PerplexitySearchResults` integrations.
### What was added
- `langchain_perplexity/embeddings.py` — `PerplexityEmbeddings` class
implementing `langchain_core.embeddings.Embeddings` with sync
(`embed_documents`, `embed_query`) and async (`aembed_documents`,
`aembed_query`) methods. Defaults to model `pplx-embed-v1-4b` and reuses
the existing `_utils.initialize_client` helper for API key resolution
(`PPLX_API_KEY` / `PERPLEXITY_API_KEY`).
- `__init__.py` exports `PerplexityEmbeddings` and adds it to `__all__`.
- Unit tests under `tests/unit_tests/test_embeddings.py` covering
sync/async paths with mocked clients (no network).
- Integration tests under `tests/integration_tests/test_embeddings.py`,
gated on `PPLX_API_KEY` (matches the pattern in `test_search_api.py`).
- README updated to advertise the new component.
### Why
LangChain users already get chat, search, and tool wrappers from
`langchain-perplexity`, but had to drop down to the raw Perplexity SDK
to use embeddings. This closes that gap.
### References
- Perplexity Embeddings docs: https://docs.perplexity.ai/docs/embeddings
- Perplexity Embeddings API reference:
https://docs.perplexity.ai/api-reference/embeddings-post
### Issue
Closes#36726
## Testing
- `cd libs/partners/perplexity && make lint` — passes (ruff, format,
mypy).
- `cd libs/partners/perplexity && make test` — all unit tests pass (59
passed, 1 skipped).
- Integration tests will run in CI with secrets; they exercise real
`embed_documents` / `embed_query` / async variants against the live API
and assert vector dimensionality consistency.
---------
Co-authored-by: Claude Agent <agent@anthropic.com>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
PR #35788 added 7 new fields to the `langchain-profiles` CLI output
(`name`, `status`, `release_date`, `last_updated`, `open_weights`,
`attachment`, `temperature`) but didn't update `ModelProfile` in
`langchain-core`. Partner packages like `langchain-aws` that set
`extra="forbid"` on their Pydantic models hit `extra_forbidden`
validation errors when Pydantic encountered undeclared TypedDict keys at
construction time. This adds the missing fields, makes `ModelProfile`
forward-compatible, provides a base-class hook so partners can stop
duplicating model-profile validator boilerplate, migrates all in-repo
partners to the new hook, and adds runtime + CI-time warnings for schema
drift.
## Changes
### `langchain-core`
- Add `__pydantic_config__ = ConfigDict(extra="allow")` to
`ModelProfile` so unknown profile keys pass Pydantic validation even on
models with `extra="forbid"` — forward-compatibility for when the CLI
schema evolves ahead of core
- Declare the 7 missing fields on `ModelProfile`: `name`, `status`,
`release_date`, `last_updated`, `open_weights` (metadata) and
`attachment`, `temperature` (capabilities)
- Add `_warn_unknown_profile_keys()` in `model_profile.py` — emits a
`UserWarning` when a profile dict contains keys not in `ModelProfile`,
suggesting a core upgrade. Wrapped in a bare `except` so introspection
failures never crash model construction
- Add `BaseChatModel._resolve_model_profile()` hook that returns `None`
by default. Partners can override this single method instead of
redefining the full `_set_model_profile` validator — the base validator
calls it automatically
- Add `BaseChatModel._check_profile_keys` as a separate
`model_validator` that calls `_warn_unknown_profile_keys`. Uses a
distinct method name so partner overrides of `_set_model_profile` don't
inadvertently suppress the check
### `langchain-profiles` CLI
- Add `_warn_undeclared_profile_keys()` to the CLI (`cli.py`), called
after merging augmentations in `refresh()` — warns at profile-generation
time (not just runtime) when emitted keys aren't declared in
`ModelProfile`. Gracefully skips if `langchain-core` isn't installed
- Add guard test
`test_model_data_to_profile_keys_subset_of_model_profile` in
model-profiles — feeds a fully-populated model dict to
`_model_data_to_profile()` and asserts every emitted key exists in
`ModelProfile.__annotations__`. CI fails before any release if someone
adds a CLI field without updating the TypedDict
### Partner packages
- Migrate all 10 in-repo partners to the `_resolve_model_profile()`
hook, replacing duplicated `@model_validator` / `_set_model_profile`
overrides: anthropic, deepseek, fireworks, groq, huggingface, mistralai,
openai (base + azure), openrouter, perplexity, xai
- Anthropic retains custom logic (context-1m beta → `max_input_tokens`
override); all others reduce to a one-liner
- Add `pr_lint.yml` scope for the new `model-profiles` package
Largely:
- Remove explicit `"Default is x"` since new refs show default inferred
from sig
- Inline code (useful for eventual parsing)
- Fix code block rendering (indentations)
Description
The Perplexity chat model already returns a search_results field, but
LangChain dropped it when mapping Perplexity responses to
additional_kwargs.
This patch adds "search_results" to the allowed attribute lists in both
_stream and _generate, so downstream code can access it just like
images, citations, or related_questions.
Dependencies
None. The change is purely internal; no new imports or optional
dependencies required.
https://community.perplexity.ai/t/new-feature-search-results-field-with-richer-metadata/398
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
This PR fixes an issue where ChatPerplexity would raise an
AttributeError when the citations attribute was missing from the model
response (e.g., when using offline models like r1-1776).
The fix checks for the presence of citations, images, and
related_questions before attempting to access them, avoiding crashes in
models that don't provide these fields.
Tested locally with models that omit citations, and the fix works as
expected.
Perplexity's importance in the space has been growing, so we think it's
time to add an official integration!
Note: following the release of `langchain-perplexity` to `pypi`, we
should be able to add `perplexity` as an extra in
`libs/langchain/pyproject.toml`, but we're blocked by a circular import
for now.
---------
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
