Perplexity's Responses API integration tests were pinned to
`openai/gpt-5.5`, which now fails against the live Agent API for this
test path. Use the stable `openai/gpt-5` Agent API model instead so
scheduled coverage continues exercising the Responses API and
tool-calling surface.
Package-version trace metadata now uses the LangChain-owned
`metadata["lc_versions"]` convention instead of the user-owned
`metadata["versions"]` key. Metadata merging is narrowed so only
`lc_versions` accumulates nested package-version entries, while generic
nested metadata keeps normal last-writer-wins behavior.
## Changes
- Renamed `BaseLanguageModel._add_version()` trace metadata from
`versions` to `lc_versions`, including docstrings and the non-dict
replacement warning.
- Scoped `_merge_metadata_dicts()` nested-map accumulation to only
`lc_versions`; duplicate package entries remain last-writer-wins and
`lc_versions` mappings are copied defensively.
- Preserved user-owned `metadata["versions"]` semantics by keeping it
out of package-version tracking and generic nested metadata merging.
- Updated runnable snapshots and partner package metadata assertions
across Anthropic, DeepSeek, Fireworks, Groq, Hugging Face, MistralAI,
Ollama, OpenAI, OpenRouter, Perplexity, and xAI to expect `lc_versions`.
## Testing
- Added/adjusted core tests for `lc_versions` accumulation, duplicate
package overwrite behavior, non-dict `lc_versions` replacement,
defensive copying, and `metadata["versions"]` last-writer-wins behavior.
- Ran focused core and partner metadata tests plus Ruff checks for
changed areas.
Standardizes inline code markup in Python docstrings and comments by
replacing Sphinx-style double backticks with single-backtick Markdown.
The cleanup keeps existing code fences intact while aligning inline
references with the repo's docstring convention.
## Changes
- Converted inline code references in core prompt-loading docs and
LangSmith tracer comments, including `..`, `allow_dangerous_paths`, and
inheritable metadata keys.
- Normalized agent-related docstrings and comments around
`wrap_model_call`, `ExtendedModelResponse`, `Command`,
`create_structured_chat_agent`, and `DockerExecutionPolicy`.
- Updated partner package docstrings for inline references such as
`json_schema`, `ToolCall`, `apply_patch_call_output`, OpenRouter content
block keys, and Perplexity tool-call serialization.
- Cleaned test and helper docstrings that referenced command separators,
fake `resource` modules, stream event names, and xdist rate-limit
environment variables.
Following on the heels of #35293
TODO:
- Packages outside of this repo (e.g. LiteLLM, Nvidia, Google, AWS)
---
## Summary
Surface partner package versions in `metadata.versions` on LangSmith
traces. Mirrors the JS SDK's `_addVersion()` pattern
([langchainjs#10106](https://github.com/langchain-ai/langchainjs/pull/10106)).
Each model constructor records its package version via `_add_version()`
on `BaseLanguageModel`. The version dict accumulates through the class
hierarchy — `langchain-core` is added in
`BaseLanguageModel.model_post_init`, `langchain-openai` in
`BaseChatOpenAI._set_openai_chat_version`, and each leaf partner in its
uniquely-named `model_validator`. Traces end up with:
```json
{
"metadata": {
"versions": {
"langchain-core": "1.4.5",
"langchain-openai": "1.3.0",
"langchain-xai": "1.2.2"
}
}
}
```
### Changes
- `BaseLanguageModel._add_version(pkg, version)` — appends to
`self.metadata["versions"]`; accepts any `Mapping` type; emits a warning
if a non-mapping value is found and replaced
- `BaseLanguageModel.model_post_init` — adds `langchain-core` version;
calls `super()` for MRO safety
- `_merge_metadata_dicts` — one-level-deep (non-recursive) merge for
nested dict metadata keys
- `CallbackManager.add_metadata` — uses `_merge_metadata_dicts` instead
of flat `dict.update()` so nested metadata dicts (like `versions`)
coexist rather than clobber
- `merge_configs` — uses `_merge_metadata_dicts` for config merging
**Partners:**
- Each now calls `self._add_version("langchain-<pkg>", __version__)`
### Design decisions
- **Constructor-based, not `_get_ls_params`-based** — versions flow
through `self.metadata` (local metadata on traces), not through
`LangSmithParams`. This matches JS and makes child-class version
inheritance automatic (no merge/clobber issues).
- **`versions` is local (non-inheritable) metadata** — `self.metadata`
is passed to `CallbackManager.configure` as `local_metadata`
(`add_metadata(..., inherit=False)`), so `versions` is attached **once
per chat-model run** and is **not** propagated to child runs or
duplicated onto every streaming chunk. This is intentionally the
opposite of the inheritable-per-chunk metadata that #36588 was reducing
for performance — `versions` does not regress that path.
- **`add_metadata` deep-merge is a correctness fix, not just for
versions** — previously `add_metadata`/`merge_configs` did a flat
top-level `dict.update`/spread, so any nested metadata dict baked into a
config (e.g. via `.with_config({"metadata": {...}})`) would be wholly
replaced when a caller also passed `metadata`. `_merge_metadata_dicts`
merges one level deep so user-provided `config.metadata.versions` and
model-set `versions` coexist instead of clobbering. The merge runs once
per `configure` (not per chunk), so it is off the streaming hot path.
- **One level deep only** — `_merge_metadata_dicts` is deliberately
*not* a recursive deep merge; values nested more than one level are
last-writer-wins. This covers the `versions` case without the
ambiguity/cost of arbitrary-depth merging.
- **Warn on non-dict `metadata["versions"]`** — if a user sets
`metadata={"versions": "some-string"}`, `_add_version` emits a warning
and replaces the value with the version dict rather than silently
discarding user data or crashing. This is a soft breaking change for
anyone who previously stored non-dict values at this key.
### Follow-ups (tracked separately, out of scope here)
- JS `mergeConfigs` still flat-spreads nested metadata, so
`metadata.versions` can still clobber on the JS side until an equivalent
deep-merge lands.
---
Made by [Open SWE](https://openswe.vercel.app)
---------
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
## Summary
Follow-up to #37911 (released in `langchain-perplexity` 1.3.2). That PR
fixed the outbound `ToolMessage` / `AIMessage.tool_calls` serialization;
this one implements **`ChatPerplexity.bind_tools`**, which flips
`has_tool_calling` to `True` and lights up the full `langchain-tests`
standard tool-calling suite — the suite that would have caught #37911 in
the first place.
Verified live against the Perplexity Agent API (`openai/gpt-5.5`,
`use_responses_api=True`): a client-side function-tool round-trip
(invoke + stream) works end-to-end.
## Core change (the `bind_tools` work + the Responses-API follow-up)
- **`bind_tools`** mirrors `langchain-openai`: converts tools via
`convert_to_openai_tool`, normalizes `tool_choice`, and passes
Perplexity built-in tools (`web_search`, etc.) through unchanged.
- **`_to_responses_payload`** now translates tool turns into the
Responses (Agent) API's typed input items: `AIMessage.tool_calls` →
`function_call`, `ToolMessage` → `function_call_output`, and flattens
function tool specs. (The Responses API has no `tool` role, so this
translation is required for round-trips.)
## Changes required to make standard-suite tests pass on the Responses
route
- Streaming: `_convert_responses_stream_event_to_chunk` emits a
`tool_call_chunk` on `response.output_item.done` function calls —
required by `test_tool_calling` (which streams and asserts tool calls).
- `_content_to_text` reduces list-shaped assistant content to text in
the tool-call branch — required by `test_agent_loop` and
`test_tool_message_histories_list_content`.
- `response_metadata["model_name"]` on the Responses route, mirroring
Chat Completions — required by `test_usage_metadata` /
`test_usage_metadata_streaming` (used by `langchain_core` usage
callbacks).
## Tests
- `sonar` standard class marked `has_tool_calling=False` (the family
returns 400 "Tool calling is not supported for this model").
- New `TestPerplexityResponsesStandard` runs the full suite on
`openai/gpt-5.5` + `use_responses_api` with `has_tool_choice=False`:
**35 passed, 13 skipped, 2 xfailed**.
- The 2 xfails (`test_unicode_tool_call_integration`,
`test_structured_few_shot_examples`) hard-code `tool_choice="any"`. The
Responses (Agent) API does not support `tool_choice` (verified: every
form returns HTTP 200 without forcing a call), which `ChatPerplexity`
surfaces as `ValueError` — **existing behavior, unchanged here.**
Softening that to a warning can be a separate change.
`make format lint` clean; unit + standard tests green.
---------
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>
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>
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>
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>
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>
