Two silent failures in the Python SDK prevented frontend context from reaching the agent:
1. langgraph_default_merge_state rebuilt copilotkit as {actions} only, dropping the
useCopilotReadable items the TypeScript runtime had placed in state.copilotkit.context.
2. CopilotKitContext.properties were never forwarded through execute_agent → agent.execute(),
so <CopilotKit properties={...} /> values never reached state.copilotkit.properties.
Both fields now land cleanly under state["copilotkit"] on every agent invocation.
Also adds tests, a showcase example, and a new docs page.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Replace custom { name, props } schema format with spec-aligned inline
catalog format (allOf + properties) so the LLM sees the same flat
structure it must produce — eliminates "props" nesting confusion.
- Restructure generation prompts: inline literal values are the default,
path binding is a narrow schema-driven exception for form inputs.
- Export InlineCatalogSchema type from a2ui-renderer.
LLMs sometimes use path bindings (e.g. {"path": "/chartData"}) on
component properties that only accept literal values, causing silent
render failures. The new guideline tells the LLM to check the schema's
anyOf type before using path bindings.
## Summary
- During frontend state merge in LangGraph agent, preserve keys that are
owned by the graph (not set by the frontend)
- Prevents graph-computed state from being overwritten when frontend
state is merged back
Closes#2893
---
*Split from #3847*
## Summary
- Add sanitization pass over LangGraph agent state to replace NaN and
Infinity with null before JSON serialization
- Prevents `ValueError: Out of range float values are not JSON
compliant` in Python SDK
Closes#1955
---
*Split from #3847*
Partially addresses #1748
When Anthropic models return multi-part content lists, only the first
element was used and the rest discarded. Now iterates all parts and
concatenates text blocks, preserving the full message content.
Split from #3838.
## Summary
Fixes#2158
Pydantic `BaseModel` instances in LangGraph agent state are not
serializable by `langchain_dumps`. This adds a recursive
`_serialize_state` helper that converts `BaseModel` instances to dicts
before serialization, preventing crashes when state contains Pydantic
models.
**Additional fixes (second commit):**
- Also applies `_serialize_state` to the `get_state()` code path, which
was missed in the original fix but has the same bug
- Fixes `filter_state_on_schema_keys` returning `None` implicitly when
schema keys are not set (the `except` branch returned `state` but the
non-matching `if` branch did not)
- Adds 17 tests covering `_serialize_state`, `_emit_state_sync_event`,
and `get_state` with Pydantic models
## Merge order note
This PR and #3851 both modify
`sdk-python/copilotkit/langgraph_agent.py`. Both add a helper function
at module level and call it from `_emit_state_sync_event` and
`get_state`. Whichever merges second will need a trivial rebase. No
semantic conflict — the fixes are complementary (this one handles
Pydantic models, #3851 handles NaN/Infinity).
## Test plan
- [x] 17 unit tests covering both code paths
- [x] Red-green verified: `get_state` tests fail without fix, pass with
it
- [x] Existing test suite (test_emit_filtering) still passes
- [x] Verify LangGraph agent with Pydantic BaseModel state serializes
correctly
- [x] Verify non-Pydantic state is unaffected
The _merge_emit_state call merges emitted state with current_graph_state
into manually_emitted_state, but the `continue` statement skips the
later current_graph_state.update(updated_state). Without this update,
the next manual emit merges against stale current_graph_state and loses
keys from the previous emit.
Also guards the update call against non-dict values from _merge_emit_state
to prevent TypeError on edge-case non-dict emits.
The original fix only covered _emit_state_sync_event but missed the
get_state() code path, which also returns state containing Pydantic
BaseModel instances to callers that will JSON-serialize downstream.
Also fixes filter_state_on_schema_keys returning None implicitly when
schema keys are not set (the except branch returned state but the
non-matching if branch did not).
Adds 17 tests covering _serialize_state, _emit_state_sync_event, and
get_state with Pydantic models (nested, lists, plain dicts, empty).
The _sanitize_for_json function was applied to state sync events and
get_state responses but not to the raw event stream yielded at line 507.
Events with NaN/Infinity float values in their data payloads would
produce invalid JSON (literal NaN) that downstream parsers cannot handle.
When Anthropic models return multi-part content lists, only the first
element was used and the rest discarded. Now iterates all parts and
concatenates text blocks, preserving the full message content.
Sequential emit_state calls with different keys now preserve all keys
in the snapshot. Previously, each call would replace the entire
manually_emitted_state, losing keys from earlier calls.
Add copilotkit.a2ui module with operation builders and prompt helpers,
fix SystemMessage ID reuse in before_agent to prevent LangGraph duplication,
add Pydantic model_dump serialization for app_context.
The re module was used in _fix_messages_for_bedrock (re.compile) but
never imported, causing NameError at runtime when the middleware is
invoked. Bumps version to 0.1.83.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Add _fix_messages_for_bedrock() to handle three issues caused by
after_agent restoring frontend tool_calls to the checkpoint:
1. Strip unanswered tool_calls without matching ToolMessages (Bedrock
rejects toolUse without a corresponding toolResult)
2. Sync msg.content tool_use blocks with msg.tool_calls
3. Fix tool_use/tool_call blocks with string input/args (must be dict)
Avoid emitting spurious empty assistant messages for tool-call-only
AIMessages (common with OpenAI models where content is empty string).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
langchain_messages_to_copilotkit previously skipped creating the assistant
message when an AIMessage had tool_calls, causing missing context in chat
history on reconnect. Also adds ActionExecutionMessage type guard in
copilotkit_messages_to_langchain to prevent KeyError on non-tool messages
with parentMessageId.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Fixes#2066
## Problem
`copilotkit_customize_config(config, emit_messages=False)` does not work -
TEXT_MESSAGE_* events are still emitted despite the configuration.
## Root Causes
1. **Metadata Reading Bug**: In `langgraph_agui_agent.py`, the code uses
`getattr(raw_event, 'metadata', {})` to read metadata, but `raw_event`
is a dict, not an object. This should use `.get()` instead.
2. **Encoder Crash Bug**: When the filtering logic works (after fixing bug #1),
it returns `""` (empty string) to skip dispatching events. However, this
empty string gets yielded to the event encoder which expects event objects
with `model_dump_json()` method, causing an `AttributeError`.
## Fixes
1. Changed metadata reading to handle both dict and object cases.
2. Changed return value from `""` to `None` for filtered events.
3. Added `run()` method override to filter out `None` values before yielding
to encoder.
Adds missing dict_repr() method to LangGraphAGUIAgent class to fix
AttributeError when SDK tries to serialize agent info.
The method was present in the parent LangGraphAgent class but not
overridden in LangGraphAGUIAgent, causing failures when calling
sdk.info() with AGUI agents in FastAPI integrations.
Fixes#2667
Martha Schumann