Extract user context for tracing.

Get video duration in seconds using av if available. Args: content: Raw video bytes. content_type: Optional MIME type for format

Handle a tool call from the LLM. Args: tool_calls: List of tool calls from the LLM available_functions: Dict of avail

Import docling submodules lazily and cache the result. Raises: ImportError: If the docling package is not installed.

Increment the usage count.

Initialize trace batch - auto-enable ephemeral for first-time users. Args: user_context: User context information. ex

Inject merged metadata into call details.

Interpolates the inputs in the tasks and agents.

Type guard to check if the embedding function is async. Args: func: The embedding function to check. Returns: True if the fu

Check if a version string represents a pre-release.

Check if an object is a Pydantic model class. This distinguishes between Pydantic model classes that support structured outputs (have model_j

Return True for regular files, excluding symlinks to files.

Create a TraceBatchManager with a pre-set trace_batch_id.

Build a MethodExecutionStartedEvent with explicit ids/sequence.

Build a 404 message that says what to do about it. OpenAI's own wording ("This is not a chat model") doesn't make the fix obvious, so

Parse and validate the input arguments against the schema. Args: raw_args: The raw arguments to parse, either as a string or dict

Reconstruct a MemoryRecord from a Qdrant payload.

Poll the token endpoint until authentication completes or times out.

Capture execution context and sync checkpoint fields on each entity. Args: root: List of entities to prepare for serialization.

Preprocess structured data to handle common LLM output format issues. Some models (especially Claude on Bedrock) may return array fields as m

Resolve user input to a full repo name, or None if not found.

Retry an operation with exponential backoff. Args: operation: Async operation to retry. timeout: Operation timeout in

Write *content* to *filename*, confined to the tool's sandbox.

Run the crew with the trigger payload using the run_with_trigger method.

Set task identity and fingerprint data on an event.

Setup and invoke before_llm_call hooks for the executor context. Args: executor_context: The executor context to setup the hooks for.

Set up messages for the agent execution.

Whether this kickoff should defer final flow trace finalization.

Whether to run PlannerObserver LLM calls after each step. Explicit ``observe_steps=False`` disables observation at any effort level.

Check if the model supports native structured outputs. Native structured outputs are only available for Claude 4.5 models (Sonnet 4.5, Opus 4

Build an in-memory tar archive via `build(tf)` and return it for reading.

Parse streamed observation JSON and update the exact step it names.

Remove key tracking for a provider.

Convert a UUID string to a stable Qdrant point ID. Falls back to hashing for non-UUID strings.

Validate keyword arguments against args_schema if present. Args: kwargs: The keyword arguments to validate. Returns:

Call the LLM with the given messages. Args: messages: Input messages for the LLM. Can be a string or list of

Get merged crew and task files asynchronously. Task files override crew files with the same name. Args: crew_id: Unique identifier f

Get all cached uploads for a provider. Args: provider: The provider name. Returns: List of cached uploads fo

Query across all knowledge sources asynchronously. Args: query: List of query strings. results_limit: Maximum number

Override streaming for ``llm`` within the current call scope.

Clear all registered global before_tool_call hooks. Returns: Number of hooks that were cleared Example: >>> register_before_

Remove the stored token file (no-op if absent).

Clear all user settings.

Nearest candidate name to a likely typo, if one is close enough.

Start the MCP server process and establish connection. Returns: Self for method chaining. Raises: Connection

Printable text content for chunk-like consumers.

Convert oneOf to anyOf for OpenAI compatibility. OpenAI's Structured Outputs support anyOf better than oneOf. This recursively converts all o

Convert a result string to a Pydantic model or JSON using instructions. Args: result: The result string to convert. model: The Py

Create a client from configuration using the appropriate factory. Args: config: The RAG client configuration. Returns: The c

Create state for a scoped public frame stream.

Create a mock LLM that returns a simple response. The mock includes all attributes required by the telemetry system, particularly the 'model'

Create research tools for testing structured planning.

Create a configured FileResolver. Args: provider: Optional provider name to load default threshold from constraints. prefer_uploa

Ensure all properties are in the required array for OpenAI strict mode. OpenAI's strict structured outputs require all properties to be listed

Records the coding tool environment context.

Return ``stem.jsonc`` or ``stem.json``, preferring JSONC.

Restate a containment rejection with a tool-specific remedy. Rejections from :func:`validate_file_path` end by advertising the process-wide e

Create a MergeAgentHandlerTool from a tool name. Args: tool_name: Name of the tool (e.g., "linear__create_issue")

Generate the ChatInputs required for the crew by analyzing the tasks and agents. Args: crew: The crew object containing tasks and agents.

Read message history from flow state or the internal fallback buffer.

Get all failed todos. Returns: List of failed TodoItem objects.

Return the project name from ``pyproject.toml``.

Return a single record by ID, or None if not found. Args: record_id: The unique ID of the record. Returns: T

Get information about a scope. Args: scope: The scope path. Returns: ScopeInfo with record count, categories

Get supported MIME type prefixes for a provider. Args: provider: Provider name string. api: Optional API variant (e.g., "response

Handle OutputParserError by updating messages and formatted_answer. Args: e: The OutputParserError that occurred messages: List o

Check if there are any built-in tool outputs.

Check if this is first time and initialize collection.

Execute the agent with given inputs. Args: inputs: Input dictionary containing prompt variables. Returns: Di

Check if code is currently running inside an asyncio event loop. This is used to detect when code is being called from within an async context

Return whether an error means native tool calling is unavailable.