> ## Documentation Index
> Fetch the complete documentation index at: https://docs.contextual.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Agent Composer YAML Step Reference

> An authoritative list of all the Agent Composer step types

<Note>
  Custom Agent Composer YAML workflows are available in public preview for enterprise users. Template agents (Basic Search and Agentic Search) are available for self-serve users, but creating custom workflows with YAML requires enterprise access. For more information or to request access, please contact your Contextual AI representative.
</Note>

## Overview

This catalog lists step types available for use in Agent Composer YAML graphs, including their configuration parameters, required inputs, outputs, and supported UI stream types.

***

### AgenticResearchStep

* **Description:** Runs a multi-turn agent loop that plans and invokes tools to gather information and produce structured research output.
* **Config Parameters:**
  * `agent_config: Dict[str, Any] = required`
  * `tools_config: Optional[List[Dict[str, Any]]] = None`
  * `version: str = "0.1"`
* **Inputs:** `message_history: List[MessageAndRole]`
* **Outputs:** *(varies by implementation; commonly includes structured research output consumed by generation steps)*
* **UI Stream Types:** `RETRIEVALS`

> Tip: For final response synthesis, pair `AgenticResearchStep` with `GenerateFromResearchStep`.

***

### AppendStep

* **Description:** Appends a given item to a list and returns the new list.
* **Config:** None
* **Inputs:** `list: List[Any]`, `element: Any`
* **Outputs:** `output: List[Any]`
* **UI Stream Types:** None

***

### AttributionStep

* **Description:** Step to handle attributions.
* **Config Parameters:**
  * `attribution: Optional[bool] = None`
  * `template_attribution: Optional[str] = None`
  * `attribution_model: Optional[str] = None`
  * `number_of_retrievals_for_attribution: Optional[int] = None`
* **Inputs:** `generation_result: GenerationResult`, `chunks_info: List[Dict]`
* **Outputs:** `attribution_result: AttributionResult`
* **UI Stream Types:** `ATTRIBUTION`

***

### BuildPromptStep

* **Description:** Step to build the final prompt.
* **Config Parameters:**
  * `untrusted_system_prompt: Optional[str] = None`
  * `untrusted_no_retrieval_system_prompt: Optional[str] = None`
  * `template_seed: Optional[str] = None`
  * `template_query: Optional[str] = None`
  * `template_knowledge: Optional[str] = None`
  * `max_new_tokens: Optional[int] = None`
  * `skip_context_truncation: Optional[bool] = None`
  * `allow_multi_turn: Optional[bool] = None`
  * `avoid_commentary: Optional[bool] = None`
  * `attribution: Optional[bool] = None`
* **Inputs:** `query: str`, `retrievals: Retrievals`, `retrieval_record: Retrieval`, `message_history: List[MessageAndRole]`, `chunks_info: List[Dict]`
* **Outputs:** `retrieval_record: Retrieval`, `message_history: List[MessageAndRole]`, `chunks_info": List[Dict]`
* **UI Stream Types:** `RETRIEVALS`

***

### CheckRetrievalNeedStep

* **Description:** Step to check if retrieval is needed for the given query.
* **Config Parameters:**
  * `should_check_retrieval_need: Optional[bool] = None`
  * `template_should_retrieve: Optional[str] = None`
* **Inputs:** `query: str`
* **Outputs:** `is_retrieval_needed: bool`, `retrievals: Retrievals`
* **UI Stream Types:** None

***

### ConcatenateStep

* **Description:** Concatenates two lists.
* **Config:** None
* **Inputs:** `list1: List[Any]`, `list2: List[Any]`
* **Outputs:** `output: List[Any]`
* **UI Stream Types:** None

***

### ContextualAgentStep

* **Description:** Step to retrieve information from contextual agents.
* **Config Parameters:** `agent_ids: Optional[List[str]] = None`
* **Inputs:** `query: str`
* **Outputs:** `retrievals: Retrievals`
* **UI Stream Types:** `RETRIEVALS`

***

### ConstantStep

* **Description:** Provides constant values as outputs.
* **Config Parameters:** `value: Any = required`
* **Inputs:** None
* **Outputs:** `output: Any`
* **UI Stream Types:** None

***

### ContextualizeChunk

* **Description:** Contextualize chunk text with surrounding document context using VLM.
* **Config Parameters:**
  * `shard_tokens: int = 20000`
  * `shard_overlap: int = 10000`
* **Inputs:** `chunk: Dict[str, Any]`, `tenant_id: str`, `document_id: str`
* **Outputs:** `chunk: Dict[str, Any]`
* **UI Stream Types:** None

***

### CreateMessageHistoryStep

* **Description:** Converts a query into a message history.
* **Config Parameters:**
  * `enable_model_armor: Optional[bool] = None`
  * `should_check_retrieval_need: Optional[bool] = None`
  * `template_should_retrieve: Optional[str] = None`
  * `untrusted_system_prompt: Optional[str] = None`
  * `untrusted_no_retrieval_system_prompt: Optional[str] = None`
  * `template_seed: Optional[str] = None`
  * `template_query: Optional[str] = None`
  * `template_knowledge: Optional[str] = None`
  * `max_new_tokens: Optional[int] = None`
  * `skip_context_truncation: Optional[bool] = None`
  * `allow_multi_turn: Optional[bool] = None`
  * `avoid_commentary: Optional[bool] = None`
  * `attribution: Optional[bool] = None`
* **Inputs:** `query: str`
* **Outputs:** `message_history: List[MessageAndRole]`
* **UI Stream Types:** `RETRIEVALS: False`

***

### DeleteMemberStep

* **Description:** Deletes the specified key from a dict or a pydantic model.
* **Config Parameters:** `allow_missing_key: bool = False`
* **Inputs:** `input: Union[dict, BaseModel]`, `key: str`
* **Outputs:** `output: Union[dict, BaseModel]`
* **UI Stream Types:** None

***

### DocumentDownloadStep

* **Description:** Downloads documents from ingestion storage using DownloadDocumentTool.
* **Config:** None
* **Inputs:** `tenant: dict`, `datastore_id: UUID`, `short_path: str`
* **Outputs:** `content: str`, `file_name: str`, `document_id: str`, `full_gcs_path: str`, `content_type: str`, `size_bytes: int`
* **UI Stream Types:** None

***

### EntitleRetrievalsStep

* **Description:** Post-process retrievals.
* **Config:** None
* **Inputs:** `retrievals: Retrievals`
* **Outputs:** `retrievals: Retrievals`, `entitlements_api_time_elapsed: float`
* **UI Stream Types:** None

***

### ExtractChunkMetadata

* **Description:** Extract key-value metadata from chunk text using VLM.
* **Config:** None
* **Inputs:** `chunk: Dict[str, Any]`, `prompt: str`, `vlm_model: str`
* **Outputs:** `metadata: Dict[str, Any]`, `chunk: Dict[str, Any]`
* **UI Stream Types:** None

***

### ExtractMetadataStep

* **Description:** Extract metadata from PDF using ExtractMetadataTool.
* **Config:** None
* **Inputs:** `content: str`, `full_gcs_path: str`, `user_id: UUID`, `file_name: str`
* **Outputs:** `shard_metadata_list: List[ShardMetadata]`
* **UI Stream Types:** None

***

### FileAnalysisInputStep

* **Description:** Analyze files uploaded at query time.
* **Config:** None
* **Inputs:** `query: str`
* **Outputs:** `retrievals: Retrievals`
* **UI Stream Types:** `RETRIEVALS`

***

### FilterRetrievalsStep

* **Description:** Filter retrievals.
* **Config Parameters:**
  * `template_filter: Optional[str] = None`
  * `filter_retrievals: Optional[bool] = None`
  * `filter_model: Optional[str] = None`
  * `structured_output: Optional[bool] = None`
  * `untrusted_filter_prompt: Optional[str] = None`
  * `enable_batch_processing: Optional[bool] = None`
* **Inputs:** `query: str`, `retrievals: Retrievals`
* **Outputs:** `retrievals: Retrievals`
* **UI Stream Types:** None

***

### GenerateEmbeddingsStep

* **Description:** Generate embeddings for the query.
* **Config Parameters:**
  * `max_encoder_length: Optional[int] = None`
  * `retrieval_encoder_model: Optional[str] = None`
* **Inputs:** `query: str`, `reformulated_query: str`, `expanded_queries: List[str]`
* **Outputs:** `query_embedding: List[float]`, `merged_embeded_reformulated_queries: List[Tuple[List[float], str]]`
* **UI Stream Types:** None

***

### GenerateFromResearchStep

* **Description:** Generate a response.
* **Config Parameters:**
  * `model_name_or_path: str`
  * `base_url: Optional[str] = None`
  * `identity_guidelines_prompt: str = "You are a helpful assistant made by Contextual AI."`
  * `response_guidelines_prompt: str = "You should respond in a friendly and helpful manner."`
  * `litellm_modify_params: bool | Literal["auto"] = "auto"`
  * `version="0.1"`
* **Inputs:** `message_history: List[MessageAndRole]`, `research: List`
* **Outputs:** `response: str`

***

### GenerationStep

* **Description:** Generate a response.
* **Config Parameters:**
  * `temperature: Optional[float] = None`
  * `max_new_tokens: Optional[int] = None`
  * `top_p: Optional[float] = None`
  * `frequency_penalty: Optional[float] = None`
  * `seed: Optional[int] = None`
  * `attribution: Optional[bool] = None`
* **Inputs:** `message_history: List[MessageAndRole]`, `chunks_info: List[Dict]`, `disable_streaming: bool`
* **Outputs:** `generation_result: GenerationResult`
* **UI Stream Types:** `GENERATION`

***

### GetAgentInfoStep

* **Description:** Answers questions about the agent itself.
* **Config:** None
* **Inputs:** `query: str`
* **Outputs:** `generation_result: GenerationResult`
* **UI Stream Types:** None

***

### GetDatastoreStatisticsStep

* **Description:** Handle datastore statistics (as provided).
* **Config:** None
* **Inputs:** `query: str`
* **Outputs:** `generation_result: GenerationResult`
* **UI Stream Types:** None

***

### GetDatastoreSummaryStep

* **Description:** Aggregates results to generate a datastore summary.
* **Config:** None
* **Inputs:** `datastore_statistics: GenerationResult`, `documents_summary: GenerationResult`, `query: str`
* **Outputs:** `generation_result: GenerationResult`
* **UI Stream Types:** None

***

### GetDocumentsSummaryStep

* **Description:** Generates a summary of documents in the datastore.
* **Config:** None
* **Inputs:** `query: str`
* **Outputs:** `generation_result: GenerationResult`
* **UI Stream Types:** None

***

### GetMemberStep

* **Description:** Extract values from dictionaries or object attributes.
* **Config Parameters:** `key: str = required`
* **Inputs:** `input: Union[dict, BaseModel]`
* **Outputs:** `output: Any`
* **UI Stream Types:** None

***

### GetPlatformInfoStep

* **Description:** Answers questions about the platform itself.
* **Config:** None
* **Inputs:** `query: str`
* **Outputs:** `generation_result: GenerationResult`
* **UI Stream Types:** None

***

### GroundednessStep

* **Description:** Compute groundedness scores.
* **Config Parameters:**
  * `attribution: Optional[bool] = None`
  * `calculate_groundedness: Optional[bool] = None`
* **Inputs:** `generation_result: GenerationResult`, `attribution_result: AttributionResult`, `chunks_info: List[Dict]`
* **Outputs:** `groundedness_scores: List[GroundednessScore]`
* **UI Stream Types:** `GROUNDEDNESS`

***

### IndexChunkMetadata

* **Description:** Index chunk with metadata in ElasticSearch.
* **Config:** None
* **Inputs:** `chunk: Dict[str, Any]`, `metadata: Dict[str, Any]`, `index_config: Dict[str, str]`, `tenant_id: str`, `document_id: str`
* **Outputs:** `indexed: bool`, `chunk_id: str`
* **UI Stream Types:** None

***

### IndexMetadataStep

* **Description:** Index metadata into Elasticsearch using IndexMetadataTool.
* **Config:** None
* **Inputs:** `shard_metadata_list: List[ShardMetadata]`, `tenant: dict`, `datastore_id: UUID`
* **Outputs:** `doc_id_list: List[str]`
* **UI Stream Types:** None

***

### IndexStep

* **Description:** Return the element at a given index of a list.
* **Config:** None
* **Inputs:** `list: List[Any]`, `index: int`
* **Outputs:** `output: Any`
* **UI Stream Types:** None

***

### IsFirstTurnStep

* **Description:** Returns whether this is the first turn in a multi-turn interaction.
* **Config:** None
* **Inputs:** None
* **Outputs:** `is_first_turn: bool`, `turn_count: int`
* **UI Stream Types:** None

***

### JSONCreatorStep

* **Description:** Creates JSON objects with dynamic variable substitution using `$`.
* **Config Parameters:** `schema: str = required`
* **Inputs:** Dynamic (based on `$variables` in schema)
* **Outputs:** `json: Dict[str, Any]`
* **UI Stream Types:** None

***

### LanguageModelStep

* **Description:** Generic language model inference with template variables.
* **Config Parameters:**
  * `prompt_template: str = required`
  * `model_id: str = required`
  * `temperature: float = 0.7`
  * `max_tokens: int = 1000`
  * `structured_output: Optional[Dict] = None`
* **Inputs:** Dynamic (template variables)
* **Outputs:** `response: str`
* **UI Stream Types:** None

***

### LengthStep

* **Description:** Return the length of a list.
* **Config:** None
* **Inputs:** `list: List[Any]`
* **Outputs:** `output: int`
* **UI Stream Types:** None

***

### MCPClientStep

* **Description:** Execute tools on Model Context Protocol servers.
* **Config Parameters:**
  * `server_url: str = required`
  * `tool_name: str = required`
  * `tool_args: str = required`
  * `transport_type: str = "http"`
  * `connection_timeout: int = 30`
  * `server_name: Optional[str] = None`
  * `auth_headers: Optional[Dict[str, str]] = None`
* **Inputs:** Dynamic (based on `tool_args`)
* **Outputs:** `mcp_result: Dict[str, Any]`
* **UI Stream Types:** None

***

### MergeStep

* **Description:** Merge two dicts (or pydantic models).
* **Config Parameters:** `allow_key_conflicts: bool = False`
* **Inputs:** `dict1: Union[dict, BaseModel]`, `dict2: Union[dict, BaseModel]`
* **Outputs:** `output: Union[dict, BaseModel]`
* **UI Stream Types:** None

***

### ModelArmorFilterUserPromptStep

* **Description:** Send user prompt to model armor for safety check.
* **Config Parameters:** `enable_model_armor: Optional[bool] = None`
* **Inputs:** `query: str`
* **Outputs:** None
* **UI Stream Types:** None

***

### ProcessMetadataStep

* **Description:** Process metadata for retrievals.
* **Config:** None
* **Inputs:** `retrievals: Retrievals`
* **Outputs:** `retrievals: Retrievals`
* **UI Stream Types:** None

***

### QueryDecompositionStep

* **Description:** Decompose the query.
* **Config Parameters:**
  * `query_decomposition_prompt: Optional[str] = None`
  * `query_decomposition_model: Optional[str] = None`
  * `enable_query_decomposition: Optional[bool] = None`
* **Inputs:** `query: str`
* **Outputs:** `expanded_queries: List[str]`
* **UI Stream Types:** None

***

### QueryExpansionStep

* **Description:** Expand the query.
* **Config Parameters:**
  * `query_expansion_prompt: Optional[str] = None`
  * `query_expansion_model: Optional[str] = None`
  * `enable_query_expansion: Optional[bool] = None`
* **Inputs:** `query: str`
* **Outputs:** `reformulated_query: str`, `documents_filters: Optional[Union[CompositeMetadataFilter, BaseMetadataFilter]]`
* **UI Stream Types:** `QUERY_REFORMULATION`

***

### QueryMultiturnStep

* **Description:** Handle query multiturn.
* **Config Parameters:**
  * `query_multiturn_model: Optional[str] = None`
  * `allow_multi_turn: Optional[bool] = None`
  * `untrusted_multiturn_system_prompt: Optional[str] = None`
  * `template_query_multiturn: Optional[str] = None`
* **Inputs:** `query: str`
* **Outputs:** `reformulated_query: str`
* **UI Stream Types:** `QUERY_REFORMULATION`

***

### QueryRegexStrippingStep

* **Description:** Strip the query.
* **Config Parameters:** `query_regex_stripping: Optional[List[str]] = None`
* **Inputs:** `query: str`
* **Outputs:** `reformulated_query: str`
* **UI Stream Types:** None

***

### ReformulateQueryStep

* **Description:** Reformulate a query for datastore search.
* **Config Parameters:** None
* **Inputs:** `query: str`
* **Outputs:** `reformulated_query: str`, `translate_needed: bool`, `detected_language: str`
* **UI Stream Types:** `QUERY_REFORMULATION`

***

### RerankRetrievalsStep

* **Description:** Rerank retrievals.
* **Config Parameters:** `rerank_top_k: Optional[int] = None`, `reranker: Optional[str] = None`, `rerank_retrievals: Optional[bool] = None`, `rerank_instructions: Optional[str] = None`, `reranker_score_filter_threshold: Optional[float] = None`, `rerank_with_llm: Optional[bool] = None`, `template_rerank: Optional[str] = None`, `structured_output: Optional[bool] = None`,
* **Inputs:** `query: str`, `retrievals: Retrievals`
* **Outputs:** `retrievals: Retrievals`
* **UI Stream Types:** None

***

### ResponseGenerationStep

* **Description:** Generate a response based on query + retrievals.
* **Config Parameters:** None
* **Inputs:** `retrievals: Retrievals`, `query: str`, `translate_needed: bool`, `detected_language: str`
* **Outputs:** `response: str`, `attribution_result: AttributionResult`, `groundedness_scores: List[GroundednessScore]`
* **UI Stream Types:** `RETRIEVALS`, `GENERATION`, `ATTRIBUTION`, `GROUNDEDNESS`

***

### SalesforceSOSLStep

* **Description:** Execute SOSL searches against Salesforce.
* **Config Parameters:** `username: Optional[str] = None`, `password: Optional[SecretStr] = None`, `security_token: Optional[SecretStr] = None`, `client_id: Optional[str] = None`, `client_secret: Optional[SecretStr] = None`, `login_url: Optional[str] = None`, `auth_token_secret: Optional[SecretStr] = None`, `objects_to_return: str = "Case(Id, Subject, Status, Priority, Account.Name, Contact.Name)"`, `limit: int = 250`, `timeout: int = 30`
* **Inputs:** `query: str`
* **Outputs:** `search_results: str`
* **UI Stream Types:** None

***

### SearchShardMetadataStep

* **Description:** Search document shard metadata using instant search.
* **Config Parameters:** `default_size: int = 10`
* **Inputs:** `query: str`
* **Outputs:** `shard_search_results: List[Dict[str, Any]]`
* **UI Stream Types:** None

***

### SearchStep

* **Description:** Perform search using the search service.
* **Config Parameters:** `datastores: Optional[List[UUID]] = None`, `disable_structured_data_search: bool = False`
* **Inputs:** `query: str`, `query_embedding: List[float]`, `merged_embeded_reformulated_queries: List[Tuple[List[float], str]]`, `documents_filters: Optional[...]`
* **Outputs:** `retrievals: Retrievals`
* **UI Stream Types:** None

***

### SearchStructuredDataStep

* **Description:** Search structured data.
* **Config Parameters:** `datastores: Optional[List[UUID]] = None`
* **Inputs:** `query: str`
* **Outputs:** `retrievals: Retrievals`
* **UI Stream Types:** None

***

### SearchUnstructuredDataStep

* **Description:** Search unstructured data and return retrievals.
* **Config Parameters:** None
* **Inputs:** `query: str`
* **Outputs:** `retrievals: Retrievals`
* **UI Stream Types:** `QUERY_REFORMULATION`

***

### SetMemberStep

* **Description:** Update values of dictionaries or pydantic objects.
* **Config Parameters:** `overwrite: bool = False`
* **Inputs:** `input: Union[dict, BaseModel]`, `key: str`, `value: Any`
* **Outputs:** `output: Union[dict, BaseModel]`
* **UI Stream Types:** None

***

### ShardImageExtractionStep

* **Description:** Extract page images from PDF shard search results.
* **Config Parameters:** `default_dpi: int = 144`
* **Inputs:** `shard_search_results: List[Dict[str, Any]]`
* **Outputs:** `extracted_images: List[str]`
* **UI Stream Types:** None

***

### SliceStep

* **Description:** Slice a list from `start_index` to `end_index`.
* **Config:** None
* **Inputs:** `list: List[Any]`, `start_index: int`, `end_index: int`
* **Outputs:** `output: List[Any]`
* **UI Stream Types:** None

***

### TranslateQueryStep

* **Description:** Translate the query.
* **Config Parameters:** `translate_confidence: Optional[float] = None`, `template_translation_forward: Optional[str] = None`, `template_translation_reverse: Optional[str] = None`, `translate_model: Optional[str] = None`, `translate_needed: Optional[bool] = None`
* **Inputs:** `query: str`
* **Outputs:** `reformulated_query: str`, `translate_needed: bool`, `detected_language: str`
* **UI Stream Types:** None

***

### TranslateResponseStep

* **Description:** Translate the response.
* **Config Parameters:** `template_translation_forward: Optional[str] = None`, `template_translation_reverse: Optional[str] = None`, `translate_model: Optional[str] = None`
* **Inputs:** `generation_result: GenerationResult`, `translate_needed: bool`, `detected_language: str`
* **Outputs:** `generation_result: GenerationResult`
* **UI Stream Types:** `GENERATION`

***

### VisionLanguageModelStep

* **Description:** Vision language model inference with multimodal inputs.
* **Config Parameters:** `model_id: str = "vertex_ai/gemini-2.0-flash"`, `temperature: float = 0.0`, `max_tokens: int = 4096`, `structured_output: Optional[Dict[str, Any]] = None`
* **Inputs:** `query: str`, `images: List[str]`
* **Outputs:** `generation_result: GenerationResult`
* **UI Stream Types:** `GENERATION`

***

### WebSearchStep

* **Description:** Perform web search.
* **Config Parameters:** `model: str = "gemini-2.5-flash"`
* **Inputs:** `query: str`
* **Outputs:** `web_result: WebResult`
* **UI Stream Types:** None

***

### WebhookStep

* **Description:** Execute a webhook call with static and dynamic configuration.
* \*\*Config Parameters: `webhook_url: str`, `method: HttpMethod = HttpMethod.POST`, `auth_token: Optional[SecretStr] = None`, `timeout: int = 30`, `retries: int = 2`, `static_headers: Optional[Dict[str, str]] = None`, `webhook_name: str = "webhook-step"`
* **Inputs:** `context_data: Dict[str, Any]`
* **Outputs:** `webhook_result: Optional[Dict[str, Any]]`
* **UI Stream Types:** None

***

### WrapStep

* **Description:** Transform data by wrapping inputs in dictionaries.
* **Config Parameters:** `key: str = required`
* **Inputs:** `input: Any`
* **Outputs:** `output: Dict[str, Any]`
* **UI Stream Types:** None

## Additional Resources

* [Agent Composer Quickstart Guide](/quickstarts/agent-composer)
* [Agent Composer GUI How-to Guide](/how-to-guides/agent-composer-gui)