`CodegenPipeline`#

class ansys.cfx.mcp.common.codegen.CodegenPipeline(*, store: ansys.cfx.mcp.common.conversation.ConversationStore)#

Default pipeline: delegate to the backend.

Subclass and override generate / clarify to add LLM orchestration, retrieval, validation passes, etc.

Overview#

Methods

`generate`	Generate CFX Python code or a clarification response from a user prompt.
`clarify`	Continue code generation after a clarification answer.

Attributes

from ansys.cfx.mcp.common.codegen import CodegenPipeline

async CodegenPipeline.generate(*, backend: ansys.cfx.mcp.common.backend.Backend, prompt: str, session_id: str | None = None, context: dict[str, Any] | None = None) → ansys.cfx.mcp.common.models.CodegenResult#

Generate CFX Python code or a clarification response from a user prompt.

Parameters:

backendBackend: Backend that provides CFX state, validation, and execution services.
promptstr: Natural-language user request to process.
session_idOptional[str], optional: Conversation identifier used to retrieve or continue context. Default is None.
contextOptional[dict[str, Any]], optional: Additional context supplied by the caller. Default is None.

Returns:

async CodegenPipeline.clarify(*, backend: ansys.cfx.mcp.common.backend.Backend, session_id: str, clarification_id: str, answer: str) → ansys.cfx.mcp.common.models.CodegenResult#

Continue code generation after a clarification answer.

Parameters:

backendBackend: Backend that provides CFX state, validation, and execution services.
session_idstr: Conversation identifier used to retrieve or continue context.
clarification_idstr: Identifier of the clarification being answered or checked.
answerstr: User answer to the clarification prompt.

Returns: