o i @sdZddlmZddlmZddlmZmZmZm Z m Z ddl m Z ddl mZddlmZmZzddlmZdd lmZWneyVZz ed ed ed Z[wwGd ddeZd S)zStrands Agent integration for Pipecat. This module provides integration with Strands Agents for handling conversational AI interactions. It supports both single agent and multi-agent graphs. )Optional)logger)FrameLLMContextFrameLLMFullResponseEndFrameLLMFullResponseStartFrame LLMTextFrame) LLMTokenUsage)OpenAILLMContextFrame)FrameDirectionFrameProcessor)Agent)GraphzIIn order to use Strands Agents, you need to `pip install strands-agents`.zMissing module: NcseZdZdZ   ddeedeedeeffdd Zde d e ffd d Z d efd dZ de fddZdededefddZZS)StrandsAgentsProcessoraProcessor that integrates Strands Agents with Pipecat's frame pipeline. This processor takes LLM message frames, extracts the latest user message, and processes it through either a single Strands Agent or a multi-agent Graph. The response is streamed back as text frames with appropriate response markers. Supports both single agent streaming and graph-based multi-agent workflows. Nagentgraphgraph_exit_nodecsLt||_||_||_|js|jsJd|jr"|js$JddSdS)aInitialize the Strands Agents processor. Args: agent: The Strands Agent to use for single-agent processing. graph: The Strands multi-agent Graph to use for graph-based processing. graph_exit_node: The exit node name when using graph-based processing. Raises: AssertionError: If neither agent nor graph is provided, or if graph is provided without a graph_exit_node. z&Either agent or graph must be providedz5graph_exit_node must be provided if graph is providedN)super__init__rrr)selfrrr __class__`/home/ubuntu/.local/lib/python3.10/site-packages/pipecat/processors/frameworks/strands_agents.pyr(s zStrandsAgentsProcessor.__init__frame directioncstt||IdHt|ttfr/|j}|r-|d}|t|d IdHdSdS| ||IdHdS)zProcess incoming frames and handle LLM message frames. Args: frame: The incoming frame to process. direction: The direction of frame flow in the pipeline. Ncontent) r process_frame isinstancerr context get_messages_ainvokestrstrip push_frame)rrrmessages last_messagerrrrCs  z$StrandsAgentsProcessor.process_frametextc s td|d}zfz|tIdH|IdH|IdH|jr|j|IdH}|r=|IdHd}z`|j |j }td|| D]K}t |dd}t |trd|vr|dD]}t |tr~d|vr~|tt|dIdHqe||jjd d |jjd d |jjd d IdHqPWnty}ztd |WYd}~nnd}~ww|j|2za3dHW} t | trd| vr|tt| dIdH|r|IdHd}t | trd| vrd| dvrd| ddvr| ddd} || d d | d d | d d IdHq6Wn1ty4t|dYn tyS} z|jd| | dIdHWYd} ~ nd} ~ wwW|ra|IdHd}|IdH|tIdHdS|r|IdHd}|IdH|tIdHw)zInvoke the Strands agent with the provided text and stream results as Pipecat frames. Args: text: The user input text to process through the agent or graph. zInvoking Strands agent with: TNFz Node result: messagerr( inputTokensr outputTokens totalTokensz-Failed to extract messages from GraphResult: dataeventmetadatausagez! generator was closed prematurelyzUnknown error occurred: ) error_msg exception)rdebugr%rstart_processing_metricsstart_ttfb_metricsr invoke_asyncstop_ttfb_metricsresultsrget_agent_resultsgetattrrdictrr#_report_usage_metricsmetricsaccumulated_usageget Exceptionwarningr stream_async GeneratorExit push_errorstop_processing_metricsr) rr( ttfb_tracking graph_result node_result agent_resultr)block parse_errr.r0errrr"Ss           &zStrandsAgentsProcessor._ainvokereturncCsdS)zCheck if this service can generate performance metrics. Returns: True as this service supports metrics generation. Tr)rrrrcan_generate_metricssz+StrandsAgentsProcessor.can_generate_metrics prompt_tokenscompletion_tokens total_tokenscs$t|||d}||IdHdS)N)rOrPrQ)r start_llm_usage_metrics)rrOrPrQtokensrrrr<sz,StrandsAgentsProcessor._report_usage_metrics)NNN)__name__ __module__ __qualname____doc__rr rr#rrr rr"boolrNintr< __classcell__rrrrrs, Gr)rWtypingrlogururpipecat.frames.framesrrrrrpipecat.metrics.metricsr 1pipecat.processors.aggregators.openai_llm_contextr "pipecat.processors.frame_processorr r strandsr strands.multiagent.graphrModuleNotFoundErrorrLerrorr@rrrrrs