QConnect#
Client#
- class QConnect.Client#
A low-level client representing Amazon Q Connect
Note
Powered by Amazon Bedrock: Amazon Web Services implements automated abuse detection. Because Amazon Q in Connect is built on Amazon Bedrock, users can take full advantage of the controls implemented in Amazon Bedrock to enforce safety, security, and the responsible use of artificial intelligence (AI).
Amazon Q in Connect is a generative AI customer service assistant. It is an LLM-enhanced evolution of Amazon Connect Wisdom that delivers real-time recommendations to help contact center agents resolve customer issues quickly and accurately.
Amazon Q in Connect automatically detects customer intent during calls and chats using conversational analytics and natural language understanding (NLU). It then provides agents with immediate, real-time generative responses and suggested actions, and links to relevant documents and articles. Agents can also query Amazon Q in Connect directly using natural language or keywords to answer customer requests.
Use the Amazon Q in Connect APIs to create an assistant and a knowledge base, for example, or manage content by uploading custom files.
For more information, see Use Amazon Q in Connect for generative AI powered agent assistance in real-time in the Amazon Connect Administrator Guide.
import boto3 client = boto3.client('qconnect')
These are the available methods:
- activate_message_template
- can_paginate
- close
- create_ai_agent
- create_ai_agent_version
- create_ai_prompt
- create_ai_prompt_version
- create_assistant
- create_assistant_association
- create_content
- create_content_association
- create_knowledge_base
- create_message_template
- create_message_template_attachment
- create_message_template_version
- create_quick_response
- create_session
- deactivate_message_template
- delete_ai_agent
- delete_ai_agent_version
- delete_ai_prompt
- delete_ai_prompt_version
- delete_assistant
- delete_assistant_association
- delete_content
- delete_content_association
- delete_import_job
- delete_knowledge_base
- delete_message_template
- delete_message_template_attachment
- delete_quick_response
- get_ai_agent
- get_ai_prompt
- get_assistant
- get_assistant_association
- get_content
- get_content_association
- get_content_summary
- get_import_job
- get_knowledge_base
- get_message_template
- get_paginator
- get_quick_response
- get_recommendations
- get_session
- get_waiter
- list_ai_agent_versions
- list_ai_agents
- list_ai_prompt_versions
- list_ai_prompts
- list_assistant_associations
- list_assistants
- list_content_associations
- list_contents
- list_import_jobs
- list_knowledge_bases
- list_message_template_versions
- list_message_templates
- list_quick_responses
- list_tags_for_resource
- notify_recommendations_received
- put_feedback
- query_assistant
- remove_assistant_ai_agent
- remove_knowledge_base_template_uri
- render_message_template
- search_content
- search_message_templates
- search_quick_responses
- search_sessions
- start_content_upload
- start_import_job
- tag_resource
- untag_resource
- update_ai_agent
- update_ai_prompt
- update_assistant_ai_agent
- update_content
- update_knowledge_base_template_uri
- update_message_template
- update_message_template_metadata
- update_quick_response
- update_session
- update_session_data
Paginators#
Paginators are available on a client instance via the get_paginator method. For more detailed instructions and examples on the usage of paginators, see the paginators user guide.
The available paginators are:
- ListAIAgentVersions
- ListAIAgents
- ListAIPromptVersions
- ListAIPrompts
- ListAssistantAssociations
- ListAssistants
- ListContentAssociations
- ListContents
- ListImportJobs
- ListKnowledgeBases
- ListMessageTemplateVersions
- ListMessageTemplates
- ListQuickResponses
- QueryAssistant
- SearchContent
- SearchMessageTemplates
- SearchQuickResponses
- SearchSessions