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For the complete documentation index for agents and LLMs, see llms.txt.

Release 2026.7

July 2026 brings updates to how agent pipelines handle chat history and adds more control over pipeline versions.

New OpenAI GPT-5.6 Models​

Three new GPT-5.6 model variants are now available on the platform: GPT-5.6 Sol, GPT-5.6 Terra, and GPT-5.6 Luna. You can select them in the LLM or Agent component configuration in Builder.

GPT-5.6 models support a reasoning_effort parameter (none, low, medium, high, xhigh, max) and a reasoning_summary parameter (auto, concise, detailed) to control the depth and verbosity of the model's reasoning process. GPT-5.5 and GPT-5.5 Pro have also been updated with reasoning_effort (up to xhigh) and reasoning_summary support. You can set these parameters on the Advanced tab of the component configuration panel.

More Control Over Pipeline Versions​

Two new actions are now available in the pipeline versions list in Builder:

  • Finalize — converts a draft version into a permanent, numbered version. Use this when you want to lock in a draft without deploying it.
  • Set as default — marks a non-draft version as the default. The default version is used by endpoints when a request identifies a pipeline by name or ID but does not specify a version. Default versions appear with a gold star Default tag in the versions list.

For details, see Manage Pipeline Versions.

AI Assistant in Builder​

Builder now has a built-in AI assistant you can chat with directly in the pipeline editor. Click AI Assistant to open the chat panel and start a conversation.

AI Assistant in Builder

The AI assistant was designed with debugging in mind — you can describe a pipeline issue, paste error messages, or ask it to help you understand unexpected behavior. But it's not limited to debugging: you can also use it to get help with pipeline design, understand how components work, or explore other use cases as you build.

When you have issues listed in the Issues panel, you can also click Fix with AI next to any issue. The AI assistant opens, reasons through the fix, and can apply it for you.

For details, see Debug with Builder.

Bedrock Prompt Caching​

Amazon Bedrock models now support prompt caching for system prompts. You can set the system_cachepoint_config_ttl for models hosted on Amazon Bedrock to cache your system prompt for 5 minutes ("5m") or 1 hour ("1h"), reducing latency and cost for repeated requests that share the same system prompt. The system prompt must stay static, with no parameters, for the cache to work. For details, see AmazonBedrockChatGenerator and Use Amazon Bedrock Models.

Full Message History for Agent Pipelines Beta​

You can now control how much chat history is replayed to agent pipelines on each turn using the chat_history_granularity setting. By default, the platform sends only user query and final answer pairs to the pipeline (QUERY_ANSWER). Setting granularity to ALL_MESSAGES sends the complete message trace from the previous turn — including tool calls, tool results, and reasoning steps — so agents retain full context across follow-up requests.

You can set this per request through the API or as a pipeline-level default in the pipeline YAML under history.granularity:

history:
  granularity: all_messages

The API field chat_history_granularity accepts ALL_MESSAGES or QUERY_ANSWER (uppercase). The YAML field accepts lowercase values. If both are set, the API request value takes priority over the YAML default.

For details, see Agent Memory.

Search History Export Improvements​

Pipeline Version ID in CSV Export​

You can now filter the search history CSV export by pipeline version ID. The export also includes a pipeline_version_id column. Each row shows the ID of the pipeline version that served the query, so you can compare behavior across versions or investigate queries tied to a specific deployment.

Feedback Created At Column​

The Search History table and CSV export now include a Feedback Created At column that shows when a user submitted feedback for each query. This column is separate from Created At, which records when the query was made. The column appears by default in both extractive and generative pipeline history views. In the CSV, the column is named feedback_created_at and is empty when no feedback has been given for a query.

For details, see Monitor Pipeline Performance.