ceven

Langbase

Manages your AI infrastructure by automating the creation of pipes, organizing conversation threads, and syncing long term memory for your deployed agents.

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Why use Ceven?

  1. AI native Langbase integration

    • Describe the outcome and Ceven picks the right Langbase calls, fills the parameters, and checks the result.
    • Structured, agent friendly tool schemas so each call runs reliably instead of by guesswork.
    • Rich coverage for reading, writing, and querying your Langbase data, across all 20 of its actions.

  2. Managed auth

    • Built in OAuth with automatic token refresh and rotation.
    • One place to manage, scope, and revoke Langbase access.
    • Per user and per environment credentials instead of shared keys.

  3. Agent optimized design

    • Actions are tuned from real success and error rates so reliability climbs over time.
    • Full execution logs so you always know what ran in Langbase, when, and on whose behalf.
    • The agent pauses and asks when Langbase is unclear instead of plowing ahead.

  4. Enterprise grade security

    • Fine grained access so you control which agents and people can reach Langbase.
    • Least privilege by default, read scopes first and only the writes a workflow needs.
    • A full audit trail of every Langbase action to support review and sign off.

Supported tools

Every action Ceven's agents can run on Langbase, and when to use it.

Split content into chunks
Use this when processing large text segments to fit downstream limits before storing them in memory.
Create thread
Use this when starting a fresh chat session or grouping messages into a distinct thread.
List documents in memory
Pull document metadata and vectors from a specific memory using a name and pagination.
Get thread details
Retrieve the full details of a specific conversation thread using its unique ID.
List thread messages
Fetch all messages within a conversation thread after you have the thread ID.
Create memory
Store a new memory record in Langbase after confirming the memory details.
Delete memory
Permanently remove a stored memory from the platform by its name.
List memories
Fetch all stored memory objects to provide context for retrieval tasks.
Create pipe
Deploy a new pipe with specific parameters to get an API key and URL.
List all pipes
Retrieve the complete list of active pipes associated with your account.
Update pipe settings
Modify the configuration or system prompt of an existing Langbase pipe.
Clear thread history
Wipe messages from a specific thread to reset the conversation state.
Create a new pipe
Tool to create a new pipe. use after configuring pipe parameters. returns pipe details including api key and url.

13 actions · scroll to see them all

Frequently asked questions

Ceven monitors your Langbase memory usage in real time to prevent overflow. When a memory store reaches its capacity based on your current plan, the agent can be configured to either trigger an alert or automatically archive the oldest documents. It uses the list documents tool to evaluate the size of the store before attempting a write operation. This ensures that your AI agents do not experience latency or failure during critical user interactions due to memory saturation. You can set custom thresholds within your Ceven workflow to manage how the agent handles these limits across different memory objects.
Yes. You can build a workflow that creates a new Langbase pipe every time you update a prompt in your version control system. Ceven takes the new prompt, calls the create pipe action, and then updates your application environment variables with the new pipe URL and API key. This allows for seamless A B testing where you route a percentage of traffic to a new pipe to compare performance. Once the new version is validated, the agent can delete the old pipe to keep your infrastructure clean and organized.
The most effective method is using the split content into chunks action. Large documents often exceed the token limits of the underlying models used by Langbase pipes. Ceven automates this by taking a raw file, breaking it into smaller overlapping segments, and then uploading those segments into a memory store. This process preserves the semantic meaning of the text while ensuring that the retrieval mechanism can pinpoint the most relevant sections. The agent manages the sequence of chunks so that the original order is maintained if the full context is needed later.
Ceven maps your application user IDs to Langbase thread IDs. When a user sends a message, Ceven first checks if a thread exists for that user. If not, it calls the create thread action and stores the mapping in your database. For every subsequent message, the agent pulls the thread details and previous messages to maintain conversation state. This allows you to build highly personalized AI experiences where the agent remembers past interactions without you having to manage the complex state logic manually within your own application code.
Yes. Langbase imposes rate limits on API requests that vary depending on your subscription tier. For example, free tier accounts have significantly lower requests per minute for pipe executions and memory writes. If Ceven hits a rate limit, it will receive a 429 error from the Langbase API. We have built in exponential backoff logic to handle these events, but for high volume production workloads, we recommend upgrading your Langbase plan to avoid delays. You can monitor these limits through the Langbase dashboard to ensure your workflows stay performant.
Ceven can facilitate data migration by reading documents from one memory and writing them into another. The agent uses the list documents in memory tool to extract the content and metadata, then applies the create memory or upload actions to populate the new store. This is particularly useful when you are restructuring how your agent personas are organized or when you want to consolidate multiple small memories into one large knowledge base for better retrieval efficiency across your entire AI application.
Ceven uses secure API key management to interact with Langbase. Your keys are encrypted at rest and are only ever used to sign requests to the Langbase API. We do not share these keys with any third parties or store them in plain text. All communication between the Ceven platform and Langbase happens over HTTPS. You can rotate your Langbase API keys at any time and update them in the Ceven integration settings to maintain a high security posture for your AI infrastructure.
Absolutely. You can set up a scheduled workflow that lists all threads and checks their last activity date. If a thread has been inactive for a specific period, such as thirty days, Ceven can call the delete memory or thread management tools to remove the data. This helps keep your Langbase environment tidy and can reduce costs if you are on a plan that charges based on the amount of stored data. The agent can also archive the final state of the thread to a database before deletion.

Alternatives to Langbase

Other tools that solve a similar problem. Ceven supports these too, so you can switch or run more than one at once.

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