Configuration for the multi-query retriever.

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Step by step guide to setup a conversational chat app to RAG a Google Big Query datasource (or any other data source)

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Retrieve a JSON object of the session from path sessionId. Will also return a list of all tasks, tools, agents, models and datasources as a front end helper

Retrieve Session

Retrieve a JSON list of all sessions the user has access to. Will also return a list of all tasks, tools, agents, models and datasources as a front end helper

Retrieve Sessions

Get all messages associated to the path sessionId

Retrieve Messages

Create a new chat session from the parameter appId

Add a session

Cancel a session by Id, best practice to cancel a session once it has completed. The session and it's associated fields will still exist within the database under the same sessionId. The session can be completley removed from the database using the delete route AFTER this has been executed.

Cancel a session

Delete a session

Retrieve a JSON object of the retrieved app. Will also return a list of all tasks, tools, agents, models and datasources as a front end helper

Get App

Retrieve a JSON list of all apps the user has access to. Will also return a list of all tasks, tools, agents, models and datasources as a front end helper

Get Apps

Retrieve a JSON object of a single agent from agentId and the resourceSlug

Retrieve Agent

Retrieve a JSON list of all agents the user has access to

Retrieve Agents

Add an agent

Edit An Agent

Delete An Agent

Retrieve a JSON object with a singular task to be retrieved by id.

Retrieve Task

Retrieve a JSON list of all tasks the user has access to

Retrieve Tasks

Add A New Task

Edit A Task

Delete A Task

Retrieve a JSON object of a single tool from toolId and the resourceSlug

Retrieve Tool

Retrieve a JSON list of all tools the user has access to

Retrieve Tools

Add A New Tool

Edit an existing tool by its ID within the specified team.

Edit A Tool

Delete a tool by its ID within the specified team.

Delete A Tool

Retrieve a JSON object of a single model within the specified team by modelId.

Retrieve Model

Retrieve a JSON list of all models the user has access to within the specified team.

Retrieve Models

Add A New Model

Edit an existing model by its ID within the specified team.

Edit A Model

Delete a model by its ID within the specified team.

Delete A Model

Retrieve A Datasource

Retrieve a JSON list of all Datasources the user has access to within the specified team.

Retrieve Datasources

Edit Schedule In Datasource - This is marked as Uncomplete

Edit Datasource Streams - This Is Marked As Unfinished

Initialise an Airbyte synchronisation for an existing datasource object

Sync Datasource

Test a new datasource. This is required to gather the datasource schema, tables and values to continue to the next stage of addition. This MUST be executed first when adding a new datasource

Test A Datasource To Be Added

Second stage of adding Datasource (check test datasource for the first step), this connects the datasource to a vectordb, creates a connection between the datasource and airbyte, starts a job to synchronise the rows and finally creates a tool for the datasource. A tool for the datasource is required as within agents a datasource is used as a 'tool' just the same as any other tool, this is required for the 'RAG' process.