# Ask a Question

Endpoint: POST /platform-config/v1/questions
Version: 1.0.0

## Request fields (application/json):

  - `tenantId` (string)
    Tenant ID of the user
    Example: "tenant-123"

  - `userId` (string)
    User ID of the requester
    Example: "user-456"

  - `question` (string)
    User query to be answered
    Example: "How do I reset my password?"

  - `knowledgeBaseId` (string)
    KnowledgeBase Identifier
    Example: "c72ab301-4658-4252-9f5f-aeb742bd38d9"

  - `ragPrompt` (any)
    Document RAG system prompy
    Example: "you are intelliget system prompt...."

## Response 200 fields (application/json):

  - `questionId` (any)
    Unique identifier for the question
    Example: "4d649cd3-54b8-4295-8dd7-23da0f913de4"

  - `answer` (any)
    Generated answer from the RAG system
    Example: "To reset your password, go to Settings > Security > Reset Password."

  - `chartable` (any)
    whether genearatred answer has chart available or not
    Example: true

  - `chart` (any)
    chart data
    Example: "iVBORw0KGgoAAAANSUhEUgAAC7gAAAcICAYAAACsf4x4AAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjMsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvZiW"

  - `context` (array)
    List of document chunks that formed the context for the answer

  - `context.content` (any)
    Content of the document chunk
    Example: "This is a relevant paragraph from the document."

  - `context.doc_name` (any)
    Name of the document
    Example: "user_manual.pdf"

  - `context.score` (any)
    Relevance score of the document chunk
    Example: 0.9982209929893932

  - `followUpQuestions` (array)
    List of follow-up questions that can be asked post QnA
    Example: ["What is the next step?","Can you elaborate on that?"]

  - `tag_result` (object)
    Detailed result object from tag query execution

  - `tag_result.sql_query` (any)
    SQL query generated
    Example: "SELECT * FROM \"xf_destination_param\";"

  - `tag_result.description` (any)
    Description of what the query does

  - `tag_result.follow_up_questions` (array)
    Follow-up questions suggested
    Example: ["What is the trend over time?","Any filters applied?"]

  - `tag_result.is_valid_sql` (any)
    Indicates if the SQL is valid
    Example: "True"

  - `tag_result.reasoning` (any)
    Reason why validation succeeded or failed
    Example: "SQL is syntactically correct."

  - `tag_result.query_execution_result` (array)
    Result of executing the query

  - `tag_result.final_answer` (any)
    Final answer or interpretation for the end user