Skip to main content
The AI Copilot API exposes programmatic access to the same assistants you use in the product: natural-language pipeline generation, config suggestions, documentation drafts, static checks on custom code, provider health, and notebook-focused helpers. Responses depend on your workspace’s enabled models and data policies. 
Authorization: Bearer YOUR_API_KEY_HERE
If your workspace uses URL versioning, insert /v1 before /api in the path. See API reference.
Long-running generations may return 202 with a job_id you poll on a status endpoint where your deployment supports async mode; the examples below show a common synchronous 200 shape.

​
Check AI status

GET https://api.planasonix.com/api/ai/status

{
  "data": {
    "available": true,
    "providers": [
      {
        "id": "azure_openai",
        "status": "healthy",
        "models": ["gpt-4o", "gpt-4o-mini"],
        "last_error": null
      },
      {
        "id": "anthropic",
        "status": "degraded",
        "models": ["claude-3-5-sonnet-20241022"],
        "last_error": "elevated_latency_region=us-east-1"
      }
    ],
    "default_model": "gpt-4o",
    "knowledge_base_indexed_docs": 1284
  }
}

​
Generate pipeline from natural language

POST https://api.planasonix.com/api/ai/generate-pipeline
Content-Type: application/json

{
  "prompt": "Ingest daily CSV drops from S3 prefix s3://acme-landing/sales/ into Snowflake table analytics.raw_sales, dedupe on order_id, and convert amounts to USD using the fx_rates table.",
  "target_environment": "staging",
  "constraints": {
    "max_nodes": 24,
    "allowed_credential_types": ["aws", "database"]
  }
}

{
  "data": {
    "summary": "Four-node pipeline: S3 source → type inference → dedupe on order_id → Snowflake load with currency join",
    "definition": {
      "nodes": [
        { "id": "n1", "type": "s3_source", "config": { "prefix": "s3://acme-landing/sales/" } },
        { "id": "n2", "type": "schema_inference", "config": {} },
        { "id": "n3", "type": "dedupe", "config": { "keys": ["order_id"] } },
        {
          "id": "n4",
          "type": "snowflake_load",
          "config": { "table": "analytics.raw_sales", "write_mode": "merge" }
        }
      ],
      "edges": [
        { "from": "n1", "to": "n2" },
        { "from": "n2", "to": "n3" },
        { "from": "n3", "to": "n4" }
      ]
    },
    "warnings": [
      "Specify credential_id for S3 and Snowflake before first run."
    ]
  }
}

​
Enhance existing pipeline

POST https://api.planasonix.com/api/ai/enhance-pipeline
Content-Type: application/json

{
  "pipeline_id": "pl_01hqxyz",
  "prompt": "Add row-level checks: order_total must equal sum(line_items); flag negative quantities.",
  "focus": "data_quality"
}

{
  "data": {
    "pipeline_id": "pl_01hqxyz",
    "suggestions": [
      {
        "kind": "add_node",
        "after": "n_transform",
        "node": {
          "type": "assertion",
          "config": {
            "expression": "order_total = SUM(line_items.amount) OVER (PARTITION BY order_id)"
          }
        }
      }
    ],
    "rationale": "Assertions keep bad aggregates from reaching the warehouse without blocking the whole batch when configured in warn mode."
  }
}

​
Generate node configuration

POST https://api.planasonix.com/api/ai/generate-node-config
Content-Type: application/json

{
  "node_type": "sql",
  "intent": "Pivot monthly revenue columns into long format for BI tools",
  "sample_input_schema": {
    "columns": [
      { "name": "region", "type": "string" },
      { "name": "rev_2024_01", "type": "decimal" },
      { "name": "rev_2024_02", "type": "decimal" }
    ]
  }
}

{
  "data": {
    "node_type": "sql",
    "config": {
      "query": "SELECT region, month, revenue FROM analytics.wide_monthly UNPIVOT (revenue FOR month IN (rev_2024_01, rev_2024_02))"
    },
    "dialect": "snowflake"
  }
}

​
Generate documentation

POST https://api.planasonix.com/api/ai/generate-documentation
Content-Type: application/json

{
  "subject_type": "pipeline",
  "subject_id": "pl_01hqxyz",
  "audience": "data_engineers",
  "format": "markdown"
}

{
  "data": {
    "title": "Finance mart refresh",
    "markdown": "## Overview\n\nThis pipeline …\n\n## Inputs\n\n…\n\n## Failure modes\n\n…"
  }
}

​
Validate custom code

POST https://api.planasonix.com/api/ai/check-code
Content-Type: application/json

{
  "language": "sql",
  "dialect": "bigquery",
  "code": "SELECT customer_id, SUM(amount) AS total FROM `analytics.sales` GROUP BY 1 HAVING total > 0"
}

{
  "data": {
    "valid": true,
    "issues": [],
    "suggestions": [
      "Consider qualifying column names with table alias for readability."
    ]
  }
}

​
Test AI provider connection

POST https://api.planasonix.com/api/ai/test-provider
Content-Type: application/json

{
  "provider_id": "azure_openai",
  "model": "gpt-4o-mini"
}

{
  "data": {
    "provider_id": "azure_openai",
    "ok": true,
    "latency_ms": 412,
    "sample_completion": "pong"
  }
}

​
Parse documentation for knowledge base

POST https://api.planasonix.com/api/ai/parse-docs
Content-Type: application/json

{
  "source_url": "https://internalwiki.example.com/data/onboarding",
  "ingest_mode": "incremental",
  "tags": ["onboarding", "pipelines"]
}

{
  "data": {
    "job_id": "kbjob_01j9kd4e5f6g7h8i9",
    "chunks_indexed": 56,
    "status": "completed"
  }
}

​
Knowledge — feedback

POST https://api.planasonix.com/api/ai/knowledge/feedback
Content-Type: application/json

{
  "message_id": "msg_01chat_turn",
  "helpful": false,
  "reason": "cited deprecated connector",
  "correction": "Use jdbc_sap_hana instead of generic jdbc for HANA 2.0"
}

{
  "data": {
    "recorded": true,
    "feedback_id": "fbb_01j9ke5f6g7h8i9j0"
  }
}

​
Knowledge — stats

GET https://api.planasonix.com/api/ai/knowledge/stats

{
  "data": {
    "documents": 1284,
    "chunks": 98210,
    "last_full_reindex_at": "2025-03-25T04:00:00Z",
    "top_sources": [
      { "host": "internalwiki.example.com", "chunks": 21034 },
      { "host": "docs.planasonix.com", "chunks": 15402 }
    ]
  }
}

​
Knowledge — recent activity

GET https://api.planasonix.com/api/ai/knowledge/recent

{
  "data": [
    {
      "type": "ingest",
      "source": "confluence://DATA/standards",
      "status": "success",
      "at": "2025-03-27T08:12:00Z"
    }
  ]
}

​
Notebook — complete cell

POST https://api.planasonix.com/api/ai/notebook/complete
Content-Type: application/json

{
  "kernel": "python",
  "prefix": "import pandas as pd\n\ndf = pd.read_parquet(\"s3://acme-landing/sales/2025-03-26.parquet\")\n# TODO: compute revenue by region\n",
  "cursor_line": 4
}

{
  "data": {
    "completion": "summary = df.groupby(\"region\")[\"amount_usd\"].sum().reset_index(name=\"revenue_usd\")\nprint(summary.head())\n"
  }
}

​
Notebook — explain error

POST https://api.planasonix.com/api/ai/notebook/explain-error
Content-Type: application/json

{
  "kernel": "python",
  "traceback": "KeyError: 'amount_usd'",
  "cell_source": "df.groupby(\"region\")[\"amount_usd\"].sum()"
}

{
  "data": {
    "explanation": "The column amount_usd is missing from the dataframe—likely the parquet uses amount_cents instead.",
    "suggested_fix": "df[\"amount_usd\"] = df[\"amount_cents\"] / 100.0"
  }
}

​
Notebook — optimize

POST https://api.planasonix.com/api/ai/notebook/optimize
Content-Type: application/json

{
  "kernel": "python",
  "cell_source": "for i in range(len(df)):\n    df.at[i, 'tax'] = df.at[i, 'subtotal'] * 0.08\n",
  "goal": "vectorize for large dataframes"
}

{
  "data": {
    "optimized": "df[\"tax\"] = df[\"subtotal\"] * 0.08\n"
  }
}

​
Notebook — generate cell

POST https://api.planasonix.com/api/ai/notebook/generate
Content-Type: application/json

{
  "kernel": "sql",
  "dialect": "snowflake",
  "intent": "Compare this week vs last week signups by country, top 10 countries only"
}

{
  "data": {
    "cell_source": "WITH bounds AS (\n  SELECT\n    DATE_TRUNC('week', CURRENT_DATE()) AS this_week,\n    DATE_TRUNC('week', CURRENT_DATE()) - INTERVAL '7 day' AS last_week\n)\nSELECT country, …"
  }
}

AI Copilot overview

Product capabilities and guardrails.

Knowledge base

Curating sources the assistant can cite.