Interactions API: Breaking changes migration guide (May 2026)

The v1beta Interactions API is introducing breaking changes that restructure the API shape to support future capabilities like mid-flight steering and asynchronous tool calls. This page explains what's changing and provides before-and-after code examples to help you migrate. There are two categories of changes:

  1. Steps schema: A new steps array replaces the outputs array, providing a structured timeline of each interaction turn.
  2. Output format configuration: A new polymorphic response_format consolidates all output format controls and removes response_mime_type.

Follow the steps in How to migrate to the new schema to update your integration.

Core change: outputs to steps

The new schema replaces the outputs array with a steps array.

  • Legacy: Responses returned a flat outputs array containing only the model's generated content.
  • New schema: Responses return a steps array containing structured steps with type discriminators.

POST /interactions returns only output steps. GET /interactions/{id} returns the full step timeline, including the initial user_input step.

Basic input/output (unary)

Before (legacy)

Python

# Request
interaction = client.interactions.create(
    model="gemini-3.7-flash", input="Tell me a joke."
)

# Response access
print(interaction.outputs[-1].text)

JavaScript

// Request
const interaction = await client.interactions.create({
    model: 'gemini-3.7-flash',
    input: 'Tell me a joke.'
});

// Response access
console.log(interaction.outputs[-1].text);

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions?key=$GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3.7-flash",
    "input": "Tell me a joke."
  }'

// Response
{
  "id": "int_123",
  "role": "model",
  "outputs": [
    {
      "type": "text",
      "text": "Why did the chicken cross the road?"
    }
  ]
}

After (new schema)

Python

# Request
interaction = client.interactions.create(
    model="gemini-3.7-flash", input="Tell me a joke."
)

# Response access (Recommended sugar)
print(interaction.output_text)

JavaScript

// Request
const interaction = await client.interactions.create({
    model: 'gemini-3.7-flash',
    input: 'Tell me a joke.'
});

// Response access (Recommended sugar)
console.log(interaction.output_text);

[sdk-convenience]: /gemini-api/docs/interactions-overview#sdk-sugar

REST

# Opt-in needed before May 26th
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions?key=$GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -H "Api-Revision: 2026-05-20" \
  -d '{
    "model": "gemini-3.7-flash",
    "input": "Tell me a joke."
  }'

// POST Response
{
  "id": "int_123",
  "steps": [
    {
      "type": "model_output",
      "content": [
        {
          "type": "text",
          "text": "Why did the chicken cross the road?"
        }
      ]
    }
  ]
}

// GET /v1beta/interactions/int_123 (returns full timeline including input)
{
  "id": "int_123",
  "steps": [
    {
      "type": "user_input",
      "content": [
        { "type": "text", "text": "Tell me a joke." }
      ]
    },
    {
      "type": "model_output",
      "content": [
        {
          "type": "text",
          "text": "Why did the chicken cross the road?"
        }
      ]
    }
  ]
}

Function calling

The request structure remains unchanged, but the response replaces the flat outputs content with structured steps.

Before (legacy)

Python

# Accessing function call in legacy schema
for output in interaction.outputs:
    if output.type == "function_call":
        print(f"Calling {output.name} with {output.arguments}")

JavaScript

// Accessing function call in legacy schema
for (const output of interaction.outputs) {
    if (output.type === 'function_call') {
        console.log(`Calling ${output.name} with ${JSON.stringify(output.arguments)}`);
    }
}

REST

// Response
{
  "id": "int_001",
  "role": "model",
  "status": "requires_action",
  "outputs": [
    {
      "type": "thought",
      "signature": "abc123..."
    },
    {
      "type": "function_call",
      "id": "fc_1",
      "name": "get_weather",
      "arguments": { "location": "Boston, MA" }
    }
  ]
}

After (new schema)

Python

# Accessing function call in new steps schema
for step in interaction.steps:
    if step.type == "function_call":
        print(f"Calling {step.name} with {step.arguments}")

JavaScript

// Accessing function call in new steps schema
for (const step of interaction.steps) {
    if (step.type === 'function_call') {
        console.log(`Calling ${step.name} with ${JSON.stringify(step.arguments)}`);
    }
}

REST

// POST Response
{
  "id": "int_001",
  "status": "requires_action",
  "steps": [
    {
      "type": "thought",
      "summary": [{
        "type": "text",
        "text": "I need to check the weather in Boston..."
      }],
      "signature": "abc123..."
    },
    {
      "type": "function_call",
      "id": "fc_1",
      "name": "get_weather",
      "arguments": { "location": "Boston, MA" }
    }
  ]
}

Server-side tools

Server-side tools (like Google Search or Code Execution) now yield specific step types in the steps array. While the legacy schema returned these operations as specific content types within the outputs array, the new schema moves them into the steps array. The following examples use Google Search.

Before (legacy)

Python

# Accessing search results in legacy schema
for output in interaction.outputs:
    if output.type == "google_search_call":
        print(f"Searched for: {output.arguments.queries}")
    elif output.type == "google_search_result":
        print(f"Found results: {output.result.rendered_content}")

JavaScript

// Accessing search results in legacy schema
for (const output of interaction.outputs) {
    if (output.type === 'google_search_call') {
        console.log(`Searched for: ${output.arguments.queries}`);
    } else if (output.type === 'google_search_result') {
        console.log(`Found results: ${output.result.renderedContent}`);
    }
}

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions?key=$GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3.7-flash",
    "input": "Who won the last Super Bowl?",
    "tools": [
      { "type": "google_search" }
    ]
  }'

// Response
{
  "id": "int_456",
  "outputs": [
    {
      "type": "google_search_call",
      "id": "gs_1",
      "arguments": { "queries": ["last Super Bowl winner"] }
    },
    {
      "type": "google_search_result",
      "call_id": "gs_1",
      "result": {
        "rendered_content": "<div>...</div>",
        "url": "https://www.nfl.com/super-bowl"
      }
    },
    {
      "type": "text",
      "text": "The Kansas City Chiefs won the last Super Bowl.",
      "annotations": [
        {
          "start_index": 4,
          "end_index": 22,
          "source": "https://www.nfl.com/super-bowl"
        }
      ]
    }
  ],
  "status": "completed"
}

After (new schema)

Python

# Accessing search results in new steps schema
for step in interaction.steps:
    if step.type == "google_search_call":
        print(f"Searched for: {step.arguments.queries}")
    elif step.type == "google_search_result":
        print(f"Found results: {step.result[0].search_suggestions}")

JavaScript

// Accessing search results in new steps schema
for (const step of interaction.steps) {
    if (step.type === 'google_search_call') {
        console.log(`Searched for: ${step.arguments.queries}`);
    } else if (step.type === 'google_search_result') {
        console.log(`Found results: ${step.result[0].search_suggestions}`);
    }
}

REST

# Opt-in needed before May 26th
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions?key=$GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -H "Api-Revision: 2026-05-20" \
  -d '{
    "model": "gemini-3.7-flash",
    "input": "Who won the last Super Bowl?",
    "tools": [
      { "type": "google_search" }
    ]
  }'

// POST Response
{
  "id": "int_456",
  "steps": [
    {
      "type": "google_search_call",
      "id": "gs_1",
      "arguments": { "queries": ["last Super Bowl winner"] },
      "signature": "abc123..."
    },
    {
      "type": "google_search_result",
      "call_id": "gs_1",
      "result": {
        "search_suggestions": "<div>...</div>"
      },
      "signature": "abc123..."
    },
    {
      "type": "model_output",
      "content": [
        {
          "type": "text",
          "text": "The Kansas City Chiefs won the last Super Bowl.",
          "annotations": [
            {
              "type": "url_citation",
              "url": "https://www.nfl.com/super-bowl",
              "title": "NFL.com",
              "start_index": 4,
              "end_index": 22
            }
          ]
        }
      ]
    }
  ],
  "status": "completed"
}

Streaming

Streaming exposes new event types:

New event types

  • interaction.created
  • interaction.completed
  • interaction.in_progress
  • interaction.requires_action
  • step.start
  • step.delta
  • step.stop

Deprecated event types

The following legacy event types are replaced by the new events listed above:

  • interaction.start → interaction.created
  • content.start → step.start
  • content.delta → step.delta
  • content.stop → step.stop
  • interaction.complete → interaction.completed
  • interaction.status_update → replaced by interaction.in_progress, interaction.requires_action, etc.

Streaming function calls: When you use streaming with function calling, the step.start event delivers the function name, and step.delta events stream the arguments as partial JSON strings (using arguments_delta). You must accumulate these deltas to get the full arguments. This differs from unary calls where you receive the complete function call object at once.

Examples

Before (Legacy)

Python

# Legacy streaming used content.delta
stream = client.interactions.create(
    model="gemini-3.7-flash",
    input="Explain quantum entanglement in simple terms.",
    stream=True,
)

for chunk in stream:
    if chunk.event_type == "content.delta":
        if chunk.delta.type == "text":
            print(chunk.delta.text, end="", flush=True)

JavaScript

// Legacy streaming used content.delta
const stream = await client.interactions.create({
    model: 'gemini-3.7-flash',
    input: 'Explain quantum entanglement in simple terms.',
    stream: true,
});

for await (const chunk of stream) {
    if (chunk.event_type === 'content.delta') {
        if (chunk.delta.type === 'text') {
            process.stdout.write(chunk.delta.text);
        }
    }
}

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions?key=$GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3.7-flash",
    "input": "Explain quantum entanglement in simple terms.",
    "stream": true
  }'

// Response (SSE Lines)
// event: interaction.start
// data: {"id": "int_123", "status": "in_progress"}
//
// event: content.start
// data: {"index": 0, "type": "text"}
//
// event: content.delta
// data: {"delta": {"type": "text", "text": "Quantum entanglement is..."}}
//
// event: content.stop
// data: {"index": 0}
//
// event: interaction.complete
// data: {"id": "int_123", "status": "done", "usage": {"total_tokens": 42}}
After (New Schema)

Python

# Consuming stream and handling new event types
for event in client.interactions.create(
    model="gemini-3.7-flash",
    input="Tell me a story.",
    stream=True,
):
    if event.event_type == "step.delta":  # CHANGED: step.delta instead of content.delta
        if event.delta.type == "text":
            print(event.delta.text, end="")

JavaScript

// Consuming stream and handling new event types
const stream = await client.interactions.create({
    model: 'gemini-3.7-flash',
    input: 'Tell me a story.',
    stream: true,
});

for await (const event of stream) {
    if (event.event_type === 'step.delta') {  // CHANGED: step.delta instead of content.delta
        if (event.delta.type === 'text') {
            process.stdout.write(event.delta.text);
        }
    }
}

REST

 # Opt-in needed before May 26th
 curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions?key=$GEMINI_API_KEY" \
   -H "Content-Type: application/json" \
   -H "Accept: text/event-stream" \
   -H "Api-Revision: 2026-05-20" \
   -d '{
     "model": "gemini-3.7-flash",
     "input": "Tell me a story.",
     "stream": true
   }'

 // Response (SSE Lines)
 // event: interaction.created
 // data: {"interaction": {"id": "int_xyz", "status": "in_progress", "object": "interaction", "model": "gemini-3.7-flash"}, "event_type": "interaction.created"}
 //
 // event: interaction.in_progress
 // data: {"interaction_id": "int_xyz", "event_type": "interaction.in_progress"}
 //
 // event: step.start
 // data: {"index": 0, "step": {"type": "thought", "signature": "abc123..."}, "event_type": "step.start"}
 //
 // event: step.stop
 // data: {"index": 0, "event_type": "step.stop"}
 //
 // event: step.start
 // data: {"index": 1, "step": {"content": [{"text": "Once upon", "type": "text"}], "type": "model_output"}, "event_type": "step.start"}
 //
 // event: step.delta
 // data: {"index": 1, "delta": {"text": " a time...", "type": "text"}, "event_type": "step.delta"}
 //
 // event: step.stop
 // data: {"type": "step.stop", "index": 1, "status": "done"}
 //
 // event: interaction.completed
 // data: {"type": "interaction.completed", "interaction": {"id": "int_xyz", "status": "completed", "usage": {"prompt_tokens": 10, "completion_tokens": 5, "total_tokens": 15}}} // NEW: Dedicated completion event

Stateless Conversation History

If you manage conversation history manually on the client side (stateless use case), you must update how you string along previous turns.

  • Legacy: Developers often collected the outputs array from responses and sent them back in the input field on the next turn.
  • New schema: You should now collect the steps array from the response and pass it in the input field of the next request, appending your new user turn as a user_input step.

Output format configuration: response_format changes

The updated API consolidates all output format controls into a unified, polymorphic response_format field. This centralizes output configuration at the top level and keeps generation_config focused on model behavior (like temperature, top_p, and thinking).

Key changes

  • The API removes response_mime_type. You now specify the MIME type per format entry inside response_format.
  • response_format is now a polymorphic object (or array). Each entry has a type discriminator (text, audio, image) and type-specific fields. To request multiple output modalities, pass an array of format entries.
  • image_config moves from generation_config to response_format. You now specify image output settings like aspect_ratio and image_size in a response_format entry with "type": "image".

Structured output (JSON)

The new schema removes the response_mime_type field. Instead, specify the MIME type and JSON schema inside a response_format object with "type": "text".

Before (legacy)

Python

interaction = client.interactions.create(
    model="gemini-3.7-flash",
    input="Summarize this article.",
    response_mime_type="application/json",
    response_format={
        "type": "object",
        "properties": {
            "summary": {"type": "string"}
        }
    },
)

print(interaction.outputs[-1].text)

JavaScript

const interaction = await client.interactions.create({
    model: 'gemini-3.7-flash',
    input: 'Summarize this article.',
    response_mime_type: 'application/json',
    response_format: {
        type: 'object',
        properties: {
            summary: { type: 'string' }
        }
    },
});

console.log(interaction.outputs[-1].text);

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions?key=$GEMINI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-3.7-flash",
    "input": "Summarize this article.",
    "response_mime_type": "application/json",
    "response_format": {
      "type": "object",
      "properties": {
        "summary": { "type": "string" }
      }
    }
  }'

After (new schema)

Python

interaction = client.interactions.create(
    model="gemini-3.7-flash",
    input="Summarize this article.",
    # response_mime_type is removed — specify mime_type inside response_format
    response_format={
        "type": "text",
        "mime_type": "application/json",
        "schema": {
            "type": "object",
            "properties": {
                "summary": {"type": "string"}
            }
        }
    },
)

# Print response
print(interaction.output_text)

JavaScript

const interaction = await client.interactions.create({
    model: 'gemini-3.7-flash',
    input: 'Summarize this article.',
    // response_mime_type is removed — specify mime_type inside response_format
    response_format: {
        type: 'text',
        mime_type: 'application/json',
        schema: {
            type: 'object',
            properties: {
                summary: { type: 'string' }
            }