> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pipecat.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Migrating to 1.0

> Guide to upgrading your Pipecat Flows application from 0.0.x to 1.0

Pipecat Flows 1.0 removes deprecated APIs from the 0.0.x series. If you were already using the non-deprecated replacements, most of these changes won't affect you.

Before upgrading, search your codebase for the deprecated imports and patterns listed below to identify what needs to change.

<Warning>
  Pipecat Flows 1.0 requires **Python 3.11 or later** and **pipecat-ai >= 1.0.0**.
  If you're also upgrading Pipecat, see the [Pipecat 1.0 migration guide](/pipecat/migration/migration-1.0) first.
</Warning>

## 1. FlowManager Initialization

The `tts` parameter was removed from `FlowManager.__init__()`. The built-in `tts_say` action now uses Pipecat's `TTSSpeakFrame` directly and no longer needs a reference to your TTS service.

### Before (1.0)

```python theme={null}
flow_manager = FlowManager(
    task=task,
    llm=llm,
    context_aggregator=context_aggregator,
    tts=tts,  # No longer accepted
)
```

### After (1.0)

```python theme={null}
flow_manager = FlowManager(
    task=task,
    llm=llm,
    context_aggregator=context_aggregator,
)
```

### What was removed

| Removed                | Replacement                                      |
| ---------------------- | ------------------------------------------------ |
| `FlowManager(tts=...)` | Remove the parameter; `tts_say` works without it |

## 2. Node Transitions

Three deprecated APIs for controlling node transitions were removed. All three are replaced by **consolidated handlers** that return a `(result, next_node)` tuple, or by `set_node_from_config()` for imperative transitions.

### Before (1.0)

**`transition_to` on FlowsFunctionSchema:**

```python theme={null}
FlowsFunctionSchema(
    name="collect_name",
    description="Collect the user's name",
    properties={"name": {"type": "string"}},
    required=["name"],
    handler=handle_name,
    transition_to="next_node",  # No longer accepted
)
```

**`transition_callback` on FlowsFunctionSchema:**

```python theme={null}
FlowsFunctionSchema(
    name="collect_name",
    description="Collect the user's name",
    properties={"name": {"type": "string"}},
    required=["name"],
    handler=handle_name,
    transition_callback=decide_next_node,  # No longer accepted
)
```

**`set_node()` on FlowManager:**

```python theme={null}
# In a transition callback or handler
await flow_manager.set_node("next_node", next_node_config)  # No longer available
```

### After (1.0)

**Consolidated handler** (preferred) -- return a tuple of `(result, next_node)`:

```python theme={null}
async def handle_name(args: FlowArgs, flow_manager: FlowManager):
    name = args["name"]
    flow_manager.state["name"] = name
    return {"name": name}, create_next_node()

FlowsFunctionSchema(
    name="collect_name",
    description="Collect the user's name",
    properties={"name": {"type": "string"}},
    required=["name"],
    handler=handle_name,
)
```

**Direct function** alternative:

```python theme={null}
async def collect_name(flow_manager: FlowManager, name: str):
    """Collect the user's name.

    Args:
        name: The user's name.
    """
    flow_manager.state["name"] = name
    return {"name": name}, create_next_node()
```

**Imperative transition** with `set_node_from_config()`:

```python theme={null}
await flow_manager.set_node_from_config(next_node_config)
```

### What was removed

| Removed                                        | Replacement                                 |
| ---------------------------------------------- | ------------------------------------------- |
| `FlowsFunctionSchema(transition_to=...)`       | Return `(result, next_node)` from handler   |
| `FlowsFunctionSchema(transition_callback=...)` | Return `(result, next_node)` from handler   |
| `flow_manager.set_node(id, config)`            | `flow_manager.set_node_from_config(config)` |

## 3. Static Flows

The `FlowConfig` type and `flow_config` parameter were removed. Static flows defined all nodes upfront in a dictionary and transitioned by node name. Dynamic flows replaced them. You create `NodeConfig` objects at runtime and return them from handlers.

### Before (1.0)

```python theme={null}
from pipecat_flows import FlowManager, FlowConfig

flow_config: FlowConfig = {
    "initial_node": "greeting",
    "nodes": {
        "greeting": {
            "role_messages": [...],
            "task_messages": [...],
            "functions": [...]
        },
        "collect_info": {
            "task_messages": [...],
            "functions": [...]
        }
    }
}

flow_manager = FlowManager(
    task=task,
    llm=llm,
    context_aggregator=context_aggregator,
    flow_config=flow_config,  # No longer accepted
)
await flow_manager.initialize()
```

### After (1.0)

```python theme={null}
from pipecat_flows import FlowManager, NodeConfig

def create_greeting_node() -> NodeConfig:
    return {
        "role_message": "You are a helpful assistant.",
        "task_messages": [{"role": "developer", "content": "Greet the user."}],
        "functions": [collect_info_func],
    }

flow_manager = FlowManager(
    task=task,
    llm=llm,
    context_aggregator=context_aggregator,
)
await flow_manager.initialize(create_greeting_node())
```

### What was removed

| Removed                        | Replacement                             |
| ------------------------------ | --------------------------------------- |
| `FlowConfig` type              | `NodeConfig` returned from functions    |
| `FlowManager(flow_config=...)` | `flow_manager.initialize(initial_node)` |
| Transition by node name string | Return `NodeConfig` from handler        |

## 4. Function Definition Format

Provider-specific function definition dicts (OpenAI, Anthropic, Gemini formats) are no longer accepted in node configs. Use `FlowsFunctionSchema` or direct functions instead.

### Before (1.0)

```python theme={null}
# OpenAI-style dict format
node_config = {
    "task_messages": [...],
    "functions": [
        {
            "type": "function",
            "function": {
                "name": "get_weather",
                "description": "Get the weather",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "location": {"type": "string"}
                    },
                    "required": ["location"]
                }
            },
            "handler": get_weather_handler,
        }
    ]
}
```

### After (1.0)

**Using `FlowsFunctionSchema`:**

```python theme={null}
from pipecat_flows import FlowsFunctionSchema

node_config = {
    "task_messages": [...],
    "functions": [
        FlowsFunctionSchema(
            name="get_weather",
            description="Get the weather",
            properties={"location": {"type": "string"}},
            required=["location"],
            handler=get_weather_handler,
        )
    ]
}
```

**Using a direct function:**

```python theme={null}
async def get_weather(flow_manager: FlowManager, location: str):
    """Get the weather for a location.

    Args:
        location: The city to check weather for.
    """
    result = await fetch_weather(location)
    return {"weather": result}, None

node_config = {
    "task_messages": [...],
    "functions": [get_weather]
}
```

### What was removed

| Removed                              | Replacement                               |
| ------------------------------------ | ----------------------------------------- |
| OpenAI-style function dicts          | `FlowsFunctionSchema`                     |
| Anthropic-style function dicts       | `FlowsFunctionSchema`                     |
| Gemini `function_declarations` dicts | `FlowsFunctionSchema`                     |
| Any provider-specific dict format    | `FlowsFunctionSchema` or direct functions |

## Still-Active Deprecations

<Tip>
  The following APIs still work in 1.0 but emit deprecation warnings. They will
  be removed in 2.0.
</Tip>

| Deprecated                                      | Since   | Replacement                                                                                |
| ----------------------------------------------- | ------- | ------------------------------------------------------------------------------------------ |
| `role_messages` (list of dicts in `NodeConfig`) | v0.0.24 | `role_message` (plain string)                                                              |
| `RESET_WITH_SUMMARY` context strategy           | v0.0.25 | Pipecat's native [`LLMSummarizeContextFrame`](/pipecat/fundamentals/context-summarization) |

**`role_messages`**: Replace the list-of-dicts `role_messages` field with the `role_message` string field. The string is sent as the LLM's system instruction and persists across node transitions until a new node explicitly sets it again.

```python theme={null}
# Before
node = {
    "role_messages": [{"role": "system", "content": "You are a helpful assistant."}],
    "task_messages": [...]
}

# After
node = {
    "role_message": "You are a helpful assistant.",
    "task_messages": [...]
}
```

**`RESET_WITH_SUMMARY`**: Instead of using the `RESET_WITH_SUMMARY` context strategy, push an `LLMSummarizeContextFrame` in a pre-action to trigger on-demand summarization during a node transition. See the [context summarization guide](/pipecat/fundamentals/context-summarization) for details.