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docs: add Conversational Flows (self.ask) section to flows docs
Add comprehensive documentation for the self.ask() feature covering: - Basic usage and API - Multiple asks in a single method - Timeout support with retry pattern - Bidirectional metadata support - Custom InputProvider protocol (Slack example) - Auto-checkpoint behavior with persistence - Comparison table: self.ask() vs @human_feedback
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@@ -572,6 +572,176 @@ The `third_method` and `fourth_method` listen to the output of the `second_metho
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When you run this Flow, the output will change based on the random boolean value generated by the `start_method`.
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### Conversational Flows (User Input)
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The `self.ask()` method pauses flow execution to request input from a user inline, then returns their response as a string. This enables conversational, interactive flows where the AI can gather information, ask clarifying questions, or request approvals during execution.
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#### Basic Usage
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```python Code
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from crewai.flow.flow import Flow, start, listen
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class GreetingFlow(Flow):
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@start()
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def greet(self):
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name = self.ask("What's your name?")
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self.state["name"] = name
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@listen(greet)
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def welcome(self):
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print(f"Welcome, {self.state['name']}!")
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flow = GreetingFlow()
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flow.kickoff()
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```
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By default, `self.ask()` uses a `ConsoleProvider` that prompts via Python's built-in `input()`.
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#### Multiple Asks in One Method
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You can call `self.ask()` multiple times within a single method to gather several inputs:
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```python Code
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from crewai.flow.flow import Flow, start
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class OnboardingFlow(Flow):
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@start()
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def collect_info(self):
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name = self.ask("What's your name?")
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role = self.ask("What's your role?")
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team = self.ask("Which team are you joining?")
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self.state["profile"] = {"name": name, "role": role, "team": team}
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print(f"Welcome {name}, {role} on {team}!")
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flow = OnboardingFlow()
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flow.kickoff()
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```
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#### Timeout Support
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Pass `timeout=` (in seconds) to avoid blocking indefinitely. If the user doesn't respond in time, `self.ask()` returns `None`:
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```python Code
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from crewai.flow.flow import Flow, start
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class ApprovalFlow(Flow):
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@start()
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def request_approval(self):
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response = self.ask("Approve deployment? (yes/no)", timeout=120)
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if response is None:
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print("No response received — timed out.")
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self.state["approved"] = False
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return
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self.state["approved"] = response.strip().lower() == "yes"
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```
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Use a `while` loop to retry on timeout:
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```python Code
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from crewai.flow.flow import Flow, start
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class RetryFlow(Flow):
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@start()
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def ask_with_retry(self):
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answer = None
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while answer is None:
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answer = self.ask("Please confirm (yes/no):", timeout=60)
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if answer is None:
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print("Timed out, asking again...")
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self.state["confirmed"] = answer.strip().lower() == "yes"
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```
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#### Metadata Support
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The `metadata` parameter enables bidirectional context passing between the flow and the input provider. Send context to the provider, and receive structured context back:
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```python Code
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from crewai.flow.flow import Flow, start
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class ContextualFlow(Flow):
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@start()
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def gather_feedback(self):
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response = self.ask(
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"Rate this output (1-5):",
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metadata={
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"step": "quality_review",
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"output_id": "abc-123",
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"options": ["1", "2", "3", "4", "5"],
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},
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)
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self.state["rating"] = int(response) if response else None
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```
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When a custom provider returns an `InputResponse`, it can include its own metadata (e.g., user identity, timestamp, channel info) that your flow can process.
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#### Custom InputProvider
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For production use cases (Slack bots, web UIs, webhooks), implement the `InputProvider` protocol:
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```python Code
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from crewai.flow.flow import Flow, start
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from crewai.flow.input_provider import InputProvider, InputResponse
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import requests
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class SlackInputProvider(InputProvider):
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def __init__(self, channel_id: str, bot_token: str):
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self.channel_id = channel_id
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self.bot_token = bot_token
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def request_input(self, message, flow, metadata=None):
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# Post the question to Slack
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requests.post(
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"https://slack.com/api/chat.postMessage",
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headers={"Authorization": f"Bearer {self.bot_token}"},
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json={"channel": self.channel_id, "text": message},
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)
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# Wait for and return the user's reply (simplified)
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reply = self.poll_for_reply()
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return InputResponse(
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value=reply["text"],
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metadata={"user": reply["user"], "ts": reply["ts"]},
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)
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def poll_for_reply(self):
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# Your implementation to wait for a Slack reply
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...
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# Use the custom provider
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flow = Flow(input_provider=SlackInputProvider(
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channel_id="C01ABC123",
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bot_token="xoxb-...",
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))
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flow.kickoff()
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```
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The `request_input` method can return:
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- A **string** — used directly as the user's response
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- An **`InputResponse`** — includes `value` (the response string) and optional `metadata`
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- **`None`** — treated as a timeout / no response
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#### Auto-Checkpoint Behavior
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<Note>
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When [persistence](/concepts/flows-persistence) is configured, the flow state is automatically saved **before** each `self.ask()` call. If the process restarts while waiting for input, the flow can resume from the checkpoint without losing progress.
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</Note>
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#### `self.ask()` vs `@human_feedback`
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| | `self.ask()` | `@human_feedback` |
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|---|---|---|
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| **Purpose** | Inline user input during execution | Approval gates and review feedback |
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| **Returns** | `str \| None` | `HumanFeedbackResult` with structured fields |
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| **Timeout** | Built-in `timeout=` parameter | Not built-in |
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| **Provider** | Pluggable `InputProvider` protocol | Console-based |
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| **Use when** | Gathering data, clarifications, confirmations | Review/approval workflows with structured feedback |
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| **Decorator** | None — call `self.ask()` anywhere | `@human_feedback` on the method |
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<Note>
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Both features coexist — you can use `self.ask()` and `@human_feedback` in the same flow. Use `self.ask()` for inline data gathering and `@human_feedback` for structured review gates.
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</Note>
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### Human in the Loop (human feedback)
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<Note>
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