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# Table of Contents
* [Structure of ReplanningFlow](#structure-of-replanningflow)
* [run\_replanning](#run_replanning)
* [ReplanningAskUserFlow](#ReplanningAskUserFlow)
* [ReplanningAskUserFlow](#ReplanningAskUserFlow.ReplanningAskUserFlow)
* [run](#ReplanningAskUserFlow.ReplanningAskUserFlow.run)
* [NewPlanGenFlow](#NewPlanGenFlow)
* [NewPlanGenFlow](#NewPlanGenFlow.NewPlanGenFlow)
* [\_\_init\_\_](#NewPlanGenFlow.NewPlanGenFlow.__init__)
* [ReplanningFlow](#ReplanningFlow)
* [ReplanningFlow](#ReplanningFlow.ReplanningFlow)
* [detect\_finish\_or\_continue](#ReplanningFlow.ReplanningFlow.detect_finish_or_continue)
* [\_\_init\_\_](#__init__)
# Structure of ReplanningFlow
```
goal (info on the old plan), plan (old plan), plan_file_location
|
v
+---------------+
| Controller | --------<<<<-----------+
+---------------+ |
| |
| (command, command args) |
| |
v |
+------------------+ |
| Executor | Each branch is an |
| (Tree Structure) | executor |
+------------------+ |
| ^
| (summary) |
| |
v |
| |
+-> goes back to the Controller>-+
```
Structure of the Executors:
```
+-------------------+
| Branching |
| Executor |
+-------------------+
/ \
/ \
/ \
/ \
write_plan ask_user
```
About the branches:
- [ask_user](https://huggingface.co/aiflows/PlanWriterFlowModule/blob/main/PlanWriterAskUserFlow.py): Ask user for info / confirmation, etc.
- [write_plan](https://huggingface.co/aiflows/InteractivePlanGenFlowModule): Generates plan (user edit is allowed) and fetches user feedback.
- The PlanGenerator of write_plan is replaced with [NewPlanGenFlow](https://huggingface.co/aiflows/ReplanningFlowModule/blob/main/NewPlanGenFlow.py) to re-plan instead of write plan.
How it works:
Controller calls write_plan until user is satisfied in the feedback, finish.
<a id="run_replanning"></a>
# run\_replanning
<a id="ReplanningAskUserFlow"></a>
# ReplanningAskUserFlow
<a id="ReplanningAskUserFlow.ReplanningAskUserFlow"></a>
## ReplanningAskUserFlow Objects
```python
class ReplanningAskUserFlow(HumanStandardInputFlow)
```
Refer to: https://huggingface.co/aiflows/ExtendLibraryFlowModule/blob/main/ExtLibAskUserFlow.py
*Input Interface*:
- `question`
*Output Interface*:
- `feedback`
- `new_plan`
*Configuration Parameters*:
- `request_multi_line_input_flag`: if True, the user can input multiple lines of text. Default: False
- `end_of_input_string`: the string that the user can input to indicate that the input is finished. Default: EOI
- `query_message_prompt_template`: the template of the message that is sent to the user to ask for input.
<a id="ReplanningAskUserFlow.ReplanningAskUserFlow.run"></a>
#### run
```python
def run(input_data: Dict[str, Any]) -> Dict[str, Any]
```
Run the flow module.
**Arguments**:
- `input_data`: the input data
**Returns**:
the output data
<a id="NewPlanGenFlow"></a>
# NewPlanGenFlow
<a id="NewPlanGenFlow.NewPlanGenFlow"></a>
## NewPlanGenFlow Objects
```python
class NewPlanGenFlow(PlanGeneratorAtomicFlow)
```
This flow module is responsible for generating a new plan based on the previous plan and the given requirements.
This flow is inherited from PlanGeneratorAtomicFlow. (https://huggingface.co/aiflows/PlanGeneratorFlowModule)
*Input Interface Non Initialized*:
- `goal`
- `old_plan`
*Input Interface Initialized*:
- `goal`
- `old_plan`
*Output Interface*:
- `new_plan`
*Configuration Parameters*:
- `system_message_prompt_template`: The template of the system message.
- `init_human_message_prompt_template`: The template of the init user message.
- `human_message_prompt_template`: The template of the user message.
<a id="NewPlanGenFlow.NewPlanGenFlow.__init__"></a>
#### \_\_init\_\_
```python
def __init__(**kwargs)
```
Initialization of the flow module.
**Arguments**:
- `kwargs`: The configuration parameters of the flow module.
<a id="ReplanningFlow"></a>
# ReplanningFlow
<a id="ReplanningFlow.ReplanningFlow"></a>
## ReplanningFlow Objects
```python
class ReplanningFlow(PlanWriterFlow)
```
This flow inherits from PlanWriterFlow.
By changing prompts and injecting proper information to the controller and the PlanGenerator, we are able to achieve the replanning.
*Input Interface*:
- `goal` (str): information on the old plan (e.g. what is wrong)
- `plan` (str): the old plan
- `plan_file_location` (str): the location of the old plan file
*Output Interface*:
- `plan` (str): the new plan
- `status`: "finished" or "unfinished"
- `summary` (str): summary of the flow, will be written to the log file of the caller flow.
- `result` (str): result of the flow, will be passed to the controller of the caller flow.
<a id="ReplanningFlow.ReplanningFlow.detect_finish_or_continue"></a>
#### detect\_finish\_or\_continue
```python
@CircularFlow.output_msg_payload_processor
def detect_finish_or_continue(output_payload: Dict[str, Any],
src_flow) -> Dict[str, Any]
```
This function is called when the replanning flow receives a message from the PlanGenerator.
It checks the command in the message and decides whether to finish the flow or continue the flow.
**Arguments**:
- `output_payload`: the message received from the PlanGenerator
- `src_flow`: the PlanGenerator
**Returns**:
the message to be sent to the controller of the caller flow
<a id="__init__"></a>
# \_\_init\_\_
|