| Name | nl2flow JSON |
| Version |
0.0.3
JSON |
| download |
| home_page | None |
| Summary | NL2Flow: A PDDL interface to flow construction |
| upload_time | 2024-05-15 16:30:56 |
| maintainer | Jung koo Kang |
| docs_url | None |
| author | Jung koo Kang |
| requires_python | >=3.8 |
| license | Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. "License" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. "Licensor" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. "Legal Entity" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. "You" (or "Your") shall mean an individual or Legal Entity exercising permissions granted by this License. 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For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof. "Contribution" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. 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Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form. 3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed. 4. Redistribution. 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The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License. You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License. 5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. 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While redistributing the Work or Derivative Works thereof, You may choose to offer, and charge a fee for, acceptance of support, warranty, indemnity, or other liability obligations and/or rights consistent with this License. However, in accepting such obligations, You may act only on Your own behalf and on Your sole responsibility, not on behalf of any other Contributor, and only if You agree to indemnify, defend, and hold each Contributor harmless for any liability incurred by, or claims asserted against, such Contributor by reason of your accepting any such warranty or additional liability. END OF TERMS AND CONDITIONS APPENDIX: How to apply the Apache License to your work. To apply the Apache License to your work, attach the following boilerplate notice, with the fields enclosed by brackets "[]" replaced with your own identifying information. (Don't include the brackets!) The text should be enclosed in the appropriate comment syntax for the file format. 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| keywords |
automated planning
natural language processing
process automation
service composition
conversational agents
generative ai
large language models
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# NL2Flow: A PDDL Interface to Flow Construction
[](https://research.ibm.com)
[](https://github.com/IBM/kstar)
This package allows developers to easily integrate automated planning applications into their systems. Migrating research efforts to product creates knowledge gaps and blindspots, along with requirements for long-term support which often cannot be followed through. Particularly, the adoption of automated planners into products requires developers to get familiar with declarative modeling and understand the requirements of the [PDDL](https://en.wikipedia.org/wiki/Planning_Domain_Definition_Language) syntax. This package mitigates this need by creating an abstraction around the underlying formal representation so that anyone can use automated planners to create workflows through a Python API, with their desired specifications.
🤓 Read more about our work on natural language to workflow construction [here](https://link.springer.com/chapter/10.1007/978-3-031-16168-1_8).
# Getting Started
#### Clone the repository
```commandline
user:~$ git clone git@github.com:IBM/nl2flow.git
user:~$ cd nl2flow
```
#### Change to a virtual environment
We also strongly recommend using a virtual environment, such
as [anaconda](https://www.anaconda.com/), for development.
```commandline
user:~$ conda create --name nl2flow
user:~$ conda activate nl2flow
```
#### Install Dependencies
```commandline
(nl2flow) user:~$ pip install -e .
```
If you want to contribute code, check [here](docs/CONTRIBUTING.md)
## Example of an NL2Flow Domain
An NL2Flow domain is a mixture of service compostiion and goal-oriented conversation. A typical plan includes elements of API calls, systems calls, and interactions with the user, in pursuit of
a higher level goal. The following is an example of a plan helping an user with a [trip approval process](https://github.com/IBM/nl2flow/blob/main/tests/sketch/sample_sketches/06-sketch_with_instantiated_goals.yaml)
involving flight and hotel bookings, taxi services to and from airports and location of the event, and subprocesses involving conference registration, visa approval, etc. handed off to the corresponding agents.
Notice the information gathering actions, either directly from the user or from other services, performed by the system to facilitate the above requirements of the goal.
```
[0] ask(conference name)
[1] ask(w3)
[2] list of papers = Author Workbench(w3, conference name)
[3] ask(username)
[4] invoice = Registration Bot(conference name, list of papers, username)
[5] map(invoice, conference registration)
[6] name, address, Employee ID, Passport = W3 Agent(w3)
[7] name, address, Employer Letter = Workday(Employee ID)
[8] visa = Visa Application(Passport, address, Employer Letter)
[9] ask(start date)
[10] ask(end date)
[11] map(home, address)
[12] map(BOS, destination)
[13] booking = Taxi(date, address, destination)
[14] map(LAX, address)
[15] map(JW Marriott Los Angeles LA 900 W Olympic Blvd, destination)
[16] booking = Taxi(date, address, destination)
[17] map(end date, date)
[18] map(JW Marriott Los Angeles LA 900 W Olympic Blvd, address)
[19] map(LAX, destination)
[20] booking = Taxi(date, address, destination)
[21] map(BOS, address)
[22] map(destination, home)
[23] booking = Taxi(date, address, destination)
[24] assert eval(is a business trip)
[25] flight_ticket, hotel_booking = Concur(start date, end date, home, destination)
[26] map(flight_ticket, ticket to conference)
[27] assert $hotel_booking.price + $flight_ticket.price < 1500
[28] approval = Trip Approval(ticket to conference, conference registration)
```
## Usage
Get started with constructing a simple flow where you have two operators, one target operator and another one which provides required items for the target operator.
```python
from nl2flow.compile.flow import Flow
from nl2flow.compile.operators import ClassicalOperator as Operator
from nl2flow.compile.schemas import SignatureItem, GoalItem, GoalItems
new_flow = Flow("Basic Test")
find_errors_api = Operator("Find Errors")
find_errors_api.add_input(SignatureItem(parameters=["database link"]))
find_errors_api.add_output(SignatureItem(parameters=["list of errors"]))
fix_errors_api = Operator("Fix Errors")
fix_errors_api.add_input(SignatureItem(parameters=["list of errors"]))
new_flow.add([find_errors_api, fix_errors_api])
goal = GoalItems(goals=GoalItem(goal_name="Fix Errors"))
new_flow.add(goal)
pddl, _ = new_flow.compile_to_pddl() # if you want the PDDL only
parsed_plans = new_flow.plan_it(planner) # if you want the plans
print(planner.pretty_print(parsed_plans))
```
```commadline
---- Plan #0 ----
Cost: 501.0, Length: 2.0
Step 0: ask, Inputs: list of errors (generic), Outputs: None
Step 1: Fix Errors, Inputs: list of errors (generic), Outputs: None
---- Plan #1 ----
Cost: 502.0, Length: 3.0
Step 0: ask, Inputs: database link (generic), Outputs: None
Step 1: Find Errors, Inputs: database link (generic), Outputs: list of errors (generic)
Step 2: Fix Errors, Inputs: list of errors (generic), Outputs: None
```
## Citation
If you end up using this code, you can cite us using the following BibTex entry. Our general focus on natural language processing pipelines for workflow construction applications is documented in that paper.
```latex
@inproceedings{chakraborti2022natural,
title={From Natural Language to Workflows: Towards Emergent Intelligence in Robotic Process Automation},
author={Tathagata Chakraborti and Yara Rizk and Vatche Isahagian and Burak Aksar and Francesco Fuggitti},
booktitle={BPM RPA Forum},
year={2022},
}
```
### Acknowledgements
This package depends **heavily** on `Tarski`, our favorite PDDL parser. Give them lots of :heart: :heart:.
[](https://github.com/aig-upf/tarski)
[](https://tarski.readthedocs.io)
Raw data
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"maintainer_email": "Tathagata Chakraborti <tchakra2@ibm.com>",
"keywords": "automated planning, natural language processing, process automation, service composition, conversational agents, generative ai, large language models",
"author": "Jung koo Kang",
"author_email": "Tathagata Chakraborti <tchakra2@ibm.com>",
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"description": "# NL2Flow: A PDDL Interface to Flow Construction\n\n[](https://research.ibm.com)\n\n\n[](https://github.com/IBM/kstar)\n\nThis package allows developers to easily integrate automated planning applications into their systems. Migrating research efforts to product creates knowledge gaps and blindspots, along with requirements for long-term support which often cannot be followed through. Particularly, the adoption of automated planners into products requires developers to get familiar with declarative modeling and understand the requirements of the [PDDL](https://en.wikipedia.org/wiki/Planning_Domain_Definition_Language) syntax. This package mitigates this need by creating an abstraction around the underlying formal representation so that anyone can use automated planners to create workflows through a Python API, with their desired specifications. \n\n\ud83e\udd13 Read more about our work on natural language to workflow construction [here](https://link.springer.com/chapter/10.1007/978-3-031-16168-1_8).\n\n# Getting Started\n\n#### Clone the repository\n\n```commandline\nuser:~$ git clone git@github.com:IBM/nl2flow.git\nuser:~$ cd nl2flow\n```\n\n#### Change to a virtual environment\n\nWe also strongly recommend using a virtual environment, such\nas [anaconda](https://www.anaconda.com/), for development.\n\n```commandline\nuser:~$ conda create --name nl2flow\nuser:~$ conda activate nl2flow\n```\n\n#### Install Dependencies\n\n```commandline\n(nl2flow) user:~$ pip install -e .\n```\n\nIf you want to contribute code, check [here](docs/CONTRIBUTING.md)\n\n## Example of an NL2Flow Domain\n\nAn NL2Flow domain is a mixture of service compostiion and goal-oriented conversation. A typical plan includes elements of API calls, systems calls, and interactions with the user, in pursuit of \na higher level goal. The following is an example of a plan helping an user with a [trip approval process](https://github.com/IBM/nl2flow/blob/main/tests/sketch/sample_sketches/06-sketch_with_instantiated_goals.yaml)\ninvolving flight and hotel bookings, taxi services to and from airports and location of the event, and subprocesses involving conference registration, visa approval, etc. handed off to the corresponding agents.\nNotice the information gathering actions, either directly from the user or from other services, performed by the system to facilitate the above requirements of the goal.\n\n```\n[0] ask(conference name)\n[1] ask(w3)\n[2] list of papers = Author Workbench(w3, conference name)\n[3] ask(username)\n[4] invoice = Registration Bot(conference name, list of papers, username)\n[5] map(invoice, conference registration)\n[6] name, address, Employee ID, Passport = W3 Agent(w3)\n[7] name, address, Employer Letter = Workday(Employee ID)\n[8] visa = Visa Application(Passport, address, Employer Letter)\n[9] ask(start date)\n[10] ask(end date)\n[11] map(home, address)\n[12] map(BOS, destination)\n[13] booking = Taxi(date, address, destination)\n[14] map(LAX, address)\n[15] map(JW Marriott Los Angeles LA 900 W Olympic Blvd, destination)\n[16] booking = Taxi(date, address, destination)\n[17] map(end date, date)\n[18] map(JW Marriott Los Angeles LA 900 W Olympic Blvd, address)\n[19] map(LAX, destination)\n[20] booking = Taxi(date, address, destination)\n[21] map(BOS, address)\n[22] map(destination, home)\n[23] booking = Taxi(date, address, destination)\n[24] assert eval(is a business trip)\n[25] flight_ticket, hotel_booking = Concur(start date, end date, home, destination)\n[26] map(flight_ticket, ticket to conference)\n[27] assert $hotel_booking.price + $flight_ticket.price < 1500\n[28] approval = Trip Approval(ticket to conference, conference registration)\n``` \n\n## Usage\n\nGet started with constructing a simple flow where you have two operators, one target operator and another one which provides required items for the target operator.\n\n```python\nfrom nl2flow.compile.flow import Flow\nfrom nl2flow.compile.operators import ClassicalOperator as Operator\nfrom nl2flow.compile.schemas import SignatureItem, GoalItem, GoalItems\n\nnew_flow = Flow(\"Basic Test\")\n\nfind_errors_api = Operator(\"Find Errors\")\nfind_errors_api.add_input(SignatureItem(parameters=[\"database link\"]))\nfind_errors_api.add_output(SignatureItem(parameters=[\"list of errors\"]))\n\nfix_errors_api = Operator(\"Fix Errors\")\nfix_errors_api.add_input(SignatureItem(parameters=[\"list of errors\"]))\n\nnew_flow.add([find_errors_api, fix_errors_api])\n\ngoal = GoalItems(goals=GoalItem(goal_name=\"Fix Errors\"))\nnew_flow.add(goal)\n\npddl, _ = new_flow.compile_to_pddl() # if you want the PDDL only\nparsed_plans = new_flow.plan_it(planner) # if you want the plans\n\nprint(planner.pretty_print(parsed_plans))\n```\n\n```commadline\n---- Plan #0 ----\nCost: 501.0, Length: 2.0\n\nStep 0: ask, Inputs: list of errors (generic), Outputs: None\nStep 1: Fix Errors, Inputs: list of errors (generic), Outputs: None\n\n\n---- Plan #1 ----\nCost: 502.0, Length: 3.0\n\nStep 0: ask, Inputs: database link (generic), Outputs: None\nStep 1: Find Errors, Inputs: database link (generic), Outputs: list of errors (generic)\nStep 2: Fix Errors, Inputs: list of errors (generic), Outputs: None\n```\n\n## Citation\n\nIf you end up using this code, you can cite us using the following BibTex entry. Our general focus on natural language processing pipelines for workflow construction applications is documented in that paper. \n\n```latex\n@inproceedings{chakraborti2022natural,\n title={From Natural Language to Workflows: Towards Emergent Intelligence in Robotic Process Automation},\n author={Tathagata Chakraborti and Yara Rizk and Vatche Isahagian and Burak Aksar and Francesco Fuggitti},\n booktitle={BPM RPA Forum},\n year={2022},\n}\n```\n\n### Acknowledgements\n\nThis package depends **heavily** on `Tarski`, our favorite PDDL parser. Give them lots of :heart: :heart:. \n\n[](https://github.com/aig-upf/tarski)\n[](https://tarski.readthedocs.io)\n",
"bugtrack_url": null,
"license": "Apache License Version 2.0, January 2004 http://www.apache.org/licenses/ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 1. Definitions. \"License\" shall mean the terms and conditions for use, reproduction, and distribution as defined by Sections 1 through 9 of this document. \"Licensor\" shall mean the copyright owner or entity authorized by the copyright owner that is granting the License. \"Legal Entity\" shall mean the union of the acting entity and all other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, \"control\" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the outstanding shares, or (iii) beneficial ownership of such entity. \"You\" (or \"Your\") shall mean an individual or Legal Entity exercising permissions granted by this License. \"Source\" form shall mean the preferred form for making modifications, including but not limited to software source code, documentation source, and configuration files. \"Object\" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types. \"Work\" shall mean the work of authorship, whether in Source or Object form, made available under the License, as indicated by a copyright notice that is included in or attached to the work (an example is provided in the Appendix below). \"Derivative Works\" shall mean any work, whether in Source or Object form, that is based on (or derived from) the Work and for which the editorial revisions, annotations, elaborations, or other modifications represent, as a whole, an original work of authorship. For the purposes of this License, Derivative Works shall not include works that remain separable from, or merely link (or bind by name) to the interfaces of, the Work and Derivative Works thereof. \"Contribution\" shall mean any work of authorship, including the original version of the Work and any modifications or additions to that Work or Derivative Works thereof, that is intentionally submitted to Licensor for inclusion in the Work by the copyright owner or by an individual or Legal Entity authorized to submit on behalf of the copyright owner. For the purposes of this definition, \"submitted\" means any form of electronic, verbal, or written communication sent to the Licensor or its representatives, including but not limited to communication on electronic mailing lists, source code control systems, and issue tracking systems that are managed by, or on behalf of, the Licensor for the purpose of discussing and improving the Work, but excluding communication that is conspicuously marked or otherwise designated in writing by the copyright owner as \"Not a Contribution.\" \"Contributor\" shall mean Licensor and any individual or Legal Entity on behalf of whom a Contribution has been received by Licensor and subsequently incorporated within the Work. 2. Grant of Copyright License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license to reproduce, prepare Derivative Works of, publicly display, publicly perform, sublicense, and distribute the Work and such Derivative Works in Source or Object form. 3. Grant of Patent License. Subject to the terms and conditions of this License, each Contributor hereby grants to You a perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable (except as stated in this section) patent license to make, have made, use, offer to sell, sell, import, and otherwise transfer the Work, where such license applies only to those patent claims licensable by such Contributor that are necessarily infringed by their Contribution(s) alone or by combination of their Contribution(s) with the Work to which such Contribution(s) was submitted. If You institute patent litigation against any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the Work or a Contribution incorporated within the Work constitutes direct or contributory patent infringement, then any patent licenses granted to You under this License for that Work shall terminate as of the date such litigation is filed. 4. Redistribution. You may reproduce and distribute copies of the Work or Derivative Works thereof in any medium, with or without modifications, and in Source or Object form, provided that You meet the following conditions: (a) You must give any other recipients of the Work or Derivative Works a copy of this License; and (b) You must cause any modified files to carry prominent notices stating that You changed the files; and (c) You must retain, in the Source form of any Derivative Works that You distribute, all copyright, patent, trademark, and attribution notices from the Source form of the Work, excluding those notices that do not pertain to any part of the Derivative Works; and (d) If the Work includes a \"NOTICE\" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed as part of the Derivative Works; within the Source form or documentation, if provided along with the Derivative Works; or, within a display generated by the Derivative Works, if and wherever such third-party notices normally appear. The contents of the NOTICE file are for informational purposes only and do not modify the License. You may add Your own attribution notices within Derivative Works that You distribute, alongside or as an addendum to the NOTICE text from the Work, provided that such additional attribution notices cannot be construed as modifying the License. You may add Your own copyright statement to Your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of Your modifications, or for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License. 5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of this License, without any additional terms or conditions. Notwithstanding the above, nothing herein shall supersede or modify the terms of any separate license agreement you may have executed with Licensor regarding such Contributions. 6. Trademarks. This License does not grant permission to use the trade names, trademarks, service marks, or product names of the Licensor, except as required for reasonable and customary use in describing the origin of the Work and reproducing the content of the NOTICE file. 7. Disclaimer of Warranty. Unless required by applicable law or agreed to in writing, Licensor provides the Work (and each Contributor provides its Contributions) on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied, including, without limitation, any warranties or conditions of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A PARTICULAR PURPOSE. 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