Pipable AI

A goal oriented intelligent system that uses specified "callables" [apis, methods, objects, functions] to accomplish RPA objectives.

Usage Details

Usage Details

Git Stars

Model Downloads



One OS Library, unlimited solutions

The library simplifies docstring creation, provides function calling capabilities, facilitates SQL query generation, and enhances development workflows with intuitive functionality from natural language input.

RPA Planning and Generation

Robotic Process Automation (RPA) involves the planning and generation of automated workflows to streamline business processes, reducing human intervention and increasing efficiency.

Code Synthesis Based on Strategic Plans

Code synthesis involves the generation of software code based on strategic plans and requirements, ensuring the alignment of software development with organizational objectives and goals.

Making API Calls Across Various Programming Languages

Making API calls involves invoking Application Programming Interfaces (APIs) across different programming languages, enabling interoperability and seamless communication between software components.

Automated Docstring Generation for Code Documentation

Automated docstring generation involves the creation of descriptive documentation strings within code files automatically, enhancing code readability, maintainability, and understanding.

Conversion of Textual Descriptions into SQL Queries

Text to SQL query generation involves the transformation of natural language textual descriptions into structured SQL queries, facilitating database interaction and query execution.

Function Invocation Using Natural Language Commands

Function calling using natural language commands enables developers to invoke functions within code using human-readable language, enhancing developer productivity and code accessibility.



Explore Our Open Source Offerings

  • All
  • Plan
  • SQL
  • DOC
  • Function Call
  • Parse Data to Json


  • Make get request to https://colab.research.google.com/
  • Create a Beautiful soup object.
  • Find all the divs in it


  • Create a dataframe using dict {"a":[1,2,3], "b":[4,5,6]}
  • Find shape of the dataframe and column names in it


  • read a.csv as dataframe.
  • describe the .25, .50 and .75 percentiles in the dataframe.


  • SELECT Name FROM department WHERE Budget_in_Billions > 3;


  • SELECT d.Name AS Department_Name, h.age AS Head_Age,
    WHEN m.temporary_acting IS NOT NULL THEN 'Yes'
    ELSE 'No'
    END AS Temporary_Acting_Head
    FROM department d
    JOIN management m ON d.Department_ID = m.department_ID
    JOIN head h ON m.head_ID = h.head_ID
    WHERE d.Budget_in_Billions > 3;


  • Docs for the method: requests.post


  • SELECT name FROM head WHERE born_state != 'California';

Function Call:

  • make_get_req(path=variable_2, data=variable_1, params={'weight': variable_3, 'width': 10}, headers={}, not_json_response=True, absolute=True);


  • Docs for written code:
  • def add_numbers(a: float, b:float):
    return a + b


  "users_list": [
      "ids": ["id234", "id4532134"],
      "info": {
        "description": "some text",
        "isActive": true


Clem Delangue ūü§ó Just reposted our pip-etl git repository‚Ķ And we are grateful and elated. Hopefully it`s the first of the many acknowledgements from the greats.

Clem Delangue

Ceo & Co-Founder Hugging Face

I have been closely following Pipable’s public AI and natural language solutions. Today, businesses revolve around three pillars: information, ability to act on information, and ability to integrate. Pipable has been growing fast to address each of these areas. They started with an incredibly efficient information retrieval solution which converts human language to SQL - the prevalent data store technology; they recently released a task execution planner which can act on any data, and they can also integrate with any solutions which support OpenAPI (Pipable offers out of the box integrations with the industry leading services such as Slack, Jira and Atlassian stack, Yahoo finance, etc.). We work in the space of networking and infrastructure, which is a highly complex area. We address management of diverse devices, as well as handle various approaches to device data processing and orchestrating people to work on infrastructure problems. Due to the chronic lack of time and staff, giving the ability to our customers to ask questions and automate tasks in human language is a game changer. Very few of our customers can afford to code their own solutions or train enough of their staff to know all the tools involved. Pipable has a unique offering in that their solutions have an extremely small footprint and can work both on-prem and in private clouds. Many enterprises still prefer this approach for their mission critical data and infrastructure. We are looking forward to seeing how Pipable scales their solutions and develops their business model.

Dr. Stanislav Miskovic

Vice President of AI at Gluware Inc., Enterprise network management and security

Pipable’s agentification of performance diagnosis is extremely valuable to the field of cloud systems management. Not only are the natural language based data querying capabilities useful for easy extraction of insights from complex performance datasets, the agents are quite suited to efficient monitoring and multi-level observability of hosted and distributed systems. With Pipable, enterprises can effortlessly navigate through vast amounts of system logs, metrics, and telemetry data, pinpointing performance bottlenecks and anomalies. Its intuitive API and seamless integration can make it an efficient tool for DevOps teams, ensuring goal-oriented resource utilization and minimizing system downtime for complex end-to-end workflows. I also see Pipable usage beyond Cloud environments, empowering edge computing solutions with real-time diagnostics and proactive maintenance.

Dr. Nishant Saurabh

Assistant Professor (Tenured), Dept. of Information and Computing Sciences, Utrecht University, Distributed Systems and Cloud Computing

I have found Pipable's agents to be very useful for generating and validating application components. The natural language based code generation capabilities - particularly, those for API integration and verification - considerably simplify component development, thereby reducing the time and effort in the development and testing life-cycles. These agents can also assist with application deployment and monitoring, thereby facilitating observability of applications over distributed infrastructure. This makes the agents pertinent to both application development teams as well as DevOps teams, which helps optimize the resource utilization and achieve great end-to-end efficiencies on the business front. I strongly recommend Pipable to fellow developers, quality engineers, and DevOps practitioners.

Amit Ashutosh

Engineering Leader at Cisco, Application Development and Integration



Gyan Ranjan, PhD

Founder and CEO, PipableAI

Soham Acharya

Co-Founder & CTO

Pratham Gupta

Founding Engineer

Ritvik Aryan Kalra

Founding Engineer

Avi Kothari

Founding Engineer



San Francisco, California


Pipable AI