FlexiGPT

Introduction
Getting started
- Installation
- Configuration
  - FlexiGPT level configuration
  - Sample Full configuration
AI Providers
Features
Prompting
- Prompting
  - Features
  - UI behavior
- Inbuilt prompts
Prompt files format
Requirements and TODO
License
Contributions
Support

Introduction

Interact with GPT AI models as a power user.

Supports multiple AI providers
- OpenAI GPT3.5/4
- Anthropic Claude 1/2
- HuggingFace Inference API
- Google Generative Language API i.e PaLM API
- All models supported by LLaMA.cpp. Current list:
  - LLaMA 🦙
  - LLaMA 2 🦙🦙
  - Alpaca
  - GPT4All
  - Chinese LLaMA / Alpaca and Chinese LLaMA-2 / Alpaca-2
  - Vigogne (French)
  - Vicuna
  - Koala
  - OpenBuddy 🐶 (Multilingual)
  - Pygmalion 7B / Metharme 7B
  - WizardLM
  - Baichuan-7B and its derivations (such as baichuan-7b-sft)
  - Aquila-7B / AquilaChat-7B
Rich prompt engineering support
- Inbuilt pre-defined prompts providing large set of features
  - Refactor selection
  - Generate unit test
  - Complete
  - Explain code
  - Generate Documentation
  - Find problems
  - Optimize selection
- Openly available prompt files that can be tweaked as needed.
- Prompts can be enriched with custom or predefined functions that can be engineered and fine-tuned to meet specific user needs.
- Prompts can be saved and used directly within VSCode
- Modify request parameters for GPT APIs as needed
- Post-process response via responseHandlers in prompts.
Flexible UI
- Chat activity bar interface for request/response interaction
  - Load/save conversations from history
  - Export conversations to a file
  - Copy/Insert/Create new files out of GPT response.
- Ask FlexiGPT via editor/command context (select and right-click)
- Ask FlexiGPT via command palette control (ctrl/cmd + shift + p)
Search Stack Overflow from within the editor
Invoke pre-cooked custom CLI commands from within your editor

Getting started

Installation

Download from: VSCode Marketplace and follow instructions.

Steps:

Install Visual Studio Code 1.74.0 or later
Launch Visual Studio Code
From the command palette Ctrl-Shift-P (Windows, Linux) or Cmd-Shift-P (macOS), run > Extensions: Install Extension.
Choose the extension FlexiGPT by ppipada.
Restart Visual Studio Code after the installation

Configuration

To configure FlexiGPT, open Visual Studio Code's settings (File > Preferences > Settings or by using the Ctrl/Cmd + , keyboard shortcut) and search for flexigpt.
Configure FlexiGPT level configuration
Configure an AI provider

FlexiGPT level configuration

Options:

flexigpt.promptFiles: A semicolon-separated list of paths to user-defined prompt configuration files. Prompt file configuration is detailed here.
flexigpt.inBuiltPrompts: A semicolon-separated list of inbuilt prompt filenames to enable. For multiple names separate with ';'. 'flexigptbasic.js' will always be enabled. Inbuilt prompts can be found at this path. Current values are: "flexigptbasic.js", "gobasic.js" and "gosql.js".
flexigpt.defaultProvider: The provider to use if multiple providers are configured. Currently, supported values: "openai", "anthropic", "huggingface", "googlegl".

Sample Full configuration

// flexigpt basic configuration
"flexigpt.promptFiles": "/home/me/my_prompt_files/myprompts.js",
"flexigpt.inBuiltPrompts": "gobasic.js;gosql.js",
"flexigpt.defaultProvider": "openai",

// openai provider configuration
"flexigpt.openai.apiKey": "sk-mkey",
"flexigpt.openai.timeout": "120",
"flexigpt.openai.defaultCompletionModel": "gpt-3.5-turbo",
"flexigpt.openai.defaultChatCompletionModel": "gpt-3.5-turbo",
"flexigpt.openai.defaultOrigin": "https://api.openai.com",

// anthropic provider configuration
"flexigpt.anthropic.apiKey": "sk-mkey",
"flexigpt.anthropic.timeout": "120",
"flexigpt.anthropic.defaultCompletionModel": "claude-3-haiku-20240307",
"flexigpt.anthropic.defaultChatCompletionModel": "claude-3-haiku-20240307",
"flexigpt.anthropic.defaultOrigin": "https://api.anthropic.com",

// huggingface provider configuration
"flexigpt.huggingface.apiKey": "hf-mkey",
"flexigpt.huggingface.timeout": "120",
"flexigpt.huggingface.defaultCompletionModel": "bigcode/starcoder2-15b",
"flexigpt.huggingface.defaultChatCompletionModel": "deepseek-ai/deepseek-coder-1.3b-instruct",
"flexigpt.huggingface.defaultOrigin": "https://api-inference.huggingface.co",

// googlegl provider configuration
"flexigpt.googlegl.apiKey": "gl-mkey",
"flexigpt.googlegl.timeout": "120",
"flexigpt.googlegl.defaultCompletionModel": "gemini-1.0-pro",
"flexigpt.googlegl.defaultChatCompletionModel": "gemini-1.0-pro",
"flexigpt.googlegl.defaultOrigin": "https://generativelanguage.googleapis.com",

// llamacpp provider configuration
"flexigpt.llamacpp.apiKey": "",
"flexigpt.llamacpp.timeout": "120",
"flexigpt.llamacpp.defaultOrigin": "127.0.0.1:8080",

AI Providers

OpenAI

OpenAI provider requires an API key to function. You can obtain one from your openAI account settings here.
Supported APIs
- https://api.openai.com/v1/chat/completions
- https://api.openai.com/v1/completions
Supported models - All models supported by above two APIs
- gpt-4
- gpt-4-*
- gpt-3.5-turbo
- gpt-3.5-turbo-*
FlexiGPT uses defaultChatCompletionModel: gpt-3.5-turbo, unless the prompt overrides it.
For an example on how to use Function calling feature of OpenAI look at this prompt file here.
Configuration Options:
- flexigpt.openai.apiKey: Your OpenAI API key.
- flexigpt.openai.timeout: The timeout for OpenAI requests, in seconds. Default: 120.
- flexigpt.openai.defaultChatCompletionModel: Default model to use for chat completion requests.
  - You can always override the default model per prompt via the prompt file command declaration.
  - FlexiGPT basic prompts will use the default models set.
  - Default: gpt-3.5-turbo. Note that gpt-3.5-turbo usage is accounted in OpenAIs billing. Only free model that is in beta as of Feb 2023 is codex (code-davinci-002).
- flexigpt.openai.defaultCompletionModel: Default model to use for completion requests.
- flexigpt.openai.defaultOrigin: Default origin to use for requests. This can be used to talk to any server that serves a compatible API.
  - Default: https://api.openai.com.

Anthropic Claude

Anthropic provider requires an API key to function. You can obtain one from the Anthropic website here.
Supported API
- https://api.anthropic.com/v1/messages
  - claude-3-*, claude-2*
FlexiGPT uses defaultChatCompletionModel: claude-3-haiku-20240307, unless the prompt overrides it.
Configuration Options:
- flexigpt.anthropic.apiKey: Your Anthropic API key.
- flexigpt.anthropic.timeout: The timeout for Anthropic requests, in seconds. Default: 120.
- flexigpt.anthropic.defaultChatCompletionModel: Default model to use for chat completion requests.
  - You can always override the default model per prompt via the prompt file command declaration.
  - FlexiGPT basic prompts will use the default models set.
  - Default: claude-3-haiku-20240307.
- flexigpt.anthropic.defaultCompletionModel: Default model to use for completion requests.
- flexigpt.anthropic.defaultOrigin: Default origin to use for requests. This can be used to talk to any server that serves a compatible API.
  - Default: https://api.anthropic.com.

Huggingface

Huggingface provider requires an API key to function. You can obtain one from the huggingface website here.
Supported API
- https://api-inference.huggingface.co/models/<MODEL_ID>
Supported models - All models supported by above API
FlexiGPT uses defaultChatCompletionModel: deepseek-ai/deepseek-coder-1.3b-instruct, unless the prompt overrides it.
Configuration Options:
- flexigpt.huggingface.apiKey: Your Huggingface API key.
- flexigpt.huggingface.timeout: The timeout for huggingface requests, in seconds. Default: 120.
- flexigpt.huggingface.defaultChatCompletionModel: Default model to use for chat completion requests.
  - You can always override the default model per prompt via the prompt file command declaration.
  - FlexiGPT basic prompts will use the default models set.
  - Default: deepseek-ai/deepseek-coder-1.3b-instruct.
- flexigpt.huggingface.defaultCompletionModel: Default model to use for completion requests.
  - Default: bigcode/starcoder2-15b.
- flexigpt.huggingface.defaultOrigin: Default origin to use for requests. This can be used to talk to any server that serves a compatible API.
  - Default: https://api-inference.huggingface.co.

Google generative language - Gemini / PaLM2 API

Googlegl provider requires an API key to function. You can obtain one from the website here.
Supported API: https://ai.google.dev/api/rest/v1/models/generateContent
- gemini-1.0-pro
- chat-bison-001 (legacy)
- text-bison-001 (legacy)
FlexiGPT uses defaultChatCompletionModel: gemini-1.0-pro, unless the prompt overrides it.
Configuration Options:
- flexigpt.googlegl.apiKey: Your API key.
- flexigpt.googlegl.timeout: The timeout for requests, in seconds. Default: 120.
- flexigpt.googlegl.defaultChatCompletionModel: Default model to use for chat completion requests.
  - You can always override the default model per prompt via the prompt file command declaration.
  - FlexiGPT basic prompts will use the default models set.
  - Default: gemini-1.0-pro.
- flexigpt.googlegl.defaultCompletionModel: Default model to use for completion requests.
  - Default: gemini-1.0-pro.
- flexigpt.googlegl.defaultOrigin: Default origin to use for requests. This can be used to talk to any server that serves a compatible API.
  - Default: https://generativelanguage.googleapis.com.

LLaMA cpp

Setup a llama.cpp server as noted here
- If you are running a python openai compatible server as described here, you can use the openai provider with modified default origin for talking to llama.cpp too.
- This provider directly talkes to the default llama server built.
Supported APIs
- https://your host:port of the llama server/completion
Supported models - All models supported by the above APIs. Note that the model in llama.cpp needs to be given when running the server itself and cannot be given at each request level.
Configuration Options:
- flexigpt.llamacpp.apiKey: Your API key.
- flexigpt.llamacpp.timeout: The timeout for requests, in seconds. Default: 120.
- flexigpt.llamacpp.defaultOrigin: Default origin to use for requests. This can be used to talk to any server that serves a compatible API.
  - Default: http://127.0.0.1:8080.

Features

Get Code

Get code using a comment in the editor.

Write a comment asking for a specific code/functionality (Keep your cursor at the end of the same comment line)
Press Ctrl + Alt + G
- Also available via select text/code and right-click as FlexiGPT: Get Code option to click/enter
Get code output below your cursor

Inbuilt Prompts

Steps to get all the below functionality (similar for all configured prompts; inbuilt or custom):

Select your code in the editor
Invoke via Ctrl + Alt + A
- Any other mechanism from below is also ok
Click on the respective prompt text

Refactor selection

Rectify and refactor selected code.

Generate unit test

Create unit test for selected code.

Complete

Complete the selection.

Explain code

Explain the selection.

Generate Documentation

Generate documentation for the selected code.

Find problems

Find problems with the selection, fix them and explain what was wrong.

Optimize selection

Optimize the selected code

Chat

UI behavior

Chat activity bar interface for request/response interaction
Use inbuilt prompts from autocomplete box or adhoc chat with AI.
You can use inbuilt system vars like {selection} or {readfile} to enhance your chat with AI. (Same capability as available for prompt files)
Load/save conversations from history
Export conversations to a file
Copy/Insert/Create new files out of GPT response.
Detailed request and response to/from to GPT APIs available in activity bar itself for better prompt engineering and debugging
Your prompt history is available at the top of the activity bar.

Invocation

The chat activity bar can be opened in following ways:

Click the FlexiGPT icon in the activity bar
Select text/code and right-click i.e editor context: You should get a FlexiGPT: Ask option to click/enter
Command Palette (Ctrl/Cmd + Shift + P): You should get a FlexiGPT: Ask option to click/enter
Keyboard shortcut: Ctrl + Alt + A

Prompts behavior

Click the input text box to load default and configured inbuilt/custom prompts.
Or use system vars to enhance adhoc chat.
Full behavior and documentation can be found here.

Search Stack Overflow

Search for stack overflow questions from your editor.

Press Ctrl + Alt + S
- Also available via select text/code and right-click as FlexiGPT: Stackoverflow Search option to click/enter
- Also available via command Palette (Ctrl/Cmd + Shift + P): You should get a FlexiGPT: Stackoverflow Search option to click/enter
An input box opens with your current line or selection autofilled. You can modify it or use it as is.
Enter and get search results.
Click on result to open stack overflow page.

Run Custom CLIs from within editor

Define your custom CLIs as cliCommands in your prompt files.
- Example can be found here
- Full documentation of how to define the prompt is in the prompt files format documentation.
Press Ctrl + Alt + C
- Also available via right click in editor as FlexiGPT: Run CLI Command to click/enter
- Also available via command Palette (Ctrl/Cmd + Shift + P): You should get a FlexiGPT: Run CLI Command option to click/enter
- Also available via the chat interface invocation to click/enter
- Note that CLI command runs do not become part of your conversation with AI, even if it appears in the chat interface.
An options box opens with available CLIs.
Click on a CLI to open chat bar with your request and get response.

Prompting

Features

Engineer and fine tune prompts, save them and use them directly within VSCode.
Supports request parameter modifications for GPT APIs
Predefined system variables can be used to enhance your question.
- Examples:
  - Use {system.selection} or just {selection} to pass on the selected text in the editor (code or otherwise).
  - Use {system.readfile} or just {readfile} to pass on the open file
  - Use {system.readfile <your file path>} to pass on the file at a given path
- Note that the system. prefix for a system variable is optional. Therefore, you can even use only {selection} to use the selected text, or {language} instead of {system.language} for language of your file.
Supports post-processing response via responseHandlers in prompts. Multiple inbuilt predefined responseHandlers available. Also supports custom responseHandlers. Example can be found here.
Function calling feature of GPT3.5/4 models is also supported. Example can be found in this prompt file.

UI behavior

On clicking on the input text box, basic prompts provided by FlexiGPT itself, any prompts defined in flexigpt.promptFiles, and any inbuilt prompts enabled using flexigpt.inBuiltPrompts, as defined in the configuration should be loaded. (If first time click on text box doesn't load some preconfigured prompts, try escaping options and clicking again. VSCode may take some time to load dynamic lists from files.)
If you select the preconfigured prompts the question template defined in the prompt command will be used after substituting defined system/user variables. Other command options will also be taken from the definition itself.
If you type a free floating question in the text box, the text itself will be used as prompt directly. You can use predefined system variables to enhance your free floating question too.
- Examples:
  - Use {selection} to pass on the selected text in the editor
  - Use {readfile} to pass on the open file

Inbuilt prompts

FlexiGPT basic prompts (Default: enabled)
- Refactor selection
- Generate unit test
- Complete
- Explain code
- Generate Documentation
- Find problems
- Optimize selection
Go basic prompts (Default: disabled, enable in configuration)
- Write godoc string
- Generate unit test
Go sqlx + squirrel prompts (Default: disabled, enable in configuration)
- Generate Create, Read, Update, Delete (CRUD) code for a table specified as a struct selection in the editor using sqlx for db operations and squirrel for query building.

Prompt files format

Sample prompt files in repo

Simple javascript prompt file

module.exports = {
  namespace: "myprompts",
  commands: [
    {
      name: "Refactor",
      template: `Refactor following function.
            function:
            {system.selection}`,
    },
  ],
};

Complex javascript prompt file

module.exports = {
  namespace: "MyComplexPrompts",
  commands: [
    {
      name: "Create unit test.",
      template: `Create unit test in {user.unitTestFramework} framework for following function.
            code:
            {system.selection}`,
      responseHandler: {
        func: "writeFile",
        args: {
          filePath: "user.testFileName",
        },
      },
      requestparams: {
        model: "gpt-3.5-turbo",
        stop: ["##", "func Test", "package main", "func main"],
      },
    },
    {
      name: "Write godoc",
      template: `Write godoc for following functions.
            code:
            {system.selection}`,
      responseHandler: {
        func: "append",
        args: {
          position: "start",
        },
      },
      requestparams: {
        model: "code-davinci-002",
        stop: ["##", "func Test", "package main", "func main"],
      },
    },
  ],
  functions: [
    // you could also write your own responseHandler.
    // Note that it takes a single object as input.
    function myHandler({ system, user }) {
      console.table({ system });
      console.table({ user });
    },
  ],
  variables: [
    {
      name: "unitTestFramework",
      value: "testing",
    },
    {
      name: "testFileName",
      value: ({ baseFolder, fileName, fileExtension }) =>
        `${baseFolder}\\${fileName}_test${fileExtension}`,
    },
  ],
  cliCommands: [
    {
      name: "Go generate all",
      command: `go generate ./...`,
      description: "Run go generate in the workspace",
    },
  ],
};

Creating Command

name: Required
- Name of command, can be whatever you want
description: Optional
- Description of command, can be whatever you want
template: Required
- prompt template to use for create GPT model requests (OpenAI, etc). You can use system or user defined variable in template. variables will replaced with proper value while preparing request
- To use system variable add {system.*variableName*}, variableName can be one of Predefined System Variables. You can also pass parameters to functions like readFile. E.g: {readfile user.testFile} is a valid template variable where input to readfile is the file pointed by the user defined variable testfile.
- To use user variable add {user.*variableName*}, variableName must be in variables field in prompt file.
requestparams: optional
- This is an object of type { [key: string]: any }.
- requestparams["provider"]: For setting a provider from non defaultProvider config
- Any params relevant to the GPT provider API can be overridden.
- Valid params for OpenAI completion request can be found in this API reference.
responseHandler: Optional
- responseHandler is used to handle a response. By default, replace function is used. Handle function can be one of Predefined System Function or a User defined function.
- You can set responseHandler in following ways:
  - Just function name. function run with default values
```
responseHandler: "replace";
```
  - With args function name to set function args
```
responseHandler: {
    func: 'replace',
    args: {
    textToReplace: 'user.answerModified'
    }
}
```

Creating Variables

Any of the variables items can be used in a command template. User-defined values must have the "user" prefix. For example, if "testFileName" is defined in variables, it can be used as "user.TestFileName" in the template file or passed to a function.

Variable values can be static or dynamic. For dynamic values, you should create a getter method. When calling the variable getter, a single object with system variables (see Predefined System Variables) is passed as first argument, any other vars can be taken as next args..

module.exports = {
variables: [
    {
        //static
        name: "testingFramework",
        value: "xUnit"
    },
    {
        //dynamic
        name: "typeNameInResponse",
        value: ({ answer/*system variable*/ }, myTestFile/*user defined var*/ ) => {}
    },
]
functions: [
  function extractTypeName({ code, system }) {/**/},
  function myOtherFunc() {},
],
commands: [
    {
        name: "Create DTO",
        template: `Create unit test with {user.testingFramework} for following class.
        class:
        {system.selection}`,
        responseHandler: {
            func: 'writeFile',
            args: {
                filePath: 'user.typeNameInResponse'/*usage for function arg*/
            }
        }
    }
]
}

Predefined System Variables

All vars are case-insensitive.

Variable Name	Description
system.selection	Selected text in editor
system.question	OpenAI question
system.answer	OpenAI answer
system.language	Programming language of active file
system.baseFolder	Project base path
system.fileFolder	Parent folder path of active file
system.fileName	Name of active file
system.filePath	Full path of active file
system.fileExtension	Extension of active file
system.commitAndTagList	Last 25 commits and associated tags
system.readFile	Read the full open editor file. Optionaly pass a filepath as a second argument

Note that the system. prefix for a system variable is optional. Therefore, you can even use only {selection} to use the selected text, or {language} instead of {system.language} for language of your file.

Creating Functions

Write a simple javascript function which takes exactly one object as input.
Add that function to the functions list.
Use in response handler as needed

Predefined System Functions

Function Name	Description	params(default)
append	Append Text	textToAppend(system.answer),postion('end')
replace	Replace selected text	textToReplace(system.answer)
writeFile	Write text to file. Append if file exists.	filePath(),content(system.answer)

Replace

Replace text with selection. Take optional parameter textToReplace In default value equals to API answer.

Default Usage

    ...
    commands: [
        {
            name: "Refactor",
            template: `Refactor following function.
            function:
            {system.selection}`
            responseHandler:'replace'
        },
    ],

Usage with params

    ...
    commands: [
        {
            name: "Refactor",
            template: `Refactor following function.
            function:
            {system.selection}`
            responseHandler:{
                func: 'replace',
                args: {
                    textToReplace: 'user.answerModified'
                }
            }
        },
    ],
    variables: [
        {
            name: "answerModified",
            value: ({answer})=>`/*\n${anwer}\n*/`
        },
    ],

Append

Append text with selection. Take optional parameter textToAppend and postion. postion can be start or end
In default textToAppend equals to OpenAI postion is end of selection

Sample usage

    ...
    commands: [
        {
            name: "Append",
            template: `Write jsdoc for following function.
            function:
            {system.selection}`
            responseHandler:{
                func: 'append',
                args: {
                    position: 'start'
                }
            }
        },
    ],

Creating CLI Commands

name: Required
- Name of the cli command, can be whatever you want
description: Optional
- Description of the cli command, can be whatever you want
command: Required
- The cli string that you want to execute.
- Note that the directory in which the command is executed is the root directory of your workspace.
- You can use system or user defined variable in the command as described in the features section. Variables will replaced with proper values while preparing request

Requirements and TODO

Functional areas	Features and Implementations	Status
Flexibility to talk to any AI	Integration with multiple AI providers through APIs.	Done
Flexibility to talk to any AI	Support parameter selection and handle different response structures.	Done
Flexibility to use custom prompts	Support for prompt engineering that enables creating and modifying prompts via a standard structure.	Done
	Allow request parameter modification	Done
	Allow adding custom response handlers to massage the response from AI.	Done
	Provide common predefined variables that can be used to enhance the prompts	Done
	Provide extra prompt enhancements using custom variables that can be static or function getters. This should allow function definitions in the prompt structure and integrate the results into prompts. Also allow passing system vars or user vars or static strings as inputs	Done
	Provide capability to evaluate different prompts, assign ELO ratings, choose and save the strongest	Long term
Seamless UI integration	Design a flexible UI, a chat interface integrated into the VSCode activity bar.	Done
	The UI must support saving, loading, and exporting of conversations.	Done
	Implement streaming typing in the UI, creating a feeling that the AI bot is typing itself.	Long term
Adhoc queries/tasks	Help the developer ask adhoc queries to AI where he can describe the questions or issues to it using the chat interface. This can be used to debug issues, understand behaviour, get hints on things to look out for, etc. The developer should be able to attach code or files to his questions.	Done
	Provide a way to define pre cooked CLI commands and fire them as needed. Interface to define CLI commands should be similar to prompts.	Done
	Provide a way to search queries on StackOverflow.	Done
	Provide a way to get results for queries from StackOverflow answers and corresponding AI answer.	Long term
Code completion and intelligence	Provide a way to generate code from a code comment	Done
	Provide a way to complete, refactor, edit, or optimize code via the chat interface. Should allow selecting relevant code from editor as needed.	Done
	Implement a context management system integrated with the Language Server Protocol (LSP) that can be used to enrich AI interactions.	Medium term
	Support generating code embeddings to understand the code context and integrate it into prompts.	Medium term
	Develop an intelligent code completion feature that predicts next lines of code. It should integrate context (LSP or embeddings) into autocomplete prompts and handle autocomplete responses in the UI.	Medium term
Code review and intelligence	Provide a way to review via the chat interface. Should allow selecting relevant code from editor as needed	Done
	Ability to fetch a Merge/Pull request from Github, Gitlab or other version providers, analyse them and provide review comments. Should provide flexibility to specify review areas and associated priority depending on usecase.	Medium term
	Provide automated code reviews and recommendations. It should provide subtle indicators for code improvements and handle code review API responses in the UI.	Long term
	Provide automated refactoring suggestions. This should handle refactoring API responses and display suggestions in the UI.	Long term
	Provide automated security suggestions. This should be able to identify potential vulnerabilities being added or deviations from security best practices used in code.	Long term
Code documentation assistance	Generate documentation for the selected code using the chat interface. Should allow selecting relevant code from editor as needed.	Done
Code documentation assistance	Develop effective inline documentation assistance. It should automatically generate and update documentation based on the code and display it in the UI.	Long term
Code Understanding and Learning Support	Provide a way to explain code via the chat interface. Should allow selecting relevant code from editor as needed.	Done
	Develop/Integrate with an integrated knowledge graph to provide detailed explanations of Services, APIs, methods, algorithms, and concepts the developer is using or may want to use	Long term
	Integrate graph search into prompts	Long term
Testing	Provide a way to generate unit tests via the chat interface. Should allow selecting relevant code from editor as needed. Should have ability to insert tests in new files or current file as needed.	Done
Testing	Provide a way to generate API and associated workflow tests via the chat interface. Should allow selecting relevant code/api definitions from editor as needed. Should have ability to insert tests in new files or current file as needed.	Short term

License

FlexiGPT is a fully open source software licensed under the MIT license.

Contributions

Contributions are welcome! Feel free to submit a pull request on GitHub.

Support

If you have any questions or problems, please open an issue on GitHub at the issues page.

FlexiGPT

Pankaj Pipada

FlexiGPT

Table of Contents

Introduction

Getting started

Installation

Configuration

FlexiGPT level configuration

Sample Full configuration

AI Providers

OpenAI

Anthropic Claude

Huggingface

Google generative language - Gemini / PaLM2 API

LLaMA cpp

Features

Get Code

Inbuilt Prompts

Refactor selection

Generate unit test

Complete

Explain code

Generate Documentation

Find problems

Optimize selection

Chat

UI behavior

Invocation

Prompts behavior

Search Stack Overflow

Run Custom CLIs from within editor

Prompting

Prompting

Features

UI behavior

Inbuilt prompts

Prompt files format

Sample prompt files in repo

Simple javascript prompt file

Complex javascript prompt file

Creating Command

Creating Variables

Predefined System Variables

Creating Functions

Predefined System Functions

Creating CLI Commands

Requirements and TODO

License

Contributions

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