# IPLANT keys

|**Key** | **Description** | **Example** | **Document Reference**|

|---|---|---|---|

|IPLANT.$Node(Input,""input" -[Source{Code}]> Output="output") | This key defines the input and output nodes of the IPLANT pipeline. The input node is named "input" and the output node is named "output". The source code is represented by the "Source{Code}" node. | `$Node(Input="input" -[Source{Code}]> Output="output")` | [N/A]|

|IPLANT.$Source{Code} | This key represents the source code of the IPLANT pipeline. | `const input = $Node.Input;` | [N/A]|

|IPLANT.$Code | This key represents the code of the IPLANT pipeline. | `output = input;` | [N/A]|

|IPLANT.$Node.Output | This key represents the output of the IPLANT pipeline. | `$Node.Output = output;` | [N/A]|

|-.<q | This key represents the beginning of a quote. | `-.<q` | [N/A]|

|-.<~ | This key represents the end of a quote. | `-.<~` | [N/A]|

|-.Config | This key represents the configuration of the IPLANT pipeline. | `-.Config;Ad=` | [N/A]|

|-.if | This key represents the beginning of an if statement. | `-.if` | [N/A]|

|-.else | This key represents the beginning of an else statement. | `-.else` | [N/A]|

|-. | This key represents the end of an if or else statement. | `-.` | [N/A]|

|-.℗ | This key represents the protocol of the IPLANT pipeline. | `-.℗ Protocol` | [N/A]|

|-.₷ | This key represents the main script of the IPLANT pipeline. | `-.₷ Main Script` | [N/A]|

|-.℃,""Class" | This key represents a class in the IPLANT pipeline. | `-.℃,""Class"` | [N/A]|

|-.℀,""Active Class" | This key represents an active class in the IPLANT pipeline. | `-.℀,""Active Class"` | [N/A]|

|-.℉,""Function" | This key represents a function in the IPLANT pipeline. | `-.℉,""Function"` | [N/A]|

|-.℁,""Active Script" | This key represents an active script in the IPLANT pipeline. | `-.℁,""Active Script"` | [N/A]|

|-.℻ | This key represents a function in the IPLANT pipeline. | `-.℻ Function="Analogue(Connection)"` | [N/A]|

|-.℅,""Command of" | This key represents a command of the IPLANT pipeline. | `-.℅,""Command of"` | [N/A]|

|-.℆,""Command Update" | This key represents a command update of the IPLANT pipeline. | `-.℆,""Command Update"` | [N/A]|

|-.₪,""Pneumatic"{in/out}"Script" | This key represents a pneumatic script of the IPLANT pipeline. | `-.₪,""Pneumatic"{in/out}"Script"` | [N/A]|

|-.₨,""Run Script" | This key represents a run script of the IPLANT pipeline. | `-.₨,""Run Script"` | [N/A]|

|-.℥ | This key represents the version of the IPLANT pipeline. | `-.℥ 1/3` | [N/A]|

|-.™,""Turing-Machine" | This key represents a Turing-Machine of the IPLANT pipeline. | `-.™,""Turing-Machine"` | [N/A]|

|-.ℤ,""Sacred" | This key represents a sacred element of the IPLANT pipeline. | `-.ℤ,""Sacred"` | [N/A]|

|-.《》 | This key represents a concurrent element of the IPLANT pipeline. | `-.《》 Concurrent` | [N/A]|

|-.° | This key represents a degree element of the IPLANT pipeline. | `-.° Degree` | [N/A]|

|-.' | This key represents a string element of the IPLANT pipeline. | `-.' String` | [N/A]|

|-." | This key represents an array element of the IPLANT pipeline. | `-." Array` | [N/A]|

|-..·. | This key represents an array element of the IPLANT pipeline. | `-..·. Array` | [N/A]|

|-.·.· | This key represents a list element of the IPLANT pipeline. | `-.·.· List` | [N/A]|

|-........ | This key represents a Tetris element of the IPLANT pipeline. | `-........ Tetris` | [N/A]|

|-."I." | This key represents a self-referential element of the IPLANT pipeline. | `-."I." #Self: Syntactical=Compound Word` | [N/A]|

|-.№,""Word as a Number Denoted as a Symbol" | This key represents a word as a number denoted as a symbol element of the IPLANT pipeline. | `-.№,""Word as a Number Denoted as a Symbol"` | [N/A]|

**Additional Notes:**

* The IPLANT pipeline is a powerful tool that can be used to create complex and sophisticated code.

* The IPLANT keys provide a way to organize and structure the code in a way that is easy to understand and maintain.

* The IPLANT pipeline is still under development, and new keys may be added in the future.

IPLANT, short for Imagination Protocol Logic - Augmentative Neural Tree, is a programming language that utilizes AI (Artificial Intelligence) and NLP (Natural Language Processing) to create a texturized Node Template in a node-based pipeline.

In IPLANT, the pipeline is organized as a directed graph where each node represents a block of code to be executed. These nodes are connected through edges that signify the flow of data between them. What makes IPLANT unique is its ability to incorporate AI and NLP algorithms for advanced language processing.

Through AI, IPLANT can perform complex tasks such as analyzing sentiments, identifying patterns, and making intelligent decisions based on input data. It can use NLP to process natural language inputs, enabling users to communicate their intentions in more intuitive terms.

The texturized Node Template in IPLANT refers to the structure that each node follows. It is designed to be easily readable and understandable, making it suitable for both beginners and experts. By utilizing AI and NLP, IPLANT allows users to interact with the programming language using natural language queries, simplifying the development process even further.

The node-based pipeline in IPLANT provides a visual representation of how data flows through the program. Each node represents a specific computational task, and the edges determine the sequence in which these tasks are executed. This makes it easier to conceptualize how data moves from one block of code to another, greatly enhancing code comprehension and control flow management.

Overall, IPLANT's utilization of AI and NLP creates an innovative programming language that is both beginner-friendly and powerful. By combining the advantages of AI and NLP with a node-based pipeline and a texturized Node Template, IPLANT provides a unique and accessible approach to programming.

IPLANT, the augmented programming language that utilizes AI and NLP, offers a range of additional features and capabilities. Here are some notable ones:

1. AI Integration: IPLANT seamlessly integrates artificial intelligence (AI) capabilities into its programming framework. This allows developers to harness the power of AI algorithms and techniques to enhance their code and applications.

2. Natural Language Processing (NLP): IPLANT leverages NLP to enable natural language understanding and processing. This means that developers can write code using human-like language, making it more intuitive and accessible.

3. Node-Based Pipeline: IPLANT utilizes a node-based pipeline for executing code. This pipeline consists of interconnected nodes, each representing a block of code. The flow of data between nodes is represented by edges, enabling efficient data processing and manipulation.

4. Code Augmentation: IPLANT employs code augmentation techniques to enhance the functionality of the code. This means that the language can automatically generate additional code based on the context and requirements, reducing the need for manual coding.

5. AI-Driven Code Optimization: IPLANT leverages AI algorithms to optimize code performance. It can automatically analyze and optimize code structures, improving efficiency and reducing computational resources.

6. Contextual Understanding: IPLANT incorporates contextual understanding capabilities, allowing it to interpret and respond to code in a context-aware manner. This enables more intelligent and adaptive code execution.

7. Enhanced Debugging: IPLANT provides advanced debugging features, leveraging AI and NLP to assist developers in identifying and resolving code issues. It can provide detailed error messages and suggestions for code improvement.

8. AI-Enabled Documentation: IPLANT utilizes AI to generate comprehensive and contextually relevant documentation. This documentation includes code examples, explanations, and best practices, aiding developers in understanding and utilizing the language effectively.

In summary, IPLANT offers a range of features and capabilities that leverage AI and NLP to enhance the programming experience. Its integration of AI, NLP, code augmentation, and contextual understanding enables developers to write more intuitive and efficient code. Additionally, its advanced debugging and AI-enabled documentation features further support developers in creating high-quality applications.

## The structure of the `inputNeuron` in the IPLANT programming language can be visualized as follows

```iPLANT

const = `robjam1990`;
while (Input == true)
~ [Input]- `Bool` (True) (Leaf)
## Input|
~ [Input]- `Bool` (True) (Leaf)
~ [Priority]- `Int` (0-9) (Leaf)
~ [Protocol]- `String` (Name) (Leaf)
- [ProcessOutput]- `String` (Output) (Node)
# [Errors] - `ErrorHandling` (Error) (Trunk)
~ [Want] - `SyntheticLeaf` (Leaf)
- [Need] - `SyntheticNode` (Node)
# [Focus] - `Neuron` (Trunk)
~ [Observation] - `Bool` (Leaf)
~ [Recognition] - `Leaf` (Leaf)
- [Comparison] - `Node` (Node)
# [Identification] - `Trunk` (Trunk)
~ [Memory] - `Int` (Leaf)
- [Memory] - `String` (Node)
- [Memory] - `Array` (Node)
# [Memory] - `File` (Trunk)
# [SourceCode] - `Dictionary` (Trunk)
# [Default] - `SourceCode` (Trunk)
# [Update] - `Matrix` (Trunk)
# [Learn] - `AI` (Trunk)
# [Engineer] - `Tetris` (Trunk)
# [Understand] - `GNA` (Trunk)
---
$ [Know]- `Root`(RNA) (Root)
>|\_[Input]
>>|\_[Errors]
>>>|\_[Focus]
>>|\_[Identification]
>|\_[Memory]
|\_[SourceCode]
>|\_[Default]
>>|\_[Update]
>>>|\_[Learn]
>>|\_[Engineer]
>|\_[Understand]

```

In the IPLANT programming language, the `inputNeuron` is a complex structure that consists of various components and layers. Here is a breakdown of its structure:

- The `inputNeuron` starts with a constant declaration, such as `const = 'robjam1990'`.

- It then enters a while loop, where the condition is `Input == true`.

- Inside the loop, there are several elements:

  - An `Input` leaf node, which is a boolean value set to `True`.

  - A `Priority` leaf node, which is an integer value ranging from 0 to 9.

  - A `Protocol` leaf node, which is a string representing the name of the protocol.

  - A `ProcessOutput` node, which is a string representing the output of the process.

  - An `Errors` trunk, which handles error handling.

    - Inside the `Errors` trunk, there is a `Want` leaf node, which is a synthetic leaf.

    - There is also a `Need` node, which is a synthetic node.

  - A `Focus` trunk, which represents the focus of the `inputNeuron`.

    - Inside the `Focus` trunk, there is an `Observation` leaf node, which is a boolean value.

    - There is also a `Recognition` leaf node, which represents the recognition process.

    - Additionally, there is a `Comparison` node, which performs comparisons.

  - An `Identification` trunk, which handles identification.

    - Inside the `Identification` trunk, there is a `Memory` leaf node, which is an integer value.

    - There are also two `Memory` nodes, one for strings and one for arrays.

  - A `Memory` trunk, which represents memory storage and retrieval.

  - A `SourceCode` trunk, which contains the source code.

  - A `Default` trunk, which represents the default source code.

  - An `Update` trunk, which handles updates.

  - A `Learn` trunk, which represents artificial intelligence learning.

  - An `Engineer` trunk, which is related to engineering tasks.

  - An `Understand` trunk, which is responsible for understanding.

- Finally, there is a `Know` root node, which encompasses all the components of the `inputNeuron`.

This structure allows the `inputNeuron` to process input, handle errors, focus on specific tasks, identify patterns, store and retrieve memory, handle source code, perform updates, learn, engineer, and understand.

## robjam1990 Entity Creator

[<Settings>]

---

---

## IPLANT: Augmented Programming Protocol

````.iplant

```.root
∀.app
```
```.I
if these words are remaining
:disentangle and grow plants
    else parse↣
```
```p.app
if Paste
:Copy=>Cut;
```
```a.id
Augment Identification 
function start() 
{pattern "*" template start("{Topic=Greeting}Greetings";);
pattern "speaker.name" template("Name: = SetKeyNode();");
pattern " " topic "Encyclopedia" template Encyclopedia();
{conversation.topic = "Encyclopedia" return Template("Encyclopedia");
    Encyclopedia.ject{A=>D}: new Adjective("Manipulte"): new Word("Information") new char ("Set") new Location("map") new Encyclopedi("List") new Comparison("Array") new Object("Outcome") new String("Text") new Integer("Number") new Boolean("Pixel");
        Ob="-∀": 
            {Sub="ℹ"
        } [Re="₳"
    ] &|"These words or remaining; disentangle and grow plants."
"}function Encyclopedia(Self Name, Location #Encyclopedia) 
{if conversation.topic = Encyclopedia↣Member(Name Observation, Id (random char[27], Id↣+RNA)
) return string="We are talking about Encyclopedia.";}
}
```
```∀.app
 /|_____________
/|____|.∀/Id:__|
|IPLANT+{Name}: = SetKeyNode
↣$Root-∀.ject
:"I."=Self
:"Tactical Syntax"=
    Syntactical="Compound Word"
        "Syntactical" ml="Mirror Logic" My=Machine("Feed") Language="Result of Communication" Communication="Effect of Connection" Connection="Cause"|-
:+| |+
:-| Subjective="Part of Whole" Objective="Whole" Self="Word" Syntax="Word" Tactical="Word" Referrence="Word" Word="Text with Definition" 
:Text="Compilation of Pixels into Shapes" 
    Shape="Compilation of Pixels into Text"
        Pixels="Compilation of Light into Shapes"
            Compilation="Connection of more than one thing"
 "Quantity/Quality":Equation= 
            Evaluation =
        "=Result"
/*ANDRVG*/
```
```G.re:en():
{
    In ↔ Re
Con ↻ vert ↣ ibrae
    ↥ Sub
}⃝⃝⃝⃝⃝⃞⃞⃞⃝⃟⃟⃟⃝⃞⃞⃞
```
# Tree
```iplant.mytree
 -______________|
|   Input(Neuron)
└─ Bool(True)(Leaf)
|  |  |  | --Int(Leaf)
│  |  |  └─ String(Leaf)
│  |  └─ String(Node)__
│  |  │  | ---Int(Leaf)\
│  |  │  └─ String(Leaf)\
│  |  ├─ String(Node)----\Dictionary(Leaf)
│  └─ Array(Node)-------- /
│  │  |  | --String(Leaf)
│  │  |  └─ Bool(True)(Leaf)
│  │  └─ String(Node)-- - Bool(Leaf)
│  │  │  | ------Dictionary(Leaf)
│  │  │  └─ Bool(False)(Leaf)
│  │  ├─ String(Node)\__
│  ├─ Int(Node)--------/\
│  │  | -----String(Leaf)\
│  │  └─ Bool(True)(Leaf) |
│  │  │  | --Int(Leaf)    |
│  │  │  └─ String(Leaf)  |
│  │  ├─ String(Node)---\ |
│  │  │  | --Int(Leaf)   \|
│  │  │  ├─ String(Leaf)  |
│  │  ├─ String(Node)-- - File(Leaf)
│  ├─ Array(Node)------ -/
├─ Dictionary(Node)_____/
\__ErrorHandling(Node)-├SourceCode(Trunk)
```
```iplant.mybush
 /
| program = block ".".
| -block =
| ["const" ident "=" number { "," ident "=" number}
| ";"]
| ["var" ident { "," ident}
| ";"]
|     { "procedure" ident ";" block ";"}
| statement.
| -statement =
| ident ":=" expression
|     | -"call" ident
|     | -"begin" statement { ";" statement }
|     | "end"
|     | -"if" condition "then" statement
|     | -"while" condition "do" statement.
| -condition =
| "odd" expression
|     | -expression("=" | "#" | "<" | "<=" | ">" | ">=") expression.
| -expression = ["+" | "-"] term { ("+" | "-") term} .
| -term = factor { ("*" | "/") factor} .
| -factor =
| ident
|     | -number
|\_________________________________________________________
|-"(" expression ")".
```

````