#### Send to LLM

Send to LLM may be the most frequently used function in NTL. This function sends all previous post-chain content to the LLM for processing.

```
{{ LLM }}
{{ LLM | prompt: "" }}
{{ LLM | prompt: "" | modelCard: "" | maxTokens: "" | minTokens: "" | temperatureMod: "" | toppMod: "" | freqpenaltyMod: "" }}
```

**Parameters:**

- Prompt: An additional prompt to prepend to the previous/existing content in the environment.
- Model Card: (BYOLLM Only) Select a model to use for this call by passing the model's identifier here.
- Max Tokens: Maximum amount of tokens to generate.
- Min Tokens: Minimum amount of tokens to generate.
- Temperature Mod: Controls the randomness of the model's output, with lower values leading to more predictable text and higher values leading to more unpredictable text.
- Top P Mod: Alternative method for controlling randomness in language models that doesn't involve the top-k method as much. Reduces the probability mass from the highest probabilities before drawing samples.
- Frequency Penalty Mod: Controls how much we want to penalize frequency of certain tokens, reducing their probabilities when generating text with these methods for more unique or varied output.

**Returns:**

- The textual generated output/response of the LLM.

**Example:**

```
Write a short poem about NeuralSeek
Here is the definition of NeuralSeek:
{{ web|url:"https://documentation.neuralseek.com/" }}=>{{ summarize|length:200 }}
{{ LLM }}
```

This will write a short poem about NeuralSeek, based on the content retrieved from our documentation.

In the LLM syntax, you can add additional prompts such as:

```
Write a short poem about NeuralSeek
Here is the definition of NeuralSeek:
{{ web|url:"https://documentation.neuralseek.com/" }}=>{{ summarize|length:200 }}
{{ LLM|prompt: "write in Spanish" }}
```

This will prepend "write in Spanish" to the whole prompt given to the LLM, outputting a poem in Spanish.

#### Table Understanding

This function allows for natural language Q/A against csv/xlsx files.

You start by uploading a spreadsheet, either an Excel or CSV file. Then, you are able to generate insightful responses about the source data by providing queries in natural language.

NeuralSeek undertakes a comprehensive examination of the provided data to output an accurate response. At the bottom of the screen, NeuralSeek provides a confidence percentage, accompanied by a statement of confidence, for example: "Table Understanding reports a confidence level of %". This percentage is based on how much the system trusts the answer it gave you based on what it found in the data.

```
{{ TableUnderstanding|query:"What year had the highest revenue?" }}
```

**Parameters:**

- Query: The natural language query to ask of the given csv/xlsx.

**Returns:**

- The expected value from the table to answer the Query.

**Example:**

#### Mathematical Equation

```
{{ math|equation:"1 + 1" }}
```

Performs mathematical equation on input strings.

It allows parsing of complex mathematical expressions, supporting a wide range of mathematical computations, from simple math and operators to trigonometric functions, logarithms, and more. The parser handles nested expressions and variables. Overall, it simplifies mathematical computations with LLMs.

**Parameters:**

- Equation: The math equation to process. Supports the following (not all inclusively):
**Expression Syntax:****Operators:**- Arithmetic:
`+`

,`-`

,`*`

,`/`

,`%`

,`^`

- Unary:
`+`

,`-`

,`!`

- Bitwise:
`&`

,`|`

,`~`

,`^|`

,`<<`

,`>>`

,`>>>`

- Logical:
`and`

,`or`

,`not`

,`xor`

- Relational:
`==`

,`!=`

,`<`

,`>`

,`<=`

,`>=`

- Assignment:
`=`

- Conditional:
`? :`

- Range:
`:`

- Unit conversion:
`to`

,`in`

- Implicit multiplication: e.g.,
`2 pi`

,`(1+2)(3+4)`

- Precedence: Grouping with
`()`

,`[]`

,`{}`

- Arithmetic:
**Functions:**- Called with parentheses: e.g.,
`sqrt(25)`

,`log(10000, 10)`

- Custom function definition: e.g.,
`f(x) = x ^ 2`

- Dynamic variables in functions, no closures
- Functions as parameters: e.g.,
`twice(func, x) = func(func(x))`

- Operator equivalent functions: e.g.,
`add(a, b)`

for`a + b`

- Associative functions with multiple arguments: e.g.,
`add(a, b, c, ...)`

- Called with parentheses: e.g.,
**Constants and Variables:**- Constants:
`pi`

,`e`

,`i`

,`Infinity`

,`NaN`

,`null`

,`phi`

, ... - Variable naming: Start with alpha, underscore, or dollar sign; may include digits

- Constants:
**Data Types:**- Types: Booleans, numbers, complex numbers, units, strings, matrices, objects
- Booleans: Convertible to numbers and strings
- Numbers: Exponential notation, binary/octal/hex formatting
- BigNumbers: Arbitrary precision
- Complex numbers: Imaginary unit
`i`

- Units: Arithmetic operations, conversions
- Strings: Enclosed by quotes,
`concat`

for concatenation - Matrices: Created with
`[]`

, indexed and ranged - Objects: Key/value pairs in
`{}`

**Returns:**

- The output value of the equation