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: "" }}


  • 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.


  • The textual generated output/response of the LLM.


Write a short poem about NeuralSeek
Here is the definition of NeuralSeek:
{{ web|url:"" }}=>{{ 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:"" }}=>{{ 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?" }}


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


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


explore_feature_tableunderstanding1 explore_feature_tableunderstanding2

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.


  • 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 (), [], {}
      • 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, ...)
      • Constants and Variables:
        • Constants: pi, e, i, Infinity, NaN, null, phi, ...
        • Variable naming: Start with alpha, underscore, or dollar sign; may include digits
      • 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 {}


  • The output value of the equation

Ⓒ 2024 NeuralSeek, all rights reserved.