MAKE TABLE
Create and fill a table for a specific theme
It effortlessly generates tables in your spreadsheet based on a specific theme or topic you provide. Ideal for organizing data, brainstorming sessions, or project planning, this function utilizes ChatGPT to create structured and insightful tables that enhance your workflow.
Examples
=MAKETABLE_X("Fictional productds table with 25 rows")

Expected Output:
Table of products with 25 rows
=MAKETABLE_X("Fictional Book Inventory", "Title, Author, Genre, Published Year")

Expected Output:
Table of books with columns Title, Author, Genre, and Published Year
=MAKETABLE_X("Fitness Routine", "Day, Exercise ,Duration, Calories Burned", {"with_web",TRUE; "temperature",0.4; "act_like","Fitness Trainer"; "extra_instructions","Factor in rest days"})

Expected Output:
Table with a fitness schedule
=MAKETABLE_X("Our clients who are working in tech", "ID, Name, Job, Email, Phone", {"with_kb",TRUE; "temperature", IFS($C$6="Very Creative", 0.6, $C$6="Medium",0.3, $C$6="Very Rational",0)})

Expected Output:
Filtered by work table from a spreadsheet Knowledge Base
Arguments List
=MAKETABLE_X(subject, [header],[options])
=MAKETABLE_Y(subject, [header],[options])
subject
The subject specifies the theme or topic around which the table will be generated, guiding the AI in structuring the data appropriately.
For example: "Fictional table of clients with realistic data", A2, or "Table with four columns about " & B2
[optional] header
It should contain table column names divided by commas to create a table with those exact columns.
For example: "ID, Name, Email, Phone", A2, or TEXTJOIN(", ", TRUE, A1:A5)
Options List
Particular object at the end of a formula which contains optional parameters values in the form {"parameter_name",value; "next_parameter_name",value}
For Example: {"output_language","French"; "extra_instructions","Remember this info: " & A1; "act_like","Data Analyst"}
with_kb
It allows the function to access and utilize the spreadsheet's Knowledge Base, enriching the table with pre-configured data and insights. This enhances the function's ability to create more context-aware and informative tables. Recommend to deactivate if a result requires general knowledge and the Knowledge Base information is not enough to make a table.
Options: FALSE or TRUE
with_web
It enables the function to fetch data from the internet, adding a layer of real-time information to your table. While this feature can provide valuable insights, be aware that it may increase both the cost and the time required for execution, and the quality of results may vary based on the search.
Options: FALSE or TRUE
output_language
Set output language for the function result; it can differ from argument language. If not set, answer language can vary depending on options and parameter values.
For Example: "EN", "French", or  "Most Popular Language in the US"
temperature
Adjust the deviation from deterministic answers from 0 (default, high-confidence) to 1 (greater diversity). In other words, it's the AI's creativity for the result. Creativity above 0.5 can destroy a result.
For Example: 0, 0.2, or 1
act_like
Specify a role, profession, or perspective for the AI to adopt when generating a response; this parameter guides the AI in providing more context-specific or specialized results.
For example: "Products Expert", "Geographer", or "Google Sheet Table"
extra_instructions
Provide additional information or instructions to get a better result.
For example: "Use metric system", "Table should have 20 rows, or "Remember this: " & B2
model
Model affects quality, speed, and tokens count of tokens to use. We choose the optimal model ("default") by default, and here it's gpt-3.5-turbo. Information about models.
Options: "default", "gpt-4, "gpt-3.5-turbo", or "gpt-3.5-turbo-16k"
max_tokens
Limit the number of tokens that can be used for one function run. By default, it's limited only by the model.
1 token ≈ 4 chars in English
1 token ≈ 3/4 words
100 tokens ≈ 75 words
1-2 sentences ≈ 30 tokens
1 paragraph ≈ 100 tokens
1,500 words ≈ 2048 tokens
For Example: 100, 350, or 2048
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