Add GPT4-Omni-mini

Project.toml

@@ -23,4 +23,4 @@ Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 TOML = "fa267f1f-6049-4f14-aa54-33bafae1ed76"
 
 [compat]
-PromptingTools = "0.33"
+PromptingTools = "0.39"

README.md

@@ -67,6 +67,7 @@ The latest Mistral model - codestral - is quite impressive (it's very fast as we
 |    claude-3-haiku-20240307 |     4.0 |  74.9 |                27.2 |                9 |              261 |       0.05 |
 |         gpt-4-0125-preview |    30.3 |  74.4 |                30.3 |               39 |              284 |       1.29 |
 |         gpt-4-1106-preview |    22.4 |  74.4 |                29.9 |               19 |              142 |       1.21 |
+|     gpt-4o-mini-2024-07-18 |     5.1 |  74.0 |                29.4 |               32 |              276 |       0.03 |
 |          gpt-4o-2024-05-13 |     4.3 |  72.9 |                29.1 |               29 |              257 |        0.0 |
 |             deepseek-coder |    13.0 |  71.6 |                32.6 |               39 |              115 |       0.01 |
 |         mistral-large-2402 |     8.5 |  71.6 |                27.2 |               13 |              223 |        0.0 |
@@ -84,6 +85,7 @@ The latest Mistral model - codestral - is quite impressive (it's very fast as we
 
 
 
+
 Note: From mid-February 2024, "gpt-3.5-turbo" will point to the latest release, "gpt-3.5-turbo-0125" (deprecating the June release).
 
 Same information, but as a bar chart:

code_generation/data_analysis/add_yearmonth/gpt-4o-mini-2024-07-18/conversation__InJulia__1SHOT__20240719_072913__113.json

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+[{"content":"Act as a helpful AI assistant","variables":[],"_type":"systemmessage"},{"content":"In Julia, Given a DataFrame `df` with column `dt` representing DateTimes. Write a function `add_yearmonth` that creates a new column `ym` by extracting year and month from `dt` and concatenating them together as an integer in format: “yyyymm”.","variables":[],"_type":"usermessage"},{"content":"You can create a function in Julia to accomplish this by using the `DataFrames` and `Dates` packages. Below is an implementation of the `add_yearmonth` function that takes a DataFrame and modifies it by adding a new column `ym` that concatenates the year and month from the `dt` column.\n\n```julia\nusing DataFrames\nusing Dates\n\nfunction add_yearmonth(df::DataFrame)\n    # Ensure the column dt is of type DateTime\n    if !haskey(df, :dt) || !(df.dt isa Vector{DateTime})\n        throw(ArgumentError(\"DataFrame must contain a DateTime column named 'dt'\"))\n    end\n\n    # Create the new ym column\n    df.ym = [year(dt) * 100 + month(dt) for dt in df.dt]\n\n    return df\nend\n\n# Example usage:\ndf = DataFrame(dt = [DateTime(2023, 1, 15), DateTime(2022, 12, 5), DateTime(2023, 5, 20)])\ndf = add_yearmonth(df)\n\nprintln(df)\n```\n\n### Explanation:\n1. **Import Packages**: The `DataFrames` package is used for DataFrame operations, and the `Dates` package provides functionality to handle and manipulate date and time.\n  \n2. **Function Definition**: `add_yearmonth` takes a DataFrame `df` as an argument.\n\n3. **Validation**: The function checks if the DataFrame has a column named `dt` and ensures that it is of type `Vector{DateTime}`. If not, it throws an error.\n\n4. **Creating the New Column**: It calculates the new `ym` column by extracting the year and month from the `dt` column, calculating `year(dt) * 100 + month(dt)` for each DateTime value, and stores it in the new column.\n\n5. **Return Value**: Finally, it returns the modified DataFrame.\n\nYou can now use this function to add the `ym` column based on your DateTime `dt` column in any DataFrame.","status":200,"tokens":[76,439],"elapsed":3.666199167,"cost":0.0002748,"log_prob":null,"finish_reason":"stop","run_id":1522981868,"sample_id":null,"_type":"aimessage"}]

code_generation/data_analysis/add_yearmonth/gpt-4o-mini-2024-07-18/conversation__InJulia__1SHOT__20240719_072918__712.json

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+[{"content":"Act as a helpful AI assistant","variables":[],"_type":"systemmessage"},{"content":"In Julia, Given a DataFrame `df` with column `dt` representing DateTimes. Write a function `add_yearmonth` that creates a new column `ym` by extracting year and month from `dt` and concatenating them together as an integer in format: “yyyymm”.","variables":[],"_type":"usermessage"},{"content":"Certainly! In Julia, you can achieve this by using the `DataFrames` and `Dates` libraries. Below is a function `add_yearmonth` that takes a DataFrame and creates a new column called `ym` by extracting the year and month from the `dt` column and concatenating them in the format \"yyyymm\".\n\nHere’s how you can implement the function:\n\n```julia\nusing DataFrames\nusing Dates\n\nfunction add_yearmonth(df::DataFrame)\n    # Ensure that the dt column exists and is of type DateTime\n    if !haskey(df, :dt) || !(eltype(df.dt) <: DateTime)\n        throw(ArgumentError(\"DataFrame must have a column 'dt' of type DateTime\"))\n    end\n    \n    # Create the new ym column\n    df.ym = year.(df.dt) .* 100 .+ month.(df.dt)\n    \n    return df\nend\n```\n\n### Usage\n\nFirst, make sure to create a DataFrame with a DateTime column:\n\n```julia\nusing DataFrames\nusing Dates\n\n# Create a sample DataFrame\ndf = DataFrame(dt = [DateTime(2023, 10, 1), DateTime(2023, 11, 15), DateTime(2024, 1, 5)])\n\n# Call the function to add the year-month column\ndf = add_yearmonth(df)\n\n# Display the result\nprintln(df)\n```\n\n### Explanation\n\n- The function `add_yearmonth` checks whether the DataFrame contains a column named `dt` and verifies that this column is of type `DateTime`.\n- It then uses broadcasting to extract the year and month from the DateTime column, performing calculations to concatenate these values into the desired format as an integer.\n- Finally, it creates a new column `ym` in the DataFrame.\n\nThis function will modify the DataFrame `df` in place to include the new `ym` column. You can return the modified DataFrame to see the results.","status":200,"tokens":[76,416],"elapsed":5.192888209,"cost":0.000261,"log_prob":null,"finish_reason":"stop","run_id":187837304,"sample_id":null,"_type":"aimessage"}]

code_generation/data_analysis/add_yearmonth/gpt-4o-mini-2024-07-18/conversation__InJulia__1SHOT__20240719_072931__235.json

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+[{"content":"Act as a helpful AI assistant","variables":[],"_type":"systemmessage"},{"content":"In Julia, Given a DataFrame `df` with column `dt` representing DateTimes. Write a function `add_yearmonth` that creates a new column `ym` by extracting year and month from `dt` and concatenating them together as an integer in format: “yyyymm”.","variables":[],"_type":"usermessage"},{"content":"To achieve the task in Julia using the `DataFrames` package, you can create a function named `add_yearmonth`. This function will extract the year and month from the `dt` column and concatenate them in the specified format (\"yyyymm\"). Here's how you can implement it:\n\n```julia\nusing DataFrames\n\nfunction add_yearmonth(df::DataFrame)\n    # Create a new column 'ym' by extracting year and month from 'dt'\n    df.ym = (year.(df.dt) .* 100 .+ month.(df.dt))\n    return df\nend\n```\n\n### Explanation:\n1. **Input:** The function takes a DataFrame `df` as an argument.\n2. **Year and Month Extraction:** It uses the `year` and `month` functions from the `Dates` standard library to extract the year and month from the `dt` column.\n3. **Concatenation:** It concatenates them by multiplying the year by 100 and adding the month to get the desired format.\n4. **New Column:** The result is assigned to a new column `ym` in the DataFrame.\n5. **Return:** The function returns the modified DataFrame.\n\n### Usage Example:\nHere is an example of how to use this function:\n\n```julia\nusing Dates\n\n# Sample DataFrame\ndata = DataFrame(dt = [DateTime(\"2021-01-15\"), DateTime(\"2021-02-20\"), DateTime(\"2022-03-05\")])\n\n# Add 'ym' column\ndata = add_yearmonth(data)\n\n# Display the updated DataFrame\nprintln(data)\n```\n\n### Expected Output:\nThe output DataFrame will have a new column `ym` in the \"yyyymm\" format:\n\n```\n3×2 DataFrame\n Row │ dt                     ym\n     │ DateTime              Int64\n─────┼───────────────────────────────\n   1 │ 2021-01-15T00:00:00  202101\n   2 │ 2021-02-20T00:00:00  202102\n   3 │ 2022-03-05T00:00:00  202203\n```\n\nMake sure that you have the `DataFrames` and `Dates` packages available in your Julia environment for this to work.","status":200,"tokens":[76,484],"elapsed":12.678581792,"cost":0.0003018,"log_prob":null,"finish_reason":"stop","run_id":148917863,"sample_id":null,"_type":"aimessage"}]

code_generation/data_analysis/add_yearmonth/gpt-4o-mini-2024-07-18/conversation__InJulia__1SHOT__20240719_072935__958.json

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+[{"content":"Act as a helpful AI assistant","variables":[],"_type":"systemmessage"},{"content":"In Julia, Given a DataFrame `df` with column `dt` representing DateTimes. Write a function `add_yearmonth` that creates a new column `ym` by extracting year and month from `dt` and concatenating them together as an integer in format: “yyyymm”.","variables":[],"_type":"usermessage"},{"content":"Certainly! You can create the `add_yearmonth` function in Julia using the `DataFrames` and `Dates` packages. Here’s how you can implement it:\n\n```julia\nusing DataFrames\nusing Dates\n\n# Define the function\nfunction add_yearmonth!(df::DataFrame)\n    # Ensure the `dt` column is of type DateTime\n    if !haskey(df, :dt) || !(eltype(df.dt) <: DateTime)\n        error(\"The DataFrame must have a column `dt` of type DateTime.\")\n    end\n\n    # Create a new column `ym` by extracting year and month\n    df.ym = (year.(df.dt) .* 100 .+ month.(df.dt))  # Concatenate year and month\n    return df\nend\n\n# Example usage\ndf = DataFrame(dt = [DateTime(\"2023-01-15\"), DateTime(\"2023-02-20\"), DateTime(\"2023-11-30\")])\nadd_yearmonth!(df)\n\n# Show the updated DataFrame\nprintln(df)\n```\n\n### Explanation:\n- The `add_yearmonth!` function takes a `DataFrame` as an argument.\n- It checks if the `dt` column exists and is of type `DateTime`.\n- It then creates a new column `ym` by concatenating the year and month. This is done by multiplying the year by 100 and adding the month, resulting in the format \"yyyymm\".\n- Finally, the DataFrame is updated in place and returned.\n\nYou can test the function with a sample DataFrame as shown in the example usage.","status":200,"tokens":[76,338],"elapsed":3.509906291,"cost":0.0002142,"log_prob":null,"finish_reason":"stop","run_id":-1483903192,"sample_id":null,"_type":"aimessage"}]

code_generation/data_analysis/add_yearmonth/gpt-4o-mini-2024-07-18/conversation__InJulia__1SHOT__20240719_072939__301.json

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+[{"content":"Act as a helpful AI assistant","variables":[],"_type":"systemmessage"},{"content":"In Julia, Given a DataFrame `df` with column `dt` representing DateTimes. Write a function `add_yearmonth` that creates a new column `ym` by extracting year and month from `dt` and concatenating them together as an integer in format: “yyyymm”.","variables":[],"_type":"usermessage"},{"content":"You can achieve this by defining a function `add_yearmonth` in Julia that takes a DataFrame as input, extracts the year and month from the `dt` column, concatenates them, and adds a new column `ym` to the DataFrame. Here's how you can do it:\n\n```julia\nusing DataFrames, Dates\n\nfunction add_yearmonth(df::DataFrame)\n    # Check if the column 'dt' exists in the DataFrame\n    if !haskey(df, :dt)\n        throw(ArgumentError(\"DataFrame must contain a column named 'dt'.\"))\n    end\n    \n    # Create the 'ym' column by formatting the year and month\n    df.ym = [year(d) * 100 + month(d) for d in df.dt]\nend\n```\n\n### Explanation:\n1. **Check Column Existence**: The function first checks if the column `dt` exists in the DataFrame. If it doesn't, it raises an error.\n2. **Extract Year and Month**: It generates a new column `ym` by iterating over each DateTime `d` in the `dt` column, extracting the year with `year(d)` and the month with `month(d)`, and concatenating them in the format \"yyyymm\".\n3. **Store Result**: The result is stored in a new column called `ym`.\n\n### Usage Example:\nHere's how you would use the `add_yearmonth` function with a sample DataFrame:\n\n```julia\nusing DataFrames, Dates\n\n# Create a sample DataFrame\ndf = DataFrame(dt = [DateTime(2021, 3, 15), DateTime(2022, 1, 8), DateTime(2022, 12, 25)])\n\n# Call the function to add the 'ym' column\nadd_yearmonth(df)\n\n# Display the updated DataFrame\nprintln(df)\n```\n\nThe DataFrame `df` will now include an additional column `ym` containing the year and month in the specified format.","status":200,"tokens":[76,419],"elapsed":3.935956125,"cost":0.0002628,"log_prob":null,"finish_reason":"stop","run_id":-1399994022,"sample_id":null,"_type":"aimessage"}]

code_generation/data_analysis/add_yearmonth/gpt-4o-mini-2024-07-18/conversation__InJulia__1SHOT__20240719_072944__635.json

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+[{"content":"Act as a helpful AI assistant","variables":[],"_type":"systemmessage"},{"content":"In Julia, Given a DataFrame `df` with column `dt` representing DateTimes. Write a function `add_yearmonth` that creates a new column `ym` by extracting year and month from `dt` and concatenating them together as an integer in format: “yyyymm”.","variables":[],"_type":"usermessage"},{"content":"Sure! Below is a Julia function called `add_yearmonth` that takes a DataFrame `df` with a DateTime column `dt` and creates a new column `ym` by extracting the year and month, then concatenating them in the \"yyyymm\" format.\n\nFirst, make sure you have the necessary packages installed. You will need the `DataFrames` and `Dates` packages. You can install them using the following commands in Julia:\n\n```julia\nusing Pkg\nPkg.add(\"DataFrames\")\nPkg.add(\"Dates\")\n```\n\nNow, here is the function:\n\n```julia\nusing DataFrames\nusing Dates\n\nfunction add_yearmonth(df::DataFrame)\n    # Check if dt column exists\n    if !haskey(df, :dt)\n        throw(ArgumentError(\"DataFrame does not contain a 'dt' column.\"))\n    end\n    \n    # Create a new column 'ym' by extracting year and month\n    df.ym = (year.(df.dt) * 100 .+ month.(df.dt))\n    \n    return df\nend\n```\n\n### Explanation:\n- The function first checks if the `dt` column exists in the DataFrame.\n- It then creates a new column `ym` by extracting the year and month from the `dt` column. \n  - `year.(df.dt)` extracts the year.\n  - `month.(df.dt)` extracts the month.\n  - The year is multiplied by 100 and added to the month to create the \"yyyymm\" format.\n  \n### Usage:\nYou can use the function like this:\n\n```julia\n# Create a sample DataFrame\nusing Random\ndf = DataFrame(dt = [DateTime(2021, 5, 1), DateTime(2022, 8, 15), DateTime(2023, 1, 10)])\n\n# Add the 'ym' column\ndf = add_yearmonth(df)\n\n# Display the updated DataFrame\nprintln(df)\n```\n\nThis will result in a DataFrame with an additional `ym` column containing the concatenated year and month values.","status":200,"tokens":[76,435],"elapsed":5.376053958,"cost":0.0002724,"log_prob":null,"finish_reason":"stop","run_id":-165151417,"sample_id":null,"_type":"aimessage"}]

code_generation/data_analysis/add_yearmonth/gpt-4o-mini-2024-07-18/conversation__InJulia__1SHOT__20240719_072947__741.json

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+[{"content":"Act as a helpful AI assistant","variables":[],"_type":"systemmessage"},{"content":"In Julia, Given a DataFrame `df` with column `dt` representing DateTimes. Write a function `add_yearmonth` that creates a new column `ym` by extracting year and month from `dt` and concatenating them together as an integer in format: “yyyymm”.","variables":[],"_type":"usermessage"},{"content":"You can create a function in Julia that adds a new column `ym` to a `DataFrame` by extracting the year and month from the `dt` column. The `DateTime` type in Julia provides functions to easily get the year and month. You can then format them and concatenate them to form the desired integer format. Here’s how you can implement this:\n\n```julia\nusing DataFrames\n\nfunction add_yearmonth(df::DataFrame)\n    # Create a new column `ym` by extracting year and month from `dt`\n    df.ym .= year.(df.dt) .* 100 .+ month.(df.dt)\n    return df\nend\n```\n\n### Example Usage:\nFirst, ensure you have the necessary packages installed and then create an example DataFrame:\n\n```julia\nusing DataFrames\n\n# Create an example DataFrame\ndf = DataFrame(dt = [DateTime(2021, 5, 1), DateTime(2022, 8, 15), DateTime(2023, 1, 30)])\n\n# Call the function to add yearmonth column\nadd_yearmonth(df)\n\n# Display the updated DataFrame\nprintln(df)\n```\n\n### Output:\nThis will modify the DataFrame `df` to include the new `ym` column, which will contain the values in the format \"yyyymm\".\n\nKeep in mind:\n- The `.=` operator is used to broadcast the assignment to the entire column efficiently.\n- Ensure that the `dt` column in your DataFrame is of `DateTime` type for the function to work correctly.","status":200,"tokens":[76,324],"elapsed":3.251614083,"cost":0.0002058,"log_prob":null,"finish_reason":"stop","run_id":264790451,"sample_id":null,"_type":"aimessage"}]

code_generation/data_analysis/add_yearmonth/gpt-4o-mini-2024-07-18/conversation__InJulia__1SHOT__20240719_072956__993.json

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+[{"content":"Act as a helpful AI assistant","variables":[],"_type":"systemmessage"},{"content":"In Julia, Given a DataFrame `df` with column `dt` representing DateTimes. Write a function `add_yearmonth` that creates a new column `ym` by extracting year and month from `dt` and concatenating them together as an integer in format: “yyyymm”.","variables":[],"_type":"usermessage"},{"content":"You can create a function `add_yearmonth` in Julia to achieve that using the `DataFrames` and `Dates` packages. Here's how you can implement the function to extract the year and month from the DateTime column and concatenate them in the desired format:\n\n```julia\nusing DataFrames\nusing Dates\n\nfunction add_yearmonth(df::DataFrame)\n    # Ensure 'dt' is present in the DataFrame\n    if !haskey(df, :dt)\n        error(\"DataFrame does not contain a 'dt' column.\")\n    end\n\n    # Extract year and month, and create 'ym' column\n    df.ym = (year.(df.dt) .* 100 .+ month.(df.dt)) .|> int\nend\n```\n\n### How it Works:\n- The function first checks if the DataFrame `df` contains a column named `dt`.\n- It then uses broadcasting (`year.(df.dt)` and `month.(df.dt)`) to extract the year and month as arrays.\n- The year is multiplied by 100, and then the month is added to create the `yyyymm` format.\n- Finally, the result is converted to integers using the `. |> int` syntax.\n\n### Example Usage\nTo use the function, you would do something like the following:\n\n```julia\nusing DataFrames, Dates\n\n# Example DataFrame with DateTime column\ndf = DataFrame(dt = [DateTime(\"2023-01-15\"), DateTime(\"2022-12-25\"), DateTime(\"2021-06-30\")])\n\n# Call the function to add the 'ym' column\nadd_yearmonth(df)\n\n# Show the updated DataFrame\nprintln(df)\n```\n\n### Output\nYou should expect your DataFrame `df` to now look like this:\n\n```\n3×2 DataFrame\n Row │ dt                   ym\n─────┼───────────────\n   1 │ 2023-01-15T00:00:00  202301\n   2 │ 2022-12-25T00:00:00  202212\n   3 │ 2021-06-30T00:00:00  202106\n```\n\nThis `ym` column contains the year and month in the required format as an integer.","status":200,"tokens":[76,481],"elapsed":8.274114083,"cost":0.0003,"log_prob":null,"finish_reason":"stop","run_id":829084942,"sample_id":null,"_type":"aimessage"}]