December

New models: Gemini 2.0 Flash, Llama 3.3 70B

December 12th, 2024

To support you in adopting the latest models, we’ve added support for more new models, including the latest experimental models for Gemini.

These include gemini-2.0-flash-exp with better performance than Gemini 1.5 Pro and tool use, and gemini-exp-1206, the latest experimental advanced model.

We’ve also added support for Llama 3.3 70B on Groq, Meta’s latest model with performance comparable to their largest Llama 3.1 405B model.

You can start using these models in your Prompts by going to the Editor and selecting the model from the dropdown. (To use the Gemini models, you need to have a Google API key saved in your Humanloop account settings.)

Gemini 2.0 Flash in Prompt Editor

Drag and Drop in the Sidebar

December 12th, 2024

You can now drag and drop files into the sidebar to organize your Prompts, Evaluators, Datasets, and Flows into Directories.

With this much requested feature, you can easily reorganize your workspace hierarchy without having to use the ‘Move…’ modals.

This improvement makes it easier to maintain a clean and organized workspace. We recommend using a Directory per project to group together related files.

Logs with user-defined IDs

December 6th, 2024

We’ve added the ability to create Logs with your own unique ID, which you can then use to reference the Log when making API calls to Humanloop.

1my_id = "my_very_own_and_unique_id"
2# create Log with "my_very_own_and_unique_id" id
3humanloop.prompts.call(
4    path="path_to_the_prompt",
5    prompt={
6      "model": "gpt-4",
7      "template": [
8        {
9          "role": "system",
10          "content": "You are a helpful assistant. Tell the truth, the whole truth, and nothing but the truth",
11        },
12      ],
13    },
14    log_id=my_id,
15    messages=[{"role": "user", "content": "Is it acceptable to put pineapples on pizza?"}],
16)
17# add evaluator judgment to this Log using your own id
18humanloop.evaluators.log(
19    parent_id=my_id,
20    path="path_to_my_evaluator",
21    judgment="good",
22    spec={
23      "arguments_type": "target_free",
24      "return_type": "select",
25      "evaluator_type": "human",
26      "options": [{"name": "bad", "valence": "negative"}, {"name": "good", "valence": "positive"}]
27    })

This is particularly useful for providing judgments on the Logs without requiring you to store Humanloop-generated IDs in your application.

Flow Trace in Review View

December 5th, 2024

We’ve added the ability to see the full Flow trace directly in the Review view. This is useful to get the full context of what was called during the execution of a Flow.

To open the Log drawer side panel, click on the Log ID above the Log output in the Review view.