fore

The fore client package

The foresight library within fore SDK allows you to easily evaluate the performance of your LLM system based on a variety of metrics.

You can sign-up and get started immediately at https://foresight.foreai.co.

Check our documentation at https://docs.foreai.co.

Quick start

1. Install the package using pip:

   pip install fore
   

   Or download the repo from GitHub and install via pip install .

2. • Get started with the following lines:

   from fore.foresight import Foresight
   
   foresight = Foresight(api_token="<YOUR_API_TOKEN>")
   
   foresight.log(query="What is the easiest programming language?",
                 response="Python",
                 contexts=["Python rated the easiest programming language"],
                 tag="my_awesome_experiment")
   
   # You can add more such queries using foresight.log
   # ....
   
   foresight.flush()
   

   • Or alternatively to curate your evalsets and run regular evals against them do:

   from fore.foresight import EvalRunConfig, Foresight, InferenceOutput, MetricType
   
   foresight = Foresight(api_token="<YOUR_API_TOKEN>")
   
   evalset = foresight.create_simple_evalset(
       evalset_id="programming-languages",
       queries=["hardest programming language?", "easiest programming language?"],
       reference_answers=["Malbolge", "Python"])
   
   run_config = EvalRunConfig(evalset_id="programming-languages",
                           experiment_id="my-smart-llm",
                           metrics=[MetricType.GROUNDEDNESS, 
                                    MetricType.REFERENCE_FACT_RECALL])
   
   
   def my_generate_fn(query: str) -> InferenceOutput:
       # Do the LLM processing with your model...
       # Here is some demo code:
       return InferenceOutput(
           generated_response="Malbolge" if "hardest" in query else "Python",
           contexts=[
               "Malbolge is the hardest language", "Python is the easiest language"
           ])
   
   foresight.generate_answers_and_run_eval(my_generate_fn, run_config)
   

Metrics

We currently offer two metrics:

• Groundedness
• Reference Fact Recall

Check here for more information.