README.MD

Write Quality Prompts

Use and evaluate prompting techniques quickly.

QualityPrompts implements 58 prompting techniques explained in this survey from OpenAI, Microsoft, et al.

1. Install Quality Prompts:

pip install quality-prompts

2. Write the components of your prompt

from quality_prompts.prompt import QualityPrompt

directive = "You are given a document and your task..."
additional_information = "In the knowledge graph, ..."
output_formatting = "You will respond with a knowledge graph in..."

prompt = QualityPrompt(
                        directive,
                        additional_information,
                        output_formatting,
                        exemplar_store
                       )

3. QualityPrompts searches and uses only the few-shot examples that are relevant to the user's query

input_text = "list the disorders included in cvd"
prompt.few_shot(input_text=input_text, n_shots=1)

4. Simply call a prompting technique to your prompt

prompt.system2attention(input_text)

5. Compile your prompt for use

print(prompt.compile())

>> You are given a document and your task is to create a knowledge graph from it.
        
In the knowledge graph, entities such as people, places, objects, institutions, topics, ideas, etc. are represented as nodes.
Whereas the relationships and actions between them are represented as edges.

Example input: Cardiovascular disease (CVD) encompasses a spectrum of...
Example output: [{'entity': 'cardiovascular disease (cvd)', 'connections': ...

You will respond with a knowledge graph in the given JSON format:

[
    {"entity" : "Entity_name", "connections" : [
        {"entity" : "Connected_entity_1", "relationship" : "Relationship_with_connected_entity_1},
        {"entity" : "Connected_entity_2", "relationship" : "Relationship_with_connected_entity_2},
        ]
    },
]

6. Upcoming: Easily evaluate different prompting techniques

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