rag-json.py

import requests
import json

input_file = open('/Users/ap2x07/Desktop/post-content.json')
corpus_of_documents = json.load(input_file)
# print(corpus_of_documents)
# corpus_of_documents = []

# corpus_of_documents = [
#     "Take a leisurely walk in the park and enjoy the fresh air.",
#     "Visit a local museum and discover something new.",
#     "Attend a live music concert and feel the rhythm.",
#     "Go for a hike and admire the natural scenery.",
#     "Have a picnic with friends and share some laughs.",
#     "Explore a new cuisine by dining at an ethnic restaurant.",
#     "Take a yoga class and stretch your body and mind.",
#     "Join a local sports league and enjoy some friendly competition.",
#     "Attend a workshop or lecture on a topic you're interested in.",
#     "Visit an amusement park and ride the roller coasters."
# ]


def jaccard_similarity(query, document):
    query = query.lower().split(" ")
    document = document.lower().split(" ")
    intersection = set(query).intersection(set(document))
    union = set(query).union(set(document))
    return len(intersection)/len(union)


def return_response(query, corpus):
    similarities = []
    for doc in corpus:
        similarity = jaccard_similarity(user_input, doc)
        similarities.append(similarity)
    return corpus_of_documents[similarities.index(max(similarities))]


# Get user input for both user preference and prompt text
user_input = input("Enter your preference / question: ")
prompt_text = input("Enter the prompt text to use: ")

# user_input = "I like to hike"
relevant_document = return_response(user_input, corpus_of_documents)

# https://github.com/jmorganca/ollama/blob/main/docs/api.md
# Construct the prompt
prompt = """
{}
This is the recommended activity: {}
The user input is: {}
Compile a recommendation to the user based on the recommended activity and the user input.
""".format(prompt_text, relevant_document, user_input)


url = 'http://localhost:11434/api/generate'
data = {
    "model": "llama2",
    "prompt": prompt.format(user_input=user_input, relevant_document=relevant_document)
}
headers = {'Content-Type': 'application/json'}
response = requests.post(url, data=json.dumps(data),
                         headers=headers, stream=True)
full_response = []
try:
    count = 0
    for line in response.iter_lines():
        # filter out keep-alive new lines
        # count += 1
        # if count % 5== 0:
        #     print(decoded_line['response']) # print every fifth token
        if line:
            decoded_line = json.loads(line.decode('utf-8'))

            full_response.append(decoded_line['response'])
finally:
    response.close()
print(''.join(full_response))