conda
using either Anaconda Distribution or Miniconda.sentence-similarity
type model downloaded onto your local machine.similarian.py
.
similarian.py
file:
base_url
base_url
with a specific /endpoint
for each function. The base_URL
can be constructed by combining the Server Address and Server Port specified in Anaconda AI Navigator, like this: http://<SERVER_ADDRESS>:<SERVER_PORT>
.
Set the base_url
to point to the default server address by adding the following line to your file.
localhost
and 127.0.0.1
are semantically identical./embedding
endpoint.
/embeddings
API specifications./health
endpoint and returns a JSON response that tells you the server’s status.
Add the following lines to your similarian.py
file:
sentence-similarity
model, you must have a function that hits the server’s /embedding
endpoint. This function processes input text and returns its vector representation (embedding).
Add the following lines to your similarian.py
file:
compare_texts
main
function and calculates the semantic and structural similarity scores.
Add the following lines to your similarian.py
file:
main
main
function ties the rest of the functions together and handles user input. It takes two inputs from the user and displays the results from the similarity calculations.
Add the following lines to your similarian.py
file:
sentence-similarity
type model!similarian.py
file.
content-compare
conda environment.similarian.py
file:
Synonyms and rephrasing
Effects of typos
Opposite meanings