1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
"""
At the command line, only need to run once to install the package via pip:
$ pip install google-generativeai
"""
import google.generativeai as genai
genai.configure(api_key="YOUR API KEY")
defaults = {
'model': 'models/text-bison-001',
'temperature': 0.7,
'candidate_count': 1,
'top_k': 40,
'top_p': 0.95,
'max_output_tokens': 1024,
}
prompt = """This is a reverse dictionary. Describe a word or concept and this will help you find the term you are looking for.
Description: A moment in a game where no one can win and you get caught in an endless loop.
Word: Stalemate
Description: Fear of running out of something to read.
Word: Abibliophobia
Description: It's another word to describe an umbrella, but very silly.
Word: Bumbershoot
Description: A type of vehicle that goes under the water
Word:"""
response = genai.generate_text(
**defaults,
prompt=prompt
)
print(response.result)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
const { TextServiceClient } = require("@google-ai/generativelanguage");
const { GoogleAuth } = require("google-auth-library");
const MODEL_NAME = "models/text-bison-001";
const API_KEY = "YOUR API KEY";
const client = new TextServiceClient({
authClient: new GoogleAuth().fromAPIKey(API_KEY),
});
const promptString = "This is a reverse dictionary. Describe a word or concept and this will help you find the term you are looking for.\nDescription: A moment in a game where no one can win and you get caught in an endless loop.\nWord: Stalemate\nDescription: Fear of running out of something to read.\nWord: Abibliophobia\nDescription: It's another word to describe an umbrella, but very silly.\nWord: Bumbershoot\nDescription: A type of vehicle that goes under the water\nWord:";
client.generateText({
// required, which model to use to generate the result
model: MODEL_NAME,
// optional, 0.0 always uses the highest-probability result
temperature: 0.7,
// optional, how many candidate results to generate
candidateCount: 1,
// optional, number of most probable tokens to consider for generation
top_k: 40,
// optional, for nucleus sampling decoding strategy
top_p: 0.95,
// optional, maximum number of output tokens to generate
max_output_tokens: 1024,
prompt: {
text: promptString,
},
}).then(result => {
console.log(JSON.stringify(result, null, 2));
});