https://github.com/codebanesr/llms-client
A client to make chat completion requests to any llm [currently supports chatgpt and claude]
https://github.com/codebanesr/llms-client
Last synced: 10 months ago
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A client to make chat completion requests to any llm [currently supports chatgpt and claude]
- Host: GitHub
- URL: https://github.com/codebanesr/llms-client
- Owner: codebanesr
- License: mit
- Created: 2023-05-19T13:31:32.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2023-05-25T23:22:59.000Z (almost 3 years ago)
- Last Synced: 2024-11-11T12:46:38.987Z (over 1 year ago)
- Language: TypeScript
- Size: 198 KB
- Stars: 14
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
## 📦 llms-client - Connect to Multiple Language Models (LLMs)
A powerful package that enables users to effortlessly connect to various Language Models, including Claude, Bard, and ChatGPT. Stay tuned for upcoming support for Vicuna and Alpaca!
🔗 Get it on [npm](https://www.npmjs.com/package/llms-client)
#AI #Development #LLMs
## Installation
To install the package, use npm:
```bash
npm install llms-client
```
## Usage
To use the package, follow these steps:
1. Import and create an instance of the `CompletionServiceSelector` class, providing the appropriate adapter configuration. The adapter configuration should include the type of LLM, base URL, and API key.
```typescript
import { CompletionServiceSelector, AdapterConfig } from 'llms-client';
const adapterConfig: AdapterConfig = {
type: 'chatGPT', // Specify the desired language model: 'chatGPT', 'claudeAI', or 'bard'
baseurl: '', // Set the base URL for the adapter
apiKey: '', // Set the API key for authentication
model: '', // Optional: Specify the model for the adapter (if applicable)
};
```
2. Get chat completions by providing a list of messages and the maximum number of tokens in the completion response.
```ts
const messages: Message[] = [
{ role: "system", content: "Welcome!" },
{ role: "user", content: "Hello, how are you?" },
{ role: "assistant", content: "I'm doing well, thank you!" },
];
const { CompletionServiceSelector } = require("../dist/index");
async function completePrompt(prompt, maxTokens) {
const config = {
apiKey: "",
baseurl: "https://api.openai.com",
type: "chatGPT",
model: "text-davinci-003",
};
const service = new CompletionServiceSelector(config);
// only supports gpt-3.5-turbo
const chat_completion = await service.getChatCompletions(messages, maxTokens);
console.log({ chat_completion });
}
completePrompt("What is the purpose of life ?", 300)
.then((data) => {
console.log(data);
})
.catch((e) => {
console.error(e);
});
```
---
### Claude full example
```ts
const { CompletionServiceSelector } = require('../dist/index');
async function completePrompt(prompt, maxTokens) {
const config = {
apiKey: '',
baseurl: 'https://api.anthropic.com/v1/complete',
type: 'claudeAI',
model: 'claude-v1'
};
const service = new CompletionServiceSelector(config);
const completionResponse = await service.complete(prompt, maxTokens);
console.log(completionResponse);
/**
* the last message's content has to be left empty... This will be filled by claude
* */
const messages = [
{ role: 'Human', content: 'Tell me a haiku about trees' },
{ role: 'Assistant', content: '' }
];
const chatResponse = await service.getChatCompletions(messages, 300);
console.log(chatResponse);
}
completePrompt('What is the capital of united states', 300)
.then(data => {
console.log(data);
})
.catch(e => {
console.error(e);
});
```
3. Make a completion with a prompt by providing the prompt and the maximum number of tokens in the completion response.
```typescript
const prompt = 'Hello, world!';
completionService.complete(prompt, maxTokens)
.then((response: string) => {
// Handle the completion response
console.log(response);
})
.catch((error: Error) => {
// Handle errors
console.error(error);
});
```
## Available Scripts
The following scripts are available in the project's `package.json` file:
- `start`: Starts the development server in watch mode.
- `build`: Builds the package for production.
- `test`: Runs tests for the package.
- `lint`: Lints the package's source code.
- `prepare`: Builds the package before publishing or versioning.
- `size`: Checks the package size using size-limit.
- `analyze`: Analyzes the package size and provides reasons using size-limit.
You can run these scripts using npm. For example:
```bash
npm run build
```
## Usage examples
[GPT usage example](test/gpt.test.js)
[Claude(Anthropic) usage example](test/claude.test.js)
[Bard usage example](test/bard.test.js) Coming soon
## Configuration
The package can be configured using the `package.json` file. Some important fields include:
- `name`: The name of the package.
- `author`: The author of the package.
- `module`: The entry point for the package's ES module version.
## Contribution
Please follow the [Contribution Guide](CONTRIBUTING.md) for detailed instructions on how to contribute to this project.
## Contributors
Thank you to the following people for their contributions to this project:
* [Shanur Rahman](https://github.com/shanur-rahman) (shanur.cse.nitap@gmail.com)
* [Marzoog AlGhazwi](https://github.com/Marzoog-Alghazwi) (marzoog.m.alghazwi@gmail.com)
## License
This package is licensed under the MIT License.
## Author
This package was created by Shanur Rahman.