Quickstart
Start building awesome AI Projects with LlamaAPI
Quickstart
In this guide you will find the essential commands for interacting with LlamaAPI, but don’t forget to check the rest of our documentation to extract the full power of our API.
Available Models
The following models are currently available through LlamaAPI. You will use their names when build a request further on this Quickstart Guide.
Llama-3
llama3-70b
(instruct model)llama3-8b
(instruct model)
Llama-2
All calls with prefix llama or llama2 migrated to Llama 3 on May/5/2024.
llama-7b-chat
or are mapped tollama3-8b
llama-13b-chat
andllama-70b-chat
are mapped tollama3-70b
codellama-7b-instruct
codellama-13b-instruct
codellama-34b-instruct
Mistral
mixtral-8x22b-instruct
mixtral-8x7b-instruct
mistral-7b-instruct
mistral-7b
(not a chat model)mixtral-8x22b
(not a chat model)
Gemma
gemma-7b
gemma-2b
Other
alpaca-7b
vicuna-7b
vicuna-13b
vicuna-13b-16k
falcon-7b-instruct
falcon-40b-instruct
openassistant-llama2-70b
Nous-Hermes-Llama2-13b
Nous-Hermes-llama-2-7b
Nous-Hermes-2-Mistral-7B-DPO
Nous-Hermes-2-Mixtral-8x7B-SFT
Nous-Hermes-2-Mixtral-8x7B-DPO
Nous-Hermes-2-Yi-34B
Nous-Capybara-7B-V1p9
OpenHermes-2p5-Mistral-7B
OpenHermes-2-Mistral-7B
Qwen1.5-72B-Chat
( replace 72B with 32B / 14B / 7B / 4B / 1.8B / 0.5B)
Installing the SDK
Our SDK allows your application to interact with LlamaAPI seamlessly, abstracting the handling
of aiohttp
sessions and headers, allowing for a simplified interaction with LlamaAPI.
Python
pip install llamaapi
Javascript
npm install llamaai
Usage
Once you have installed our library, you can follow the examples in this section to build powerfull applications, interacting with different models and making them invoke custom functions to enchance the user experience.
Python
import json
from llamaapi import LlamaAPI
# Initialize the SDK
llama = LlamaAPI("<your_api_token>")
# Build the API request
api_request_json = {
"messages": [
{"role": "user", "content": "What is the weather like in Boston?"},
],
"functions": [
{
"name": "get_current_weather",
"description": "Get the current weather in a given location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA",
},
"days": {
"type": "number",
"description": "for how many days ahead you wants the forecast",
},
"unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
},
},
"required": ["location", "days"],
}
],
"stream": False,
"function_call": "get_current_weather",
}
# Execute the Request
response = llama.run(api_request_json)
print(json.dumps(response.json(), indent=2))
Other parameters that you can pass in the request json are:
{
...
"max_length" = 500,
"temperature"= 0.1,
"top_p"= 1.0,
"frequency_penalty"=1.0
...
}
Javascript
-
Import the Library:
import LlamaAI from 'llamaai';
-
Initialize the Library:
const apiToken = 'INSERT_YOUR_API_TOKEN_HERE'; const llamaAPI = new LlamaAI(apiToken);
-
Make a Request
// Build the Request const apiRequestJson = { "messages": [ {"role": "user", "content": "What is the weather like in Boston?"}, ], "functions": [ { "name": "get_current_weather", "description": "Get the current weather in a given location", "parameters": { "type": "object", "properties": { "location": { "type": "string", "description": "The city and state, e.g. San Francisco, CA", }, "days": { "type": "number", "description": "for how many days ahead you wants the forecast", }, "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}, }, }, "required": ["location", "days"], } ], "stream": false, "function_call": "get_current_weather", }; // Execute the Request llamaAPI.run(apiRequestJson) .then(response => { // Process response }) .catch(error => { // Handle errors });
Change Log
Version 0.1: Initial release
Contributing
We welcome contributions to this project. Please see the Contributing Guidelines for more details.
License
Llamaapi SDK is licensed under the MIT License. Please see the License File for more details.