Completions and Chat

Static Chat Completions

Static chat completions enable a more interactive session by providing conversation-like exchanges, you can send a series of messages. Each message has a role, such as user, assistant or system. The model processes these to continue the conversation naturally. This is useful for applications requiring a back-and-forth dialogue.

Using Regolo ClientPythonCURL

import regolo

regolo.default_key = "<YOUR_REGOLO_KEY>"
regolo.default_chat_model = "Llama-3.3-70B-Instruct"

print(regolo.static_chat_completions(messages=[{"role": "user", "content": "Tell me something about rome"}]))

import requests

api_url = "https://api.regolo.ai/v1/chat/completions"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer YOUR_REGOLO_KEY"
}
data = {
    "model": "Llama-3.3-70B-Instruct",
    "messages": [
        {"role": "user", "content": "Tell me something about Rome."}
    ]
}

response = requests.post(api_url, headers=headers, json=data)
print(response.json())

curl -X POST https://api.regolo.ai/v1/chat/completions 
-H "Content-Type: application/json" 
-H "Authorization: Bearer YOUR_REGOLO_KEY" 
-d '{
    "model": "gpt-4o",
    "messages": [
        {
            "role": "user",
            "content": "Tell me something about Rome."
        }
    ]
}'

Stream Chat Completions

Stream chat completions provide real-time, incremental responses from the model, enabling dynamic interactions and reducing latency. This feature is beneficial for applications that require immediate feedback and continuous conversation flow.

The streaming response is structured as JSON objects sent line by line. Each line typically contains metadata, including fields like id, created, model, and object, along with the choices array. Within choices, there is a delta object, which holds the content field representing the actual text response from the model. This structure allows applications to parse and process the conversational content as it arrives, ensuring efficient and timely updates to the user interface.

Using Regolo ClientPython

import regolo

regolo.default_key = "<YOUR_REGOLO_KEY>"
regolo.default_chat_model = "Llama-3.3-70B-Instruct"

client = regolo.RegoloClient()
response = client.run_chat(user_prompt="Tell me something about Rome.", full_output=True, stream=True)


while True:
    try:
        print(next(response))
    except StopIteration:
        break

import requests

api_url = "https://api.regolo.ai/v1/chat/completions"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer YOUR_REGOLO_KEY"
}
data = {
    "model": "Llama-3.3-70B-Instruct",
    "messages": [
        {"role": "user", "content": "Tell me something about Rome."}
    ],
    "stream": True
}

response = requests.post(api_url, headers=headers, json=data, stream=True)

for line in response.iter_lines():
    if line:
        print(line.decode('utf-8'))

Text Static Completions (Deprecated)

Warning

The static text completions are currently deprecated, and Regolo no longer provides any model that supports them natively. They are still listed among the available endpoints only for backward compatibility and internal use, but no public model currently supports them. Use the chat completions instead.

Static completions allow you to generate text responses based on a given prompt using the Regolo API.

Using Regolo ClientPythonCURL

import regolo

regolo.default_key = "<YOUR_REGOLO_KEY>"
regolo.default_chat_model = "Llama-3.3-70B-Instruct"

print(regolo.static_completions(prompt="Tell me something about Rome."))

import requests

api_url = "https://api.regolo.ai/v1/completions"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer YOUR_REGOLO_KEY"
}
data = {
    "model": "Llama-3.3-70B-Instruct",
    "prompt": "Tell me something about Rome.",
    "temperature": 0.7
}

response = requests.post(api_url, headers=headers, json=data)
print(response.json())

curl -X POST https://api.regolo.ai/v1/completions 
-H "Content-Type: application/json" 
-H "Authorization: Bearer YOUR_REGOLO_KEY" 
-d '{
    "model": "Llama-3.3-70B-Instruct",
    "prompt": "Tell me something about Rome.",
    "temperature": 0.7
}'

For the exhaustive API's endpoints documentation visit docs.api.regolo.ai.