Completions and Chat
Static Completions
Static completions allow you to generate text responses based on a given prompt using the Regolo API.
import regolo
regolo.default_key = "<YOUR_REGOLO_KEY>"
regolo.default_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
}'
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.
import regolo
regolo.default_key = "<YOUR_REGOLO_KEY>"
regolo.default_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.
import regolo
regolo.default_key = "<YOUR_REGOLO_KEY>"
regolo.default_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'))
For the exhaustive API's endpoints documentation visit docs.api.regolo.ai.