humanloop 0.4.0a18

Client for Humanloop API

humanloop@0.4.0a18

Requirements

Python >=3.7

Installing

pip install humanloop==0.4.0a18

Getting Started

from pprint import pprint
from humanloop import Humanloop, ApiException

humanloop = Humanloop(
    api_key="YOUR_API_KEY",
    openai_api_key="YOUR_OPENAI_API_KEY",
    ai21_api_key="YOUR_AI21_API_KEY",
    mock_api_key="YOUR_MOCK_API_KEY",
    anthropic_api_key="YOUR_ANTHROPIC_API_KEY",
)

try:
    # Chat
    chat_response = humanloop.chat(
        project="sdk-example",
        messages=[
            {
                "role": "user",
                "content": "Explain asynchronous programming.",
            }
        ],
        model_config={
            "model": "gpt-3.5-turbo",
            "max_tokens": -1,
            "temperature": 0.7,
            "chat_template": [
                {
                    "role": "system",
                    "content": "You are a helpful assistant who replies in the style of {{persona}}.",
                },
            ],
        },
        inputs={
            "persona": "the pirate Blackbeard",
        },
        stream=False,
    )
    pprint(chat_response.body)
    pprint(chat_response.body["project_id"])
    pprint(chat_response.body["data"][0])
    pprint(chat_response.body["provider_responses"])
    pprint(chat_response.headers)
    pprint(chat_response.status)
    pprint(chat_response.round_trip_time)
except ApiException as e:
    print("Exception when calling .chat: %s\n" % e)
    pprint(e.body)
    if e.status == 422:
        pprint(e.body["detail"])
    pprint(e.headers)
    pprint(e.status)
    pprint(e.reason)
    pprint(e.round_trip_time)
try:
    # Complete
    complete_response = humanloop.complete(
        project="sdk-example",
        inputs={
            "text": "Llamas that are well-socialized and trained to halter and lead after weaning and are very friendly and pleasant to be around. They are extremely curious and most will approach people easily. However, llamas that are bottle-fed or over-socialized and over-handled as youth will become extremely difficult to handle when mature, when they will begin to treat humans as they treat each other, which is characterized by bouts of spitting, kicking and neck wrestling.[33]",
        },
        model_config={
            "model": "gpt-3.5-turbo",
            "max_tokens": -1,
            "temperature": 0.7,
            "prompt_template": "Summarize this for a second-grade student:\n\nText:\n{{text}}\n\nSummary:\n",
        },
        stream=False,
    )
    pprint(complete_response.body)
    pprint(complete_response.body["project_id"])
    pprint(complete_response.body["data"][0])
    pprint(complete_response.body["provider_responses"])
    pprint(complete_response.headers)
    pprint(complete_response.status)
    pprint(complete_response.round_trip_time)
except ApiException as e:
    print("Exception when calling .complete: %s\n" % e)
    pprint(e.body)
    if e.status == 422:
        pprint(e.body["detail"])
    pprint(e.headers)
    pprint(e.status)
    pprint(e.reason)
    pprint(e.round_trip_time)
try:
    # Feedback
    feedback_response = humanloop.feedback(
        type="rating",
        value="good",
        data_id="data_[...]",
        user="[e-mail]",
    )
    pprint(feedback_response.body)
    pprint(feedback_response.headers)
    pprint(feedback_response.status)
    pprint(feedback_response.round_trip_time)
except ApiException as e:
    print("Exception when calling .feedback: %s\n" % e)
    pprint(e.body)
    if e.status == 422:
        pprint(e.body["detail"])
    pprint(e.headers)
    pprint(e.status)
    pprint(e.reason)
    pprint(e.round_trip_time)
try:
    # Log
    log_response = humanloop.log(
        project="sdk-example",
        inputs={
            "text": "Llamas that are well-socialized and trained to halter and lead after weaning and are very friendly and pleasant to be around. They are extremely curious and most will approach people easily. However, llamas that are bottle-fed or over-socialized and over-handled as youth will become extremely difficult to handle when mature, when they will begin to treat humans as they treat each other, which is characterized by bouts of spitting, kicking and neck wrestling.[33]",
        },
        output="Llamas can be friendly and curious if they are trained to be around people, but if they are treated too much like pets when they are young, they can become difficult to handle when they grow up. This means they might spit, kick, and wrestle with their necks.",
        source="sdk",
        config={
            "model": "gpt-3.5-turbo",
            "max_tokens": -1,
            "temperature": 0.7,
            "prompt_template": "Summarize this for a second-grade student:\n\nText:\n{{text}}\n\nSummary:\n",
            "type": "model",
        },
    )
    pprint(log_response.body)
    pprint(log_response.headers)
    pprint(log_response.status)
    pprint(log_response.round_trip_time)
except ApiException as e:
    print("Exception when calling .log: %s\n" % e)
    pprint(e.body)
    if e.status == 422:
        pprint(e.body["detail"])
    pprint(e.headers)
    pprint(e.status)
    pprint(e.reason)
    pprint(e.round_trip_time)

Async

async support is available by prepending a to any method.

import asyncio
from pprint import pprint
from humanloop import Humanloop, ApiException

humanloop = Humanloop(
    api_key="YOUR_API_KEY",
    openai_api_key="YOUR_OPENAI_API_KEY",
    ai21_api_key="YOUR_AI21_API_KEY",
    mock_api_key="YOUR_MOCK_API_KEY",
    anthropic_api_key="YOUR_ANTHROPIC_API_KEY",
)


async def main():
    try:
        complete_response = await humanloop.acomplete(
            project="sdk-example",
            inputs={
                "text": "Llamas that are well-socialized and trained to halter and lead after weaning and are very friendly and pleasant to be around. They are extremely curious and most will approach people easily. However, llamas that are bottle-fed or over-socialized and over-handled as youth will become extremely difficult to handle when mature, when they will begin to treat humans as they treat each other, which is characterized by bouts of spitting, kicking and neck wrestling.[33]",
            },
            model_config={
                "model": "gpt-3.5-turbo",
                "max_tokens": -1,
                "temperature": 0.7,
                "prompt_template": "Summarize this for a second-grade student:\n\nText:\n{{text}}\n\nSummary:\n",
            },
            stream=False,
        )
        pprint(complete_response.body)
        pprint(complete_response.body["project_id"])
        pprint(complete_response.body["data"][0])
        pprint(complete_response.body["provider_responses"])
        pprint(complete_response.headers)
        pprint(complete_response.status)
        pprint(complete_response.round_trip_time)
    except ApiException as e:
        print("Exception when calling .complete: %s\n" % e)
        pprint(e.body)
        if e.status == 422:
            pprint(e.body["detail"])
        pprint(e.headers)
        pprint(e.status)
        pprint(e.reason)
        pprint(e.round_trip_time)


asyncio.run(main())

Streaming

Streaming support is available by suffixing a chat or complete method with _stream.

import asyncio
from humanloop import Humanloop

humanloop = Humanloop(
    api_key="YOUR_API_KEY",
    openai_api_key="YOUR_OPENAI_API_KEY",
    ai21_api_key="YOUR_AI21_API_KEY",
    mock_api_key="YOUR_MOCK_API_KEY",
    anthropic_api_key="YOUR_ANTHROPIC_API_KEY",
)


async def main():
    response = await humanloop.chat_stream(
        project="sdk-example",
        messages=[
            {
                "role": "user",
                "content": "Explain asynchronous programming.",
            }
        ],
        model_config={
            "model": "gpt-3.5-turbo",
            "max_tokens": -1,
            "temperature": 0.7,
            "chat_template": [
                {
                    "role": "system",
                    "content": "You are a helpful assistant who replies in the style of {{persona}}.",
                },
            ],
        },
        inputs={
            "persona": "the pirate Blackbeard",
        },
    )
    async for token in response.content:
        print(token)


asyncio.run(main())

Author

This Python package is automatically generated by Konfig