Python client for SeekrAI
Project description
The Seekr Python Library is the official Python client for SeekrFlow's API platform, providing a convenient way for interacting with the REST APIs and enables easy integrations with Python 3.8+ applications with easy to use synchronous and asynchronous clients.
Installation
🚧 The library was rewritten in v1.0.0 released in April of 2024. There were significant changes made.
To install Seekr Python Library from PyPi, simply run:
pip install --upgrade seekrai
Setting up API Key
🚧 You will need to create an account with Seekr.com to obtain a SeekrFlow API Key.
Once logged in to the SeekrFlow Playground, you can find available API keys in this settings page.
Setting environment variable
export SEEKRFLOW_API_KEY=xxxxx
Using the client
from seekrai import SeekrFlow
client = SeekrFlow(api_key="xxxxx")
This library contains both a python library and a CLI. We'll demonstrate how to use both below.
Usage – Python Client
Chat Completions
import os
from seekrai import SeekrFlow
client = SeekrFlow(api_key=os.environ.get("SEEKRFLOW_API_KEY"))
response = client.chat.completions.create(
model="mistralai/Mixtral-8x7B-Instruct-v0.1",
messages=[{"role": "user", "content": "tell me about new york"}],
)
print(response.choices[0].message.content)
Streaming
import os
from seekrai import SeekrFlow
client = SeekrFlow(api_key=os.environ.get("SEEKRFLOW_API_KEY"))
stream = client.chat.completions.create(
model="mistralai/Mixtral-8x7B-Instruct-v0.1",
messages=[{"role": "user", "content": "tell me about new york"}],
stream=True,
)
for chunk in stream:
print(chunk.choices[0].delta.content or "", end="", flush=True)
Async usage
import os, asyncio
from seekrai import AsyncSeekrFlow
async_client = AsyncSeekrFlow(api_key=os.environ.get("SEEKRFLOW_API_KEY"))
messages = [
"What are the top things to do in San Francisco?",
"What country is Paris in?",
]
async def async_chat_completion(messages):
async_client = AsyncSeekrFlow(api_key=os.environ.get("SEEKRFLOW_API_KEY"))
tasks = [
async_client.chat.completions.create(
model="mistralai/Mixtral-8x7B-Instruct-v0.1",
messages=[{"role": "user", "content": message}],
)
for message in messages
]
responses = await asyncio.gather(*tasks)
for response in responses:
print(response.choices[0].message.content)
asyncio.run(async_chat_completion(messages))
Completions
Completions are for code and language models shown here. Below, a code model example is shown.
import os
from seekrai import SeekrFlow
client = SeekrFlow(api_key=os.environ.get("SEEKRFLOW_API_KEY"))
response = client.completions.create(
model="codellama/CodeLlama-34b-Python-hf",
prompt="Write a Next.js component with TailwindCSS for a header component.",
)
print(response.choices[0].text)
Streaming
import os
from seekrai import SeekrFlow
client = SeekrFlow(api_key=os.environ.get("SEEKRFLOW_API_KEY"))
stream = client.completions.create(
model="codellama/CodeLlama-34b-Python-hf",
prompt="Write a Next.js component with TailwindCSS for a header component.",
stream=True,
)
for chunk in stream:
print(chunk.choices[0].delta.content or "", end="", flush=True)
Async usage
import os, asyncio
from seekrai import AsyncSeekrFlow
async_client = AsyncSeekrFlow(api_key=os.environ.get("SEEKRFLOW_API_KEY"))
prompts = [
"Write a Next.js component with TailwindCSS for a header component.",
"Write a python function for the fibonacci sequence",
]
async def async_chat_completion(prompts):
async_client = AsyncSeekrFlow(api_key=os.environ.get("SEEKRFLOW_API_KEY"))
tasks = [
async_client.completions.create(
model="codellama/CodeLlama-34b-Python-hf",
prompt=prompt,
)
for prompt in prompts
]
responses = await asyncio.gather(*tasks)
for response in responses:
print(response.choices[0].text)
asyncio.run(async_chat_completion(prompts))
Image generation
import os
from seekrai import SeekrFlow
client = SeekrFlow(api_key=os.environ.get("SEEKRFLOW_API_KEY"))
response = client.images.generate(
prompt="space robots",
model="stabilityai/stable-diffusion-xl-base-1.0",
steps=10,
n=4,
)
print(response.data[0].b64_json)
Embeddings
from typing import List
from seekrai import SeekrFlow
client = SeekrFlow(api_key=os.environ.get("SEEKRFLOW_API_KEY"))
def get_embeddings(texts: List[str], model: str) -> List[List[float]]:
texts = [text.replace("\n", " ") for text in texts]
outputs = client.embeddings.create(model=model, input=texts)
return [outputs.data[i].embedding for i in range(len(texts))]
input_texts = ['Our solar system orbits the Milky Way galaxy at about 515,000 mph']
embeddings = get_embeddings(input_texts, model='seekrflowcomputer/m2-bert-80M-8k-retrieval')
print(embeddings)
Files
The files API is used for fine-tuning and allows developers to upload data to fine-tune on. It also has several methods to list all files, retrive files, and delete files. Please refer to our fine-tuning docs here.
import os
from seekrai import SeekrFlow
client = SeekrFlow(api_key=os.environ.get("SEEKRFLOW_API_KEY"))
client.files.upload(file="somedata.jsonl") # uploads a file
client.files.list() # lists all uploaded files
client.files.retrieve(id="file-d0d318cb-b7d9-493a-bd70-1cfe089d3815") # retrieves a specific file
client.files.retrieve_content(id="file-d0d318cb-b7d9-493a-bd70-1cfe089d3815") # retrieves content of a specific file
client.files.delete(id="file-d0d318cb-b7d9-493a-bd70-1cfe089d3815") # deletes a file
Fine-tunes
The finetune API is used for fine-tuning and allows developers to create finetuning jobs. It also has several methods to list all jobs, retrive statuses and get checkpoints. Please refer to our fine-tuning docs here.
import os
from seekrai import SeekrFlow
client = SeekrFlow(api_key=os.environ.get("SEEKRFLOW_API_KEY"))
client.fine_tuning.create(
training_file='file-d0d318cb-b7d9-493a-bd70-1cfe089d3815',
model='mistralai/Mixtral-8x7B-Instruct-v0.1',
n_epochs=3,
n_checkpoints=1,
batch_size=4,
learning_rate=1e-5,
suffix='my-demo-finetune',
wandb_api_key='1a2b3c4d5e.......',
)
client.fine_tuning.list() # lists all fine-tuned jobs
client.fine_tuning.retrieve(id="ft-c66a5c18-1d6d-43c9-94bd-32d756425b4b") # retrieves information on finetune event
client.fine_tuning.cancel(id="ft-c66a5c18-1d6d-43c9-94bd-32d756425b4b") # Cancels a fine-tuning job
client.fine_tuning.list_events(id="ft-c66a5c18-1d6d-43c9-94bd-32d756425b4b") # Lists events of a fine-tune job
client.fine_tuning.download(
id="ft-c66a5c18-1d6d-43c9-94bd-32d756425b4b") # downloads compressed fine-tuned model or checkpoint to local disk
Models
This lists all the models that SeekrFlow supports.
import os
from seekrai import SeekrFlow
client = SeekrFlow(api_key=os.environ.get("SEEKRFLOW_API_KEY"))
models = client.models.list()
for model in models:
print(model)
Usage – CLI
Chat Completions
seekrai chat.completions \
--message "system" "You are a helpful assistant named SeekrFlow" \
--message "user" "What is your name?" \
--model mistralai/Mixtral-8x7B-Instruct-v0.1
The Chat Completions CLI enables streaming tokens to stdout by default. To disable streaming, use --no-stream
.
Completions
seekrai completions \
"Large language models are " \
--model mistralai/Mixtral-8x7B-v0.1 \
--max-tokens 512 \
--stop "."
The Completions CLI enables streaming tokens to stdout by default. To disable streaming, use --no-stream
.
Image Generations
seekrai images generate \
"space robots" \
--model stabilityai/stable-diffusion-xl-base-1.0 \
--n 4
The image is opened in the default image viewer by default. To disable this, use --no-show
.
Files
# Help
seekrai files --help
# Check file
seekrai files check example.jsonl
# Upload file
seekrai files upload example.jsonl
# List files
seekrai files list
# Retrieve file metadata
seekrai files retrieve file-6f50f9d1-5b95-416c-9040-0799b2b4b894
# Retrieve file content
seekrai files retrieve-content file-6f50f9d1-5b95-416c-9040-0799b2b4b894
# Delete remote file
seekrai files delete file-6f50f9d1-5b95-416c-9040-0799b2b4b894
Fine-tuning
# Help
seekrai fine-tuning --help
# Create fine-tune job
seekrai fine-tuning create \
--model seekrflowcomputer/llama-2-7b-chat \
--training-file file-711d8724-b3e3-4ae2-b516-94841958117d
# List fine-tune jobs
seekrai fine-tuning list
# Retrieve fine-tune job details
seekrai fine-tuning retrieve ft-c66a5c18-1d6d-43c9-94bd-32d756425b4b
# List fine-tune job events
seekrai fine-tuning list-events ft-c66a5c18-1d6d-43c9-94bd-32d756425b4b
# Cancel running job
seekrai fine-tuning cancel ft-c66a5c18-1d6d-43c9-94bd-32d756425b4b
# Download fine-tuned model weights
seekrai fine-tuning download ft-c66a5c18-1d6d-43c9-94bd-32d756425b4b
Models
# Help
seekrai models --help
# List models
seekrai models list
Contributing
Refer to the Contributing Guide
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