Deploy Streamlit apps

Deploy Streamlit apps to Hal9

Deploy Streamlit apps

In order to deploy Streamlit apps to our cloud, use the hal9 python package:


$ pip install hal9
$ hal9 deploy app --type streamlit --main app.py

import streamlit as st
import numpy as np
import pandas as pd
chart_data = pd.DataFrame(
  np.random.randn(9,2), columns=['a','b'])
st.line_chart(chart_data)

ON GITHUB RUN IN COLLAB

What kind of Streamlit apps can Hal9 create?

Explore Streamlit apps created with Hal9

What to Expect?

STEP 1

Create a chatbot, applicaiton, website, or API using AI in less than 30 seconds.

STEP 2

Share you creation by embedding into your website or integrating with other tools.

GO PRO

STEP 3

Customize with code: Bring your experts, work with our partners or get help from us

How it Works?

Bootstrap with AI

Leverage Hal9's frontend to build your application and reuse our frontend components with ease: Authentication, project and asset management, chat interface, API integration, site embedding, etc.

Avoid building common components most generative AI applications require.

Focus on Differentiating

Every product and every team are different, so must the backend powering your application. Our frontend and AI will generate your backend code, but to truly differentiate, you can customize the backend code through your experts, our partners or reach out to our team for help. Easy to get started:


$ pip install hal9
$ hal9 create my-project
$ hal9 deploy my-project

Tell your technical team to checkout Hal9's GitHub repo to deploy chatbots, streamlit apps, APIs, etc. using techologogies like LangChain, DSPy, Chainlit, and so on.


# read chat input from stdin
prompt = input()

# write chat output with stdout
print(f"Echo {prompt}")

# is that easy!


# use langchain to implement chat
from langchain_openai import ChatOpenAI

llm = ChatOpenAI(api_key="AAABBB")
parser = StrOutputParser()

input | llm | parser | print


# use llama and groq to implement chat
from groq import Groq
client = Groq()

completion = client.create(model="llama3")

print(completion)

ON GITHUB RUN IN COLLAB

Use Cases

Lead Generation

Find potential customers and generate quality leads for your business. Analyze target markets, track user behaviors, and connect with the right prospects. Automate outreach, manage follow-ups, and create reports on lead performance to keep your sales pipeline growing

Marketing Content

Create custom marketing images that match your brand’s style, from social media graphics to banners. Provide guidelines to analyze your brand, and deliver unique visuals that enhance your marketing. Whether launching a campaign or refreshing content, ensures your visuals stand out and engage your audience.

Web Research

Browse the web and receive email updates from findings and summarized information that meets your needs, like market trends, competitor analysis, or industry insights. Quickly gather details and provide clear summaries, saving you time and effort by reducing manual research.

Documents Analyst

Analyze complex documents like patents, engineering specs, and technical reports to help you grasp key details. Simplify dense content, highlight important parts, and summarize it clearly. Whether reviewing technical requirements or compliance standards, provide thorough insights, saving you time and ensuring nothing is missed.

Field Service

Assist your mobile workforce teams by providing on-the-go access to critical information via SMS. Whether you're troubleshooting an outage, repairing equipment, or maintaining infrastructure, this delivers instant insights, step-by-step guides, and answers to your technical questions. No matter where you are, ensure you have the right knowledge at your fingertips to fix issues quickly and efficiently.

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