Embedchain is a Data Platform for LLMs - load, index, retrieve, and sync any unstructured data. Using embedchain, you can easily create LLM powered apps over any data.

Install embedchain python package:

pip install embedchain

Embedchain now supports OpenAI’s latest gpt-4-turbo model. Checkout the FAQs.

Creating an app involves 3 steps:

1

⚙️ Import app instance

from embedchain import Pipeline as App
app = App()
2

🗃️ Add data sources

app.add("https://en.wikipedia.org/wiki/Elon_Musk")
app.add("https://www.forbes.com/profile/elon-musk")
# app.add("path/to/file/elon_musk.pdf")
3

💬 Ask questions, chat, or search through your data with ease

app.query("What is the net worth of Elon Musk today?")
# Answer: The net worth of Elon Musk today is $258.7 billion.
4

🚀 Seamlessly launch your App on the Embedchain Platform!

app.deploy()
# 🔑 Enter your Embedchain API key. You can find the API key at https://app.embedchain.ai/settings/keys/
# ec-xxxxxx

# 🛠️ Creating pipeline on the platform...
# 🎉🎉🎉 Pipeline created successfully! View your pipeline: https://app.embedchain.ai/pipelines/xxxxx

# 🛠️ Adding data to your pipeline...
# ✅ Data of type: web_page, value: https://www.forbes.com/profile/elon-musk added successfully.

Putting it together, you can run your first app using the following Google Colab. Make sure to set the OPENAI_API_KEY 🔑 environment variable in the code.

Open in Colab

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📚 Introduction