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WMS id is: 11619, RAG lab for AI Vector Search (#121)
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mw-orcl authored May 4, 2024
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168 changes: 0 additions & 168 deletions ai-vector-emmbeding-python/lab1-tabs/similarity_search_Cohere.py

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143 changes: 0 additions & 143 deletions ai-vector-emmbeding-python/lab1-tabs/vectorize_table_Cohere.py

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2 changes: 1 addition & 1 deletion langchain-rag-23ai/introduction/introduction.md
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# 7 Easy Steps to Building a RAG application with Oracle AI Vector Search and LangChain
# AI Vector Search - 7 Easy Steps to Building a RAG application with Oracle AI Vector Search and LangChain

## About this Workshop

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22 changes: 12 additions & 10 deletions langchain-rag-23ai/lab1/rag1.md
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Expand Up @@ -28,9 +28,11 @@ In this lab, you will:

## Task 1: Launch Jupyter Lab Notebook

1. From the Activities menu, open a terminal window
1. From the Activities menu, open a terminal window.

2. From the terminal OS prompt type: jupyter notebook.
![Open terminal](images/browser.png)

2. From the terminal OS prompt type the following:

```
$ cd /home/oracle/AIdemo
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![Run Jupyter](images/runjupyter.png)


1. Open the saved notebook RAG_with_Oracle23ai_gold1.ipynb. You can double click the file or right-click and select **Open**.
1. Open the notebook **RAG_with_Oracle23ai_gold1.ipynb**. You can double click or right-click and select **Open**.

![Open RAG notebook](images/openragwithoracle23ai.png)

The window with the Python code for the RAG application should look like this.
![Open RAG notebook](images/openragwithoracle23ai.png)

![RAG notebook opened](images/cellwithcode.png)

If you want to enlarge the window and have larger fonts, you can zoom in with the browser.

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1. Select the code snippet and click **Run** in Jupyter. A blue line indicates the cell is selected.

![Run code in Jupyter](images/selectcodecellrun.png)
![Select code in Jupyter](images/selectcell.png)

You may get a warning message as shown below. You can ignore this and click **Run** to proceed.

You may get a warning message as shown above. You can ignore this and click **Run** to proceed.
![ignore warning](images/ignorewarning1.png)

```python
# Import libraries and modules
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**Choose an LLM to generate your response**

You have 3 choices in this lab. Choose only one, but you can go back and choose a different one to see its response. Just go back to the LLM cell and run it. Note: For OpenAI, you CANNOT run this in the LiveLabs environment. This sample code is for informational purposes so you can run this example in your own environment.
You have 3 choices in this lab. Choose only one, but you can go back and choose a different one to see its response. Just go back to the LLM cell and run it.
Note: For OpenAI, you **CANNOT** run this in the LiveLabs environment. This sample code is for informational purposes so you can run this example in your own environment.

* Choice 1 - OCI GenAI LLM with meta.llama-2.70b-chat
* Choice 2 - OpenAI ChatGPT 3.5 (CANNOT run in this LiveLabs environment)
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