Added first pass at local RAG with anythingllm

Added a first pass at anythingllm rag

Signed-off-by: JJ Asghar <[email protected]>

Author: jjasghar

docs/images/adding_pdf.png

@@ -0,0 +1,116 @@
+---
+title: Using AnythingLLM for a local RAG
+description: Learn how to build a simple local RAG
+logo: images/ibm-blue-background.png
+---
+
+## Configuration and Sanity Check
+
+Open up AnyThingLLM, and you should see something like the following:
+![default screen](../images/anythingllm_open_screen.png)
+
+If you see this that means AnythingLLM is installed correctly, and we can continue configuration, if not, please find a workshop TA or
+raise your hand we'll be there to help you ASAP.
+
+Next as a sanity check, run the following command to confirm you have the [granite3.1-dense](https://ollama.com/library/granite3.1-dense)
+model downloaded in `ollama`. This may take a bit, but we should have a way to copy it directly on your laptop.
+
+```bash
+ollama pull granite3.1-dense:8b
+```
+
+If you didn't know, the supported languages with `granite3.1-dense` now include:
+
+- English, German, Spanish, French, Japanese, Portuguese, Arabic, Czech, Italian, Korean, Dutch, Chinese (Simplified)
+
+And the Capabilities also include:
+
+- Summarization
+- Text classification
+- Text extraction
+- Question-answering
+- Retrieval Augmented Generation (RAG)
+- Code related tasks
+- Function-calling tasks
+- Multilingual dialog use cases
+- Long-context tasks including long document/meeting summarization, long document QA, etc.
+
+Next click on the `wrench` icon, and open up the settings. For now we are going to configure the global settings for `ollama`
+but you may want to change it in the future.
+
+![wrench icon](../images/anythingllm_wrench_icon.png)
+
+Click on the "LLM" section, and select **Ollama** as the LLM Provider. Also select the `granite3-dense:8b` model. (You should be able to
+see all the models you have access to through `ollama` there.)
+
+![llm configuration](../images/anythingllm_llm_config.png)
+
+Click the "Back to workspaces" button where the wrench was. And Click "New Workspace."
+
+![new workspace](../images/anythingllm_new_workspace.png)
+
+Name it something like "learning llm" or the name of the event we are right now, something so you know it's somewhere you are learning
+how to use this LLM.
+
+![naming new workspace](../images/anythingllm_naming_workspace.png)
+
+Now we can test our connections _through_ AnythingLLM! I like the "Who is Batman?" question, as a sanity check on connections and that
+it knows _something_.
+
+![who is batman](../images/anythingllm_who_is_batman.png)
+
+Now you may notice that the answer is slighty different then the screen shot above. That's expected and nothing to worry about. If
+you have more questions about it raise your hand and one of the helpers would love to talk you about it.
+
+Congratulations! You have AnythingLLM running now, configured to work with `granite3.1-dense` and `ollama`!
+
+## Creating your own local RAG
+
+Now that you have everything set up, lets build our own RAG. You need a document, of some sort to questions to answer against
+it. Lets start with something fun. As of right now, our Granite model doesn't know about the US Federal Budget in 2024, so lets
+ask it a question about it to verify.
+
+Create a new workspace, and call it whatever you want:
+
+![new budget workspace](../images/new_budget_workspace.png)
+
+Now you have a new workspace, ask it a question like:
+
+```
+What was the US federal budget for 2024?
+```
+
+You should come back with something like the following, it may be different, but the gist is there.
+
+![doesnt know the budget](../images/doesnt_know.png)
+
+Not great right? Well now we need to give it a way to look up this data, luckly, we have a backed up
+copy of the budget pdf [here](https://github.com/user-attachments/files/18510560/budget_fy2024.pdf).
+Go ahead and save it to your local machine, and be ready to grab it.
+
+Now spin up a new workspace, (yes, please a new workspace, it seems that sometimes AnythingLLM has
+issues with adding things, so a clean environment is always easier to teach in) and call it
+something else.
+
+![budget workspace](../images/budget_workspace.png)
+
+Click on the "upload a document" to get the pdf added.
+
+Next we need to add it to the workspace.
+
+![adding pdf](../images/adding_pdf.png)
+
+Next click the upload or drag and drop and put the pdf in there, and then the arrow to move it to the
+workspace. Click Save and Embed.
+
+You have now added the pdf to the workspace.
+
+Now when the chat comes back up ask the same question, and you should see some new answers!
+
+![success pdf](../images/success.png)
+
+It won't be exactly what we are looking for, but it's enough to now see that the Granite model can
+leverage the local RAG and in turn can _look things up_ for you. You'll need some prompt engineering
+to get exactly what you want but this is just the start of leveraging the AI!
+
+

docs/images/budget_workspace.png

@@ -20,6 +20,7 @@ nav:
     - Lab 3.5 Configuring Open-WebUI: lab-3.5/README.md
     - Lab 4. Prompt engineering overview: lab-4/README.md
     - Lab 5. Useful prompts and use cases: lab-5/README.md
+    - Lab 6. Using AnythingLLM for a Local RAG: lab-6/README.md
   - References:
     - Additional Resources: resources/RESOURCES.md
     - MkDocs Cheatsheet: resources/MKDOCS.md