Add files via upload

Author: zoharsan

examples/agentic-streamlit-chatbot/README.md

@@ -1,31 +1,31 @@
 # Prerequisites
 
-
+- Clone this repo and navigate to this directory.
 - You need a python virtual environment. For this demo, `Python 3.13.1` was used, but any Python environment 3.11+ should work.
 - You will need [Vespa CLI](https://docs.vespa.ai/en/vespa-cli.html) that you can deploy on MacOS with `brew install vespa-cli`
 - Libraries dependencies can be installed with: `pip install -R requirements.txt`
 - Sign-up with [Tavily](https://tavily.com/) and Get an API key.
 - Spin-up a Vespa Cloud [Trial](https://vespa.ai/free-trial) account:
   - Login to the account you just created and create a tenant at [console.vespa-cloud.com](https://console.vespa-cloud.com/).
   - Save the tenant name.
-- A Valid OpenAI API key. Note that you have the option to use any other LLM, which may support Langgraph tools binding.
-- Git clone the repo `https://github.com/vespa-engine/system-test.git`
-- The ecommerce_hybrid_search app will be deployed. For more information about the app, please review the [README.md](https://github.com/vespa-engine/system-test/blob/master/tests/performance/ecommerce_hybrid_search/dataprep/README.md). You do not have to follow the data prep steps there. Follow the instructions below instead.
-- Uncompress the data file: `zstd -d data/vespa_update-96k.json.zst`
+- A Valid [OpenAI](https://openai.com/index/openai-api/) API key. Note that you have the option to use any other LLM, which may support Langgraph tools binding.
+- Uncompress the data file: `zstd -d data/vespa_feed-96k.json.zst`
 
 
 
-# Deploy the Ecommerce Vespa Application
+# Deploy the Vespa Application
 
 
-- In the system-test repo you just cloned, navigate to `tests/performance/ecommerce_hybrid_search/app`
+- Navigate to the `app` subdirectory
 - Choose a name for your app. For example `ecommercebot`
 - Follow instructions in the [**Getting Started**](https://cloud.vespa.ai/en/getting-started) document. Please note the following as you go through the documentation:
+  - Skip Step 5. as you have already cloned the app directory.
   - You will need your tenant name you created previously.
   - When adding the public certificates with `vespa auth cert`, it will give you the absolute path of the certificate and the private key. Please note them down.
-  - To feed the application, return to the original directory and run:
+  - Return to the parent directory. To feed the application, run:
   ```
-  vespa feed data/vespa_update-96k.json
+  cd ..
+  vespa feed data/vespa_feed-96k.json
   ```
 - You can test the following query from the Vespa CLI:
   ```
@@ -45,22 +45,10 @@
 
   A template for `secrets.toml` file to store streamlit secrets has been provided. Please create a subdirectory `.streamlit` and copy the template there. 
 
-  Update all the fields with all the information collected previously and save the file as `secrets.toml`
+  Update all the fields with all the information collected previously including the certicate locations and save the file as `secrets.toml`
 
   Launch your streamlit application:
   ```
   streamlit run streamlit_vespa_app.py
   ```
-  # Testing the Application
-
-  You can try a mix of questions like:
-
-  `What is the weather in Toronto ?`
-
-  Followed by:
-
-  `I'm looking for a screwdriver`
-
-  And then:
 
-  `Which one do you recommend to fix a watch?`