update readme

python/samples/agentchat_graphrag/README.md

@@ -21,33 +21,32 @@ Local Search: Local search focuses on a specific subset of the data, such as a p
 
 By combining these search strategies, GraphRAG ensures comprehensive and context-sensitive responses from the multi-agent team.
 
+
 ## Setup
 
 To set up the project, follow these steps:
 
-1. Download the plain text version of "The Adventures of Sherlock Holmes" from [Project Gutenberg](https://www.gutenberg.org/ebooks/1661) and save it to `data/input/sherlock_book.txt`.
-
-2. Adjust the `settings.yaml` file with your LLM and embedding configuration. Ensure that the API keys and other necessary details are correctly set.
+1. Install the required Python packages by running:
 
-3. Replace the LLM client and credentials in `app.py` as needed to match your setup.
+```bash
+pip install -r requirements.txt
+```
 
-4. Run the `graphrag prompt-tune` command to tune the prompts. This step adjusts the prompts to better fit the context of the downloaded text.
+2. Download the plain text version of "The Adventures of Sherlock Holmes" from [Project Gutenberg](https://www.gutenberg.org/ebooks/1661) and save it to `data/input/sherlock_book.txt`.
 
-5. After tuning, run the `graphrag index` command to index the data. This process will create the necessary data structures for performing searches.
+3. Adjust the `settings.yaml` file with your LLM and embedding configuration. Ensure that the API keys and other necessary details are correctly set.
 
-The outputs will be located in the `data/output/` directory.
+4. Create a model_config.json file with the Assistant model configuration. Use the `model_config_template.json` file as a reference.
 
-## Running the Sample
+5. Run the `graphrag prompt-tune` command to tune the prompts. This step adjusts the prompts to better fit the context of the downloaded text.
 
-The sample is currently configured to use Azure OpenAI
+6. After tuning, run the `graphrag index` command to index the data. This process will create the necessary data structures for performing searches. The indexing may take some time, at least 10 minutes on most machines, depending on the connection to the model API.
 
-2. Install the required Python packages by running:
+The outputs will be located in the `data/output/` directory.
 
-```bash
-pip install -r requirements.txt
-```
+## Running the Sample
 
-3. Run the sample by executing the following command:
+Run the sample by executing the following command:
 
 ```bash
 python app.py