patients_file_path syntax error

README.md

@@ -67,11 +67,14 @@ deactivate
 ### OpenAI API Key, Model Name, and Endpoint URL
 
 
-1. You can add your OpenAI-compatible API key to the [Hugging Face Settings](https://huggingface.co/spaces/Intel/preventative_healthcare/settings) under "Variables and secrets". They are called by a function called `st.secrets` [here in the app.py code](https://huggingface.co/spaces/Intel/preventative_healthcare/blob/main/app.py#L295).
+1. If using the Hugging Face Spaces app, you can add your OpenAI-compatible API key and the model endpoint URL to the [Hugging Face Settings](https://huggingface.co/spaces/Intel/preventative_healthcare/settings) under "Variables and secrets". They are called by a function called `st.secrets` [here in the app.py code](https://huggingface.co/spaces/Intel/preventative_healthcare/blob/main/app.py#L295). 
 
-Or, you can add them directly to the [OAI_CONFIG_LIST.json](https://huggingface.co/spaces/Intel/preventative_healthcare/blob/main/OAI_CONFIG_LIST.json) file if you are keeping everything local. Don't expose your precious API key to the world!
-
-2. Modify the `model` and `base_url` to the model name and endpoint URL that you are using. The `OAI_CONFIG_LIST.json` should look like:
+2. If deploying a local version with Streamlit frontend, you can add your details to a file under `.streamlit/secrets.toml` that looks like this:
+```bash
+OPENAI_API_KEY = "your-api-key"
+OPENAI_BASE_URL = "https://api.inference.denvrdata.com/v1/"
+```
+3. Finally, if you just want to use the Python script without any Streamlit front-end, you can just add your API key to the [OAI_CONFIG_LIST.json](https://huggingface.co/spaces/Intel/preventative_healthcare/blob/main/OAI_CONFIG_LIST.json) file. Just don't expose your precious API key to the world! You can modify the `api_key`, `model` and `base_url` to the model name and endpoint URL that you are using. This file should look like:
 ```json
 [
     {

intelpreventativehealthcare.py

@@ -628,7 +628,7 @@ if __name__ == "__main__":
     
     # The user proxy agent and data analyst
     # will filter the patients based on the criteria defined by the epidemiologist and doctor critic.
-    patients_df, arguments_criteria = asyncio.run(find_patients(criteria,config_list_llama, patient_data_path=filepath))
+    patients_df, arguments_criteria = asyncio.run(find_patients(criteria,config_list_llama, patients_file_path=filepath))
     
     # Initialize OpenAI client
     openai_client = OpenAI(