recall user to add Together AI API Key

README.md

@@ -10,124 +10,72 @@ pinned: false
 license: mit
 ---
 
-# RasaBot Local Deployment Instructions
+# RasaBot
 
-This guide provides clear instructions for running the RasaBot locally on your machine. The setup includes two distinct microservices:
+## Project Overview
 
-* **Rasa Main Service** (requires Python 3.8)
-* **Classifier Backend** (requires Python 3.10)
+RasaBot is an intelligent chatbot leveraging Rasa (version 2.8.3) for conversational management and a classifier microservice built with FastAPI and Outlines. It is composed of two main components running in separate Docker containers:
 
----
+* **Rasa Server**: Handles conversations using Rasa.
+* **Classifier Microservice**: Classifies user intents using LLM hosted by Together AI.
 
-## Prerequisites
+## Requirements
 
 * Docker
 * Docker Compose
+* Together AI API Key
 
-Ensure Docker and Docker Compose are installed and running on your system.
-
----
-
-## Directory Structure
-
-Your directory should resemble the following structure:
-
-```text
-RasaBot/
-├── actions/
-│   └── actions.py
-├── app.py
-├── build.sh
-├── classifier/
-│   ├── classifier.py
-│   ├── Dockerfile
-│   └── requirements.txt
-├── config.yml
-├── custom_components/
-│   └── llm_intent_classifier_client.py
-├── data/
-│   ├── nlu.yml
-│   └── rules.yml
-├── Dockerfile
-├── domain.yml
-├── endpoints.yml
-├── envs.sh
-├── models/
-├── README.md
-├── requirements.txt
-├── run_classifier.sh
-└── run_rasa.sh
-```
-
----
-
-## Build Docker Images
+## Setup
 
-Run the provided build script to build both Docker images:
+### 1. Clone Repository
 
 ```bash
-sh build.sh
+git clone <repository-url>
+cd RasaBot
 ```
 
----
-
-## Run Services
-
-### Run the Classifier Service
+### 2. Provide Together AI API Key
 
-Execute the following command:
+Set the Together AI API Key as an environment variable:
 
 ```bash
-sh run_classifier.sh
+export TOGETHERAI_API_KEY="your_together_ai_api_key_here"
 ```
 
-This will start the classifier backend service.
+Ensure this environment variable is set before running the classifier.
 
-### Run the Rasa Main Service
+### 3. Build Docker Images
 
-Execute the following command in a separate terminal:
+Execute the provided build script to create the necessary Docker images:
 
 ```bash
-sh run_rasa.sh
+sh build.sh
 ```
 
-This will start the Rasa server along with its Gradio frontend.
+### 4. Run Services
 
----
-
-## Stop the Services
-
-To stop the running services, use:
+Start the classifier service:
 
 ```bash
-docker-compose down
+sh run_classifier.sh
 ```
 
-or press `Ctrl+C` in each terminal running a service.
-
----
-
-## Access the Chat UI
-
-Once both services are running, open your browser and navigate to:
+Then, in a separate terminal, start the Rasa server:
 
-```
-http://localhost:7860
+```bash
+sh run_rasa.sh
 ```
 
-You can now interact with your RasaBot via the Gradio UI.
+Your chatbot services will now be running locally.
 
----
+## Usage
 
-## Troubleshooting
+Interact with the chatbot via the provided UI or API endpoints.
 
-* Ensure no port conflicts (`7860`, `8000`, `5005`) occur.
-* Verify environment variables in `envs.sh`.
-* Check Docker logs if encountering issues:
+## Stopping Services
 
-```bash
-docker logs <container_name>
-```
+To stop the running services, press `Ctrl+C` in the respective terminals or stop the Docker containers manually.
 
----
+## Notes
 
+* The classifier microservice relies on Together AI for classification. Ensure the `TOGETHERAI_API_KEY` environment variable is properly configured to avoid runtime errors.