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ls1intum · Oct 7, 2024 · 005bcfa · 005bcfa
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diff --git a/README.MD b/README.MD
@@ -1,16 +1,344 @@
 # Pyris V2
-## With local environment
 
-### Setup
- - Check python version: `python --version` (should be 3.12)
- - Install packages: `pip install -r requirements.txt`
+Pyris is an intermediary system that connects the [Artemis](https://github.com/ls1intum/Artemis) platform with various Large Language Models (LLMs). It provides a REST API that allows Artemis to interact with different pipelines based on specific tasks.
 
-### Run server
- - Run server: 
-   ```[bash]
-     APPLICATION_YML_PATH=<path-to-your-application-yml-file> LLM_CONFIG_PATH=<path-to-your-llm-config-yml> uvicorn app.main:app --reload
-    ```
- - Access API docs: http://localhost:8000/docs
+Currently, Pyris powers [Iris](https://artemis.cit.tum.de/about-iris), a virtual AI tutor that assists students with their programming exercises on Artemis in a pedagogically meaningful way.
 
-## With docker
-TBD
+## Table of Contents
+- [Features](#features)
+- [Setup](#setup)
+  - [Prerequisites](#prerequisites)
+  - [Local Development Setup](#local-development-setup)
+  - [Docker Setup](#docker-setup)
+    - [Development Environment](#development-environment)
+    - [Production Environment](#production-environment)
+- [Customizing Configuration](#customizing-configuration)
+- [Troubleshooting](#troubleshooting)
+- [Additional Notes](#additional-notes)
+
+## Features
+
+- **Exercise Support**: Empowers Iris to provide feedback on programming exercises, enhancing the learning experience for students. Iris analyzes submitted code, feedback, and build logs generated by Artemis to provide detailed insights.
+
+- **Course Content Support**: Leverages RAG (Retrieval-Augmented Generation) to enable Iris to provide detailed explanations for course content, making it easier for students to understand complex topics based on instructor-provided learning materials.
+
+- **Competency Generation**: Automates the generation of competencies for courses, reducing manual effort in creating Artemis competencies.
+
+## Setup
+
+### Prerequisites
+
+- **Python 3.12**: Ensure that Python 3.12 is installed.
+
+  ```bash
+  python --version
+  ```
+
+- **Docker and Docker Compose**: Required for containerized deployment.
+
+---
+
+### Local Development Setup
+
+> **Note:** If you need to modify the local Weaviate vector database setup, please refer to the [Weaviate Documentation](https://weaviate.io/developers/weaviate/quickstart).
+
+#### Steps
+
+1. **Clone the Pyris Repository**
+
+   Clone the Pyris repository into a directory on your machine:
+
+   ```bash
+   git clone https://github.com/ls1intum/Pyris.git Pyris
+   ```
+
+2. **Install Dependencies**
+
+   Navigate to the Pyris directory and install the required Python packages:
+
+   ```bash
+   cd Pyris
+   pip install -r requirements.txt
+   ```
+
+3. **Create Configuration Files**
+
+   - **Create an Application Configuration File**
+
+     Create an `application.local.yml` file in the root directory. You can use the provided `application.example.yml` as a base.
+
+     ```bash
+     cp application.example.yml application.local.yml
+     ```
+
+     **Example `application.local.yml`:**
+
+     ```yaml
+     api_keys:
+       - token: "your-secret-token"
+
+     weaviate:
+       host: "localhost"
+       port: "8001"
+       grpc_port: "50051"
+
+     env_vars:
+     ```
+
+   - **Create an LLM Config File**
+
+     Create an `llm-config.local.yml` file in the root directory. You can use the provided `llm-config.example.yml` as a base.
+
+     ```bash
+     cp llm-config.example.yml llm-config.local.yml
+     ```
+
+     **Example OpenAI Configuration:**
+
+     ```yaml
+     - id: "oai-gpt-35-turbo"
+       name: "GPT 3.5 Turbo"
+       description: "GPT 3.5 16k"
+       type: "openai_chat"
+       model: "gpt-3.5-turbo"
+       api_key: "<your_openai_api_key>"
+       tools: []
+       capabilities:
+         input_cost: 0.5
+         output_cost: 1.5
+         gpt_version_equivalent: 3.5
+         context_length: 16385
+         vendor: "OpenAI"
+         privacy_compliance: false
+         self_hosted: false
+         image_recognition: false
+         json_mode: true
+     ```
+
+     **Example Azure OpenAI Configuration:**
+
+     ```yaml
+     - id: "azure-gpt-4-omni"
+       name: "GPT 4 Omni"
+       description: "GPT 4 Omni on Azure"
+       type: "azure_chat"
+       endpoint: "<your_azure_model_endpoint>"
+       api_version: "2024-02-15-preview"
+       azure_deployment: "gpt4o"
+       model: "gpt4o"
+       api_key: "<your_azure_api_key>"
+       tools: []
+       capabilities:
+         input_cost: 6
+         output_cost: 16
+         gpt_version_equivalent: 4.5  # Equivalent GPT version of the model
+         context_length: 128000
+         vendor: "OpenAI"
+         privacy_compliance: true
+         self_hosted: false
+         image_recognition: true
+         json_mode: true
+     ```
+
+     **Explanation of Configuration Parameters**
+
+     The configuration parameters are used by Pyris's capability system to select the appropriate model for a task.
+
+     **Parameter Descriptions:**
+
+     - `api_key`: The API key for the model.
+     - `capabilities`: The capabilities of the model.
+
+       - `context_length`: The maximum number of tokens the model can process in a single request.
+       - `gpt_version_equivalent`: The equivalent GPT version of the model in terms of overall capabilities.
+       - `image_recognition`: Whether the model supports image recognition (for multimodal models).
+       - `input_cost`: The cost of input tokens for the model.
+       - `output_cost`: The cost of output tokens for the model.
+       - `json_mode`: Whether the model supports structured JSON output mode.
+       - `privacy_compliance`: Whether the model complies with privacy regulations.
+       - `self_hosted`: Whether the model is self-hosted.
+       - `vendor`: The provider of the model (e.g., OpenAI).
+       - `speed`: The model's processing speed.
+
+     - `description`: Additional information about the model.
+     - `id`: Unique identifier for the model across all models.
+     - `model`: The official name of the model as used by the vendor.
+     - `name`: A custom, human-readable name for the model.
+     - `type`: The model type, used to select the appropriate client (e.g., `openai_chat`, `azure_chat`, `ollama`).
+     - `endpoint`: The URL to connect to the model.
+     - `api_version`: The API version to use with the model.
+     - `azure_deployment`: The deployment name of the model on Azure.
+     - `tools`: The tools supported by the model.
+
+     > **Notes on `gpt_version_equivalent`:** The `gpt_version_equivalent` field is subjective and used to compare capabilities of different models using GPT models as a reference. For example:
+     >- GPT-4 Omni equivalent: 4.5
+     >- GPT-4 Omni Mini equivalent: 4.25
+     >- GPT-4 equivalent: 4
+     >- GPT-3.5 Turbo equivalent: 3.5
+
+     > **Warning:** Most existing pipelines in Pyris require a model with a `gpt_version_equivalent` of **4.5 or higher**. It is advised to define models in the `llm-config.local.yml` file with a `gpt_version_equivalent` of 4.5 or higher.
+
+4. **Run the Server**
+
+   Start the Pyris server:
+
+   ```bash
+   APPLICATION_YML_PATH=./application.local.yml \
+   LLM_CONFIG_PATH=./llm-config.local.yml \
+   uvicorn app.main:app --reload
+   ```
+
+5. **Access API Documentation**
+
+   Open your browser and navigate to [http://localhost:8000/docs](http://localhost:8000/docs) to access the interactive API documentation.
+
+---
+
+### Docker Setup
+
+Deploying Pyris using Docker ensures a consistent environment and simplifies the deployment process.
+
+#### Prerequisites
+
+- **Docker**: Install Docker from the [official website](https://www.docker.com/get-started).
+- **Docker Compose**: Comes bundled with Docker Desktop or install separately on Linux.
+- **Clone the Pyris Repository**: If not already done, clone the repository.
+- **Create Configuration Files**: Create the `application.local.yml` and `llm-config.local.yml` files as described in the [Local Development Setup](#local-development-setup) section.
+
+  ```bash
+  git clone https://github.com/ls1intum/Pyris.git Pyris
+  cd Pyris
+  ```
+
+#### Docker Compose Files
+
+- **Development**: `docker-compose/pyris-dev.yml`
+- **Production with Nginx**: `docker-compose/pyris-production.yml`
+- **Production without Nginx**: `docker-compose/pyris-production-internal.yml`
+
+#### Running the Containers
+
+##### **Development Environment**
+
+1. **Start the Containers**
+
+   ```bash
+   docker-compose -f docker-compose/pyris-dev.yml up --build
+   ```
+
+   - Builds the Pyris application.
+   - Starts Pyris and Weaviate in development mode.
+   - Mounts local configuration files for easy modification.
+
+2. **Access the Application**
+
+   - Application URL: [http://localhost:8000](http://localhost:8000)
+   - API Docs: [http://localhost:8000/docs](http://localhost:8000/docs)
+
+##### **Production Environment**
+
+###### **Option 1: With Nginx**
+
+1. **Prepare SSL Certificates**
+
+   - Place your SSL certificate (`fullchain.pem`) and private key (`priv_key.pem`) in the specified paths or update the paths in the Docker Compose file.
+
+2. **Start the Containers**
+
+   ```bash
+   docker-compose -f docker-compose/pyris-production.yml up -d
+   ```
+
+   - Pulls the latest Pyris image.
+   - Starts Pyris, Weaviate, and Nginx.
+   - Nginx handles SSL termination and reverse proxying.
+
+3. **Access the Application**
+
+   - Application URL: `https://your-domain.com`
+
+###### **Option 2: Without Nginx**
+
+1. **Start the Containers**
+
+   ```bash
+   docker-compose -f docker-compose/pyris-production-internal.yml up -d
+   ```
+
+   - Pulls the latest Pyris image.
+   - Starts Pyris and Weaviate.
+
+2. **Access the Application**
+
+   - Application URL: [http://localhost:8000](http://localhost:8000)
+
+---
+
+#### Managing the Containers
+
+- **Stop the Containers**
+
+  ```bash
+  docker-compose -f <compose-file> down
+  ```
+
+  Replace `<compose-file>` with the appropriate Docker Compose file.
+
+- **View Logs**
+
+  ```bash
+  docker-compose -f <compose-file> logs -f <service-name>
+  ```
+
+  Example:
+
+  ```bash
+  docker-compose -f docker-compose/pyris-dev.yml logs -f pyris-app
+  ```
+
+- **Rebuild Containers**
+
+  If you've made changes to the code or configurations:
+
+  ```bash
+  docker-compose -f <compose-file> up --build
+  ```
+
+#### Customizing Configuration
+
+- **Environment Variables**
+
+  You can customize settings using environment variables:
+
+  - `PYRIS_DOCKER_TAG`: Specifies the Pyris Docker image tag.
+  - `PYRIS_APPLICATION_YML_FILE`: Path to your `application.yml` file.
+  - `PYRIS_LLM_CONFIG_YML_FILE`: Path to your `llm-config.yml` file.
+  - `PYRIS_PORT`: Host port for Pyris application (default is `8000`).
+  - `WEAVIATE_PORT`: Host port for Weaviate REST API (default is `8001`).
+  - `WEAVIATE_GRPC_PORT`: Host port for Weaviate gRPC interface (default is `50051`).
+
+- **Configuration Files**
+
+  Modify configuration files as needed:
+
+  - **Pyris Configuration**: Update `application.yml` and `llm-config.yml`.
+  - **Weaviate Configuration**: Adjust settings in `weaviate.yml`.
+  - **Nginx Configuration**: Modify Nginx settings in `nginx.yml` and related config files.
+
+## Troubleshooting
+
+- **Port Conflicts**
+
+  If you encounter port conflicts, change the host ports using environment variables:
+
+  ```bash
+  export PYRIS_PORT=8080
+  ```
+
+- **Permission Issues**
+
+  Ensure you have the necessary permissions for files and directories, especially for SSL certificates.
+
+- **Docker Resources**
+
+  If services fail to start, ensure Docker has sufficient resources allocated.
diff --git a/app/pipeline/competency_extraction_pipeline.py b/app/pipeline/competency_extraction_pipeline.py
@@ -31,7 +31,12 @@ def __init__(self, callback: Optional[CompetencyExtractionCallback] = None):
             implementation_id="competency_extraction_pipeline_reference_impl"
         )
         self.callback = callback
-        self.request_handler = CapabilityRequestHandler(requirements=RequirementList())
+        self.request_handler = CapabilityRequestHandler(
+            requirements=RequirementList(
+                gpt_version_equivalent=4.5,
+                context_length=16385,
+            )
+        )
         self.output_parser = PydanticOutputParser(pydantic_object=Competency)
 
     def __call__(

diff --git a/application.test.yml → application.example.yml b/application.test.yml → application.example.yml
@@ -4,7 +4,4 @@ api_keys:
 weaviate:
   host: "localhost"
   port: "8001"
-  grpc_port: "50051"
-
-env_vars:
-    test: "test"
+  grpc_port: "50051"