Update project Dockerfile link and add QualityFlow project

Author: htahir1

ADDING_PROJECTS.md

@@ -57,7 +57,7 @@ ENV ZENML_ENABLE_TUTORIAL=true
 ### When No Dockerfile is Needed
 
 If your project only requires Python dependencies listed in `requirements.txt`, **do not include a Dockerfile**. The projects backend will automatically build your project using the generic Dockerfile available at:
-[https://github.com/zenml-io/zenml-projects-backend/blob/main/.docker/project.Dockerfile](https://github.com/zenml-io/zenml-projects-backend/blob/main/.docker/project.Dockerfile)
+[https://raw.githubusercontent.com/zenml-io/zenml-projects-backend/refs/heads/main/.docker/project.Dockerfile?token=GHSAT0AAAAAADISFM36XGBCROFV7ZUEFSUK2FMHITA](https://raw.githubusercontent.com/zenml-io/zenml-projects-backend/refs/heads/main/.docker/project.Dockerfile?token=GHSAT0AAAAAADISFM36XGBCROFV7ZUEFSUK2FMHITA)
 
 ## 🔧 Backend Integration
 

README.md

@@ -59,6 +59,7 @@ etc.
 | [Nightwatch AI](nightwatch-ai)                               | 🤖 LLMOps | 📝 Summarization, 📊 Reporting                              | openai, supabase, slack              |
 | [ResearchRadar](research-radar)                              | 🤖 LLMOps | 📝 Classification, 📊 Comparison                            | anthropic, huggingface, transformers |
 | [Deep Research](deep_research)                   | 🤖 LLMOps | 📝 Research, 📊 Reporting, 🔍 Web Search                     | anthropic, mcp, agents, openai |
+| [QualityFlow](qualityflow)                                   | 🤖 LLMOps | 🧪 Test Generation, 📊 Coverage Analysis, ⚡ Automation      | openai, anthropic, pytest, jinja2    |
 | [End-to-end Computer Vision](end-to-end-computer-vision)     | 👁 CV      | 🔎 Object Detection, 🏷️ Labeling                            | pytorch, label_studio, yolov8        |
 | [Magic Photobooth](magic-photobooth)                         | 👁 CV      | 📷 Image Gen, 🎞️ Video Gen                                  | stable-diffusion, huggingface        |
 | [OmniReader](omni-reader)                                    | 👁 CV      | 📑 OCR, 📊 Evaluation, ⚙️ Batch Processing                  | polars, litellm, openai, ollama      |

llm-complete-guide/README.md

@@ -235,7 +235,7 @@ python run.py synthetic
 
 You will also need to have set up and connected to an Argilla instance for this
 to work. Please follow the instructions in the [Argilla
-documentation](https://docs.argilla.io/latest/getting_started/quickstart/)
+documentation](https://docs.v1.argilla.io/en/latest/)
 to set up and connect to an Argilla instance on the Hugging Face Hub. [ZenML's
 Argilla integration
 documentation](https://docs.zenml.io/v/docs/stack-components/annotators/argilla)
@@ -254,7 +254,7 @@ zenml secret update llm-complete -v '{"argilla_api_key": "YOUR_ARGILLA_API_KEY",
 
 As with the previous pipeline, you will need to have set up and connected to an Argilla instance for this
 to work. Please follow the instructions in the [Argilla
-documentation](https://docs.argilla.io/latest/getting_started/quickstart/)
+documentation](https://docs.v1.argilla.io/en/latest/)
 to set up and connect to an Argilla instance on the Hugging Face Hub. [ZenML's
 Argilla integration
 documentation](https://docs.zenml.io/v/docs/stack-components/annotators/argilla)

qualityflow/README.md

@@ -289,7 +289,6 @@ Set up automated regression testing using ZenML's scheduling capabilities or you
 QualityFlow follows ZenML best practices and is designed to be extended:
 
 1. **Add New LLM Providers**: Extend `gen_tests_agent.py` with new provider integrations
-2. **Custom Materializers**: Create materializers for new artifact types
 3. **Additional Metrics**: Expand evaluation capabilities with new quality metrics
 4. **Selection Strategies**: Add new code selection algorithms
 
@@ -327,8 +326,6 @@ python run.py --config configs/experiment.default.yaml
 ## 📚 Resources
 
 - [ZenML Documentation](https://docs.zenml.io/)
-- [Model Control Plane](https://docs.zenml.io/user-guide/model-control-plane)
-- [Kubernetes Orchestrator](https://docs.zenml.io/stacks/stack-components/orchestrators/kubernetes)
 
 ---