Update README.md

README.md

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-## 🧠 Agentic Research Abstract Generator & Web Summariser-2
-An agent-based system using LangGraph and HuggingFace models to generate research abstracts and summarize web content, with modular workflows, memory handling, and task-specific agents.
-
-This builds upon the previous repo 
-- [Project Link](https://github.com/daniau23/agentic_researcher)
-- [ReadyTensor-Publication](https://app.readytensor.ai/publications/the-agentic-research-abstract-generator-and-web-content-summariser-agent-with-langraph-gYeyu875mKsB)
-
-
-### 🚀 Features Improvements
-- 📈 Evaluation metrics and logging
-- 📈 Evaluation metrics and logging
-- 📈 Testing features incorporated
-- 🚀 Model deployment with streamlit
-
-![Research Assistant Flow Chart](img/Agentic-Research-Assistant-AI-pub-main-image.jpg)
-
-### **How the project goes**
-- All files can only work after installing all dependencies in the `environment.yml` file
-- The `notebooks folder` contains the jupyter notebook file for testing the project as a whole and for experimenting. `research_graph2.ipynb` contains the experimentation for abstract generation while `research_graph3.ipynb` contains the experimentation for web content summarisation.
-- The `graph_article` folder contains the critic, writer and graph_article python files. The `writer.py`(writer agent) file takes the category and title needed for drafting the abstract while the `critic.py` (reviewer agent) reviews the generated abstract. The `graph_article.py` connects boths `writer.py`and `critic.py` by using LangGraph.
-- The graph_web folder contains the grap_web, loader, search and summarizer python files. The `search.py` (search agent) file searches takes in the URL link for web search, while the `loader.py` (loader agent) loads the web page but limits it to appoximately 32,000 tokens to not exceed the max token limit. The summarizer agent in `summarizer.py` files, provides a concise summary for the the URL given. The graph_web.py connects all components together as one.
-- The utils folder contains the `visualizer.py` file which creates the graphs of the `grah_web.py` and `graph_article.py` files when called in `main.py`. The generatd graphs are saved to the visuals folder.
-- The `shared.py` file contains the shared state for the summarizer and abstract generator graphs.
-- The `main.py` file calls all graphs together and prompts the user for if the would like to generate an abstract or summarise a webpage.
-- The img folder contains the images used for visualisation, also `Langsmith_run.png` show the an example run when Langsmith is used for tracing the graph.
-- The tests folder contains all necessary tests for the each component for proper integration of the project, making it ready for deployment.
-
-![LangSmith](img/LangSmith_run.png)
-
-### **Replicating this project and Example Usage**
-Kindly refer to the GitHub link for the previous project for replication.
-
-- **Run `pip install pytest>=8.4` and `pip install pytest-mock==3.14` after using the environment.yml from the previous repo**
-### **Example Streamlit Outputs**
-![Abstract-generator](img/streamlit_abstract_generator.png)
-
-![Webpage-summariser](img/streamlit_web_page_summariser.png)
-
-**NB:** 
-- **You must have a huggingface api key to use the streamlit app. Kindly refer to the previous github repo to know how to generate a huggingface api key**
-
-Here is the Publication on;
-- [Edit ReadyTensor](https://app.readytensor.ai/publications/the-agentic-research-abstract-generator-and-web-content-summariser-agent-with-langraph-gYeyu875mKsB)
-
-### **Issues faced**:
-- Integrating tests for the LLM agents
-- Conflicts when deploying app on Streamlit, hence the environment.yml file was removed. 
+---
+license: mit
+title: Agentic Research Abstract Generator & Web Summariser-2
+sdk: gradio
+emoji: 📚
+colorFrom: red
+colorTo: green
+---
+## 🧠 Agentic Research Abstract Generator & Web Summariser-2
+An agent-based system using LangGraph and HuggingFace models to generate research abstracts and summarize web content, with modular workflows, memory handling, and task-specific agents.
+
+This builds upon the previous repo 
+- [Project Link](https://github.com/daniau23/agentic_researcher)
+- [ReadyTensor-Publication](https://app.readytensor.ai/publications/the-agentic-research-abstract-generator-and-web-content-summariser-agent-with-langraph-gYeyu875mKsB)
+
+
+### 🚀 Features Improvements
+- 📈 Evaluation metrics and logging
+- 📈 Evaluation metrics and logging
+- 📈 Testing features incorporated
+- 🚀 Model deployment with streamlit
+
+![Research Assistant Flow Chart](img/Agentic-Research-Assistant-AI-pub-main-image.jpg)
+
+### **How the project goes**
+- All files can only work after installing all dependencies in the `environment.yml` file
+- The `notebooks folder` contains the jupyter notebook file for testing the project as a whole and for experimenting. `research_graph2.ipynb` contains the experimentation for abstract generation while `research_graph3.ipynb` contains the experimentation for web content summarisation.
+- The `graph_article` folder contains the critic, writer and graph_article python files. The `writer.py`(writer agent) file takes the category and title needed for drafting the abstract while the `critic.py` (reviewer agent) reviews the generated abstract. The `graph_article.py` connects boths `writer.py`and `critic.py` by using LangGraph.
+- The graph_web folder contains the grap_web, loader, search and summarizer python files. The `search.py` (search agent) file searches takes in the URL link for web search, while the `loader.py` (loader agent) loads the web page but limits it to appoximately 32,000 tokens to not exceed the max token limit. The summarizer agent in `summarizer.py` files, provides a concise summary for the the URL given. The graph_web.py connects all components together as one.
+- The utils folder contains the `visualizer.py` file which creates the graphs of the `grah_web.py` and `graph_article.py` files when called in `main.py`. The generatd graphs are saved to the visuals folder.
+- The `shared.py` file contains the shared state for the summarizer and abstract generator graphs.
+- The `main.py` file calls all graphs together and prompts the user for if the would like to generate an abstract or summarise a webpage.
+- The img folder contains the images used for visualisation, also `Langsmith_run.png` show the an example run when Langsmith is used for tracing the graph.
+- The tests folder contains all necessary tests for the each component for proper integration of the project, making it ready for deployment.
+
+![LangSmith](img/LangSmith_run.png)
+
+### **Replicating this project and Example Usage**
+Kindly refer to the GitHub link for the previous project for replication.
+
+- **Run `pip install pytest>=8.4` and `pip install pytest-mock==3.14` after using the environment.yml from the previous repo**
+### **Example Streamlit Outputs**
+![Abstract-generator](img/streamlit_abstract_generator.png)
+
+![Webpage-summariser](img/streamlit_web_page_summariser.png)
+
+**NB:** 
+- **You must have a huggingface api key to use the streamlit app. Kindly refer to the previous github repo to know how to generate a huggingface api key**
+
+Here is the Publication on;
+- [Edit ReadyTensor](https://app.readytensor.ai/publications/the-agentic-research-abstract-generator-and-web-content-summariser-agent-with-langraph-gYeyu875mKsB)
+
+### **Issues faced**:
+- Integrating tests for the LLM agents
+- Conflicts when deploying app on Streamlit, hence the environment.yml file was removed.