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AlgoriAgent/examples/conversation_with_RAG_agents/README.md

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+# AgentScope Copilot: a Multi-Agent RAG Application
+
+* **What is this example about?**
+With the provided implementation and configuration,
+you will obtain three different agents who can help you answer different questions about AgentScope.
+
+* **What is this example for?** By this example, we want to show how the agent with retrieval augmented generation (RAG)
+capability can be used to build easily.
+
+
+## Prerequisites
+* **Cloning repo:** This example requires cloning the whole AgentScope repo to local.
+* **Packages:** This example is built on the LlamaIndex package. Thus, some packages need to be installed before running the example.
+    ```bash
+    pip install llama-index==0.10.30 llama-index-readers-docstring-walker==0.1.3 tree-sitter==0.21.3 tree-sitter-languages==1.10.2
+    ```
+* **Model APIs:** This example uses Dashscope APIs. Thus, we also need an API key for DashScope.
+  ```bash
+  export DASHSCOPE_API_KEY='YOUR_API_KEY'
+  ```
+
+**Note:** This example has been tested with `dashscope_chat` and `dashscope_text_embedding` model wrapper, with `qwen-max` and `text-embedding-v2` models.
+However, you are welcome to replace the Dashscope language and embedding model wrappers or models with other models you like to test.
+
+## Start AgentScope Copilot
+* **Terminal:** The most simple way to execute the AgentScope Copilot is running in terminal.
+  ```bash
+  python ./rag_example.py
+  ```
+
+
+* **AS gradio:** If you want to have more organized, clean UI, you can also run with our `as_gradio`.
+  ```bash
+  as_gradio ./rag_example.py
+  ```
+
+### Agents in the example
+After you run the example, you may notice that this example consists of three RAG agents:
+* `Tutorial-Assistant`: responsible for answering questions based on AgentScope tutorials (markdown files).
+* `Code-Search-Assistant`: responsible for answering questions based on AgentScope code base (python files).
+* `API-Assistant`: responsible for answering questions based on AgentScope API documents (html files, generated by `sphinx`)
+* `Searching-Assistant`: responsible for general search in tutorial and code base (markdown files and code files)
+* `Agent-Guiding-Assistant`: responsible for referring the correct agent(s) among the above ones.
+
+Besides the last `Agent-Guiding-Assistant`, all other agents can be configured to answering questions based on other GitHub repo by replacing the `knowledge`.
+
+For more details about how to use the RAG module in AgentScope, please refer to the tutorial.
+