From c41496a061b9f516d782b318c237f019f82858bc Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E9=81=93=E8=BE=95?= Date: Fri, 19 Jan 2024 16:21:47 +0800 Subject: [PATCH] fix according to xuchen's comments [hyperlinks] --- docs/sphinx_doc/source/tutorial/103-example.md | 6 +++--- docs/sphinx_doc/source/tutorial/104-usecase.md | 4 ++-- docs/sphinx_doc/source/tutorial/201-agent.md | 6 +++--- 3 files changed, 8 insertions(+), 8 deletions(-) diff --git a/docs/sphinx_doc/source/tutorial/103-example.md b/docs/sphinx_doc/source/tutorial/103-example.md index a5f514f46..02995edc2 100644 --- a/docs/sphinx_doc/source/tutorial/103-example.md +++ b/docs/sphinx_doc/source/tutorial/103-example.md @@ -26,7 +26,7 @@ model_config = { } ``` -For open-source models, we support integration with various model interfaces such as HuggingFace, ModelScope, FastChat, and vllm. You can find scripts on deploying these services in the `scripts` directory, and we defer the detailed instructions to [[Using Different Model Sources with Model API]](https://alibaba.github.io/AgentScope/tutorial/203-model.md). +For open-source models, we support integration with various model interfaces such as HuggingFace, ModelScope, FastChat, and vllm. You can find scripts on deploying these services in the `scripts` directory, and we defer the detailed instructions to [[Using Different Model Sources with Model API]](https://alibaba.github.io/AgentScope/tutorial/203-model.html). You can register your configuration by calling AgentScope's initilization method as follow. Besides, you can also load more than one config by calling init mutliple times. ```python @@ -55,7 +55,7 @@ dialogAgent = DialogAgent(name="assistant", model="gpt-4") userAgent = UserAgent() ``` -**NOTE**: Please refer to [[Customizing Your Custom Agent with Agent Pool]](https://alibaba.github.io/AgentScope/tutorial/201-agent.md) for all available agents. +**NOTE**: Please refer to [[Customizing Your Custom Agent with Agent Pool]](https://alibaba.github.io/AgentScope/tutorial/201-agent.html) for all available agents. ## Step3: Agent Conversation @@ -96,7 +96,7 @@ while x is None or x.content != "exit": x = sequentialpipeline([dialog_agent, user_agent]) ``` -For more details about how to utilize pipelines for complex agent interactions, please refer to [[Agent Interactions: Dive deeper into Pipelines and Message Hub]](https://alibaba.github.io/AgentScope/tutorial/202-pipeline.md). +For more details about how to utilize pipelines for complex agent interactions, please refer to [[Agent Interactions: Dive deeper into Pipelines and Message Hub]](https://alibaba.github.io/AgentScope/tutorial/202-pipeline.html). diff --git a/docs/sphinx_doc/source/tutorial/104-usecase.md b/docs/sphinx_doc/source/tutorial/104-usecase.md index c1608df7b..edd35ea7b 100644 --- a/docs/sphinx_doc/source/tutorial/104-usecase.md +++ b/docs/sphinx_doc/source/tutorial/104-usecase.md @@ -10,7 +10,7 @@ Let the adventure begin to unlock the potential of multi-agent applications with ## Getting Started -Firstly, ensure that you have installed and configured AgentScope properly. Besides, we will involve the basic concepts of `Model API`, `Agent`, `Msg`, and `Pipeline,` as described in [Tutorial-Concept](https://alibaba.github.io/AgentScope/tutorial/102-concepts.md). The overview of this tutorial is shown below: +Firstly, ensure that you have installed and configured AgentScope properly. Besides, we will involve the basic concepts of `Model API`, `Agent`, `Msg`, and `Pipeline,` as described in [Tutorial-Concept](https://alibaba.github.io/AgentScope/tutorial/102-concepts.html). The overview of this tutorial is shown below: * [Step 1: Prepare **Model API** and Set Model Configs](#step-1-prepare-model-api-and-set-model-configs) * [Step 2: Define the Roles of Each **Agent**](#step-2-define-the-roles-of-each-agent) @@ -22,7 +22,7 @@ Firstly, ensure that you have installed and configured AgentScope properly. Besi ### Step 1: Prepare Model API and Set Model Configs -As we discussed in the last tutorial, you need to prepare your model configurations into a JSON file for standard OpenAI chat API, FastChat, and vllm. More details and advanced usages such as configuring local models with POST API are presented in [Tutorial-Model-API](https://alibaba.github.io/AgentScope/tutorial/203-model.md). +As we discussed in the last tutorial, you need to prepare your model configurations into a JSON file for standard OpenAI chat API, FastChat, and vllm. More details and advanced usages such as configuring local models with POST API are presented in [Tutorial-Model-API](https://alibaba.github.io/AgentScope/tutorial/203-model.html). ```json [ diff --git a/docs/sphinx_doc/source/tutorial/201-agent.md b/docs/sphinx_doc/source/tutorial/201-agent.md index 58c9b5658..e1cfb7a95 100644 --- a/docs/sphinx_doc/source/tutorial/201-agent.md +++ b/docs/sphinx_doc/source/tutorial/201-agent.md @@ -8,11 +8,11 @@ The `AgentBase` class is the architectural cornerstone for all agent constructs Each AgentBase derivative is composed of several key characteristics: -* `memory`: This attribute enables agents to retain and recall past interactions, allowing them to maintain context in ongoing conversations. For more details about `memory`, we defer to [Memory and Message Management](https://alibaba.github.io/AgentScope/tutorial/205-memory.md). +* `memory`: This attribute enables agents to retain and recall past interactions, allowing them to maintain context in ongoing conversations. For more details about `memory`, we defer to [Memory and Message Management](https://alibaba.github.io/AgentScope/tutorial/205-memory.html). -* `model`: The model is the computational engine of the agent, responsible for making a response given existing memory and input. For more details about `model`, we defer to [Using Different Model Sources with Model API]https://alibaba.github.io/AgentScope/tutorial/203-model.md). +* `model`: The model is the computational engine of the agent, responsible for making a response given existing memory and input. For more details about `model`, we defer to [Using Different Model Sources with Model API]https://alibaba.github.io/AgentScope/tutorial/203-model.html). -* `sys_prompt` & `engine`: The system prompt acts as predefined instructions that guide the agent in its interactions; and the `engine` is used to dynamically generate a suitable prompt. For more details about them, we defer to [Prompt Engine](https://alibaba.github.io/AgentScope/tutorial/206-prompt.md). +* `sys_prompt` & `engine`: The system prompt acts as predefined instructions that guide the agent in its interactions; and the `engine` is used to dynamically generate a suitable prompt. For more details about them, we defer to [Prompt Engine](https://alibaba.github.io/AgentScope/tutorial/206-prompt.html). In addition to these attributes, `AgentBase` endows agents with pivotal methods such as `observe` and `reply`: