Update docs for new executors (#2119)

* Update docs for new executors

* Update website/docs/FAQ.mdx

Co-authored-by: gagb <[email protected]>

* Update website/docs/FAQ.mdx

Co-authored-by: gagb <[email protected]>

* Update website/docs/installation/Installation.mdx

Co-authored-by: gagb <[email protected]>

* Update website/docs/installation/Installation.mdx

Co-authored-by: gagb <[email protected]>

---------

Co-authored-by: gagb <[email protected]>

Author: ekzhu

website/docs/FAQ.mdx

@@ -71,31 +71,46 @@ in the system message. This line is in the default system message of the `Assist
 If the `# filename` doesn't appear in the suggested code still, consider adding explicit instructions such as "save the code to disk" in the initial user message in `initiate_chat`.
 The `AssistantAgent` doesn't save all the code by default, because there are cases in which one would just like to finish a task without saving the code.
 
-## Code execution
+## Legacy code executor
 
-We strongly recommend using docker to execute code. There are two ways to use docker:
+:::note
+The new code executors offers more choices of execution backend.
+Read more about [code executors](/docs/tutorial/code-executors).
+:::
 
-1. Run AutoGen in a docker container. For example, when developing in [GitHub codespace](https://codespaces.new/microsoft/autogen?quickstart=1), AutoGen runs in a docker container. If you are not developing in Github codespace, follow instructions [here](installation/Docker.md#option-1-install-and-run-autogen-in-docker) to install and run AutoGen in docker.
-2. Run AutoGen outside of a docker, while performing code execution with a docker container. For this option, make sure docker is up and running. If you want to run the code locally (not recommended) then `use_docker` can be set to `False` in `code_execution_config` for each code-execution agent, or set `AUTOGEN_USE_DOCKER` to `False` as an environment variable.
+The legacy code executor is used by specifying the `code_execution_config` in the agent's constructor.
 
-### Enable Python 3 docker image
-
-You might want to override the default docker image used for code execution. To do that set `use_docker` key of `code_execution_config` property to the name of the image. E.g.:
 ```python
-user_proxy = autogen.UserProxyAgent(
-    name="agent",
-    human_input_mode="TERMINATE",
-    max_consecutive_auto_reply=10,
+from autogen import UserProxyAgent
+
+user_proxy = UserProxyAgent(
+    name="user_proxy",
     code_execution_config={"work_dir":"_output", "use_docker":"python:3"},
-    llm_config=llm_config,
-    system_message=""""Reply TERMINATE if the task has been solved at full satisfaction.
-Otherwise, reply CONTINUE, or the reason why the task is not solved yet."""
 )
 ```
 
-If you have problems with agents running `pip install` or get errors similar to `Error while fetching server API version: ('Connection aborted.', FileNotFoundError(2, 'No such file or directory')`, you can choose **'python:3'** as image as shown in the code example above and that should solve the problem.
-
-### Agents keep thanking each other when using `gpt-3.5-turbo`
+In this example, the `code_execution_config` specifies that the code will be
+executed in a docker container with the image `python:3`.
+By default, the image name is `python:3-slim` if not specified.
+The `work_dir` specifies the directory where the code will be executed.
+If you have problems with agents running `pip install` or get errors similar to
+`Error while fetching server API version: ('Connection aborted.', FileNotFoundError(2, 'No such file or directory')`,
+you can choose **'python:3'** as image as shown in the code example above and
+that should solve the problem.
+
+By default it runs code in a docker container. If you want to run code locally
+(not recommended) then `use_docker` can be set to `False` in `code_execution_config`
+for each code-execution agent, or set `AUTOGEN_USE_DOCKER` to `False` as an
+environment variable.
+
+You can also develop your AutoGen application in a docker container.
+For example, when developing in [GitHub codespace](https://codespaces.new/microsoft/autogen?quickstart=1),
+AutoGen runs in a docker container.
+If you are not developing in GitHub Codespaces,
+follow instructions [here](installation/Docker.md#option-1-install-and-run-autogen-in-docker)
+to install and run AutoGen in docker.
+
+## Agents keep thanking each other when using `gpt-3.5-turbo`
 
 When using `gpt-3.5-turbo` you may often encounter agents going into a "gratitude loop", meaning when they complete a task they will begin congratulating and thanking each other in a continuous loop. This is a limitation in the performance of `gpt-3.5-turbo`, in contrast to `gpt-4` which has no problem remembering instructions. This can hinder the experimentation experience when trying to test out your own use case with cheaper models.
 

website/docs/installation/Installation.mdx

@@ -78,35 +78,29 @@ pip install pyautogen
 
 :::
 
+## Install Docker for Code Execution
 
-## Code execution with Docker (default)
+We recommend using Docker for code execution.
+To install Docker, follow the instructions for your operating system on the [Docker website](https://docs.docker.com/get-docker/).
 
-Even if you install AutoGen locally, we highly recommend using Docker for [code execution](FAQ.mdx#code-execution).
-
-The default behaviour for code-execution agents is for code execution to be performed in a docker container.
-
-**To turn this off**: if you want to run the code locally (not recommended) then `use_docker` can be set to `False` in `code_execution_config` for each code-execution agent, or set `AUTOGEN_USE_DOCKER` to `False` as an environment variable.
-
-You might want to override the default docker image used for code execution. To do that set `use_docker` key of `code_execution_config` property to the name of the image. E.g.:
+A simple example of how to use Docker for code execution is shown below:
 
 ```python
-user_proxy = autogen.UserProxyAgent(
-    name="agent",
-    human_input_mode="TERMINATE",
-    max_consecutive_auto_reply=10,
-    code_execution_config={"work_dir":"_output", "use_docker":"python:3"},
-    llm_config=llm_config,
-    system_message=""""Reply TERMINATE if the task has been solved at full satisfaction.
-Otherwise, reply CONTINUE, or the reason why the task is not solved yet."""
-)
+from pathlib import Path
+from autogen import UserProxyAgent
+from autogen.coding import DockerCommandLineCodeExecutor
+
+work_dir = Path("coding")
+work_dir.mkdir(exist_ok=True)
+
+with DockerCommandLineCodeExecutor(work_dir=work_dir) as code_executor:
+    user_proxy = UserProxyAgent(
+        name="user_proxy",
+        code_execution_config={"executor": code_executor},
+    )
 ```
 
-**Turn off code execution entirely**: if you want to turn off code execution entirely, set `code_execution_config` to `False`. E.g.:
+To learn more about code executors, see the [code executors tutorial](/docs/tutorial/code-executors).
 
-```python
-user_proxy = autogen.UserProxyAgent(
-    name="agent",
-    llm_config=llm_config,
-    code_execution_config=False,
-)
-```
+You might have seen a different way of defining the executors without creating the
+executor object, please refer to FAQ for this [legacy code executor](/docs/FAQ#legacy-code-executor).

website/docs/topics/non-openai-models/cloud-togetherai.md

@@ -21,76 +21,88 @@ set TOGETHER_API_KEY=YourTogetherAIKeyHere
 Create your LLM configuration, with the [model you want](https://docs.together.ai/docs/inference-models).
 
 ```python
-import autogen
 import os
 
-llm_config={
-    "config_list": [
-        {
-            # Available together.ai model strings:
-            # https://docs.together.ai/docs/inference-models
-            "model": "mistralai/Mistral-7B-Instruct-v0.1",
-            "api_key": os.environ['TOGETHER_API_KEY'],
-            "base_url": "https://api.together.xyz/v1"
-        }
-    ],
-    "cache_seed": 42
-}
+config_list = [
+    {
+        # Available together.ai model strings:
+        # https://docs.together.ai/docs/inference-models
+        "model": "mistralai/Mistral-7B-Instruct-v0.1",
+        "api_key": os.environ['TOGETHER_API_KEY'],
+        "base_url": "https://api.together.xyz/v1"
+    }
+]
 ```
 
 ## Construct Agents
 
 ```python
+from pathlib import Path
+from autogen import AssistantAgent, UserProxyAgent
+from autogen.coding import LocalCommandLineCodeExecutor
+
+work_dir = Path("groupchat")
+work_dir.mkdir(exist_ok=True)
+
+# Create local command line code executor.
+code_executor = LocalCommandLineCodeExecutor(work_dir=work_dir)
+
 # User Proxy will execute code and finish the chat upon typing 'exit'
-user_proxy = autogen.UserProxyAgent(
+user_proxy = UserProxyAgent(
     name="UserProxy",
     system_message="A human admin",
     code_execution_config={
         "last_n_messages": 2,
-        "work_dir": "groupchat",
-        "use_docker": False,
-    },  # Please set use_docker=True if docker is available to run the generated code. Using docker is safer than running the generated code directly.
+        "executor": code_executor,
+    },
     human_input_mode="TERMINATE",
     is_termination_msg=lambda x: "TERMINATE" in x.get("content"),
 )
 
 # Python Coder agent
-coder = autogen.AssistantAgent(
+coder = AssistantAgent(
     name="softwareCoder",
     description="Software Coder, writes Python code as required and reiterates with feedback from the Code Reviewer.",
     system_message="You are a senior Python developer, a specialist in writing succinct Python functions.",
-    llm_config=llm_config,
+    llm_config={"config_list": config_list},
 )
 
 # Code Reviewer agent
-reviewer = autogen.AssistantAgent(
+reviewer = AssistantAgent(
     name="codeReviewer",
     description="Code Reviewer, reviews written code for correctness, efficiency, and security. Asks the Software Coder to address issues.",
     system_message="You are a Code Reviewer, experienced in checking code for correctness, efficiency, and security. Review and provide feedback to the Software Coder until you are satisfied, then return the word TERMINATE",
     is_termination_msg=lambda x: "TERMINATE" in x.get("content"),
-    llm_config=llm_config,
+    llm_config={"config_list": config_list},
 )
 ```
 
 ## Establish the group chat
 
 ```python
+from autogen import GroupChat, GroupChatManager
+
 # Establish the Group Chat and disallow a speaker being selected consecutively
-groupchat = autogen.GroupChat(agents=[user_proxy, coder, reviewer], messages=[], max_round=12, allow_repeat_speaker=False)
+groupchat = GroupChat(agents=[user_proxy, coder, reviewer], messages=[], max_round=12, allow_repeat_speaker=False)
 
 # Manages the group of multiple agents
-manager = autogen.GroupChatManager(groupchat=groupchat, llm_config=llm_config)
+manager = GroupChatManager(groupchat=groupchat, llm_config={"config_list": config_list})
 ```
 
 ## Start Chat
 
 ```python
-# Start the chat with a request to write a function
-user_proxy.initiate_chat(
-    manager,
-    message="Write a Python function for the Fibonacci sequence, the function will have one parameter for the number in the sequence, which the function will return the Fibonacci number for."
-)
-# type exit to terminate the chat
+from autogen.cache import Cache
+
+# Cache LLM responses.
+with Cache.disk() as cache:
+    # Start the chat with a request to write a function
+    user_proxy.initiate_chat(
+        manager,
+        message="Write a Python function for the Fibonacci sequence, the function will have one parameter for the number in the sequence, which the function will return the Fibonacci number for.",
+        cache=cache,
+    )
+    # type exit to terminate the chat
 ```
 
 Output: