CMDLLM is an intelligent interface for interacting with command-line tools using natural language. It supports any command-line tool, such as bash, kubectl, ros2, etc. It leverages Large Language Models (LLM) to translate your natural language queries into corresponding commands and provides options to execute these commands.
The original purpose of developing this tool was to help myself quickly use the podman command line. Since my new company doesn't allow the use of docker commands, I was struggling to adapt from docker to podman. So I tried to develop this tool, and after several updates, I decided to open-source it. I hope it will be useful to you.
- Multi-tool Support: Works with any command-line tool, such as Bash, kubectl, ros2, docker, etc.
- Natural Language Processing: Translates everyday language into corresponding tool commands.
- Command Execution: Offers the option to directly execute suggested commands.
- Context Management: Maintains conversation history to support more complex interactions.
- Safety Prompts: Provides warnings and confirmations for potentially dangerous operations (like deleting data).
- Interactive Sessions: Supports both interactive session mode and one-time query mode.
- Command-line Configuration: Provides convenient command-line configuration management without the need to manually edit configuration files.
- Multiple LLM Providers: Supports OpenAI API-compatible services and Azure OpenAI services (such as OpenAI, DeepSeek, etc.).
pip install cmdllmgit clone https://github.com/yexia553/cmdllm.git
cd cmdllm
pip install -e .CMDLLM provides an interactive session mode:
Start an interactive session with a specific tool:
cmdllm chat -t bashThis will start an interactive session where you can input multiple queries continuously, and the program will maintain the context. Type exit or quit to end the session.
$ cmdllm chat -t bash
Starting interactive bash session. Type 'exit' or 'quit' to end.
-----------------------------------------------------
bash> List all files in the current directory
Processing your query...
Suggested command:
ls -la
Execution result:
total 64
drwxr-xr-x 15 user staff 480 5 Jun 15:30 .
drwxr-xr-x 25 user staff 800 5 Jun 14:22 ..
-rw-r--r-- 1 user staff 1550 5 Jun 15:30 LICENSE
-rw-r--r-- 1 user staff 133 5 Jun 15:30 MANIFEST.in
-rw-r--r-- 1 user staff 3122 5 Jun 15:30 README.md
...
-----------------------------------------------------
bash> Create a directory named test
Processing your query...
Suggested command:
mkdir test
Execution result:
-----------------------------------------------------
bash> exit
Exiting chat session.$ cmdllm chat -t kubectl
Starting interactive kubectl session. Type 'exit' or 'quit' to end.
-----------------------------------------------------
kubectl> List all namespaces
Processing your query...
Suggested command:
kubectl get namespaces
Execution result:
NAME STATUS AGE
default Active 45d
kube-node-lease Active 45d
kube-public Active 45d
kube-system Active 45d
-----------------------------------------------------
kubectl> Show all pods in the default namespace
Processing your query...
Suggested command:
kubectl get pods -n default
Execution result:
NAME READY STATUS RESTARTS AGE
nginx-deployment-66b6c48dd5-8ph2j 1/1 Running 0 24h
nginx-deployment-66b6c48dd5-vb6l8 1/1 Running 0 24h
-----------------------------------------------------
kubectl> Describe the first nginx pod
Processing your query...
Suggested command:
kubectl describe pod nginx-deployment-66b6c48dd5-8ph2j -n default
Execution result:
Name: nginx-deployment-66b6c48dd5-8ph2j
Namespace: default
Priority: 0
Service Account: default
Node: minikube/192.168.49.2
Start Time: Thu, 21 Mar 2024 09:30:42 +0800
...
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Normal Scheduled 24h default-scheduler Successfully assigned default/nginx-deployment-66b6c48dd5-8ph2j to minikube
Normal Pulled 24h kubelet Container image "nginx:1.14.2" already present on machine
Normal Created 24h kubelet Created container nginx
Normal Started 24h kubelet Started container nginx
-----------------------------------------------------
kubectl> exit
Exiting chat session.CMDLLM provides convenient command-line configuration management without the need to manually edit configuration files.
The simplest way is to use the interactive configuration command to set up the LLM provider:
cmdllm config setupThis will guide you through setting up all necessary LLM configuration items, such as API keys, endpoints, model or deployment names. You can choose to use either OpenAI API-compatible services or Azure OpenAI services.
CMDLLM provides dedicated commands for managing available command-line tools:
# View all available tools
cmdllm tools list
# Add a new tool
cmdllm tools add kubectl
# Remove a tool
cmdllm tools del kubectlcmdllm config setup can help you configure interactively, but if you want to configure or modify a single option, you can use the following commands to configure manually:
# Set LLM provider to Azure
cmdllm config set llm_provider azure
# Configure Azure OpenAI parameters, remember to replace the values with your actual values
cmdllm config set azure.api_key YOUR_AZURE_API_KEY
cmdllm config set azure.endpoint https://your-resource-name.openai.azure.com
cmdllm config set azure.deployment your-deployment-name
cmdllm config set azure.api_version 2023-05-15If you want to use OpenAI API-compatible services (such as OpenAI, DeepSeek, etc.):
# Set LLM provider to OpenAI compatible
cmdllm config set llm_provider openai_compatible
# Configure OpenAI compatible parameters, remember to replace the values with your actual values
cmdllm config set openai_compatible.api_key YOUR_API_KEY
cmdllm config set openai_compatible.base_url https://api.openai.com/v1
cmdllm config set openai_compatible.model gpt-3.5-turboYou can set the maximum number of messages carried in the conversation, default is 20:
# Set context message count
cmdllm config set-context-messages 10
# View current context message setting
cmdllm config get-context-messagescmdllm config listcmdllm config get llm_provider
cmdllm config get azure.endpointcmdllm config initIf you still want to manually edit the configuration file, CMDLLM's configuration file is located at ~/.cmdllm/config.yaml:
tools:
- bash
- kubectl
- ros2
llm_provider: openai_compatible # LLM provider being used: openai_compatible or azure
openai_compatible:
base_url: https://api.openai.com/v1 # OpenAI compatible API endpoint
api_key: your_API_key # API key
model: gpt-3.5-turbo # Model being used
azure:
api_key: your_Azure_key # Azure OpenAI API key
endpoint: https://your-resource-name.openai.azure.com # Azure endpoint
deployment: your-deployment-name # Azure model deployment name
api_version: 2023-05-15 # Azure API version
context:
max_messages: 10 # Maximum number of messages saved in contextSupported LLM services:
- OpenAI API-compatible services (such as OpenAI, DeepSeek, etc.)
- Azure OpenAI
$ cmdllm clear
Context has been successfully cleared.- Before use, ensure that the corresponding command-line tools are installed on your system and available in the PATH.
- Some operations may require administrator privileges.
- Commands generated by large language models are assessed for risk by the model itself before execution, but this process has certain security issues
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This project is licensed under the Apache 2.0 License - see the LICENSE file for details.