Nerve is a tool that creates stateful agents with any LLM — without writing a single line of code. Agents created with Nerve are capable of both planning and enacting step-by-step whatever actions are required to complete a user-defined task. This is done by dynamically updating the system prompt with new information gathered during previous actions, making the agent stateful across multiple inferences.

• 🧠 Automated Problem Solving: Nerve provides a standard library of actions the agent uses autonomously to inform and enhance its performance. These include identifying specific goals required to complete the task, devising and revising a plan to achieve those goals, and creating and recalling memories comprised of pertinent information gleaned during previous actions.
• 🧑‍💻 User-Defined Agents: Agents are defined using a standard YAML template. The sky is the limit! You can define an agent for any task you desire — check out the existing examples for inspiration.
• 🛠️ Universal Tool Calling: Nerve will automatically detect if the selected model natively supports function calling. If not, it will provide a compatibility layer that empowers the LLM to perform function calling anyway.
• 🤖 Works with any LLM: Nerve is an LLM-agnostic tool.
• 💯 Zero Code: The project's main goal and core difference with other tools is to allow the user to instrument smart agents without writing code.

LLM Support

Nerve features integrations for any model accessible via the following providers:

Name	API Key Environment Variable	Generator Syntax
Ollama	-	ollama://llama3@localhost:11434
Groq	GROQ_API_KEY	groq://llama3-70b-8192
OpenAI¹	OPENAI_API_KEY	openai://gpt-4
Fireworks	LLM_FIREWORKS_KEY	fireworks://llama-v3-70b-instruct
Huggingface²	HF_API_TOKEN	hf://[email protected]
Anthropic	ANTHROPIC_API_KEY	anthropic://claude
Nvidia NIM	NIM_API_KEY	nim://nvidia/nemotron-4-340b-instruct
DeepSeek	DEEPSEEK_API_KEY	deepseek://deepseek-chat
xAI	XAI_API_KEY	xai://grok-beta
Mistral.ai	MISTRAL_API_KEY	mistral://mistral-large-latest
Novita	NOVITA_API_KEY	novita://meta-llama/llama-3.1-70b-instruct

¹ o1-preview and o1 models do not support function calling directly and do not support a system prompt. Nerve will try to detect this and fallback to user prompt. It is possible to force this behaviour by adding the --user-only flag to the command line.

² Refer to this document for how to configure a custom Huggingface endpoint.

Installing with Cargo

cargo install nerve-ai

Installing from DockerHub

A Docker image is available on Docker Hub:

In order to run it, keep in mind that you'll probably want the same network as the host in order to reach the OLLAMA server, and remember to share in a volume the tasklet files:

docker run -it --network=host -v ./examples:/root/.nerve/tasklets evilsocket/nerve -h

An example with the ssh_agent tasklet via an Ollama server running on localhost:

docker run -it --network=host \
  -v ./examples:/root/.nerve/tasklets \
  evilsocket/nerve -G "ollama://llama3@localhost:11434" -T ssh_agent -P'find which process is consuming more ram'

Building from sources

To build from source:

cargo build --release

Run a tasklet with a given OLLAMA server:

./target/release/nerve -G "ollama://<model-name>@<ollama-host>:11434" -T /path/to/tasklet 

Building with Docker

docker build . -t nerve

Example

Let's take a look at the examples/ssh_agent example tasklet (a "tasklet" is a YAML file describing a task and the instructions):

# If this block is not specified, the agent will be able to access all of the 
# standard function namespaces. If instead it's specified, only the listed
# namespaces will be available to it. Use it to limit what the agent can do.
using:
  # the agent can save and recall memories
  - memory
  # the agent can update its own goal
  - goal
  # the agent can set the task as completed or impossible autonomously
  - task
  # the agent can create an action plan for the task
  - planning
  #  give the agent a sense of time
  - time

# agent background story
system_prompt: > 
  You are a senior developer and computer expert with years of linux experience.
  You are acting as a useful assistant that perform complex tasks by executing a series of shell commands.

# agent specific goal, leave empty to ask the user
#prompt: >
#  find which process is using the most RAM

# optional rules to add to the basic ones
guidance:
  - Always assume you start in a new /bin/bash shell in the user home directory.
  - Prefer using full paths to files and directories.
  - Use the /tmp directory for any file write operations.
  - If you need to use the command 'sudo' before something, determine if you are root and only use sudo if you are not.

# optional global action timeout
timeout: 120s

# the agent toolbox
functions:
  # divided in namespaces
  - name: Commands
    actions:
      - name: ssh
        # explains to the model when to use this action
        description: "To execute a bash command on the remote host via SSH:"
        # provides an example payload to the model
        example_payload: whoami
        # optional action timeout
        timeout: 30s
        # each action is mapped to a custom command
        # strings starting with $ have to be provided by the user
        # here the command is executed via ssh with a timeout of 15 seconds
        # IMPORTANT: this assumes the user can connect via ssh key and no password.
        tool: ssh $SSH_USER_HOST_STRING

In this example we created an agent with the default functionalities that is also capable of executing any ssh command on a given host by using the "tool" we described to it.

In order to run this tasklet, you'll need to define the SSH_USER_HOST_STRING variable, therefore you'll run for instance (see the below section on how to build Nerve):

nerve -G "ollama://llama3@localhost:11434" \
  -T /path/to/ssh_agent \
  -DSSH_USER_HOST_STRING=user@example-ssh-server-host

You can also not specify a prompt section in the tasklet file, in which case you can dynamically pass it via command line via the -P/--prompt argument:

nerve -G "ollama://llama3@localhost:11434" \
  -T /path/to/ssh_agent \
  -DSSH_USER_HOST_STRING=user@example-ssh-server-host \
  -P 'find which process is using the most RAM'

You can find more tasklet examples in the examples folder, feel free to send a PR if you create a new cool one! :D

Robopages

Nerve can use functions from a robopages server. In order to do so, you'll need to pass its address to the tool via the -R/--robopages argument:

nerve -G "openai://gpt-4o" \
  -T /path/to/tasklet \
  -R "localhost:8000"

To import only a subset of tools:

nerve -G "openai://gpt-4o" \
  -T /path/to/tasklet \
  -R "localhost:8000/cybersecurity/reverse-engineering"

License

Nerve is released under the GPL 3 license. To see the licenses of the project dependencies, install cargo license with cargo install cargo-license and then run cargo license.