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lib/mix/tasks/mcpixir.blender.ex
defmodule Mix.Tasks.Mcpixir.Blender do
@moduledoc """
Demonstrates using Mcpixir to control Blender 3D via MCP.
This task allows controlling Blender through natural language commands
processed by an LLM.
## Prerequisites
You need to have the Blender MCP addon installed from:
https://github.com/ahujasid/blender-mcp
Make sure the addon is enabled in Blender preferences and the
WebSocket server is running before executing this task.
## Usage
mix mcpixir.blender
## Options
--provider=PROVIDER LLM provider (openai or anthropic, default: anthropic)
--model=MODEL Model to use (default: claude-3-sonnet-20240229 for Anthropic, gpt-4o for OpenAI)
--query=QUERY Query to send to the LLM (default is a cube creation)
--command=COMMAND Command to launch Blender MCP server (default: "uvx blender-mcp")
## Examples
mix mcpixir.blender
mix mcpixir.blender --provider=openai
mix mcpixir.blender --query="Create a red torus floating above a blue plane"
"""
use Mix.Task
alias Mcpixir
@shortdoc "Runs a Blender 3D modeling example with an LLM"
@impl Mix.Task
def run(args) do
{opts, _, _} =
OptionParser.parse(args,
strict: [
provider: :string,
model: :string,
query: :string,
command: :string
]
)
# Load applications
Application.ensure_all_started(:mcpixir)
Application.ensure_all_started(:httpoison)
Application.ensure_all_started(:jason)
Application.ensure_all_started(:langchain)
# Force load LangChain core modules
Code.ensure_loaded?(LangChain)
Code.ensure_loaded?(LangChain.Message)
Code.ensure_loaded?(LangChain.ChatModels)
# Get LLM provider and model
provider = Keyword.get(opts, :provider, "anthropic")
model = get_default_model(provider, Keyword.get(opts, :model))
query =
Keyword.get(
opts,
:query,
"Create an inflatable cube with soft material and a plane as ground."
)
command = Keyword.get(opts, :command, "uvx blender-mcp")
run_blender_example(provider, model, query, command)
end
defp get_default_model(provider, model) do
if model do
model
else
case provider do
"anthropic" -> "claude-3-sonnet-20240229"
_ -> "gpt-4o"
end
end
end
defp run_blender_example(provider, model, query, command) do
# Explicitly ensure LangChain is started
Application.ensure_all_started(:langchain)
# Skip the LangChain check since we've made it a required dependency
# Load required API keys
load_api_keys()
# Show banner
IO.puts(IO.ANSI.bright() <> "Mcpixir Blender Example" <> IO.ANSI.reset())
IO.puts("Provider: #{provider}, Model: #{model}\n")
# Create Blender configuration
config = %{
"mcpServers" => %{
"blender" => %{
"command" => "stdio:#{command}"
}
}
}
# Create LLM configuration
llm_config = %{
provider: String.to_atom(provider),
model: model
}
IO.puts("Connecting to Blender MCP server...")
# Create the MCP client
client = Mcpixir.new_client(config)
IO.puts("Creating MCP agent...")
# Create a real agent connected to the LLM
{:ok, agent} =
Mcpixir.new_agent(%{
llm: llm_config,
client: client
})
# Run the chat
IO.puts("\nUser query: #{query}")
start_time = :os.system_time(:millisecond)
{:ok, result, _updated_agent} = Mcpixir.run(agent, query)
end_time = :os.system_time(:millisecond)
duration = (end_time - start_time) / 1000
IO.puts("\nResult (completed in #{duration}s):")
IO.puts("------------------------------")
IO.puts(result)
IO.puts("------------------------------")
# Clean up
Mcpixir.Client.stop_all_sessions(client)
end
defp load_api_keys do
# Check for API keys in environment variables
openai_key = System.get_env("OPENAI_API_KEY")
anthropic_key = System.get_env("ANTHROPIC_API_KEY")
if is_nil(openai_key) do
IO.puts(
IO.ANSI.yellow() <>
"Warning: OPENAI_API_KEY environment variable not set. " <>
"OpenAI models won't work without it." <>
IO.ANSI.reset()
)
end
if is_nil(anthropic_key) do
IO.puts(
IO.ANSI.yellow() <>
"Warning: ANTHROPIC_API_KEY environment variable not set. " <>
"Anthropic models won't work without it." <>
IO.ANSI.reset()
)
end
end
end