Controlling System Context in Swarmauri | A Guide to Building Countless Chatbot Applications
Summary
TLDRThis video tutorial guides viewers on creating a quick app using the SumarCrack model in Python. It covers installation of the SumarF package, loading environment variables, initializing the C model with an API key, and setting up a Max system context conversation. The script demonstrates dynamic model selection based on user input, interacting with the agent, and executing commands. It showcases the model's versatility in providing assistance for university students, generating funny responses, and creating specialized content like a Python boot camp curriculum and a medical report.
Takeaways
- 🛠️ The video demonstrates how to set up a system using the Sumar Crack model in a Gradio app.
- 📦 The Sumar F package version 0.4.1 and Python are required for the project.
- 💾 Environment variables are loaded from an .env file for API key and other configurations.
- 🔑 An API key is fetched from the environment variables, which can be obtained from console.cr.com.
- 🤖 The C model is initialized with the API key to access allowed models.
- 📈 The available models are retrieved from the LLM (Large Language Model) instance.
- 🗣️ A Max system context conversation instance is initialized for interaction.
- ⚙️ Functions are defined to dynamically change the model based on user input from a dropdown menu.
- 💬 The agent is initialized with the selected model, and input text is processed to return results.
- 🌐 A Gradio interface is set up for model selection, and the application is launched as a local server.
- 🎓 The application is intended to serve as a visual assistant for university students, demonstrating versatility in answering questions and providing information on various topics.
Q & A
What is the first step in creating a system using the Sumar Crack model?
-The first step is to install the Sumar F package version 0.4.1 and Python.
Which package does the script mention for creating an application?
-The script mentions using the 'gradio' package for creating the application interface.
How does the script suggest loading environment variables?
-The script suggests loading environment variables from an .env file.
What is the purpose of fetching the API key from the environment variables?
-The API key is fetched from the environment variables to initialize the C model with the API key to access allowed models.
What is the role of the 'Max system context conversation' instance in the script?
-The 'Max system context conversation' instance is initialized to handle the conversation context within the application.
How does the script propose to change the model dynamically based on user input?
-The script proposes defining a function that changes the model based on dropdown input, allowing the user to select the desired model.
What is the script's approach to ensuring the input text is a string before executing commands?
-The script ensures that the input text is a string by explicitly checking and converting it before executing the input command with the agent.
What is the purpose of setting up a C interface with a dropdown for model selection?
-The purpose is to allow users to easily select and switch between different models within the application.
How does the script handle the transition between different bot personalities, such as a funny bot or a specialist?
-The script handles the transition by initializing the agent with a new model dynamically based on the user's selection, which changes the bot's behavior and responses.
What is the script's approach to creating a curriculum for a Python boot camp?
-The script suggests using the application to create a curriculum by inputting a command to generate a curriculum outline for a Python boot camp.
How does the script demonstrate the application's capability to generate a medical report?
-The script demonstrates this by changing the context to 'medical trage' and then asking the application to write a report, which generates a medical TR report based on the context.
Outlines
💻 Setting Up a Sumar-based System Context
The paragraph outlines the process of creating a system using the Sumar crack model in a university context. It starts with the installation of the Sumar F package version 0.4.1 and Python. The speaker then details the steps to load necessary modules, import system messages, and set up conversation agents. The process involves loading environment variables from an .env file and fetching an API key from console.cr.com. The C model is initialized with the API key to access allowed models, and the available models are retrieved from the language model instance. A Max system context conversation instance is initialized, and functions are defined to change the model based on user input and to interact with the agent. The input text is checked to ensure it's a string, and the agent executes the input command, returning results as a string. The paragraph concludes with setting up a user interface for model selection and launching the application, which creates a local server.
Mindmap
Keywords
💡Sumar
💡Python
💡Environment Variables
💡API Key
💡Model
💡Gradio
💡Conversation Agent
💡Specialist
💡Culum
💡Medical Trage
Highlights
Installing the Summar F package version 0.4.1 and Python environment setup.
Loading AMV and importing necessary libraries like OS, Gradio, and others.
Importing the C model and system message for interaction.
Loading environment variables from the EMV file.
Fetching the API key from environment variables for model access.
Initializing the C model with the API key to access allowed models.
Getting available models from the LLM instance.
Initializing a Max system context conversation instance.
Defining a function to dynamically change the model based on user input.
Defining another function to interact with the agent.
Initializing the agent with the new model based on user selection.
Ensuring input text is a string before executing commands with the agent.
Executing input commands and returning results as a string.
Setting up the C interface with a drop-down for model selection.
Launching the application and creating a local server.
Creating a visual assistant for university students.
Asking the model a question about compound matter and receiving a coded answer.
Changing the model to a funny bot and receiving humorous responses.
Specializing the model to provide ideas on sustainable development in agriculture.
Creating a curriculum for a Python boot camp using the model.
Testing the model as a medical trauma assistant and writing a medical report.
Invitation to try out the application and follow on GitHub.
Transcripts
quick app in sumar creating a system
context in grad using sumar crack model
now the first thing we need to do is to
install the sumar F package version
0.4.1 and python. EMV then we need to
load the AMV and import OS
gradio import the C
model import system
message import simple conversation
agents import the max system context
conversation then we need to load the
environment variables from the EMV file
then we need to fetch the API key from
the environment variables remember you
can get your API keys from console.
cr.com
Keys now you need to initialize the C
model with the API key to access allowed
models then we need to get the available
models from the llm
instance then we need to initialize a
Max system context conversation
instance then we need to define a
function to dramatically change the
model based on drop down
input with this function then we need to
Define another function to interact with
the
agent then in the same function we need
to initialize the the model dynamically
based on user
selection then we to initialize the
agent with the new model then we need to
ensure that the input text is a
string then we need to execute the input
command with the
agent then we need to return the results
as a
string now the next thing we need to do
is to set up the C interface with the
drop down for model
selection
and we need to launch the
application just running this
now creates a local
server so I want to test this out so I
want to create a visual assistant for
student of a university so this model
would mainly work for visual assistance
so I asked the question what is what
compound matter and it gave me a code
answer so this model now is trained
based on F assistance now I'm asking it
again I'm giving it another command be a
funny
bot so most of the messages that is
going to bring out is mostly a joke like
so I'm going to say tell me a
[Music]
joke and yeah so this is a funny joke
say why could School
stand so I want to check okay I want to
give it another specialist again I want
to say should
specialize a specialist in cfy planning
and agriculture so I say share some
ideas so as you can see on the screen
say for sustainable development not
disability to Agriculture and
plants now I'm testing again to be
create a culum for a boot camp for a
python boot camp
so for a python boot camp course so I'm
going to say create
AUM now mind you didn't add python so it
will definitely bring out a
python
[Music]
ccum yeah so definitely so this is just
a boam curriculum first div 12s 12 weeks
and now I want to create a medical trage
so I'll be testing this with another
model so a medical trage
assistant so that's the
context now let me test it out write a
medical
report or write a
report so this came out as a medical TR
report because the context is on
trage so you can try this out and thank
you so much for watching don't forget to
follow us on GitHub
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