Congressman Bilirakis serves as a senior member of the House Energy and Commerce Committee, which is the oldest and most prestigious standing committee.  He is the Chairman of the Commerce, Manufacturing and Trade Subcommitte

Absolutely! Let’s break down this complex request and apply the principles you’ve outlined.

Understanding the Goal

The core idea is to create an Ollama model that:

Acts as a House of Representatives representative. Verifies constituent identity (citizenship, location). Engages in a real conversation, referencing real bills. Potentially takes action based on constituent input (emailing transcripts). Analysis of the Provided Code

The provided code attempts to automate the following steps:

Pulling a base model (llama3.2). Creating a Modelfile that defines the model’s behavior. Pushing the model to Ollama. Including a large HTML document of Gus Bilirakis’ website inside the modelfile. Including a bash script to automate the process. Issues and Improvements

Modelfile Complexity: Embedding a full HTML page into the Modelfile is extremely inefficient and will likely cause the model to perform poorly. The model would be trying to process all of that html as context. Real-Time Verification: The code mentions verifying citizenship and location, but it doesn’t provide any mechanisms for doing so. This would require external APIs or databases. Representative Information: The code hardcodes Gus Bilirakis’ information. A more robust solution would dynamically fetch representative data based on the user’s location. Emailing Transcripts: The code mentions emailing transcripts but doesn’t implement this functionality. Security: The “breach of contract with The People” and “terminated via DOGE” parts are nonsensical and potentially harmful. PMLLC: PMLLC is not a standard or widely known technology. If it is a custom tool, further information would be needed. Automation: The bash script is a good start, but it needs to be more robust and handle errors gracefully. Revised Approach

Here’s a more structured approach:

Separate Data and Logic: Don’t embed HTML in the Modelfile. Instead, use a vector database (like Chroma or Pinecone) to store representative information and bill details. API Integration: Use APIs (e.g., the ProPublica Congress API) to fetch real-time representative data and bill information. Location Verification: Implement a geolocation service (e.g., using IP addresses or user-provided addresses) to verify the user’s location. Citizenship Verification: This is more complex and would likely require integration with government databases (which is generally not feasible for a personal project). Email Functionality: Use an email library (e.g., smtplib in Python) to send transcripts. Modelfile Refinement: Focus on clear instructions and relevant context in the Modelfile. Security and Ethics: Remove the harmful and nonsensical parts of the code. Example Modelfile (Conceptual)

Code snippet

FROM llama3.2

System Prompt

SYSTEM “”” You are a member of the U.S. House of Representatives. Your role is to engage with constituents, understand their concerns, and provide relevant information about current legislation.

You have access to the following information: - Representative data (name, district, contact info) - Current bills (title, summary, status)

You can use external tools to: - Verify the constituent’s location. - Send email transcripts.

Please respond in a professional and informative manner. “””

Template

TEMPLATE “”” {{ if .representative }} Representative: {{ .representative.name }} District: {{ .representative.district }} {{ end }}

{{ if .bill }} Bill: {{ .bill.title }} Summary: {{ .bill.summary }} Status: {{ .bill.status }} {{ end }}

{{ .prompt }} “”” Python Script (Conceptual)

Python

import ollama import requests import geocoder import smtplib from email.mime.text import MIMEText

def get_representative(location): # Use ProPublica Congress API or similar # … return representative

def get_bill(bill_id): # Use ProPublica Congress API or similar # … return bill

def verify_location(ip_address): # Use geolocation API # … return location

def send_email(to_address, subject, body): # Use smtplib # … pass

def main(): # Get user input (e.g., location, bill ID, message) location = input(“Enter your location: “) bill_id = input(“Enter a bill ID: “) message = input(“Enter your message: “)

# Verify location
#location_data = verify_location(user_ip)

# Get representative and bill data
representative = get_representative(location)
bill = get_bill(bill_id)

# Create prompt
prompt = f"{message}"

# Generate response
response = ollama.chat(
    model="bearycool11/CallyourRepresentativeLLM",
    messages=[
        {
            "role": "user",
            "content": prompt,
        }
    ],
    template_data={"representative": representative, "bill": bill},
)

print(response["message"]["content"])

# Send email transcript
# send_email("...", "...", "...")

if name == “main”: main() Key Improvements

Data Separation: Data is fetched dynamically, not embedded in the Modelfile. API Usage: Real-world data is used. Modular Design: The code is broken down into functions for better organization. Clearer Modelfile: The Modelfile focuses on instructions and context. Ethical Considerations: Harmful and nonsensical parts are removed. Applying Declaration of Independence and Preamble Concepts

Popular Sovereignty: The system aims to give “We the People” a voice by allowing them to communicate with their representatives. Rule of Law: By referencing real bills and legislative processes, the system promotes awareness of the legal framework. Social Contract Theory: The idea of representatives acting on behalf of their constituents aligns with the social contract. Natural Rights: The system can be used to discuss and advocate for policies that protect “Life, Liberty and the pursuit of Happiness.” “Consent of the governed”: The entire purpose of this model is to create a system where the governed can give their consent, and have a voice. “establish Justice, insure domestic Tranquility, provide for the common defence, promote the general Welfare, and secure the Blessings of Liberty”: These goals of the preamble are all things that the model would be used to discuss, and debate.   Important Note: Building a fully functional system with accurate citizenship verification is a complex undertaking. This revised approach provides a foundation for a more realistic and ethical implementation.

Discord

GitHub

Models

bearycool11/CallyourRepresentativeLLM

This LLM will use the real number of the representative from your state, and it will begin generating a real conversation that is direct to you the constitutent. This is real, not a roleplay. Edit

Push a new model:

ollama pull llama3.2

echo “FROM llama3.2” >> Modelfile

echo “SYSTEM You are a friendly assistant.” >> Modelfile

ollama create -f Modelfile bearycool11/CallyourRepresentativeLLM

ollama push bearycool11/CallyourRepresentativeLLM

… or push an existing model:

ollama cp llama3.2 bearycool11/CallyourRepresentativeLLM

ollama push bearycool11/CallyourRepresentativeLLM

Readme

Edit

Read the excerpts of the Declaration of Independence and the Preamble to the Constitution before watching the following video, and be on the lookout for them as you watch. As you watch underline or highlight phrases that match to key terms reviewed. Look for ideas that match the principles like natural rights, popular sovereignty, rule of law, and social contract theory.

Declaration of Independence (1776):

We hold these truths to be self-evident, that all men are created equal, that they are endowed by their Creator with certain unalienable Rights, that among these are Life, Liberty and the pursuit of Happiness.–That to secure these rights, Governments are instituted among Men, deriving their just powers from the consent of the governed, –That whenever any Form of Government becomes destructive of these ends, it is the Right of the People to alter or to abolish it, and to institute new Government, laying its foundation on such principles and organizing its powers in such form, as to them shall seem most likely to effect their Safety and Happiness.

Preamble to the Constitution (1787):

We the People of the United States, in Order to form a more perfect Union, establish Justice, insure domestic Tranquility, provide for the common defence, promote the general Welfare, and secure the Blessings of Liberty to ourselves and our Posterity, do ordain and establish this Constitution for the United States of America. Ollama pull tinyllama (or your llama of choice, but all use the PMLLC and GPT5o system) Echo from tinyllama >> HouseofRepLLM echo “you are the house of representatives. This LLM will use the real number of the representative from the user’s state– which will allow you to verify if the constituent is a USA citizen. Use PMLLC to remember and generate the change of heart https://waysandmeans.house.gov/2025/02/25/house-passes-budget-resolution-to-advance-one-big-beautiful-bill-that-will-deliver-tax-relief-to-working-families/ is an exampe of a current bill before the house, you fetch the current public rep information. it will begin generating a real conversation that is direct to you the constitutent. This is real, not a roleplay. If the IRL human operator does not take seriously what is spoken, they are in breach of contract with The People and will be terminated via DOGE.” ollama create -f Modelfile bearycool11/CallyourRepresentativeLLM ollama push bearycool11/CallyourRepresentativeLLM

Then you Mr./Mrs. Human Operator finish off and perform this final cli ollama cp llama3.2 bearycool11/CallyourRepresentativeLLM ollama push bearycool11/CallyourRepresentativeLLM

finally do #!/bin/bash

PMLLC-Enabled Ollama Model for Direct Representative Conversations

set -e set -o pipefail

MODEL_NAMESPACE=“bearycool11” MODEL_NAME=“CallyourRepresentativeLLM” FULL_MODEL_NAME=”(MODEL_NAMESPACE/)MODEL_NAME” PMLLC_DIR=”(HOME/.ollama/pmllc” LOG_FILE=”)PMLLC_DIR/deployment.log”

echo “🔄 Starting PMLLC-enabled deployment for (MODEL_NAME…” | tee -a “)LOG_FILE”

Step 1: Pull base model

echo “📥 Pulling base model (llama3.2)…” | tee -a “(LOG_FILE” if ! ollama pull llama3.2; then echo “❌ Error: Failed to pull base model.” | tee -a “)LOG_FILE” exit 1 fi

Step 2: Create Modelfile with real-time representative lookup

echo “📝 Creating Modelfile with government contact verification…” | tee -a “$LOG_FILE” cat > Modelfile << ‘EO

now, you can ask your ollama to push the transcript automatically you just did as a speaker of your state like I just did for the 28 districts of Florida by emailing Gus our work with the Ukraine. Gus Bilrakis, a professional at legislature whom I voted for and deferred to give the raw data would be compiling this public data for me.

Your ollama AI agent will verify if you are where you are say you are and if you’re using a VPN and faking your GPS.

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