add main.py

main.py

@@ -1,33 +1,80 @@
-# Personal AI Fluency Plan
+#!/usr/bin/env python3
+"""Personal AI Fluency Plan
 
-## Overview
-This plan outlines the steps to develop AI fluency using the framework from the Ai Fluency course.
+This script demonstrates a simple personal AI fluency plan.
+It prints a structured plan with learning objectives, resources, and milestones.
+"""
 
-## Goals
-1. Understand core concepts of AI fluency.
-2. Apply LangChain and LangGraph to build simple agents.
-3. Create a personal learning roadmap.
+from datetime import datetime
 
-## Plan
-1. **Foundations** – Complete the course modules.
-2. **Hands‑on** – Build a small LangChain chain that answers a question.
-3. **LangGraph** – Create a graph that routes queries to different tools.
-4. **Reflection** – Document lessons learned and next steps.
+plan = {
+    "goal": "Become proficient in using AI tools for personal productivity and creative projects.",
+    "timeline": "6 months",
+    "milestones": [
+        {
+            "month": 1,
+            "focus": "Foundations of AI and language models",
+            "resources": [
+                "https://anthropic.skilljar.com/ai-fluency-framework-foundations",
+                "Coursera: AI For Everyone by Andrew Ng",
+            ],
+        },
+        {
+            "month": 2,
+            "focus": "Hands‑on with LangChain and OpenAI API",
+            "resources": [
+                "LangChain documentation",
+                "OpenAI API quickstart",
+            ],
+        },
+        {
+            "month": 3,
+            "focus": "Building simple chatbots and retrieval‑augmented generation",
+            "resources": [
+                "LangChain tutorials",
+                "Hugging Face Spaces",
+            ],
+        },
+        {
+            "month": 4,
+            "focus": "Advanced prompting and chain composition",
+            "resources": [
+                "Prompt Engineering Guide",
+                "LangChain advanced examples",
+            ],
+        },
+        {
+            "month": 5,
+            "focus": "Deploying AI solutions locally and in the cloud",
+            "resources": [
+                "Docker for AI",
+                "AWS SageMaker",
+            ],
+        },
+        {
+            "month": 6,
+            "focus": "Reflect, iterate, and plan next steps",
+            "resources": [
+                "Personal portfolio of AI projects",
+                "Community feedback and mentorship",
+            ],
+        },
+    ],
+    "evaluation": "Self‑assessment and peer review after each milestone.",
+}
 
-## Deliverable
-A written plan (this file) and a minimal working example in `main.py`.
 
-## Example Code
-```python
-from langchain import OpenAI, LLMChain
-from langchain.prompts import PromptTemplate
+def print_plan(p):
+    print("Personal AI Fluency Plan")
+    print("Goal:", p["goal"])
+    print("Timeline:", p["timeline"])
+    print("\nMilestones:")
+    for m in p["milestones"]:
+        print(f"  Month {m['month']}: {m['focus']}")
+        for r in m["resources"]:
+            print(f"    - {r}")
+    print("\nEvaluation:", p["evaluation"])
+    print("\nGenerated on", datetime.utcnow().isoformat(), "UTC")
 
-prompt = PromptTemplate(
-    input_variables=["question"],
-    template="Answer the following question concisely: {question}"
-)
-llm = OpenAI(temperature=0.7)
-chain = LLMChain(llm=llm, prompt=prompt)
-
-print(chain.run(question="What is AI fluency?"))
-```
+if __name__ == "__main__":
+    print_plan(plan)