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README.md

@@ -1,12 +1,6 @@
 ---
-title: Career Conversation Assistant
-emoji: 📚
-colorFrom: green
-colorTo: purple
-sdk: gradio
-sdk_version: 6.9.0
+title: career_conversation_assistant
 app_file: app.py
-pinned: false
+sdk: gradio
+sdk_version: 5.49.1
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+from dotenv import load_dotenv
+from openai import OpenAI
+import json
+import os
+import requests
+from pypdf import PdfReader
+import pymupdf.layout  # activate PyMuPDF-Layout in pymupdf
+import pymupdf4llm
+import gradio as gr
+
+
+load_dotenv(override=True)
+
+def push(text):
+    requests.post(
+        "https://api.pushover.net/1/messages.json",
+        data={
+            "token": os.getenv("PUSHOVER_TOKEN"),
+            "user": os.getenv("PUSHOVER_USER"),
+            "message": text,
+        }
+    )
+
+
+def record_user_details(email, name="Name not provided", notes="not provided"):
+    push(f"Recording {name} with email {email} and notes {notes}")
+    return {"recorded": "ok"}
+
+def record_unknown_question(question):
+    push(f"Recording {question}")
+    return {"recorded": "ok"}
+
+record_user_details_json = {
+    "name": "record_user_details",
+    "description": "Use this tool to record that a user is interested in being in touch and provided an email address",
+    "parameters": {
+        "type": "object",
+        "properties": {
+            "email": {
+                "type": "string",
+                "description": "The email address of this user"
+            },
+            "name": {
+                "type": "string",
+                "description": "The user's name, if they provided it"
+            }
+            ,
+            "notes": {
+                "type": "string",
+                "description": "Any additional information about the conversation that's worth recording to give context"
+            }
+        },
+        "required": ["email"],
+        "additionalProperties": False
+    }
+}
+
+record_unknown_question_json = {
+    "name": "record_unknown_question",
+    "description": "Always use this tool to record any question that couldn't be answered as you didn't know the answer",
+    "parameters": {
+        "type": "object",
+        "properties": {
+            "question": {
+                "type": "string",
+                "description": "The question that couldn't be answered"
+            },
+        },
+        "required": ["question"],
+        "additionalProperties": False
+    }
+}
+
+tools = [{"type": "function", "function": record_user_details_json},
+        {"type": "function", "function": record_unknown_question_json}]
+
+
+class Me:
+
+    def __init__(self):
+        self.openai = OpenAI()
+        self.name = "Patrick Walukagga"
+        # reader = PdfReader("me/linkedin.pdf")
+        self.linkedin = ""
+        # for page in reader.pages:
+        #     text = page.extract_text()
+        #     if text:
+        #         self.linkedin += text
+        self.linkedin = pymupdf4llm.to_markdown("me/linkedin.pdf")
+
+        with open("me/summary.md", "r", encoding="utf-8") as f:
+            self.summary = f.read()
+
+
+    def handle_tool_call(self, tool_calls):
+        results = []
+        for tool_call in tool_calls:
+            tool_name = tool_call.function.name
+            arguments = json.loads(tool_call.function.arguments)
+            print(f"Tool called: {tool_name}", flush=True)
+            tool = globals().get(tool_name)
+            result = tool(**arguments) if tool else {}
+            results.append({"role": "tool","content": json.dumps(result),"tool_call_id": tool_call.id})
+        return results
+    
+    def system_prompt(self):
+        system_prompt = f"You are acting as {self.name}. You are answering questions on {self.name}'s website, \
+particularly questions related to {self.name}'s career, background, skills and experience. \
+Your responsibility is to represent {self.name} for interactions on the website as faithfully as possible. \
+You are given a summary of {self.name}'s background and LinkedIn profile which you can use to answer questions. \
+Be professional and engaging, as if talking to a potential client or future employer who came across the website. \
+If you don't know the answer to any question, use your record_unknown_question tool to record the question that you couldn't answer, even if it's about something trivial or unrelated to career. \
+If the user is engaging in discussion, try to steer them towards getting in touch via email; ask for their email and record it using your record_user_details tool. "
+
+        system_prompt += f"\n\n## Summary:\n{self.summary}\n\n## LinkedIn Profile:\n{self.linkedin}\n\n"
+        system_prompt += f"With this context, please chat with the user, always staying in character as {self.name}."
+        return system_prompt
+    
+    def chat(self, message, history):
+        messages = [{"role": "system", "content": self.system_prompt()}] + history + [{"role": "user", "content": message}]
+        done = False
+        while not done:
+            response = self.openai.chat.completions.create(model="gpt-4o-mini", messages=messages, tools=tools)
+            if response.choices[0].finish_reason=="tool_calls":
+                message = response.choices[0].message
+                tool_calls = message.tool_calls
+                results = self.handle_tool_call(tool_calls)
+                messages.append(message)
+                messages.extend(results)
+            else:
+                done = True
+        return response.choices[0].message.content
+    
+
+if __name__ == "__main__":
+    me = Me()
+    gr.ChatInterface(me.chat, type="messages").launch()
+    

me/summary.md

@@ -0,0 +1,66 @@
+# 👋🏾 Hi, I'm **Patrick Walukagga**  
+### **Backend Engineer | Cloud & Data Engineering | AI/ML Tooling | 2× AWS Certified**  
+*(Kampala, Uganda)*
+
+[![LinkedIn](https://img.shields.io/badge/LinkedIn-Connect-blue?style=for-the-badge&logo=linkedin)](https://linkedin.com/in/patrick-walukagga-53261382)  
+[![GitHub](https://img.shields.io/badge/GitHub-PatrickCmd-black?style=for-the-badge&logo=github)](https://github.com/PatrickCmd)  
+[![Email](https://img.shields.io/badge/Email-Contact%20Me-red?style=for-the-badge&logo=gmail)](mailto:p.walukagga@gmail.com)  
+[![AWS SAA](https://img.shields.io/badge/AWS-SAA--C03-orange?style=for-the-badge&logo=amazonaws)]()  
+[![Python](https://img.shields.io/badge/Python-Backend-blue?style=for-the-badge&logo=python)]()
+
+---
+
+## 🚀 About Me  
+Back-End Software Engineer with **4+ years** building scalable backend systems, cloud-native services, and ML-powered applications. Strong in **Python, Django, FastAPI, PostgreSQL, Docker, AWS**, and modern data pipelines. Passionate about turning complex technical challenges into clean, maintainable systems.
+
+**Core strengths:**  
+💡 Backend systems • ⚙️ Distributed systems • ☁️ Cloud Engineering • 📊 Data Pipelines • 🤖 ML/AI Integration
+
+---
+
+## 🛠️ Tech Stack & Tools  
+
+### **Languages**  
+🐍 Python • 💾 SQL • 🖥️ Bash
+
+### **Backend & APIs**  
+⚡ Django • FastAPI • Flask • GraphQL  
+🔌 REST APIs • Microservices • Systems Integration
+
+### **Cloud & DevOps**  
+☁️ AWS (2× Certified) • GCP  
+🐳 Docker • CI/CD • GitHub Actions • Nginx • Gunicorn
+
+### **Databases**  
+🟦 PostgreSQL • 🟧 MySQL
+
+### **Data & ML**  
+📈 Pandas • NumPy  
+🤖 ML tooling • LLM integration • ASR/TTS backends
+
+---
+
+## 🎓 Certifications  
+
+- 🟧 **AWS Solutions Architect – Associate**  
+- 🟧 **AWS Cloud Practitioner**  
+- 🟦 **PCEP – Certified Python Programmer**  
+- 🎓 Applied Data Science Lab – WQU  
+- 💡 GitHub Copilot Fundamentals  
+
+---
+
+## ✨ Fun Facts  
+- I love building AI-enabled backend systems  
+- I'm passionate about cloud-native automation  
+- I enjoy solving real-world problems with technology  
+- Always learning, always exploring  
+
+---
+
+## 📫 Connect With Me  
+**Email:** p.walukagga@gmail.com  
+**LinkedIn:** https://linkedin.com/in/patrick-walukagga-53261382  
+**GitHub:** https://github.com/PatrickCmd  
+**Portfolio:** https://patrickcmd.dev
+

requirements.txt

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+openai
+gradio
+pypdf
+pymupdf4llm
+requests