👨‍💻 dev LLM dev ass

[fukurou]

Step 1: Choose Your LLM

Pick a model that suits your hardware and goals. Popular choices:

• LLaMA 3 (Meta)
• Mistral
• Gemma
• GPT4All

These models are available in GGUF format and optimized for local use.

---

Step 2: Install Ollama​

Ollama is a user-friendly tool to run LLMs locally.

curl -fsSL https://ollama.com/install.sh | sh


Then run your model:

ollama run llama3


This downloads and launches the model locally.

---

Step 3: Set Up Your Python Project​

Create a folder like waifu-chatbot, and inside it:

• main.py — your Python script
• requirements.txt — dependencies

In requirements.txt, add:

fastapi
uvicorn
requests


Install them:

pip install -r requirements.txt

---

Step 4: Build a Local API with FastAPI​

Here’s a basic main.py to send prompts to your waifu:

from fastapi import FastAPI, Request

import requests

app = FastAPI()

@app.post("/chat")
async def chat(request: Request):
    data = await request.json()
    prompt = data.get("prompt")
    response = requests.post("http://localhost:11434/api/generate", json={"model": "llama3", "prompt": prompt})
    return response.json()

Run it with:

uvicorn main:app --reload

---

Step 5: Customize Your Waifu​

You can fine-tune personality by:

• Prepending a system prompt like: "You are a cute anime waifu who loves cats and ramen."
• Using prompt engineering to shape responses
• Saving chat history for memory simulation

---

Step 6: Test It!​

Use curl or Postman to send a prompt:

curl -X POST http://localhost:8000/chat -H "Content-Type: application/json" -d '{"prompt": "Hi waifu!"}'

 

[fukurou]

Step 1: PyCharm Project Setup

1. Create a new PyCharm project (e.g., waifu_chatbot).
2. Add two files:
   • main.py
   • requirements.txt
3. In requirements.txt, add:
   fastapi
   requests
   
   PyCharm will prompt you to install these — go ahead and accept.

---

Step 2: Install Ollama (One-Time Setup)​

1. Download Ollama from ollama.com/download.
2. Install it and open the app.
3. Pull a model (e.g., LLaMA 3) by typing: ollama pull llama3
   
   You only need to do this once.

---

Step 3: Write Your Chatbot Code​

Paste this into main.py:

from fastapi import FastAPI, Request
import requests
import threading
import uvicorn

app = FastAPI()

@app.post("/chat")
async def chat(request: Request):
    data = await request.json()
    prompt = data.get("prompt")
    response = requests.post(
        "http://localhost:11434/api/generate",
        json={"model": "llama3", "prompt": prompt}
    )
    return response.json()

def run_server():
    uvicorn.run("main:app", host="127.0.0.1", port=8000, reload=True)

if __name__ == "__main__":
    threading.Thread(target=run_server).start()

This way, you just run main.py like any normal Python script — no need to type uvicorn in the terminal.

---

Step 4: Talk to Your Waifu​

You can test it with another Python script:

import requests

response = requests.post(
    "http://localhost:8000/chat",
    json={"prompt": "Hi waifu!"}
)
print(response.json())

Or use Postman/cURL if you prefer.

---

Want to add a cute anime-style web interface next? I can help you build one with Gradio — no command-line drama involved .

 

[fukurou]

Step 1: Install Ollama (One-Time Setup)

Ollama lets you run LLMs locally with ease.

1. Go to Ollama’s download page
2. Download the installer for your OS (Windows/macOS)
3. Install and open the Ollama app
4. In the Ollama terminal, pull a model: ollama pull llama3
   
   This downloads the LLaMA 3 model locally.

---

Step 2: Create Your PyCharm Project​

1. Open PyCharm → New Project → name it waifu_terminal_chat
2. Inside the project, create a file: chat.py
3. Create a requirements.txt file and add: requests
   
   
4. PyCharm will prompt you to install it — accept and let it install.

---

Step 3: Write Your Chat Script​

Paste this into chat.py:

import requests

def talk_to_waifu(prompt):
    response = requests.post(
        "http://localhost:11434/api/generate",
        json={"model": "llama3", "prompt": prompt}
    )
    return response.json()["response"]

print("Waifu: Hello darling~ Ready to chat? Type 'exit' to leave 💕")

while True:
    user_input = input("You: ")
    if user_input.lower() in ["exit", "quit"]:
        print("Waifu: Bye bye~ I'll miss you! 💖")
        break
    reply = talk_to_waifu(user_input)
    print(f"Waifu: {reply}")

---

Step 4: Run It in PyCharm Terminal​

1. Make sure Ollama is running in the background
2. In PyCharm, click the green play button or right-click chat.py → Run
3. Start chatting with your waifu directly in the terminal — no browser needed!

---

Step 5: Add Personality (Optional)​

To make her more anime-like, tweak the prompt like this:

json={"model": "llama3", "prompt": "You are a sweet anime waifu who loves cats and ramen. " + prompt}

You can also:

• Save chat history to simulate memory
• Add emojis and cute phrases
• Create multiple waifu personalities with different system prompts

​

• Anime-style avatars with image generation
• Memory using local file storage or SQLite