কনটেন্টে যান

Talk to LM Studio

Learn how to connect your scripts to LM Studio's local LLM server.

Connection Architecture

flowchart TD
    A[Python Script] -->|POST /v1/chat/completions| B[LM Studio API]
    B --> C{Qwen Model<br/>Loaded?}
    C -->|Yes| D[Process Request]
    C -->|No| E[Load Model]
    E --> D
    D --> F[Return JSON]

    style A fill:#e3f2fd
    style F fill:#c8e6c9

API Request Structure

sequenceDiagram
    participant S as Script
    participant A as API

    S->>A: POST /v1/chat/completions
    Note over S: {<br/>"model": "qwen",<br/>"messages": [<br/>{"role": "user",<br/>"content": "..."}<br/>]<br/>}
    A-->>S: {<br/>"choices": [<br/>{"message": {...}}<br/>]<br/>}

Setup Checklist

Step Task Status
1 Download LM Studio ⬜
2 Download Qwen 2.5 1.5B ⬜
3 Load model in UI ⬜
4 Click "Start Server" ⬜
5 Note port (default 1234) ⬜
6 Run script ⬜

Connection Code

import requests

url = "http://localhost:1234/v1/chat/completions"
headers = {"Content-Type": "application/json"}
payload = {
    "model": "qwen2.5-1.5b",
    "messages": [
        {"role": "user", "content": "Hello!"}
    ]
}

response = requests.post(url, json=payload, headers=headers)
print(response.json()["choices"][0]["message"]["content"])

Common Issues

flowchart TD
    A[Connection Error] --> B{Server Running?}
    B -->|No| C[Start LM Studio server]
    B -->|Yes| D{Correct Port?}
    D -->|No| E[Check port in script]
    D -->|Yes| F{Cors enabled?}
    F -->|No| G[Enable CORS in settings]
    F -->|Yes| H[Firewall issue]

    style C fill:#c8e6c9
    style E fill:#c8e6c9
    style G fill:#c8e6c9

Configuration Options

Setting Default Description
Port 1234 Server port
Model Name varies Model identifier
Max Tokens 512 Response length
Temperature 0.7 Randomness

Next Steps