|
|
| import gradio as gr |
| import torch |
| import requests |
| import json |
| import time |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| from peft import PeftModel |
|
|
| BASE_MODEL = "Qwen/Qwen2.5-0.5B" |
| PEFT_REPO = "coderofpears/gimkit-copilot" |
| SB_URL = "https://unztspukhwdzrllavnef.supabase.co" |
| SB_ANON = "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6InVuenRzcHVraHdkenJsbGF2bmVmIiwicm9sZSI6ImFub24iLCJpYXQiOjE3NzM2MDMzNTAsImV4cCI6MjA4OTE3OTM1MH0.eUWx9O9uX-BqI7oUikVvSAwljgt4Gw3Fl6hb-Xz_YWo" |
|
|
| ALL_TOOLS = [ |
| "gkc_create_build","gkc_undo_last_build","gkc_get_map_devices", |
| "gkc_look_around","gkc_capture_screenshot","gkc_remove_elements", |
| "gkc_vc_checkpoint","gkc_list_devices","gkc_search_terrain", |
| "gkc_search_props","gkc_get_device_info","gkc_skill_search", |
| "gkc_web_search","gkc_wiki_search", |
| ] |
|
|
| |
| print("Loading model...") |
| tokenizer = AutoTokenizer.from_pretrained(BASE_MODEL, trust_remote_code=True) |
| if tokenizer.pad_token is None: |
| tokenizer.pad_token = tokenizer.eos_token |
|
|
| _base = AutoModelForCausalLM.from_pretrained( |
| BASE_MODEL, |
| dtype=torch.float16 if torch.cuda.is_available() else torch.float32, |
| device_map="auto" if torch.cuda.is_available() else None, |
| trust_remote_code=True, |
| ) |
| model = PeftModel.from_pretrained(_base, PEFT_REPO) |
| model.eval() |
| DEVICE = next(model.parameters()).device |
| print("Model ready.") |
|
|
| |
| def base_h(): |
| return {"Content-Type": "application/json", "apikey": SB_ANON} |
|
|
| def auth_h(token): |
| return {**base_h(), "Authorization": "Bearer " + token} |
|
|
| def queue_tool(token, name, args, timeout=30): |
| r = requests.post( |
| SB_URL + "/rest/v1/tool_calls", |
| headers={**auth_h(token), "Prefer": "return=representation"}, |
| json={"name": name, "args": args, "status": "pending"}, |
| timeout=10, |
| ) |
| r.raise_for_status() |
| row_id = r.json()[0]["id"] |
| deadline = time.time() + timeout |
| while time.time() < deadline: |
| time.sleep(1.2) |
| pr = requests.get( |
| SB_URL + f"/rest/v1/tool_calls?id=eq.{row_id}&select=status,result", |
| headers=auth_h(token), timeout=10, |
| ) |
| pr.raise_for_status() |
| rows = pr.json() |
| if rows and rows[0]["status"] in ("complete", "error"): |
| return rows[0]["result"], rows[0]["status"] |
| return {"error": "Timed out — is the Gimloader plugin open and connected?"}, "error" |
|
|
| |
| SYSTEM = ( |
| "You are Gimkit Copilot, an AI that helps build Gimkit Creative maps. " |
| "Call tools by responding with JSON: {\"tool\":\"<name>\",\"args\":{...}} " |
| "Otherwise reply normally. Tools: " + ", ".join(ALL_TOOLS) |
| ) |
|
|
| def run_model(history, user_msg): |
| prompt = SYSTEM + "\n\n" |
| for u, a in history: |
| prompt += f"User: {u}\nAssistant: {a}\n" |
| prompt += f"User: {user_msg}\nAssistant:" |
| inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=1024).to(DEVICE) |
| with torch.no_grad(): |
| out = model.generate( |
| **inputs, |
| max_new_tokens=256, |
| do_sample=True, |
| temperature=0.7, |
| top_p=0.9, |
| pad_token_id=tokenizer.eos_token_id, |
| eos_token_id=tokenizer.eos_token_id, |
| ) |
| new_tokens = out[0][inputs["input_ids"].shape[1]:] |
| return tokenizer.decode(new_tokens, skip_special_tokens=True).strip() |
|
|
| def try_parse_tool(text): |
| start, end = text.find("{"), text.rfind("}") + 1 |
| if start == -1 or end == 0: |
| return None |
| try: |
| obj = json.loads(text[start:end]) |
| if "tool" in obj and obj["tool"] in ALL_TOOLS: |
| return obj["tool"], obj.get("args", {}) |
| except Exception: |
| pass |
| return None |
|
|
| def respond(message, history, token): |
| if not token or not token.strip(): |
| history.append((message, "❌ Enter your GimkitCopilot token in the sidebar first.")) |
| return history, "" |
| model_out = run_model(history, message) |
| tool_call = try_parse_tool(model_out) |
| if tool_call: |
| name, args = tool_call |
| history.append((message, f"🔧 Calling `{name}`...")) |
| result, status = queue_tool(token.strip(), name, args) |
| icon = "✅" if status == "complete" else "❌" |
| result_str = json.dumps(result, indent=2) if isinstance(result, dict) else str(result) |
| followup = run_model( |
| history + [(message, model_out)], |
| f"Tool result for {name}: {result_str}. Summarise what happened." |
| ) |
| history[-1] = (message, f"🔧 `{name}`\n\n{icon} ```\n{result_str}\n```\n\n{followup}") |
| else: |
| history.append((message, model_out)) |
| return history, "" |
|
|
| |
| CSS = """ |
| @import url('https://fonts.googleapis.com/css2?family=Space+Mono:wght@400;700&family=DM+Sans:wght@300;400;600&display=swap'); |
| :root { |
| --bg:#070b07; --surface:#0c120c; --border:#162016; |
| --green:#4CAF50; --green-dim:#1a3a1a; --glow:rgba(76,175,80,.12); |
| --text:#cce0cc; --muted:#4a664a; --accent:#a3e635; |
| } |
| body, .gradio-container { background:var(--bg)!important; font-family:'DM Sans',sans-serif; color:var(--text); } |
| #logo { font-family:'Space Mono',monospace; color:var(--green); font-size:20px; font-weight:700; padding:16px 0 2px; } |
| #sub { color:var(--muted); font-size:11px; font-family:'Space Mono',monospace; margin-bottom:20px; } |
| .token-box textarea { |
| background:#040804!important; border:1px solid var(--border)!important; |
| color:var(--accent)!important; font-family:'Space Mono',monospace!important; font-size:11px!important; |
| border-radius:8px!important; |
| } |
| .token-box textarea:focus { border-color:var(--green)!important; box-shadow:0 0 0 2px var(--glow)!important; } |
| #chatbot { background:var(--bg)!important; border-color:var(--border)!important; } |
| .send-btn button { |
| background:var(--green-dim)!important; border:1px solid var(--green)!important; |
| color:var(--green)!important; font-family:'Space Mono',monospace!important; font-weight:700!important; |
| } |
| .send-btn button:hover { background:#223a22!important; } |
| .clear-btn button { |
| background:transparent!important; border:1px solid var(--border)!important; |
| color:var(--muted)!important; font-size:11px!important; |
| } |
| .msg-box textarea { |
| background:var(--surface)!important; border:1px solid var(--border)!important; |
| color:var(--text)!important; font-family:'DM Sans',sans-serif!important; border-radius:8px!important; |
| } |
| .msg-box textarea:focus { border-color:var(--green)!important; } |
| """ |
|
|
| with gr.Blocks(title="Gimkit Copilot") as demo: |
| token_state = gr.State("") |
|
|
| with gr.Row(): |
| |
| with gr.Column(scale=1, min_width=220): |
| gr.HTML('<div id="logo">◆ Gimkit<br>Copilot</div>') |
| gr.HTML('<div id="sub">Qwen2.5-0.5B + MCP</div>') |
| token_box = gr.Textbox( |
| label="GimkitCopilot Token", |
| placeholder="Paste Bearer token…", |
| lines=4, |
| type="password", |
| elem_classes=["token-box"], |
| ) |
| gr.HTML( |
| '''<div style="font-size:10px;color:#2a4a2a;line-height:1.6;margin-top:6px;"> |
| Get token from the<br>Gimloader plugin:<br> |
| <b style="color:#3a6a3a">Shift+X → Account<br>→ Copy Token</b><br><br> |
| Plugin must show<br><span style="color:#4CAF50">● Connected</span> for<br>map tools to work. |
| </div>''' |
| ) |
| clear_btn = gr.Button("Clear chat", size="sm", elem_classes=["clear-btn"]) |
|
|
| |
| with gr.Column(scale=4): |
| chatbot = gr.Chatbot( |
| elem_id="chatbot", |
| height=520, |
| show_label=False, |
| placeholder="<div style=\'text-align:center;color:#2a4a2a;font-family:Space Mono,monospace;margin-top:40px\'>Sign in via token and start building →</div>", |
| ) |
| with gr.Row(): |
| msg_box = gr.Textbox( |
| placeholder="Ask me to build something, inspect your map, search the wiki…", |
| show_label=False, |
| lines=2, |
| scale=8, |
| elem_classes=["msg-box"], |
| ) |
| send_btn = gr.Button("Send ▶", variant="primary", scale=1, elem_classes=["send-btn"]) |
|
|
| |
| token_box.change(lambda t: t, inputs=[token_box], outputs=[token_state]) |
|
|
| send_btn.click(respond, inputs=[msg_box, chatbot, token_state], outputs=[chatbot, msg_box]) |
| msg_box.submit(respond, inputs=[msg_box, chatbot, token_state], outputs=[chatbot, msg_box]) |
| clear_btn.click(lambda: ([], ""), outputs=[chatbot, msg_box]) |
|
|
| demo.launch(css=CSS) |
|
|
