Update app.py

app.py

@@ -1,53 +1,282 @@
-"""
-llama-cpp-python bootstrap — MUST import before gradio or anything else.
-
-2026-07-27: simplified after the great wheel hunt.
-- PyPI = source-only (compiles 20+ min — the "runs and runs" bug).
-- abetlen CUDA indexes = abandoned (newest cu121 wheel is v0.2.59). Do NOT attempt.
-- abetlen CPU index = current prebuilt wheels. That is the only fast path.
-GPU speed returns via the Level-2 llama-server route (official llama.cpp CUDA
-binaries + MTP flags) — see the Level 2 spec, not this file.
-"""
-
-from __future__ import annotations
+import llama_bootstrap  # noqa: F401 — MUST be first
 
+import gradio as gr
 import os
-import subprocess
+import json
 import sys
+import threading
+from pathlib import Path
+from typing import Optional
+
+MODEL_REPO = os.environ.get("MODEL_REPO", "DavidAU/Qwen3.6-27B-Heretic-Uncensored-FINETUNE-NEO-CODE-Di-IMatrix-MAX-GGUF")
+MODEL_FILE = os.environ.get("MODEL_FILE", "Qwen3.6-27B-NEO-CODE-HERE-2T-OT-Q4_K_M.gguf")
+N_CTX = int(os.environ.get("N_CTX", "16384"))
+MAX_TOKENS = int(os.environ.get("MAX_TOKENS", "4096"))
+N_GPU = int(os.environ.get("N_GPU_LAYERS", os.environ.get("DAVIDAU_N_GPU_LAYERS", "0")))
+
+SYSTEM_PROMPT = """You are codeMax, an uncensored 27B coding assistant. You excel at:
+- Writing production code in Python, TypeScript, JavaScript, Rust, Go, C/C++, SQL, shell
+- Debugging, refactoring, reviewing complex codebases
+- Explaining algorithms, architecture, system design
+- Reading shared files and answering about them
+Rules: put code in ```language blocks. Be precise and thorough."""
+
+CSS = """footer { display: none !important; }"""
+
+_llm = None
+_model_path: Optional[str] = None
+_load_lock = threading.Lock()  # one load, ever — HF imports app.py twice; this makes that harmless
+
+def _download():
+    global _model_path
+    if _model_path is not None:
+        return _model_path
+    from huggingface_hub import hf_hub_download
+    print(f"[MODEL] Downloading {MODEL_FILE}...", file=sys.stderr, flush=True)
+    _model_path = hf_hub_download(repo_id=MODEL_REPO, filename=MODEL_FILE)
+    print(f"[MODEL] Cached -> {_model_path}", file=sys.stderr, flush=True)
+    return _model_path
 
-CPU_WHEEL_INDEX = "https://abetlen.github.io/llama-cpp-python/whl/cpu"
+def _load():
+    """LAZY: nothing loads at import. First chat message triggers the one and only load."""
+    global _llm
+    if _llm is not None:
+        return _llm
+    with _load_lock:
+        if _llm is not None:
+            return _llm
+        from llama_cpp import Llama
+        path = _download()
+        print(f"[MODEL] Loading (n_gpu_layers={N_GPU}, n_ctx={N_CTX})...", file=sys.stderr, flush=True)
+        _llm = Llama(
+            model_path=path,
+            n_ctx=N_CTX,
+            n_gpu_layers=N_GPU,
+            chat_format="chatml",
+            verbose=False,
+            seed=-1,
+        )
+        print("[MODEL] Ready.", file=sys.stderr, flush=True)
+    return _llm
 
+def _read_text(path, enc="utf-8"):
+    for e in [enc, "utf-8-sig", "latin-1", "cp1252", "utf-16"]:
+        try:
+            with open(path, "r", encoding=e) as f:
+                return f.read()
+        except UnicodeError:
+            continue
+    with open(path, "r", encoding="utf-8", errors="replace") as f:
+        return f.read()
 
-def _pip(args: list) -> None:
-    cmd = [sys.executable, "-m", "pip", *args]
-    print(f"[LLAMA] $ {' '.join(cmd)}", flush=True)
-    env = os.environ.copy()
-    env["PIP_DISABLE_PIP_VERSION_CHECK"] = "1"
-    env["PIP_ROOT_USER_ACTION"] = "ignore"
-    subprocess.check_call(cmd, env=env)
+def parse_file(file_path, file_name):
+    suffix = Path(file_name).suffix.lower()
+    name = Path(file_name).name
 
+    if suffix in (
+        ".txt", ".md", ".py", ".ts", ".tsx", ".js", ".jsx", ".mjs",
+        ".css", ".scss", ".less", ".html", ".htm", ".xml", ".svg",
+        ".yaml", ".yml", ".toml", ".ini", ".cfg", ".conf",
+        ".sh", ".bash", ".zsh", ".fish", ".ps1", ".bat",
+        ".sql", ".prisma",
+        ".c", ".cpp", ".cc", ".cxx", ".h", ".hpp", ".hh",
+        ".java", ".kt", ".kts", ".scala", ".groovy",
+        ".go", ".rs", ".rb", ".php", ".pl", ".pm",
+        ".swift", ".r", ".lua", ".zig", ".nim", ".dart",
+        ".env", ".gitignore", ".editorconfig",
+        ".tf", ".tfvars", ".hcl", ".vue", ".svelte", ".astro",
+    ):
+        content = _read_text(file_path)
+        lang = suffix.lstrip(".")
+        if suffix == ".md": lang = "markdown"
+        elif suffix in (".yml",): lang = "yaml"
+        elif suffix in (".tf", ".tfvars"): lang = "hcl"
+        elif suffix in (".htm",): lang = "html"
+        return f"### `{name}`\n```{lang}\n{content}\n```\n\n---\n"
 
-def try_import_llama():
-    import llama_cpp  # noqa: F401
-    return llama_cpp
+    if suffix == ".json":
+        content = _read_text(file_path)
+        try:
+            parsed = json.loads(content)
+            content = json.dumps(parsed, indent=2, ensure_ascii=False)
+        except Exception:
+            pass
+        return f"### `{name}`\n```json\n{content}\n```\n\n---\n"
 
+    if suffix == ".csv":
+        import csv, io
+        content = _read_text(file_path)
+        rows = list(csv.reader(io.StringIO(content)))
+        if len(rows) > 51:
+            rows = rows[:50] + [[f"... {len(rows) - 50} rows truncated"]]
+        widths = [max(len(str(c)) for c in col) for col in zip(*rows)]
+        sep = "|-" + "-|-".join("-" * x for x in widths) + "-|"
+        table = "\n".join(
+            "| " + " | ".join(str(c).ljust(widths[i]) for i, c in enumerate(row)) + " |"
+            for row in rows
+        )
+        table = table.split("\n", 1)
+        table.insert(1, sep)
+        return f"### `{name}`\n" + "\n".join(table) + "\n\n---\n"
 
-def bootstrap_llama_cpp():
+    if suffix == ".docx":
+        try:
+            import docx
+            doc = docx.Document(file_path)
+            text = "\n\n".join(p.text for p in doc.paragraphs if p.text.strip())
+            return f"### `{name}`\n{text}\n\n---\n"
+        except Exception as e:
+            return f"### `{name}` (DOCX error: {e})\n\n---\n"
+
+    if suffix == ".pdf":
+        try:
+            import pdfplumber
+            with pdfplumber.open(file_path) as pdf:
+                text = "\n\n".join(page.extract_text() or "" for page in pdf.pages)
+            return f"### `{name}`\n{text}\n\n---\n"
+        except Exception as e:
+            return f"### `{name}` (PDF error: {e})\n\n---\n"
+
+    try:
+        content = _read_text(file_path)
+        return f"### `{name}`\n```\n{content[:10000]}\n```\n\n---\n"
+    except Exception as e:
+        return f"### `{name}` (could not read: {e})\n\n---\n"
+
+def parse_all_files(files):
+    if not files:
+        return ""
+    parts = []
+    for f in files:
+        if isinstance(f, dict):
+            path = f.get("path") or f.get("name")
+            name = f.get("orig_name") or f.get("name", "unknown")
+        elif hasattr(f, "name"):
+            path = f.name
+            name = getattr(f, "orig_name", Path(path).name)
+        else:
+            path = str(f)
+            name = Path(path).name
+        try:
+            parts.append(parse_file(path, name))
+        except Exception as e:
+            parts.append(f"### `{name}`\nParse error: {e}\n\n---\n")
+    return "\n".join(parts)
+
+def respond(message, history, uploaded_files):
+    if _llm is None:
+        yield history + [
+            {"role": "user", "content": message},
+            {"role": "assistant", "content": "⏳ **First run:** downloading + loading the 27B brain — a few minutes, one time only. I'm on it…"},
+        ]
     try:
-        mod = try_import_llama()
-        print("[LLAMA] Ready (prebuilt wheel already installed)", flush=True)
-    except ImportError:
-        print("[LLAMA] Not installed — installing CPU wheel (fast path)...", flush=True)
-        _pip([
-            "install", "--no-cache-dir", "llama-cpp-python==0.3.34",
-            "--extra-index-url", CPU_WHEEL_INDEX,
-        ])
-        mod = try_import_llama()
-
-    # CPU wheel => CPU inference. Be explicit so nothing pretends otherwise.
-    os.environ.setdefault("DAVIDAU_N_GPU_LAYERS", "0")
-    print("[LLAMA] CPU mode (n_gpu_layers=0) — GPU speed is the Level-2 llama-server job", flush=True)
-    return mod
-
-
-bootstrap_llama_cpp()
+        llm = _load()
+    except Exception as e:
+        yield history + [
+            {"role": "user", "content": message},
+            {"role": "assistant", "content": f"⚠️ Model failed to load: `{type(e).__name__}: {e}`\n\nMost likely: RAM too small for this quant (Q4_K_M needs a 32GB space) — or the download hiccuped, just send again."},
+        ]
+        return
+
+    file_context = parse_all_files(uploaded_files)
+    messages = [{"role": "system", "content": SYSTEM_PROMPT}]
+
+    if file_context:
+        messages.append({"role": "user", "content": "[Uploaded files]\n\n" + file_context})
+        messages.append({"role": "assistant", "content": "Got it! I’ve read through all the uploaded files."})
+
+    for entry in history:
+        role = entry.get("role", "user")
+        content = entry.get("content", "")
+        if isinstance(content, str) and content:
+            messages.append({"role": role, "content": content})
+
+    messages.append({"role": "user", "content": message})
+
+    stream = llm.create_chat_completion(
+        messages=messages,
+        temperature=0.6,
+        top_p=0.8,
+        top_k=20,
+        max_tokens=MAX_TOKENS,
+        stream=True,
+    )
+
+    partial = ""
+    for chunk in stream:
+        if chunk.get("choices"):
+            delta = chunk["choices"][0].get("delta", {})
+            content = delta.get("content", "")
+            if content:
+                partial += content
+        yield history + [
+            {"role": "user", "content": message},
+            {"role": "assistant", "content": partial},
+        ]
+
+def create_demo():
+    with gr.Blocks(title="codeMax — Qwen 3.6 27B Coder", css=CSS) as demo:
+        gr.Markdown(
+            "# codeMax\n"
+            "**Qwen 3.6 27B · Uncensored · Code-optimized · Dedicated GPU**\n"
+            "Drop code, docs, JSON, CSVs — chat with a 27B coding LLM."
+        )
+
+        with gr.Row(equal_height=True):
+            with gr.Column(scale=3):
+                chatbot = gr.Chatbot(
+                    label="Chat",
+                    height=580,
+                    type="messages",
+                    avatar_images=(None, "https://huggingface.co/front/assets/huggingface_logo-noborder.svg"),
+                )
+                with gr.Row():
+                    msg = gr.Textbox(placeholder="Ask about code, share files, or chat...", scale=8, show_label=False, container=False)
+                    send = gr.Button(">", scale=1, variant="primary", min_width=48)
+                clear_btn = gr.Button("Clear", size="sm")
+
+            with gr.Column(scale=1):
+                gr.Markdown("### Drop Files")
+                files = gr.File(
+                    file_count="multiple",
+                    label="Code, docs, data...",
+                    file_types=[
+                        ".py", ".ts", ".tsx", ".js", ".jsx", ".json",
+                        ".md", ".txt", ".csv", ".yaml", ".yml", ".toml",
+                        ".html", ".css", ".xml", ".sql", ".sh", ".go",
+                        ".rs", ".rb", ".java", ".c", ".cpp", ".h",
+                        ".docx", ".pdf", ".env", ".cfg", ".ini",
+                    ],
+                )
+                uploaded_info = gr.Markdown("_No files uploaded._")
+
+        def update_info(uploaded):
+            if not uploaded:
+                return "_No files uploaded._"
+            names = []
+            for f in uploaded:
+                if isinstance(f, dict):
+                    names.append(f.get("orig_name", "?"))
+                else:
+                    names.append(getattr(f, "orig_name", Path(str(f)).name))
+            return "**Uploaded:**\n" + "\n".join(f"- `{n}`" for n in names)
+
+        def stream_response(message, history, current_files):
+            for h in respond(message, history, current_files):
+                yield h
+
+        msg.submit(stream_response, [msg, chatbot, files], [chatbot]).then(lambda: "", None, [msg])
+        send.click(stream_response, [msg, chatbot, files], [chatbot]).then(lambda: "", None, [msg])
+        clear_btn.click(lambda: [], None, chatbot, queue=False)
+        files.change(update_info, files, uploaded_info)
+
+    return demo
+
+if __name__ == "__main__":
+    demo = create_demo()
+    demo.queue(default_concurrency_limit=1, max_size=4)
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        ssr_mode=False,
+    )