Upload 4 files

Dockerfile

@@ -0,0 +1,52 @@
+FROM python:3.10-slim
+
+# ── HuggingFace يحتاج user بـ UID=1000
+RUN useradd -m -u 1000 user
+
+ENV HOME=/home/user \
+    PATH=/home/user/.local/bin:$PATH \
+    PYTHONUNBUFFERED=1 \
+    PLAYWRIGHT_BROWSERS_PATH=/home/user/.cache/ms-playwright
+
+WORKDIR /home/user/app
+
+# ── System libs (نفس الأصلي)
+RUN apt-get update && apt-get install -y \
+    wget gnupg ca-certificates curl \
+    libnss3 libnspr4 \
+    libatk1.0-0 libatk-bridge2.0-0 \
+    libcups2 libdrm2 libxkbcommon0 \
+    libxcomposite1 libxdamage1 libxext6 \
+    libxfixes3 libxrandr2 libgbm1 \
+    libpango-1.0-0 libcairo2 libasound2 \
+    && rm -rf /var/lib/apt/lists/*
+
+# ── Install Python packages
+COPY --chown=user requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# ── Install Google Chrome (عشان channel="chrome" يشتغل)
+RUN mkdir -p /etc/apt/keyrings \
+    && wget -q -O - https://dl-ssl.google.com/linux/linux_signing_key.pub \
+       | gpg --dearmor -o /etc/apt/keyrings/google-chrome.gpg \
+    && echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/google-chrome.gpg] \
+       http://dl.google.com/linux/chrome/deb/ stable main" \
+       > /etc/apt/sources.list.d/google-chrome.list \
+    && apt-get update && apt-get install -y google-chrome-stable \
+    && rm -rf /var/lib/apt/lists/*
+
+# ── Install Playwright Chromium (fallback)
+RUN playwright install chromium
+
+# ── Copy project files
+COPY --chown=user . .
+
+USER user
+
+# ── HuggingFace port = 7860
+EXPOSE 7860
+
+HEALTHCHECK --interval=30s --timeout=15s --start-period=120s --retries=3 \
+    CMD curl -f http://localhost:7860/health || exit 1
+
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]

README.md

@@ -1,10 +1,13 @@
 ---
-title: Api
-emoji: 🏆
-colorFrom: indigo
-colorTo: yellow
+title: MSE AI API
+emoji: 🤖
+colorFrom: blue
+colorTo: indigo
 sdk: docker
+app_port: 7860
 pinned: false
+license: mit
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# MSE AI API
+OpenAI-compatible API via FastAPI + Playwright + Chrome.

main.py

@@ -0,0 +1,422 @@
+import os
+import uuid
+import time
+import asyncio
+import threading
+import json
+import re
+from typing import Optional
+from fastapi import FastAPI, Header, HTTPException, Request
+from fastapi.responses import JSONResponse
+
+
+API_SECRET_KEY = os.getenv("API_SECRET_KEY", "change-secret-key-2026")
+
+
+class AsyncBrowserThread(threading.Thread):
+    def __init__(self):
+        super().__init__(daemon=True)
+        self.loop = asyncio.new_event_loop()
+        self.ready_event = threading.Event()
+        self.browser = None
+        self.playwright = None
+
+    def run(self):
+        asyncio.set_event_loop(self.loop)
+        self.loop.run_until_complete(self._start_browser())
+        self.ready_event.set()
+        print("[LITE-SERVER] Browser is ready!")
+        self.loop.run_forever()
+
+    async def _start_browser(self):
+        from playwright.async_api import async_playwright
+        print("[LITE-SERVER] Starting Chrome...")
+        self.playwright = await async_playwright().start()
+        self.browser = await self.playwright.chromium.launch(
+            headless=True,
+            channel="chrome",
+            args=[
+                '--disable-blink-features=AutomationControlled',
+                '--no-sandbox',
+                '--disable-gpu',
+                '--disable-dev-shm-usage',
+                '--disable-setuid-sandbox',
+                '--single-process',
+                '--no-zygote',
+            ]
+        )
+        print("[LITE-SERVER] Chrome launched!")
+
+    async def _talk_to_chatgpt(self, prompt: str):
+        context = await self.browser.new_context(
+            user_agent="Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36",
+            viewport={'width': 1920, 'height': 1080}
+        )
+
+        await context.add_init_script("Object.defineProperty(navigator, 'webdriver', {get: () => undefined})")
+
+        page = await context.new_page()
+
+        try:
+            page.set_default_timeout(120000)
+            await page.goto("https://chatgpt.com/", wait_until="domcontentloaded")
+
+            await page.wait_for_selector('#prompt-textarea', timeout=60000)
+            await page.fill('#prompt-textarea', prompt)
+            await asyncio.sleep(0.5)
+            await page.press('#prompt-textarea', 'Enter')
+
+            await page.wait_for_selector('[data-message-author-role="assistant"]', timeout=120000)
+
+            last_text = ""
+            unchanged_count = 0
+            while unchanged_count < 4:
+                messages = await page.query_selector_all('[data-message-author-role="assistant"]')
+                if messages:
+                    current_text = await messages[-1].inner_text()
+                    if current_text == last_text and current_text.strip() != "":
+                        unchanged_count += 1
+                    else:
+                        last_text = current_text
+                        unchanged_count = 0
+                await asyncio.sleep(0.5)
+
+            return last_text.strip()
+
+        except Exception as e:
+            print(f"[LITE-SERVER] Error: {e}")
+            raise e
+        finally:
+            await page.close()
+            await context.close()
+
+    def process_request(self, prompt: str):
+        if not self.ready_event.wait(timeout=60):
+            raise Exception("Error From Browser")
+
+        future = asyncio.run_coroutine_threadsafe(self._talk_to_chatgpt(prompt), self.loop)
+        return future.result(timeout=120)
+
+browser_engine = AsyncBrowserThread()
+browser_engine.start()
+
+# ====================================================================
+# Smart Prompt Builder
+# ====================================================================
+def format_prompt(messages, tools=None):
+    parts = []
+    system_parts = []
+    has_tool_results = False
+    user_question = ""
+
+    for msg in messages:
+        role = msg.get("role", "")
+        msg_type = msg.get("type", "")
+        content = msg.get("content", "")
+
+        if isinstance(content, list):
+            text_parts = []
+            for item in content:
+                if isinstance(item, dict):
+                    text_parts.append(item.get("text", item.get("content", str(item))))
+                else:
+                    text_parts.append(str(item))
+            content = "\n".join(text_parts)
+
+        if role == "system":
+            system_parts.append(content)
+        elif role == "tool":
+            has_tool_results = True
+            tool_name = msg.get("name", "tool")
+            parts.append(f"[TOOL RESULT from '{tool_name}']:\n{content}")
+        elif msg_type == "function_call_output":
+            has_tool_results = True
+            call_id = msg.get("call_id", "")
+            output_content = msg.get("output", content)
+            parts.append(f"[TOOL RESULT (call_id: {call_id})]:\n{output_content}")
+        elif msg_type == "function_call":
+            func_name = msg.get("name", "?")
+            func_args = msg.get("arguments", "{}")
+            parts.append(f"[PREVIOUS TOOL CALL: Called '{func_name}' with arguments: {func_args}]")
+        elif role == "assistant":
+            assistant_content = content if content else ""
+            tool_calls_in_msg = msg.get("tool_calls", [])
+            if tool_calls_in_msg:
+                tc_descriptions = []
+                for tc in tool_calls_in_msg:
+                    func = tc.get("function", {})
+                    tc_descriptions.append(f"Called '{func.get('name', '?')}' with: {func.get('arguments', '{}')}")
+                assistant_content += "\n[Previous tool calls: " + "; ".join(tc_descriptions) + "]"
+            if assistant_content.strip():
+                parts.append(f"[Assistant]: {assistant_content}")
+        elif role == "user" or (msg_type == "message" and role != "system"):
+            user_question = content
+            parts.append(content)
+            has_tool_results = False
+        elif content:
+            parts.append(content)
+
+    final = ""
+
+    if system_parts:
+        if tools and not has_tool_results:
+            final += "=== YOUR ROLE ===\n"
+            final += "\n\n".join(system_parts)
+            final += "\n=== END OF ROLE ===\n\n"
+        else:
+            final += "=== SYSTEM INSTRUCTIONS (FOLLOW STRICTLY) ===\n"
+            final += "\n\n".join(system_parts)
+            final += "\n=== END OF INSTRUCTIONS ===\n\n"
+
+    if tools and not has_tool_results:
+        final += format_tools_instruction(tools, user_question)
+
+    if has_tool_results:
+        final += "=== CONTEXT FROM TOOLS ===\n"
+        final += "The following information was retrieved by the tools you requested.\n"
+        final += "Use ONLY this information to answer the user's question.\n\n"
+
+    if parts:
+        final += "\n".join(parts)
+
+    if has_tool_results:
+        final += "\n\n=== INSTRUCTION ===\n"
+        final += "Now answer the user's question based ONLY on the tool results above.\n"
+
+    return final
+
+def format_tools_instruction(tools, user_question=""):
+    instruction = "\n=== MANDATORY TOOL USAGE ===\n"
+    instruction += "You MUST use one of the tools below to answer this question.\n"
+    instruction += "Do NOT answer directly. Do NOT say you don't have information.\n"
+    instruction += "You MUST respond with ONLY a JSON object to call the tool.\n\n"
+
+    instruction += "RESPONSE FORMAT - respond with ONLY this JSON, nothing else:\n"
+    instruction += '{"tool_calls": [{"name": "TOOL_NAME", "arguments": {"param": "value"}}]}\n\n'
+
+    instruction += "RULES:\n"
+    instruction += "- Your ENTIRE response must be valid JSON only\n"
+    instruction += "- No markdown, no code blocks, no explanation\n"
+    instruction += "- No text before or after the JSON\n\n"
+
+    instruction += "Available tools:\n\n"
+
+    for tool in tools:
+        func = tool.get("function", tool)
+        name = func.get("name", "unknown")
+        desc = func.get("description", "No description")
+        params = func.get("parameters", {})
+
+        instruction += f"Tool: {name}\n"
+        instruction += f"Description: {desc}\n"
+
+        if params.get("properties"):
+            instruction += "Parameters:\n"
+            required_params = params.get("required", [])
+            for param_name, param_info in params["properties"].items():
+                param_type = param_info.get("type", "string")
+                param_desc = param_info.get("description", "")
+                is_required = "required" if param_name in required_params else "optional"
+                instruction += f"  - {param_name} ({param_type}, {is_required}): {param_desc}\n"
+        instruction += "\n"
+
+    instruction += "=== END OF TOOLS ===\n\n"
+
+    first_tool = tools[0] if tools else {}
+    first_func = first_tool.get("function", first_tool)
+    first_name = first_func.get("name", "tool")
+
+    instruction += f'EXAMPLE: If the user asks a question, respond with:\n'
+    instruction += '{"tool_calls": [{"name": "' + first_name + '", "arguments": {"input": "the user question here"}}]}\n\n'
+
+    instruction += "Now respond with the JSON to call the appropriate tool:\n\n"
+    return instruction
+
+def parse_tool_calls(response_text):
+    cleaned = response_text.strip()
+    if "```" in cleaned:
+        code_block_match = re.search(r'```(?:json)?\s*\n?(.*?)\n?\s*```', cleaned, re.DOTALL)
+        if code_block_match:
+            cleaned = code_block_match.group(1).strip()
+
+    json_candidates = [cleaned]
+    json_match = re.search(r'\{[\s\S]*"tool_calls"[\s\S]*\}', cleaned)
+    if json_match:
+        json_candidates.append(json_match.group(0))
+
+    for candidate in json_candidates:
+        try:
+            parsed = json.loads(candidate)
+            if isinstance(parsed, dict) and "tool_calls" in parsed:
+                raw_calls = parsed["tool_calls"]
+                if isinstance(raw_calls, list) and len(raw_calls) > 0:
+                    formatted_calls = []
+                    for call in raw_calls:
+                        tool_name = call.get("name", "")
+                        arguments = call.get("arguments", {})
+                        if isinstance(arguments, dict):
+                            arguments_str = json.dumps(arguments, ensure_ascii=False)
+                        else:
+                            arguments_str = str(arguments)
+
+                        formatted_calls.append({
+                            "id": f"call_{uuid.uuid4().hex[:24]}",
+                            "type": "function",
+                            "function": {
+                                "name": tool_name,
+                                "arguments": arguments_str
+                            }
+                        })
+                    return formatted_calls
+        except (json.JSONDecodeError, TypeError, KeyError):
+            continue
+    return None
+
+# ====================================================================
+# FastAPI App
+# ====================================================================
+app = FastAPI(title="mse_ai_api for n8n")
+
+@app.post("/v1/chat/completions")
+async def chat_completions(request: Request):
+    try:
+        data = await request.json()
+    except Exception:
+        return JSONResponse(status_code=400, content={"error": {"message": "Invalid JSON payload"}})
+
+    authorization = request.headers.get("authorization", "")
+    if not authorization or authorization.replace("Bearer ", "").strip() != API_SECRET_KEY:
+        return JSONResponse(status_code=401, content={"error": {"message": "Invalid API Key"}})
+
+    messages = data.get("messages", [])
+    if not messages:
+        return JSONResponse(status_code=400, content={"error": {"message": "messages field is required"}})
+
+    try:
+        tools = data.get("tools", None)
+        prompt = format_prompt(messages, tools=tools)
+        start_time = time.time()
+        print(f"[LITE-SERVER] Processing request ({len(prompt)} chars)")
+        response_text = browser_engine.process_request(prompt)
+        p_tokens = len(prompt.split())
+        c_tokens = len(response_text.split())
+        tool_calls = None
+        if tools:
+            tool_calls = parse_tool_calls(response_text)
+
+        if tool_calls:
+            return {
+                "id": f"chatcmpl-{uuid.uuid4().hex[:29]}",
+                "object": "chat.completion",
+                "created": int(start_time),
+                "model": data.get("model", "gpt-4o-mini"),
+                "choices": [{"index": 0, "message": {"role": "assistant", "content": None,
+                    "tool_calls": tool_calls}, "finish_reason": "tool_calls"}],
+                "usage": {"prompt_tokens": p_tokens, "completion_tokens": c_tokens,
+                    "total_tokens": p_tokens + c_tokens}
+            }
+        else:
+            return {
+                "id": f"chatcmpl-{uuid.uuid4().hex[:29]}",
+                "object": "chat.completion",
+                "created": int(start_time),
+                "model": data.get("model", "gpt-4o-mini"),
+                "choices": [{"index": 0, "message": {"role": "assistant", "content": response_text},
+                    "finish_reason": "stop"}],
+                "usage": {"prompt_tokens": p_tokens, "completion_tokens": c_tokens,
+                    "total_tokens": p_tokens + c_tokens}
+            }
+    except Exception as e:
+        return JSONResponse(status_code=500, content={"error": str(e)})
+
+
+@app.post("/v1/responses")
+async def responses(request: Request):
+    try:
+        data = await request.json()
+    except Exception:
+        return JSONResponse(status_code=400, content={"error": {"message": "Invalid JSON payload"}})
+
+    authorization = request.headers.get("authorization", "")
+    if not authorization or authorization.replace("Bearer ", "").strip() != API_SECRET_KEY:
+        return JSONResponse(status_code=401, content={"error": {"message": "Invalid API Key"}})
+
+    input_data = data.get("input", "")
+    if isinstance(input_data, str):
+        messages = [{"role": "user", "content": input_data}]
+    elif isinstance(input_data, list):
+        messages = input_data
+    else:
+        messages = data.get("messages", [])
+
+    if not messages:
+        return JSONResponse(status_code=400, content={"error": {"message": "input field is required"}})
+
+    try:
+        tools = data.get("tools", None)
+        instructions = data.get("instructions", "")
+        if instructions:
+            messages.insert(0, {"role": "system", "content": instructions})
+        prompt = format_prompt(messages, tools=tools)
+        start_time = time.time()
+        response_text = browser_engine.process_request(prompt)
+        p_tokens = len(prompt.split())
+        c_tokens = len(response_text.split())
+        tool_calls = None
+        if tools:
+            tool_calls = parse_tool_calls(response_text)
+
+        if tool_calls:
+            output_items = []
+            for tc in tool_calls:
+                output_items.append({
+                    "type": "function_call",
+                    "id": tc["id"],
+                    "call_id": tc["id"],
+                    "name": tc["function"]["name"],
+                    "arguments": tc["function"]["arguments"],
+                    "status": "completed"
+                })
+            return {
+                "id": f"resp-{uuid.uuid4().hex[:29]}",
+                "object": "response",
+                "created_at": int(start_time),
+                "model": data.get("model", "gpt-4o-mini"),
+                "status": "completed",
+                "output": output_items,
+                "usage": {"input_tokens": p_tokens, "output_tokens": c_tokens,
+                    "total_tokens": p_tokens + c_tokens}
+            }
+        else:
+            return {
+                "id": f"resp-{uuid.uuid4().hex[:29]}",
+                "object": "response",
+                "created_at": int(start_time),
+                "model": data.get("model", "gpt-4o-mini"),
+                "status": "completed",
+                "output": [{"type": "message", "role": "assistant",
+                    "content": [{"type": "output_text", "text": response_text}]}],
+                "usage": {"input_tokens": p_tokens, "output_tokens": c_tokens,
+                    "total_tokens": p_tokens + c_tokens}
+            }
+    except Exception as e:
+        return JSONResponse(status_code=500, content={"error": str(e)})
+
+
+@app.get("/v1/models")
+async def list_models():
+    return {"object": "list",
+            "data": [{"id": "gpt-4o-mini", "object": "model", "owned_by": "mse_ai_api"}]}
+
+
+# ── تغيير 1: إضافة /health endpoint (مطلوب لـ HuggingFace healthcheck)
+@app.get("/health")
+@app.get("/")
+async def health_check():
+    return {"status": "running", "message": "mse_ai_api Server is active!"}
+
+
+if __name__ == "__main__":
+    import uvicorn
+    # ── تغيير 2: port 7777 → 7860 (مطلوب لـ HuggingFace)
+    uvicorn.run(app, host="0.0.0.0", port=7860)

requirements.txt

@@ -0,0 +1,5 @@
+fastapi==0.110.0
+uvicorn==0.27.1
+playwright==1.42.0
+pydantic==2.6.3
+python-multipart==0.0.9