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README.md

@@ -1,12 +1,17 @@
 ---
-title: LanguageBridge MathHybrid Phi2
-emoji: 🐨
-colorFrom: pink
-colorTo: yellow
+title: LanguageBridge — Math Hybrid (Phi + SymPy)
+emoji: 🧮
+colorFrom: yellow
+colorTo: blue
 sdk: gradio
-sdk_version: 5.49.1
+sdk_version: "4.44.1"
 app_file: app.py
 pinned: false
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+一個**小型 LLM（Phi-2 / Phi-3-mini）+ SymPy** 的數學混合推理 Space：  
+- LLM：把**文字題**解析為可計算的數學式或步驟  
+- SymPy：遇到**可符號計算**的部分（方程、微積分、因式分解…）直接算出精準解  
+- 自動偵測：若輸入就是算式/方程 → 直接 SymPy；否則走 LLM→SymPy 流程
+
+> 預設模型：`microsoft/phi-2`（可在 app.py 換成你喜歡的小型模型）

app.py

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+import os, sys, re, json
+import gradio as gr
+import sympy as sp
+
+from transformers import (
+    AutoTokenizer, AutoModelForCausalLM, pipeline
+)
+
+TITLE = "LanguageBridge — Math Hybrid (Phi + SymPy)"
+MODEL_ID = "microsoft/phi-2"
+MAX_NEW_TOKENS = 512
+
+def try_sympy_direct(q: str):
+    """若使用者輸入就是算式/方程，走 SymPy 精準計算。支援多行 / 分號分隔 / 聯立。"""
+    q = (q or "").strip()
+    if not q:
+        return None
+
+    # 粗略偵測：若含 = 或 明顯算式符號
+    if any(s in q for s in ["=", "+", "-", "*", "/", "^", "sin", "cos", "tan", "log", "sqrt", "∫", "d/dx"]):
+        try:
+            # 支援多式/聯立：以分號或換行切
+            parts = [s.strip() for seg in q.split(";") for s in seg.split("\n")]
+            eqs, syms = [], set()
+            for s in parts:
+                if not s: 
+                    continue
+                if "=" in s:
+                    left, right = s.split("=", 1)
+                    eq = sp.Eq(sp.sympify(left), sp.sympify(right))
+                    eqs.append(eq)
+                    syms |= eq.free_symbols
+                    syms |= eq.rhs.free_symbols if hasattr(eq, "rhs") else set()
+                else:
+                    # 非方程，當作一般表達式，做一輪常見操作
+                    expr = sp.sympify(s)
+                    tips = []
+                    try:
+                        tips.append(f"簡化：{sp.simplify(expr)}")
+                    except Exception:
+                        pass
+                    try:
+                        x = list(expr.free_symbols)[0] if expr.free_symbols else sp.symbols("x")
+                        tips.append(f"對 {x} 微分：{sp.diff(expr, x)}")
+                        tips.append(f"對 {x} 積分：{sp.integrate(expr, x)}")
+                    except Exception:
+                        pass
+                    if tips:
+                        return "\n".join(tips)  # 只要有一行就回傳
+                    else:
+                        return f"結果：{expr}"
+
+            if eqs:
+                if not syms:
+                    x = sp.symbols("x")
+                    syms = {x}
+                sol = sp.solve(eqs, list(syms), dict=True)
+                if not sol:
+                    return "SymPy：無解或需要更多條件。"
+                lines = []
+                for i, sdict in enumerate(sol, 1):
+                    lines.append("解 {}: ".format(i) + ", ".join([f"{k} = {sp.simplify(v)}" for k, v in sdict.items()]))
+                return "\n".join(lines)
+
+        except Exception as e:
+            # 交給 LLM 流程
+            return None
+
+    return None
+
+
+def build_llm():
+    """嘗試以 4-bit 啟動（有 CUDA 時），否則退回 CPU。"""
+    import torch
+    has_cuda = torch.cuda.is_available()
+    load_kwargs = {"device_map":"auto"}
+
+    if has_cuda:
+        try:
+            import bitsandbytes as bnb  # 檢查有無 bnb
+            load_kwargs.update({"load_in_4bit": True})
+        except Exception:
+            # 沒有 bnb 就用 fp16
+            load_kwargs.update({"torch_dtype": torch.float16})
+    else:
+        # CPU：讓 transformers 自行決定 dtype
+        pass
+
+    tok = AutoTokenizer.from_pretrained(MODEL_ID, trust_remote_code=True)
+    if tok.pad_token_id is None and tok.eos_token_id is not None:
+        tok.pad_token = tok.eos_token
+
+    mdl = AutoModelForCausalLM.from_pretrained(
+        MODEL_ID,
+        trust_remote_code=True,
+        **load_kwargs
+    )
+
+    pipe = pipeline(
+        "text-generation",
+        model=mdl,
+        tokenizer=tok,
+        do_sample=False,
+        max_new_tokens=MAX_NEW_TOKENS,
+        temperature=0.2,
+        top_p=0.9
+    )
+    return pipe
+
+LLM = None
+
+SYSTEM_PROMPT = (
+    "You are a math teacher. When the user asks a word problem,\n"
+    "1) parse it into a clean mathematical expression or a system of equations;\n"
+    "2) if it is solvable by SymPy, output a single line starting with 'SymPy:' followed by a Python/SymPy expression;\n"
+    "3) then give a concise final answer on the next line starting with 'Answer:'."
+)
+
+def llm_to_sympy_and_answer(pipe, q: str):
+    prompt = (
+        f"<s>System:\n{SYSTEM_PROMPT}\n</s>\n"
+        f"User: {q}\n"
+        f"Assistant:"
+    )
+    out = pipe(prompt, pad_token_id=pipe.tokenizer.eos_token_id)[0]["generated_text"]
+    # 嘗試抓 SymPy: 行
+    sym_line = None
+    ans_line = None
+    for line in out.splitlines():
+        if line.strip().startswith("SymPy:"):
+            sym_line = line.split("SymPy:",1)[-1].strip()
+        if line.strip().startswith("Answer:"):
+            ans_line = line.split("Answer:",1)[-1].strip()
+
+    checked = ""
+    if sym_line:
+        try:
+            val = eval(sym_line, {"sp": sp, "sympy": sp})
+            # 若是可列印的結果（非方程），試著數值化或簡化
+            if isinstance(val, (int, float, sp.Basic)):
+                checked = f"SymPy 檢算：{sp.simplify(val)}"
+        except Exception as e:
+            checked = f"SymPy 檢算失敗：{e}"
+
+    merge = []
+    if sym_line: merge.append(f"SymPy: {sym_line}")
+    if ans_line: merge.append(f"Answer: {ans_line}")
+    if checked:  merge.append(checked)
+    return "\n".join(merge) if merge else out
+
+
+def solve(q: str):
+    global LLM
+    q = (q or "").strip()
+    if not q:
+        return "請輸入題目或算式。"
+
+    # 1) 先嘗試 SymPy 直接處理
+    direct = try_sympy_direct(q)
+    if direct:
+        return direct
+
+    # 2) 走 LLM → SymPy
+    if LLM is None:
+        LLM = build_llm()
+    try:
+        return llm_to_sympy_and_answer(LLM, q)
+    except Exception as e:
+        return f"[LLM流程失敗] {e}"
+
+with gr.Blocks(title=TITLE) as demo:
+    gr.Markdown(f"## {TITLE}\n貼上文字題或算式：LLM 解析 → SymPy 精算（可聯立）")
+    with gr.Row():
+        q = gr.Textbox(label="題目 / 算式", lines=8, placeholder="例如：一個數加上 5 等於 11，求這個數。\n或：2*x + 5 = 11；或：sin(x)**2 + cos(x)**2")
+    with gr.Row():
+        out = gr.Textbox(label="輸出", lines=12)
+    btn = gr.Button("送出 🚀")
+    btn.click(fn=solve, inputs=q, outputs=out)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+gradio==4.44.1
+transformers==4.44.2
+accelerate>=0.31.0
+bitsandbytes==0.43.3
+sentencepiece
+sympy>=1.12
+huggingface_hub>=0.24.0
+safetensors
+einops
+numpy<2