c

local_ai_setup.md

@@ -0,0 +1,149 @@
+# Local AI Coding Setup — Windows 11 (Aider + Ollama)
+
+## Hardware
+- GPU: RTX 5070 Ti, 12GB VRAM
+- RAM: 32GB
+- OS: Windows 11
+
+---
+
+## Prerequisites
+
+### 1. Install Ollama
+Download from https://ollama.com and install.
+
+### 2. Pull a model
+```powershell
+ollama pull qwen3-coder:30b   # 18GB, strong coding model (MoE, VRAM+RAM split)
+ollama pull gemma4:12b        # 12GB, responds in English more reliably
+```
+
+Confirm models are available:
+```powershell
+ollama list
+```
+
+Confirm Ollama is serving:
+```powershell
+curl http://localhost:11434/api/tags
+```
+
+---
+
+## Install Aider
+
+```powershell
+pip install aider-chat
+aider --version   # should print version number
+```
+
+---
+
+## Project Config
+
+Create `.aider.conf.yml` in your project root:
+
+```yaml
+model: ollama/gemma4:12b
+openai-api-base: http://localhost:11434/v1
+openai-api-key: ollama
+edit-format: whole
+map-tokens: 2048
+no-auto-commits: true
+system-prompt: "Always respond in English only. Never use Chinese or any other language."
+```
+
+**Config notes:**
+- `edit-format: whole` — more reliable file writes for local models (avoids code showing in chat only)
+- `map-tokens: 2048` — limits repo map size, important for smaller context windows
+- `no-auto-commits: true` — review changes before they hit git
+- `system-prompt` — forces English responses (important for Qwen3 which defaults to Chinese)
+
+Switch models without editing the file:
+```
+/model ollama/qwen3-coder:30b
+```
+
+---
+
+## Optional: Performance Tuning (if inference is slow)
+
+Create a `Modelfile` in the project root:
+
+```
+FROM qwen3-coder:30b
+PARAMETER num_ctx 8192
+PARAMETER num_gpu 99
+```
+
+Register it:
+```powershell
+ollama create qwen3-coder-tuned -f Modelfile
+```
+
+Update `.aider.conf.yml`:
+```yaml
+model: ollama/qwen3-coder-tuned
+```
+
+**Why:** `num_gpu 99` maximizes VRAM usage. `num_ctx 8192` prevents the KV cache from
+spilling too much into RAM. Recommended context range: 4096–16384.
+
+---
+
+## Daily Aider Workflow
+
+Start Aider (reads config automatically):
+```powershell
+aider
+```
+
+| Command | What it does |
+|---------|-------------|
+| `/add src/foo.py` | Add file to context |
+| `/drop src/foo.py` | Remove file from context |
+| `/diff` | See pending changes |
+| `/undo` | Revert last change |
+| `/run pytest` | Run command, share output with model |
+| `/run git rm --cached file.py` | Run git commands from inside Aider |
+| `/clear` | Clear chat history (keep files) |
+| `/settings` | Show loaded config (verify auto_commits, system_prompt) |
+| `/model ollama/gemma4:12b` | Switch model on the fly |
+| `/exit` | Quit |
+
+---
+
+## Known Issues & Fixes
+
+### Model responds in Chinese
+Cause: Qwen3 is a Chinese model and defaults to Chinese.
+Fix: `system-prompt` in `.aider.conf.yml` (already included above). Restart Aider after config change.
+
+### Aider shows code in chat but doesn't write files
+Cause: Model didn't follow Aider's edit format.
+Fix 1: `/add target_file.py` before asking — hints the target file to the model.
+Fix 2: `edit-format: whole` in config (already included above).
+
+### "File not found" / repo-map warnings for deleted files
+Cause: File deleted from disk but still tracked in git index.
+Fix:
+```powershell
+git rm --cached filename.py
+```
+Or from inside Aider:
+```
+/run git rm --cached filename.py
+```
+
+### Config changes not taking effect
+Fix: Exit Aider (`/exit`) and restart. Config is only read at startup.
+
+---
+
+## Verify Everything Works
+
+1. `ollama list` — model appears
+2. `aider --version` — prints version
+3. Start Aider, run `/settings` — confirm `auto_commits: False` and `system_prompt` present
+4. Ask Aider to create a simple file — it should write to disk, not just chat
+5. Response is in English

local_llm.md

@@ -0,0 +1,342 @@
+# Local AI Coding Environment Implementation Plan
+
+## Objective
+
+Build a local-first AI coding environment on a Windows 11 workstation with the following requirements:
+
+### Hardware
+
+* NVIDIA RTX 5070 Ti 12GB VRAM
+* 64GB+ system RAM (if available)
+* Windows 11
+* WSL2 Ubuntu
+* VS Code
+
+### Existing Software
+
+* Ollama installed and operational
+* Qwen3-Coder 30B installed in Ollama
+* Claude Code CLI installed
+* Git installed
+
+### Constraints
+
+* Source code is confidential.
+* All code must remain local by default.
+* Cloud models may be used only as an optional fallback.
+* Minimize API costs.
+* Support large codebases.
+
+---
+
+# Target Architecture
+
+```text
+VS Code
+    |
+    +---- Continue Extension
+    |
+    +---- Claude Code CLI
+    |
+    +---- Aider
+              |
+              v
+           Ollama
+              |
+              v
+      Qwen3-Coder 30B
+```
+
+---
+
+# Project Goals
+
+Implement and validate the following workflows.
+
+## Workflow 1: Local Chat
+
+Developer can:
+
+* Ask coding questions
+* Explain code
+* Generate code
+* Review code
+
+using:
+
+```text
+VS Code
+    +
+Continue
+    +
+Ollama
+    +
+Qwen3-Coder 30B
+```
+
+---
+
+## Workflow 2: Local Agent
+
+Developer can:
+
+* Refactor code
+* Create files
+* Modify files
+* Run git-aware edits
+
+using:
+
+```text
+Aider
+    +
+Ollama
+    +
+Qwen3-Coder 30B
+```
+
+---
+
+## Workflow 3: Claude Code Optional
+
+Developer can:
+
+* Use Claude Code against local Ollama models
+* Compare behavior against Aider
+* Determine whether Claude Code provides additional value
+
+using:
+
+```text
+Claude Code
+    +
+Ollama
+    +
+Qwen3-Coder 30B
+```
+
+---
+
+# Deliverables
+
+Produce the following:
+
+## Deliverable 1
+
+Environment verification script.
+
+Verify:
+
+* Ollama installed
+* NVIDIA GPU visible
+* CUDA available
+* WSL functioning
+* Qwen3-Coder model available
+
+Expected output:
+
+```text
+PASS: Ollama
+PASS: GPU
+PASS: CUDA
+PASS: Qwen3-Coder
+```
+
+---
+
+## Deliverable 2
+
+Aider installation guide.
+
+Include:
+
+### Linux / WSL installation
+
+Commands:
+
+```bash
+pipx install aider-chat
+```
+
+or preferred installation method.
+
+### Ollama integration
+
+Configuration examples.
+
+### Verification steps
+
+Simple repository test.
+
+---
+
+## Deliverable 3
+
+Continue configuration.
+
+Create:
+
+### VS Code setup instructions
+
+Install Continue extension.
+
+### Model configuration
+
+Configure Continue to use:
+
+```text
+Ollama
+Qwen3-Coder 30B
+```
+
+### Example config files
+
+Include complete examples.
+
+---
+
+## Deliverable 4
+
+Claude Code local model integration.
+
+Research and implement the best available approach for:
+
+```text
+Claude Code
+        ->
+OpenAI-compatible endpoint
+        ->
+Ollama
+```
+
+Requirements:
+
+* Use officially supported methods where possible.
+* Avoid unsupported hacks.
+* Document limitations.
+* Provide rollback procedure.
+
+---
+
+## Deliverable 5
+
+Performance optimization.
+
+Analyze:
+
+### VRAM usage
+
+Qwen3-Coder 30B on RTX 5070 Ti 12GB.
+
+### Recommended quantization
+
+Evaluate:
+
+* Q4
+* Q5
+* IQ3
+
+Recommend the best balance between:
+
+* Quality
+* Speed
+* Memory usage
+
+---
+
+## Deliverable 6
+
+Benchmark suite.
+
+Create repeatable tests:
+
+### Test 1
+
+Generate a REST API.
+
+### Test 2
+
+Refactor a medium-sized module.
+
+### Test 3
+
+Write unit tests.
+
+### Test 4
+
+Debug a failing application.
+
+Measure:
+
+* Completion time
+* Accuracy
+* Token throughput
+* User effort
+
+Compare:
+
+```text
+Aider + Qwen3-Coder 30B
+Claude Code + Qwen3-Coder 30B
+Continue + Qwen3-Coder 30B
+```
+
+---
+
+# Preferred Outcome
+
+Primary development workflow:
+
+```text
+VS Code
+    +
+Continue
+    +
+Qwen3-Coder 30B
+```
+
+Agent workflow:
+
+```text
+Aider
+    +
+Qwen3-Coder 30B
+```
+
+Optional advanced workflow:
+
+```text
+Claude Code
+    +
+Qwen3-Coder 30B
+```
+
+---
+
+# Success Criteria
+
+The project is successful if:
+
+1. All code remains local.
+2. No cloud services are required.
+3. Developer can perform daily coding tasks locally.
+4. Aider successfully edits repositories.
+5. Continue provides a productive IDE experience.
+6. Claude Code local integration is evaluated and documented.
+7. Setup can be reproduced on a fresh machine.
+
+---
+
+# Final Report
+
+Produce a final report containing:
+
+* Architecture diagram
+* Installation steps
+* Configuration files
+* Benchmark results
+* Known limitations
+* Recommended workflow
+* Future upgrade path
+
+The report should be suitable for long-term maintenance and onboarding of additional developers.

merge_excel.py

@@ -1,74 +0,0 @@
-import os
-import sys
-import pandas as pd
-from pathlib import Path
-
-def merge_excel_files(input_dir):
-    """
-    合并指定目录下所有包含"交易流水"工作表的Excel文件
-    """
-    # 创建输出文件路径
-    output_file = os.path.join(input_dir, "txn_summary.xlsx")
-    
-    # 存储所有数据的列表
-    all_data = []
-    
-    # 遍历输入目录中的所有文件
-    for filename in os.listdir(input_dir):
-        if filename.endswith(('.xlsx', '.xls')):
-            file_path = os.path.join(input_dir, filename)
-            
-            try:
-                # 读取Excel文件的所有工作表
-                excel_file = pd.ExcelFile(file_path)
-                
-                # 检查是否包含"交易流水"工作表
-                if "交易流水" in excel_file.sheet_names:
-                    # 读取"交易流水"工作表
-                    df = pd.read_excel(file_path, sheet_name="交易流水")
-                    
-                    # 检查数据是否为空
-                    if not df.empty:
-                        # 添加源文件名列
-                        df['来源文件'] = filename
-                        
-                        # 将数据添加到列表中
-                        all_data.append(df)
-                    else:
-                        print(f"警告: 文件 {filename} 中的'交易流水'工作表为空")
-                        
-            except Exception as e:
-                print(f"处理文件 {filename} 时出错: {e}")
-    
-    # 如果没有找到任何匹配的文件，退出
-    if not all_data:
-        print("未找到包含'交易流水'工作表的Excel文件或所有文件都为空")
-        return
-    
-    # 合并所有数据
-    merged_df = pd.concat(all_data, ignore_index=True)
-    
-    # 保存合并后的数据到输出文件
-    merged_df.to_excel(output_file, index=False)
-    
-    print(f"成功合并 {len(all_data)} 个文件，结果已保存到: {output_file}")
-
-def main():
-    # 从命令行参数获取输入目录路径
-    if len(sys.argv) != 2:
-        print("请提供输入目录路径作为命令行参数")
-        print("使用方法: python merge_excel.py <input_directory>")
-        return
-    
-    input_dir = sys.argv[1]
-    
-    # 检查输入目录是否存在
-    if not os.path.isdir(input_dir):
-        print(f"错误: 目录 '{input_dir}' 不存在")
-        return
-    
-    # 合并Excel文件
-    merge_excel_files(input_dir)
-
-if __name__ == "__main__":
-    main()

merge_transactions.py

@@ -1,63 +0,0 @@
-import os
-import pandas as pd
-from pathlib import Path
-import sys
-
-def merge_transaction_data():
-    # 获取用户输入的路径
-    input_path_str = input("请输入包含 Excel 文件的文件夹路径: ").strip()
-    input_dir = Path(input_path_str)
-
-    # 检查路径是否有效
-    if not input_dir.is_dir():
-        print(f"错误：提供的路径 '{input_path_str}' 不是一个有效的目录。")
-        return
-
-    all_data = []
-    target_sheet = "交易流水"
-    
-    # 获取目录下所有的 excel 文件 (支持 .xlsx 和 .xls)
-    files = list(input_dir.glob("*.xlsx")) + list(input_dir.glob("*.xls"))
-    
-    if not files:
-        print("在该目录下未找到任何 Excel 文件。")
-        return
-
-    for file_path in files:
-        try:
-            # 读取指定的 sheet
-            # 使用 pandas 的 read_excel，如果 sheet 不存在会抛出 ValueError
-            df = pd.read_excel(file_path, sheet_name=target_sheet)
-            
-            if df.empty:
-                print(f"跳过 {file_path.name}：工作表 '{target_sheet}' 为空。")
-                continue
-                
-            all_data.append(df)
-            print(f"成功读取: {file_path.name}")
-        except ValueError:
-            # 如果找不到指定的 sheet 名称，则跳过该文件
-            print(f"跳过 {file_path.name}：未找到名为 '{target_sheet}' 的工作表。")
-        except Exception as e:
-            print(f"处理文件 {file_path.name} 时发生错误: {e}")
-
-    if all_data:
-        # 合并所有 DataFrame
-        merged_df = pd.concat(all_data, ignore_index=True)
-        
-        # 定义输出路径
-        output_file = input_dir / "txn_summary.xlsx"
-        
-        # 保存结果
-        # 使用 openpyxl 作为引擎以确保兼容性
-        merged_df.to_excel(output_file, index=False, engine='openpyxl')
-        print("-" * 30)
-        print(f"合并成功！")
-        print(f"总计处理文件数: {len(all_data)}")
-        print(f"结果已保存至: {output_file}")
-    else:
-        print("未找到包含 '" + target_sheet + "' 工作表的有效数据，未生成输出文件。")
-
-if __name__ == "__main__":
-    # 确保安装了必要的库：pip install pandas openpyxl
-    merge_transaction_data()

practice.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "id": "259a585b",
    "metadata": {},
    "outputs": [],
@@ -30,7 +30,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 3,
    "id": "fe7bf6eb",
    "metadata": {},
    "outputs": [
@@ -58,7 +58,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 4,
    "id": "4bddedb8",
    "metadata": {},
    "outputs": [
@@ -95,18 +95,70 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "id": "b33dcb00",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "65\n",
+      "\n",
+      " !$&',-.3:;?ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz\n"
+     ]
+    }
+   ],
    "source": [
-    "set(text)"
+    "chars = sorted(list(set(text)))\n",
+    "vocab_size = len(chars)\n",
+    "print(vocab_size\n",
+    ")\n",
+    "print(\"\".join(chars\n",
+    "))\n",
+    "\n"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7c84058a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'!'"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "stoi = {char:i for i, char in enumerate(chars)}\n",
+    "itos = {i:char for i, char in enumerate(chars)}\n",
+    "# print (itos)\n",
+    "\n",
+    "stoi['a'] # 0\n",
+    "itos[2]\n",
+    "\n",
+    "encode = lambda s: \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4f43742c",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": ".venv",
+   "display_name": ".venv (3.12.10)",
    "language": "python",
    "name": "python3"
   },