{
    "Kurama622/llm.nvim",
    dependencies = { "nvim-lua/plenary.nvim", "MunifTanjim/nui.nvim" },
    cmd = { "LLMSesionToggle", "LLMSelectedTextHandler" },
    config = function()
      require("llm").setup({
        prompt = "You are a helpful chinese assistant.",

        prefix = {
          user = { text = "😃 ", hl = "Title" },
          assistant = { text = "⚡ ", hl = "Added" },
        },

        style = "float", -- right | left | above | below | float

        -- [[ Github Models ]]
        url = "https://models.inference.ai.azure.com/chat/completions",
        model = "gpt-4o",
        api_type = "openai",
        --[[ Optional: If you need to use models from different platforms simultaneously,
        you can configure the `fetch_key` to ensure that different models use different API Keys.]]
        fetch_key = function()
          return switch("enable_gpt")
        end,

        -- [[ cloudflare ]]
        -- model = "@cf/google/gemma-7b-it-lora",

        -- [[ ChatGLM ]]
        -- url = "https://open.bigmodel.cn/api/paas/v4/chat/completions",
        -- model = "glm-4-flash",

        -- [[ kimi ]]
        -- url = "https://api.moonshot.cn/v1/chat/completions",
        -- model = "moonshot-v1-8k", -- "moonshot-v1-8k", "moonshot-v1-32k", "moonshot-v1-128k"
        -- api_type = "openai",

        -- [[ local llm ]]
        -- url = "http://localhost:11434/api/chat",
        -- model = "llama3.2:1b",
        -- streaming_handler = local_llm_streaming_handler,
        -- parse_handler = local_llm_parse_handler,

        -- [[ siliconflow ]]
        -- url = "https://api.siliconflow.cn/v1/chat/completions",
        -- api_type = "openai",
        -- model = "Qwen/Qwen2.5-7B-Instruct",
        -- -- [optional: fetch_key]
        -- fetch_key = function()
        --   return switch("enable_siliconflow")
        -- end,

        -- [[ openrouter ]]
        -- url = "https://openrouter.ai/api/v1/chat/completions",
        -- model = "google/gemini-2.0-flash-exp:free",
        -- max_tokens = 8000,
        -- api_type = "openai",
        -- fetch_key = function()
        --   return switch("enable_openrouter")
        -- end,

        max_tokens = 1024,
        save_session = true,
        max_history = 15,
        history_path = "/tmp/history",    -- where to save history
        temperature = 0.3,
        top_p = 0.7,

        spinner = {
          text = {
            "󰧞󰧞",
            "󰧞󰧞",
            "󰧞󰧞",
            "󰧞󰧞",
          },
          hl = "Title",
        },

        display = {
          diff = {
            layout = "vertical", -- vertical|horizontal split for default provider
            opts = { "internal", "filler", "closeoff", "algorithm:patience", "followwrap", "linematch:120" },
            provider = "mini_diff", -- default|mini_diff
          },
        },

        -- stylua: ignore
        keys = {
          -- The keyboard mapping for the input window.
          ["Input:Cancel"]      = { mode = "n", key = "<C-c>" },
          ["Input:Submit"]      = { mode = "n", key = "<cr>" },
          ["Input:Resend"]      = { mode = "n", key = "<C-r>" },

          -- only works when "save_session = true"
          ["Input:HistoryNext"] = { mode = "n", key = "<C-j>" },
          ["Input:HistoryPrev"] = { mode = "n", key = "<C-k>" },

          -- The keyboard mapping for the output window in "split" style.
          ["Output:Ask"]        = { mode = "n", key = "i" },
          ["Output:Cancel"]     = { mode = "n", key = "<C-c>" },
          ["Output:Resend"]     = { mode = "n", key = "<C-r>" },

          -- The keyboard mapping for the output and input windows in "float" style.
          ["Session:Toggle"]    = { mode = "n", key = "<leader>ac" },
          ["Session:Close"]     = { mode = "n", key = "<esc>" },
        },
      })
    end,
    keys = {
      { "<leader>ac", mode = "n", "<cmd>LLMSessionToggle<cr>" },
      { "<leader>ae", mode = "v", "<cmd>LLMSelectedTextHandler 请解释下面这段代码<cr>" },
      { "<leader>t", mode = "x", "<cmd>LLMSelectedTextHandler 英译汉<cr>" },
    },
  },

  {
    "Kurama622/llm.nvim",
    dependencies = { "nvim-lua/plenary.nvim", "MunifTanjim/nui.nvim" },
    cmd = { "LLMSesionToggle", "LLMSelectedTextHandler" },
    config = function()
      require("llm").setup({
        style = "float", -- right | left | above | below | float

        -- [[ Github Models ]]
        url = "https://models.inference.ai.azure.com/chat/completions",
        model = "gpt-4o",
        api_type = "openai",

        input_box_opts = {
          relative = "editor",
          position = {
            row = "85%",
            col = 15,
          },
          size = {
            height = "5%",
            width = 120,
          },

          enter = true,
          focusable = true,
          zindex = 50,
          border = {
            style = "rounded",
            text = {
              top = " Enter Your Question ",
              top_align = "center",
            },
          },
          win_options = {
            -- set window transparency
            winblend = 20,
            -- set window highlight
            winhighlight = "Normal:Normal,FloatBorder:FloatBorder",
          },
        },
        output_box_opts = {
          relative = "editor",
          position = {
            row = "35%",
            col = 15,
          },
          size = {
            height = "65%",
            width = 90,
          },
          enter = true,
          focusable = true,
          zindex = 20,
          border = {
            style = "rounded",
            text = {
              top = " Preview ",
              top_align = "center",
            },
          },
          win_options = {
            winblend = 20,
            winhighlight = "Normal:Normal,FloatBorder:FloatBorder",
          },
        },

        history_box_opts = {
          relative = "editor",
          position = {
            row = "35%",
            col = 108,
          },
          size = {
            height = "65%",
            width = 27,
          },
          zindex = 70,
          enter = false,
          focusable = false,
          border = {
            style = "rounded",
            text = {
              top = " History ",
              top_align = "center",
            },
          },
          win_options = {
            winblend = 20,
            winhighlight = "Normal:Normal,FloatBorder:FloatBorder",
          },
        },

        -- LLMSelectedTextHandler windows options
        popwin_opts = {
          relative = "cursor",
          position = {
            row = -7,
            col = 20,
          },
          size = {
            width = "50%",
            height = 15,
          },
          enter = true,
          border = {
            style = "rounded",
            text = {
              top = " Explain ",
            },
          },
        },
      })
    end,
    keys = {
      { "<leader>ac", mode = "n", "<cmd>LLMSessionToggle<cr>" },
      { "<leader>ae", mode = "v", "<cmd>LLMSelectedTextHandler 请解释下面这段代码<cr>" },
      { "<leader>t", mode = "x", "<cmd>LLMSelectedTextHandler 英译汉<cr>" },
    },
  },

  {
    "Kurama622/llm.nvim",
    dependencies = { "nvim-lua/plenary.nvim", "MunifTanjim/nui.nvim" },
    cmd = { "LLMSesionToggle", "LLMSelectedTextHandler", "LLMAppHandler" },
    config = function()
      local tools = require("llm.common.tools")
      require("llm").setup({
        app_handler = {
          OptimizeCode = {
            handler = tools.side_by_side_handler,
            -- opts = {
            --   streaming_handler = local_llm_streaming_handler,
            -- },
          },
          TestCode = {
            handler = tools.side_by_side_handler,
            prompt = [[ Write some test cases for the following code, only return the test cases.
            Give the code content directly, do not use code blocks or other tags to wrap it. ]],
            opts = {
              right = {
                title = " Test Cases ",
              },
            },
          },
          OptimCompare = {
            handler = tools.action_handler,
            opts = {
              fetch_key = function()
                return switch("enable_gpt")
              end,
              url = "https://models.inference.ai.azure.com/chat/completions",
              model = "gpt-4o",
              api_type = "openai",
            },
          },

          Translate = {
            handler = tools.qa_handler,
            opts = {
              fetch_key = function()
                return switch("enable_glm")
              end,
              url = "https://open.bigmodel.cn/api/paas/v4/chat/completions",
              model = "glm-4-flash",
              api_type = "zhipu",

              component_width = "60%",
              component_height = "50%",
              query = {
                title = " 󰊿 Trans ",
                hl = { link = "Define" },
              },
              input_box_opts = {
                size = "15%",
                win_options = {
                  winhighlight = "Normal:Normal,FloatBorder:FloatBorder",
                },
              },
              preview_box_opts = {
                size = "85%",
                win_options = {
                  winhighlight = "Normal:Normal,FloatBorder:FloatBorder",
                },
              },
            },
          },

          -- check siliconflow's balance
          UserInfo = {
            handler = function()
              local key = os.getenv("LLM_KEY")
              local res = tools.curl_request_handler(
                "https://api.siliconflow.cn/v1/user/info",
                { "GET", "-H", string.format("'Authorization: Bearer %s'", key) }
              )
              if res ~= nil then
                print("balance: " .. res.data.balance)
              end
            end,
          },
          WordTranslate = {
            handler = tools.flexi_handler,
            prompt = "Translate the following text to Chinese, please only return the translation",
            opts = {
              fetch_key = function()
                return switch("enable_glm")
              end,
              url = "https://open.bigmodel.cn/api/paas/v4/chat/completions",
              model = "glm-4-flash",
              api_type = "zhipu",
              args = [=[return string.format([[curl %s -N -X POST -H "Content-Type: application/json" -H "Authorization: Bearer %s" -d '%s']], url, LLM_KEY, vim.fn.json_encode(body))]=],
              exit_on_move = true,
              enter_flexible_window = false,
            },
          },
          CodeExplain = {
            handler = tools.flexi_handler,
            prompt = "Explain the following code, please only return the explanation, and answer in Chinese",
            opts = {
              fetch_key = function()
                return switch("enable_glm")
              end,
              url = "https://open.bigmodel.cn/api/paas/v4/chat/completions",
              model = "glm-4-flash",
              api_type = "zhipu",
              enter_flexible_window = true,
            },
          },
          CommitMsg = {
            handler = tools.flexi_handler,
            prompt = function()
              return string.format(
                [[You are an expert at following the Conventional Commit specification. Given the git diff listed below, please generate a commit message for me:
1. Start with an action verb (e.g., feat, fix, refactor, chore, etc.), followed by a colon.
2. Briefly mention the file or module name that was changed.
3. Describe the specific changes made.

Examples:
- feat: update common/util.py, added test cases for util.py
- fix: resolve bug in user/auth.py related to login validation
- refactor: optimize database queries in models/query.py

Based on this format, generate appropriate commit messages. Respond with message only. DO NOT format the message in Markdown code blocks, DO NOT use backticks:

```diff
%s
```
]],
                vim.fn.system("git diff --no-ext-diff --staged")
              )
            end,
            opts = {
              fetch_key = function()
                return switch("enable_glm")
              end,
              url = "https://open.bigmodel.cn/api/paas/v4/chat/completions",
              model = "glm-4-flash",
              api_type = "zhipu",
              enter_flexible_window = true,
              apply_visual_selection = false,
            },
          },
        },
    })
    end,
    keys = {
      { "<leader>ac", mode = "n", "<cmd>LLMSessionToggle<cr>" },
      { "<leader>ts", mode = "x", "<cmd>LLMAppHandler WordTranslate<cr>" },
      { "<leader>ae", mode = "v", "<cmd>LLMAppHandler CodeExplain<cr>" },
      { "<leader>at", mode = "n", "<cmd>LLMAppHandler Translate<cr>" },
      { "<leader>tc", mode = "x", "<cmd>LLMAppHandler TestCode<cr>" },
      { "<leader>ao", mode = "x", "<cmd>LLMAppHandler OptimCompare<cr>" },
      { "<leader>au", mode = "n", "<cmd>LLMAppHandler UserInfo<cr>" },
      { "<leader>ag", mode = "n", "<cmd>LLMAppHandler CommitMsg<cr>" },
      -- { "<leader>ao", mode = "x", "<cmd>LLMAppHandler OptimizeCode<cr>" },
    },
  },

local function local_llm_streaming_handler(chunk, line, assistant_output, bufnr, winid, F)
  if not chunk then
    return assistant_output
  end
  local tail = chunk:sub(-1, -1)
  if tail:sub(1, 1) ~= "}" then
    line = line .. chunk
  else
    line = line .. chunk
    local status, data = pcall(vim.fn.json_decode, line)
    if not status or not data.message.content then
      return assistant_output
    end
    assistant_output = assistant_output .. data.message.content
    F.WriteContent(bufnr, winid, data.message.content)
    line = ""
  end
  return assistant_output
end

local function local_llm_parse_handler(chunk)
  local assistant_output = chunk.message.content
  return assistant_output
end

return {
  {
    "Kurama622/llm.nvim",
    dependencies = { "nvim-lua/plenary.nvim", "MunifTanjim/nui.nvim" },
    cmd = { "LLMSesionToggle", "LLMSelectedTextHandler" },
    config = function()
      require("llm").setup({
        url = "http://localhost:11434/api/chat", -- your url
        model = "llama3.2:1b",

        streaming_handler = local_llm_streaming_handler,
        app_handler = {
          WordTranslate = {
            handler = tools.flexi_handler,
            prompt = "Translate the following text to Chinese, please only return the translation",
            opts = {
              parse_handler = local_llm_parse_handler,
              exit_on_move = true,
              enter_flexible_window = false,
            },
          },
        }
      })
    end,
    keys = {
      { "<leader>ac", mode = "n", "<cmd>LLMSessionToggle<cr>" },
    },
  }
}

{
  "kdheepak/lazygit.nvim",
  lazy = true,
  cmd = {
    "LazyGit",
    "LazyGitConfig",
    "LazyGitCurrentFile",
    "LazyGitFilter",
    "LazyGitFilterCurrentFile",
  },
  -- optional for floating window border decoration
  dependencies = {
    "nvim-lua/plenary.nvim",
  },
  config = function()
    vim.keymap.set("t", "<C-c>", function()
      vim.api.nvim_win_close(vim.api.nvim_get_current_win(), true)
      vim.api.nvim_command("LLMAppHandler CommitMsg")
    end, { desc = "AI Commit Msg" })
  end,
}