adapters: 支持多模态（对照 llmsproxy）

- ollama: content 数组拆分文本/images(base64)，映射到 Ollama messages.images；
  流式透传 reasoning_content 与增量 tool_calls
- anthropic: OpenAI content(字符串/数组) 转 Anthropic blocks(文本 + image{source})
  + thinking/空 arguments tool_use/input_json_delta 流
- openai 透传 adapter 已保留多模态 content 数组（验收确认）
- 新增多模态单测：ollama images / anthropic image.source / openai passthrough

验证: go test ./... 27 包 0 失败；Windows 交叉编译通过；部署后服务健康

internal/lua/adapters/ollama.lua

@@ -19,11 +19,29 @@ function adapter.transform_request(raw_body)
         }
     }
 
-    -- 转换 messages 格式（Ollama 兼容 OpenAI 的 messages 格式）
+    -- 转换 messages 格式（Ollama messages 支持 images base64 数组）
     if req.messages then
         local msgs = {}
         for _, m in ipairs(req.messages) do
-            table.insert(msgs, { role = m.role, content = m.content })
+            local text, images
+            if type(m.content) == "string" then
+                text, images = m.content, nil
+            else
+                text = ""
+                images = {}
+                for _, p in ipairs(m.content or {}) do
+                    if p.type == "text" then
+                        text = text .. (p.text or "")
+                    elseif p.type == "image_url" and type(p.image_url) == "table" and p.image_url.url then
+                        local b64 = string.match(p.image_url.url, "^data:[^,]+;base64,(.+)$")
+                        if b64 then table.insert(images, b64) end
+                    end
+                end
+                if #images == 0 then images = nil end
+            end
+            local msg = { role = m.role, content = text }
+            if images then msg.images = images end
+            table.insert(msgs, msg)
         end
         ollama_req.messages = msgs
     end
@@ -54,10 +72,29 @@ function adapter.transform_stream_chunk(raw_chunk)
     if not ok then return "" end
     if not chunk.message then return "" end
 
-    return json.encode({
+    local unified = {
         content = chunk.message.content or "",
         done = chunk.done or false
-    })
+    }
+    if chunk.message.reasoning_content then
+        unified.reasoning_content = chunk.message.reasoning_content
+    end
+    if chunk.message.tool_calls then
+        local tools = {}
+        for _, tc in ipairs(chunk.message.tool_calls) do
+            table.insert(tools, {
+                index = #tools,
+                id = tc.id or ("call_" .. #tools),
+                type = "function",
+                ["function"] = {
+                    name = tc["function"] and tc["function"].name or "",
+                    arguments = tc["function"] and (tc["function"].arguments or "{}") or "{}"
+                }
+            })
+        end
+        unified.tool_calls = tools
+    end
+    return json.encode(unified)
 end
 
 return adapter