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/anthropic.lua

@@ -11,13 +11,42 @@ function adapter.transform_request(raw_body)
     local ok, req = pcall(json.decode, raw_body)
     if not ok then return raw_body end
 
+    -- 将 OpenAI 风格 content（字符串或 [{type:*}] 数组）拆成文本/图片块
+    local function collect_blocks(content)
+        if type(content) == "string" then
+            return { { type = "text", text = content } }
+        end
+        local blocks = {}
+        for _, p in ipairs(content or {}) do
+            if p.type == "text" then
+                table.insert(blocks, { type = "text", text = p.text })
+            elseif p.type == "image_url" and type(p.image_url) == "table" and p.image_url.url then
+                local mt, b64 = string.match(p.image_url.url, "^data:([^,]+);base64,(.+)$")
+                if b64 then
+                    table.insert(blocks, { type = "image", source = { type = "base64", media_type = mt or "image/png", data = b64 } })
+                else
+                    table.insert(blocks, { type = "image", source = { type = "url", url = p.image_url.url } })
+                end
+            end
+        end
+        return blocks
+    end
+    local function text_of(content)
+        if type(content) == "string" then return content end
+        local t = ""
+        for _, p in ipairs(content or {}) do
+            if p.type == "text" and p.text then t = t .. p.text end
+        end
+        return t
+    end
+
     local msgs = {}
     local system = ""
     for _, m in ipairs(req.messages or {}) do
         if m.role == "system" then
-            system = system .. m.content .. "\n"
+            system = system .. text_of(m.content) .. "\n"
         else
-            table.insert(msgs, { role = m.role, content = m.content })
+            table.insert(msgs, { role = m.role, content = collect_blocks(m.content) })
         end
     end
 
@@ -74,12 +103,41 @@ function adapter.transform_stream_chunk(raw_chunk)
     if chunk.type == "message_delta" then
         return json.encode({ content = "", done = (chunk.delta and chunk.delta.stop_reason ~= nil) })
     end
+    if chunk.type == "content_block_start" and chunk.content_block
+        and chunk.content_block.type == "tool_use" then
+        -- first fragment of a tool call: emit index + id + name, empty args
+        return json.encode({
+            content = "", done = false,
+            tool_calls = { {
+                index = chunk.index or 0,
+                id = chunk.content_block.id or "",
+                type = "function",
+                ["function"] = { name = chunk.content_block.name or "", arguments = "" }
+            } }
+        })
+    end
     if chunk.type == "content_block_delta" and chunk.delta then
+        if chunk.delta.type == "input_json_delta" then
+            -- incremental JSON fragment; clients accumulate across chunks
+            local unified = { content = "", done = false, tool_calls = { {
+                index = chunk.index or 0,
+                id = "",
+                type = "function",
+                ["function"] = { name = "", arguments = chunk.delta.partial_json or "" }
+            } } }
+            return json.encode(unified)
+        end
+        if chunk.delta.type == "thinking_delta" and chunk.delta.thinking then
+            return json.encode({ content = "", done = false, reasoning_content = chunk.delta.thinking })
+        end
         return json.encode({ content = chunk.delta.text or "", done = false })
     end
     if chunk.type == "message_stop" then
         return json.encode({ content = "", done = true })
     end
+    if chunk.type == "content_block_stop" then
+        return json.encode({ content = "", done = false })
+    end
     return ""
 end