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https://gitcode.com/JianFeeeee/HomeAgent.git
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27183312ad
- 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
101 lines
3.1 KiB
Lua
101 lines
3.1 KiB
Lua
local adapter = {}
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adapter.name = "ollama"
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adapter.version = "2.0.0"
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adapter.endpoint = "/api/chat"
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adapter.headers = {}
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-- Ollama API 格式：{ model, messages, stream, options:{temperature,num_predict} }
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function adapter.transform_request(raw_body)
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local ok, req = pcall(json.decode, raw_body)
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if not ok then return raw_body end
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local ollama_req = {
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model = req.model or "llama3",
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stream = req.stream or false,
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options = {
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temperature = req.temperature or 0.7,
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num_predict = req.max_tokens or 2048
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}
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}
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-- 转换 messages 格式（Ollama messages 支持 images base64 数组）
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if req.messages then
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local msgs = {}
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for _, m in ipairs(req.messages) do
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local text, images
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if type(m.content) == "string" then
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text, images = m.content, nil
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else
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text = ""
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images = {}
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for _, p in ipairs(m.content or {}) do
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if p.type == "text" then
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text = text .. (p.text or "")
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elseif p.type == "image_url" and type(p.image_url) == "table" and p.image_url.url then
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local b64 = string.match(p.image_url.url, "^data:[^,]+;base64,(.+)$")
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if b64 then table.insert(images, b64) end
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end
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end
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if #images == 0 then images = nil end
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end
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local msg = { role = m.role, content = text }
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if images then msg.images = images end
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table.insert(msgs, msg)
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end
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ollama_req.messages = msgs
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end
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return json.encode(ollama_req)
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end
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function adapter.transform_response(raw_body)
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local ok, resp = pcall(json.decode, raw_body)
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if not ok then return raw_body end
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local unified = {
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content = "",
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finish_reason = resp.done_reason or "",
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tool_calls = {},
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usage = { prompt = 0, completion = 0, total = 0 }
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}
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if resp.message then
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unified.content = resp.message.content or ""
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end
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return json.encode(unified)
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end
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function adapter.transform_stream_chunk(raw_chunk)
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local ok, chunk = pcall(json.decode, raw_chunk)
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if not ok then return "" end
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if not chunk.message then return "" end
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local unified = {
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content = chunk.message.content or "",
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done = chunk.done or false
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}
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if chunk.message.reasoning_content then
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unified.reasoning_content = chunk.message.reasoning_content
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end
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if chunk.message.tool_calls then
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local tools = {}
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for _, tc in ipairs(chunk.message.tool_calls) do
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table.insert(tools, {
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index = #tools,
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id = tc.id or ("call_" .. #tools),
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type = "function",
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["function"] = {
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name = tc["function"] and tc["function"].name or "",
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arguments = tc["function"] and (tc["function"].arguments or "{}") or "{}"
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}
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})
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end
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unified.tool_calls = tools
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end
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return json.encode(unified)
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end
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return adapter
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