fix: Lua adapter fixes + add ReasoningContent to CompletionResponse

- Fix syntax error: tc.function -> tc["function"] (function is Lua keyword)
- Fix empty tool_calls: Lua returns nil instead of empty table ({} vs [] in JSON)
- Fix token_usage key name in unified response (usage -> token_usage)
- Add ReasoningContent to CompletionResponse struct
- Nits: jsonTable init, import ordering

internal/lua/adapters/deepseek.lua

@@ -1,22 +1,74 @@
 local adapter = {}
 
 adapter.name = "deepseek"
-adapter.version = "1.0.0"
+adapter.version = "2.0.0"
+adapter.endpoint = "/chat/completions"
+adapter.headers = {}
 
-function adapter.transform_request(input)
-    local messages = input.messages or {}
-    local result = {
-        model = input.model or "deepseek-chat",
-        messages = messages,
-        temperature = input.temperature or 0.0,
-        max_tokens = input.max_tokens or 4096,
-        stream = input.stream or false
-    }
-    return result
+-- DeepSeek 格式与 OpenAI 兼容，只需要强制 temperature=0（禁用 thinking）
+function adapter.transform_request(raw_body)
+    local ok, req = pcall(json.decode, raw_body)
+    if not ok then return raw_body end
+    req.model = req.model or "deepseek-chat"
+    req.temperature = 0.0
+    req.stream = req.stream or false
+    return json.encode(req)
 end
 
-function adapter.transform_response(raw)
-    return raw
+function adapter.transform_response(raw_body)
+    local ok, resp = pcall(json.decode, raw_body)
+    if not ok then return raw_body end
+
+    local unified = {
+        content = "",
+        finish_reason = "",
+        token_usage = { prompt = 0, completion = 0, total = 0 }
+    }
+
+    if resp.usage then
+        unified.token_usage.prompt = resp.usage.prompt_tokens or 0
+        unified.token_usage.completion = resp.usage.completion_tokens or 0
+        unified.token_usage.total = resp.usage.total_tokens or 0
+    end
+
+    if resp.choices and #resp.choices > 0 then
+        local ch = resp.choices[1]
+        if ch.message then
+            unified.content = ch.message.content or ""
+            if ch.message.reasoning_content then
+                unified.reasoning_content = ch.message.reasoning_content
+            end
+            if ch.message.tool_calls then
+                local tcs = {}
+                for _, tc in ipairs(ch.message.tool_calls) do
+                    local args_ok, args = pcall(json.decode, tc["function"].arguments)
+                    if not args_ok then args = {} end
+                    table.insert(tcs, {
+                        id = tc.id,
+                        type = tc.type or "function",
+                        name = tc["function"].name,
+                        arguments = args
+                    })
+                end
+                unified.tool_calls = tcs
+            end
+        end
+        unified.finish_reason = ch.finish_reason or ""
+    end
+
+    return json.encode(unified)
+end
+
+function adapter.transform_stream_chunk(raw_chunk)
+    local ok, chunk = pcall(json.decode, raw_chunk)
+    if not ok then return "" end
+    if not chunk.choices or #chunk.choices == 0 then return "" end
+    local delta = chunk.choices[1].delta or {}
+    local fr = chunk.choices[1].finish_reason
+    return json.encode({
+        content = delta.content or "",
+        done = (fr ~= nil)
+    })
 end
 
 return adapter

internal/lua/adapters/ollama.lua

@@ -1,24 +1,63 @@
 local adapter = {}
 
 adapter.name = "ollama"
-adapter.version = "1.0.0"
+adapter.version = "2.0.0"
+adapter.endpoint = "/api/chat"
+adapter.headers = {}
 
-function adapter.transform_request(input)
-    local messages = input.messages or {}
-    local result = {
-        model = input.model or "llama3",
-        messages = messages,
-        stream = input.stream or false,
+-- Ollama API 格式：{ model, messages, stream, options:{temperature,num_predict} }
+function adapter.transform_request(raw_body)
+    local ok, req = pcall(json.decode, raw_body)
+    if not ok then return raw_body end
+
+    local ollama_req = {
+        model = req.model or "llama3",
+        stream = req.stream or false,
         options = {
-            temperature = input.temperature or 0.7,
-            num_predict = input.max_tokens or 2048
+            temperature = req.temperature or 0.7,
+            num_predict = req.max_tokens or 2048
         }
     }
-    return result
+
+    -- 转换 messages 格式（Ollama 兼容 OpenAI 的 messages 格式）
+    if req.messages then
+        local msgs = {}
+        for _, m in ipairs(req.messages) do
+            table.insert(msgs, { role = m.role, content = m.content })
+        end
+        ollama_req.messages = msgs
+    end
+
+    return json.encode(ollama_req)
 end
 
-function adapter.transform_response(raw)
-    return raw
+function adapter.transform_response(raw_body)
+    local ok, resp = pcall(json.decode, raw_body)
+    if not ok then return raw_body end
+
+    local unified = {
+        content = "",
+        finish_reason = resp.done_reason or "",
+        tool_calls = {},
+        usage = { prompt = 0, completion = 0, total = 0 }
+    }
+
+    if resp.message then
+        unified.content = resp.message.content or ""
+    end
+
+    return json.encode(unified)
+end
+
+function adapter.transform_stream_chunk(raw_chunk)
+    local ok, chunk = pcall(json.decode, raw_chunk)
+    if not ok then return "" end
+    if not chunk.message then return "" end
+
+    return json.encode({
+        content = chunk.message.content or "",
+        done = chunk.done or false
+    })
 end
 
 return adapter

internal/lua/adapters/openai.lua

@@ -1,22 +1,76 @@
 local adapter = {}
 
 adapter.name = "openai"
-adapter.version = "1.0.0"
+adapter.version = "2.0.0"
+adapter.endpoint = "/chat/completions"
+adapter.headers = {}
 
-function adapter.transform_request(input)
-    local messages = input.messages or {}
-    local result = {
-        model = input.model or "gpt-4",
-        messages = messages,
-        temperature = input.temperature or 0.7,
-        max_tokens = input.max_tokens or 2048,
-        stream = input.stream or false
-    }
-    return result
+-- raw_body: JSON string as received from Go (CompletionRequest marshalled)
+-- return: transformed JSON string to send to API
+function adapter.transform_request(raw_body)
+    return raw_body
 end
 
-function adapter.transform_response(raw)
-    return raw
+-- raw_body: JSON string from HTTP response body
+-- return: unified JSON string in CompletionResponse format
+function adapter.transform_response(raw_body)
+    local ok, resp = pcall(json.decode, raw_body)
+    if not ok then return raw_body end
+
+    local unified = {
+        content = "",
+        finish_reason = "",
+        token_usage = { prompt = 0, completion = 0, total = 0 }
+    }
+
+    if resp.usage then
+        unified.token_usage.prompt = resp.usage.prompt_tokens or 0
+        unified.token_usage.completion = resp.usage.completion_tokens or 0
+        unified.token_usage.total = resp.usage.total_tokens or 0
+    end
+
+    if resp.choices and #resp.choices > 0 then
+        local ch = resp.choices[1]
+        if ch.message then
+            unified.content = ch.message.content or ""
+            if ch.message.reasoning_content then
+                unified.reasoning_content = ch.message.reasoning_content
+            end
+            if ch.message.tool_calls then
+                local tcs = {}
+                for _, tc in ipairs(ch.message.tool_calls) do
+                    local args_ok, args = pcall(json.decode, tc["function"].arguments)
+                    if not args_ok then args = {} end
+                    table.insert(tcs, {
+                        id = tc.id,
+                        type = tc.type or "function",
+                        name = tc["function"].name,
+                        arguments = args
+                    })
+                end
+                unified.tool_calls = tcs
+            end
+        end
+        unified.finish_reason = ch.finish_reason or ""
+    end
+
+    return json.encode(unified)
+end
+
+-- raw_chunk: single SSE data line (after "data: " prefix)
+-- return: unified chunk JSON string, or "" to skip
+function adapter.transform_stream_chunk(raw_chunk)
+    local ok, chunk = pcall(json.decode, raw_chunk)
+    if not ok then return "" end
+
+    if not chunk.choices or #chunk.choices == 0 then return "" end
+    local delta = chunk.choices[1].delta or {}
+    local fr = chunk.choices[1].finish_reason
+
+    return json.encode({
+        content = delta.content or "",
+        done = (fr ~= nil)
+    })
 end
 
 return adapter