core: pass ReasoningContent to assistant messages in process.go

- process.go: attach resp.ReasoningContent when building assistant messages - deepseek.lua v2.1.0: remove last_reasoning closure hack; rely on core-provided reasoning_content in messages - openai.lua: strip reasoning_content from messages in transform_request (not supported by OpenAI API)
2026-09-21 17:38:10 +00:00 · 2026-07-28 17:06:59 +08:00
parent f91b20ee16
commit 51f190e0b6
10 changed files with 263 additions and 89 deletions
--- a/assets/docs/en/ADAPTER.md
+++ b/assets/docs/en/ADAPTER.md
@ -2,9 +2,11 @@

 # Lua Adapter — LLM Source Adaptation Guide

-Each LLM API source corresponds to a Lua script, responsible for request transformation (Go unified format → API format) and response transformation (API format → Go unified format).
+> **Kernel Internal Format Notice**: The CompletionRequest / CompletionResponse JSON formats described below are the kernel LLM adapter's **private internal wire protocol**.
+> These types are defined as Go structs in `internal/agent/api/provider.go` and are **not exported as an external API**.
+> This document publicly describes this format solely as the contract standard for Lua adapter scripts — users follow this documentation to write Lua scripts that integrate any LLM API source.

-<img src="../../assets/branding/mascot-xiaozhai.webp" width="20" style="border-radius:50%;vertical-align:middle"> :
+Each LLM API source corresponds to a Lua script, responsible for request transformation (kernel private format → API format) and response transformation (API format → kernel private format).

 ## Adapter Contract

@ -19,59 +21,105 @@ adapter.version = "2.0.0"
 adapter.endpoint = "/v1/chat/completions"   -- API path, appended to base_url
 adapter.headers = {}                        -- Additional HTTP request headers

-- Request transformation: Go → API
+-- Request transformation: kernel private format → API format
 function adapter.transform_request(raw_json)
-    -- raw_json: Go's CompletionRequest JSON string
+    -- raw_json: Kernel's CompletionRequest JSON string (full fields below)
    -- Returns: JSON string to send to API
    return transformed_json
 end

-- Response transformation: API → Go
+-- Response transformation: API format → kernel private format
 function adapter.transform_response(raw_json)
    -- raw_json: API's raw response JSON string
-    -- Returns: Unified CompletionResponse JSON string
-    -- Unified format:
-    --   { content: "", finish_reason: "", token_usage: { prompt: N, completion: N, total: N }, tool_calls?: [...] }
+    -- Returns: Unified CompletionResponse JSON string (full format below)
    return unified_json
 end

 -- Stream chunk transformation (optional)
 function adapter.transform_stream_chunk(raw_line)
-    -- raw_line: JSON string after data: in SSE
-    -- Returns: JSON of { content: "", done: bool }, return "" to skip this chunk
+    -- raw_line: Raw JSON string after data: in SSE
+    -- Returns: Unified StreamChunk JSON string (format below), return "" to skip this chunk
    return chunk_json
 end

 return adapter
 ```

-<img src="../../assets/branding/mascot-xiaozhai.webp" width="20" style="border-radius:50%;vertical-align:middle"> :
-
-## Unified CompletionRequest Format (Go → Adapter)
+## Kernel Private CompletionRequest Format (Go → Lua)

 ```json
 {
  "model": "deepseek-v4-flash",
  "messages": [
-    { "role": "system", "content": "..." },
-    { "role": "user", "content": "..." },
-    { "role": "assistant", "content": "...", "tool_calls": [...] }
+    { "role": "system", "content": "You are an AI assistant" },
+    { "role": "user", "content": "Hello" },
+    { "role": "assistant", "content": "Hi!", "reasoning_content": "thinking...", "tool_calls": [ { "id": "call_xxx", "type": "function", "function": { "name": "get_weather", "arguments": "{\"city\": \"Beijing\"}" } } ] },
+    { "role": "tool", "tool_call_id": "call_xxx", "content": "Weather: sunny" }
  ],
  "temperature": 0.7,
  "max_tokens": 4096,
  "stream": false,
-  "tools": [...],
-  "tool_choice": "auto"
+  "tools": [ { "type": "function", "function": { "name": "get_weather", "description": "...", "parameters": { ... } } } ],
+  "tool_choice": "auto",
+  "disable_thinking": true
 }
 ```

-<img src="../../assets/branding/mascot-xiaozhai.webp" width="20" style="border-radius:50%;vertical-align:middle"> :
+### Field Reference

-## Unified CompletionResponse Format (Adapter → Go)
+| Field | Type | Required | Description |
+|-------|------|----------|-------------|
+| `model` | string | no | Model name, auto-filled by kernel from BaseConfig.Model |
+| `messages` | array | yes | Message list (see Message below) |
+| `temperature` | float | no | Sampling temperature, default 0.7 |
+| `max_tokens` | int | no | Max generated tokens, default 4096 |
+| `stream` | bool | no | Whether to stream output |
+| `tools` | array | no | Tool definitions (OpenAI tools format) |
+| `tool_choice` | string/object | no | Tool selection strategy: "auto" / "none" / { type: "function", function: { name: "..." } } |
+| `disable_thinking` | bool | no | Disable CoT reasoning (for reasoning models like DeepSeek-R1) |
+
+**Extra fields**: The kernel may merge additional keys into the top-level JSON object (via an internal ExtraBody mechanism not listed in this table). Lua scripts should pass through or handle these fields as needed.
+
+### Message Object
+
+| Field | Type | Required | Description |
+|-------|------|----------|-------------|
+| `role` | string | yes | Role: `system` / `user` / `assistant` / `tool` |
+| `content` | string/array | no | Text content; for multimodal, can be an array of ContentBlock (see below) |
+| `reasoning_content` | string | no | Chain-of-thought reasoning content (assistant only, if available) |
+| `tool_call_id` | string | no | Tool call ID (tool role only, corresponding to assistant's tool_calls) |
+| `tool_calls` | array | no | Tool call list (assistant role only) |
+
+### ContentBlock Object (Multimodal Messages)
+
+When `content` is an array, each element format:
+
+```json
+{ "type": "text", "text": "Describe the image" }
+{ "type": "image_url", "image_url": { "url": "https://...", "detail": "auto" } }
+{ "type": "audio_url", "audio_url": { "url": "https://..." } }
+```
+
+### ToolCall Object (in CompletionRequest messages)
+
+| Field | Type | Required | Description |
+|-------|------|----------|-------------|
+| `id` | string | yes | Unique tool call ID |
+| `type` | string | yes | Always `"function"` |
+| `function` | object | yes | Contains `name` (string) and `arguments` (JSON **string**, not an object!) |
+
+**Note**: In CompletionRequest messages, tool_calls use the OpenAI wire format:
+`{id, type, function: {name: string, arguments: string}}` — `arguments` is a **stringified JSON**, not an object.
+The kernel's `Message.MarshalJSON` performs this conversion.
+
+In the CompletionResponse (returned by `transform_response`), tool_calls use a **flat format** as documented in the next section.
+
+## Kernel Private CompletionResponse Format (Lua → Go)

 ```json
 {
  "content": "Response content",
+  "reasoning_content": "Chain of thought",
  "finish_reason": "stop",
  "token_usage": { "prompt": 10, "completion": 20, "total": 30 },
  "tool_calls": [
@ -80,7 +128,32 @@ return adapter
 }
 ```

-<img src="../../assets/branding/mascot-xiaozhai.webp" width="20" style="border-radius:50%;vertical-align:middle"> :
+### Field Reference
+
+| Field | Type | Required | Description |
+|-------|------|----------|-------------|
+| `content` | string | yes | Response text |
+| `reasoning_content` | string | no | Chain-of-thought content (if returned by model) |
+| `finish_reason` | string | no | Finish reason: `"stop"` / `"tool_calls"` / `"length"` etc. |
+| `token_usage` | object | no | Token usage with `prompt` / `completion` / `total` (int) fields |
+| `tool_calls` | array | no | Tool call list in **flat format**: `{id, type, name, arguments: {object}}`. This differs from the `function:{name, arguments:string}` wire format used inside CompletionRequest messages — do not confuse them. |
+
+## Stream Chunk Format (StreamChunk)
+
+`transform_stream_chunk` should return JSON in this format:
+
+```json
+{ "content": "delta text", "done": false }
+{ "content": "", "done": true, "tool_call": { "id": "call_xxx", "type": "function", "name": "get_weather", "arguments": { "city": "Bei" } } }
+```
+
+| Field | Type | Required | Description |
+|-------|------|----------|-------------|
+| `content` | string | yes | Delta content for this chunk |
+| `done` | bool | yes | Whether stream is finished |
+| `tool_call` | object | no | Tool call delta (arguments may be partial/incomplete JSON) |
+
+Return empty string `""` to skip the chunk.

 ## Lua VM Built-in Functions

@ -94,14 +167,12 @@ return adapter

 `http_post(url, body)` — Perform HTTP POST request, returns response body as string

-<img src="../../assets/branding/mascot-xiaozhai.webp" width="20" style="border-radius:50%;vertical-align:middle"> :
-
 ## Adapting Typical APIs

 | API | endpoint | auth method | Format differences |
 |-----|----------|-------------|-------------------|
 | **OpenAI** | `/chat/completions` | `Authorization: Bearer <key>` | Standard OpenAI format |
-| **DeepSeek** | `/chat/completions` | `Authorization: Bearer <key>` | OpenAI compatible, forces temperature=0 |
+| **DeepSeek** | `/chat/completions` | `Authorization: Bearer <key>` | OpenAI compatible, forces temperature=1 |
 | **Anthropic** | `/v1/messages` | `x-api-key: <key>` | Messages API, system message separated, content as block array |
 | **Gemini** | `/v1/models/{model}:generateContent` | `?key=<key>` or Bearer | contents/parts format, role uses model instead of assistant |
 | **Mistral** | `/v1/chat/completions` | `Authorization: Bearer <key>` | OpenAI compatible |
@ -109,12 +180,14 @@ return adapter
 | **GitHub Models** | `/chat/completions` | `Authorization: Bearer <pat>` | OpenAI compatible |
 | **Ollama** | `/api/chat` | None | Different options format |

-<img src="../../assets/branding/mascot-xiaozhai.webp" width="20" style="border-radius:50%;vertical-align:middle"> :
+## Steps to Add a New LLM Source

-## Steps to Add a New Source
+1. Write a Lua adapter script defining `transform_request` and `transform_response`
+2. (Optional) Define `transform_stream_chunk` for streaming support
+3. Place the script `<name>.lua` in the `adapters/` subdirectory under the data directory (i.e. `daemon.data_dir/adapters/`)
+4. Reference the adapter in configuration: `"adapter": "<name>"` (must match `adapter.name` in the script)
+5. No recompilation needed — the VM automatically scans and loads all `.lua` files from that directory at startup

-1. Create `<name>.lua` under `internal/lua/adapters/`
-2. Script defines `transform_request` and `transform_response`
-3. (Optional) Define `transform_stream_chunk` for streaming support
-4. Build verification: `go build ./cmd/homed/`
-5. Test verification: `go test ./...`
+> **Note**: Built-in adapters are located in `internal/lua/adapters/` and compiled into the binary.
+> User-defined custom adapters **do not** need to go into the source directory — place them in `daemon.data_dir/adapters/`.
+> If the same adapter name exists in both locations, the custom file takes precedence.