Cyrene_v2/internal/runtime/model/openai_encode.go

package model

import (
	"encoding/json"
	"fmt"
)

// openAIChatRequest is the JSON body sent to /chat/completions. Field names
// match the provider protocol so the struct marshals directly.
type openAIChatRequest struct {
	Model         string            `json:"model"`
	Messages      []openAIMessage   `json:"messages"`
	Temperature   *float64          `json:"temperature,omitempty"`
	MaxTokens     int               `json:"max_tokens,omitempty"`
	Stream        bool              `json:"stream,omitempty"`
	StreamOptions *openAIStreamOpts `json:"stream_options,omitempty"`
	Tools         []openAITool      `json:"tools,omitempty"`
	// Thinking is DeepSeek's top-level thinking switch. It is sent only for
	// DeepSeek and only from an explicit switch (or an explicit off that must be
	// honoured): leaving it out keeps the provider default, which is ENABLED, so
	// an omitted field is not a way to switch thinking off (design/04 §3.2
	// fact 2).
	Thinking *openAIThinking `json:"thinking,omitempty"`
	// ReasoningEffort is the OpenAI-compatible reasoning strength knob. It is set
	// only after validation against the detected vendor's whitelist (design/04
	// §3.2); an unrecognized value is dropped, never turned into a different tier.
	ReasoningEffort string `json:"reasoning_effort,omitempty"`
}

// openAIThinking is the wire form of DeepSeek's thinking switch: enabled or
// disabled. It is only ever sent to a DeepSeek endpoint.
type openAIThinking struct {
	Type string `json:"type"`
}

// openAIStreamOpts asks the provider to include usage in the final stream chunk.
type openAIStreamOpts struct {
	IncludeUsage bool `json:"include_usage"`
}

// openAIMessage is one request message in the wire body. Content is either a
// plain string (text-only) or an array of {type,text|image_url} parts. Tool
// messages carry ToolCallID (required by OpenAI); assistant messages that
// requested functions carry ToolCalls so the following tool messages can be
// correlated.
type openAIMessage struct {
	Role       string           `json:"role"`
	Content    any              `json:"content"`
	ToolCallID string           `json:"tool_call_id,omitempty"`
	ToolCalls  []openAIToolCall `json:"tool_calls,omitempty"`
}

// openAIToolCall is the wire form of one assistant tool_call in a request. OpenAI
// requires each subsequent tool message to reference the id back to these calls.
type openAIToolCall struct {
	ID       string           `json:"id"`
	Type     string           `json:"type"`
	Function openAIToolCallFn `json:"function"`
}

// openAITool is the wire form of a function tool schema (M2 placeholder).
type openAITool struct {
	Type     string       `json:"type"`
	Function openAIToolFn `json:"function"`
}

// openAIToolFn carries the function definition.
type openAIToolFn struct {
	Name        string `json:"name"`
	Description string `json:"description,omitempty"`
	Parameters  any    `json:"parameters,omitempty"`
}

// openAIToolCallFn is the function part of a streaming tool-call fragment.
type openAIToolCallFn struct {
	Name      string `json:"name"`
	Arguments string `json:"arguments"`
}

func (a *OpenAIChatAdapter) buildRequest(req Request, stream bool) ([]byte, error) {
	msgs, err := buildMessages(req.Messages)
	if err != nil {
		return nil, err
	}
	// The vendor behind an OpenAI-compatible endpoint decides which
	// reasoning_effort tiers are legal and whether it has a thinking switch;
	// classify it from the resolved model (and the base URL as a fallback) before
	// touching the request (design/04 §3.2).
	vendor := reasoningVendorFor(req.Model, a.baseURL)
	effort := resolveReasoningEffort(a.log, vendor, req.ReasoningEffort, req.Model)
	thinking, effort := resolveOpenAIReasoning(a.log, vendor, req.Model, req.Thinking, effort)
	reportForcedToolChoiceWithThinking(a.log, req.Model, req.ToolChoice, openAIThinkingOn(thinking, effort))
	wire := openAIChatRequest{
		Model:           req.Model,
		Messages:        msgs,
		Temperature:     req.Temperature,
		MaxTokens:       req.MaxTokens,
		Stream:          stream,
		Tools:           buildTools(req.Tools),
		Thinking:        thinking,
		ReasoningEffort: effort,
	}
	if stream {
		wire.StreamOptions = &openAIStreamOpts{IncludeUsage: true}
	}
	buf, err := json.Marshal(wire)
	if err != nil {
		return nil, fmt.Errorf("model: %w: marshal request: %v", ErrBadRequest, err)
	}
	return buf, nil
}

func buildMessages(msgs []Message) ([]openAIMessage, error) {
	out := make([]openAIMessage, 0, len(msgs))
	for _, m := range msgs {
		wire, err := encodeOpenAIMessage(m)
		if err != nil {
			return nil, err
		}
		out = append(out, wire)
	}
	return out, nil
}

// encodeOpenAIMessage renders one normalized message in OpenAI wire form. A
// RoleTool turn becomes a tool message carrying tool_call_id (required by OpenAI,
// and the audit's gap); an assistant turn that advertised tool calls carries the
// corresponding tool_calls array so the provider can correlate the tool messages.
func encodeOpenAIMessage(m Message) (openAIMessage, error) {
	if m.Role == RoleTool {
		return openAIMessage{
			Role:       string(RoleTool),
			ToolCallID: toolMessageCallID(m),
			Content:    messageText(m),
		}, nil
	}
	content, err := encodeContent(m.Content)
	if err != nil {
		return openAIMessage{}, err
	}
	return openAIMessage{Role: string(m.Role), Content: content, ToolCalls: encodeToolCalls(m.Content)}, nil
}

// toolMessageCallID resolves the tool_call_id for a RoleTool turn: the
// message-level id, else the id carried on the first tool-result part.
func toolMessageCallID(m Message) string {
	if m.ToolCallID != "" {
		return m.ToolCallID
	}
	for _, p := range m.Content {
		if p.ToolCallID != "" {
			return p.ToolCallID
		}
	}
	return ""
}

// encodeToolCalls builds the assistant tool_calls array from a turn's tool-call
// parts. Arguments are serialized to JSON because OpenAI expects a string.
func encodeToolCalls(parts []Content) []openAIToolCall {
	calls := make([]openAIToolCall, 0, len(parts))
	for _, p := range parts {
		if p.Type != ContentTypeToolCall {
			continue
		}
		arguments := "{}"
		if len(p.ToolArgs) > 0 {
			if b, err := json.Marshal(p.ToolArgs); err == nil {
				arguments = string(b)
			}
		}
		calls = append(calls, openAIToolCall{
			ID:       p.ToolCallID,
			Type:     "function",
			Function: openAIToolCallFn{Name: p.ToolCallName, Arguments: arguments},
		})
	}
	return calls
}

func encodeContent(parts []Content) (any, error) {
	if len(parts) == 0 {
		return "", nil
	}
	arr := make([]any, 0, len(parts))
	for _, p := range parts {
		switch p.Type {
		case ContentTypeText:
			arr = append(arr, map[string]any{"type": "text", "text": p.Text})
		case ContentTypeImage:
			arr = append(arr, map[string]any{
				"type":      "image_url",
				"image_url": map[string]any{"url": p.ImageURL},
			})
		case ContentTypeToolCall, ContentTypeToolResult:
			// Tool-call and tool-result parts are encoded at the message level
			// (tool_calls array / tool_call_id), never as text-image content.
			continue
		default:
			return nil, fmt.Errorf("model: %w: unsupported content type %q", ErrBadRequest, p.Type)
		}
	}
	if len(arr) == 0 {
		return "", nil
	}
	if len(arr) == 1 {
		if blk, ok := arr[0].(map[string]any); ok && blk["type"] == "image_url" {
			return arr, nil
		}
		return arr[0].(map[string]any)["text"], nil
	}
	return arr, nil
}

func buildTools(tools []ToolSpec) []openAITool {
	if len(tools) == 0 {
		return nil
	}
	out := make([]openAITool, 0, len(tools))
	for _, t := range tools {
		out = append(out, openAITool{Type: "function", Function: openAIToolFn{
			Name:        t.Name,
			Description: t.Description,
			Parameters:  t.Parameters,
		}})
	}
	return out
}