package rag

import (
	"context"
	"fmt"
	"strings"
	"time"

	"github.com/VictorVargas/rony-llm-agent/pkg/llm"
)

// DefaultCapturePrompt is the summarization instruction EpisodeCapture uses
// when Config doesn't provide one. Consumers localize it by passing their
// own (e.g. the Rony harness passes a Spanish prompt).
const DefaultCapturePrompt = "Summarize the following exchange between a user and an AI assistant " +
	"in 1-2 sentences, in the past tense, focusing on what was asked and what was done or answered. " +
	"Respond ONLY with the summary, no headers or extra commentary."

// captureMaxInputChars bounds how much of the turn is sent to the
// summarizing LLM. Auto-capture runs after every successful turn, so its
// cost must stay small and constant — the start of a long reply carries the
// gist; the tail of a truncated one rarely changes the 1-2 sentence summary.
const captureMaxInputChars = 6000

// EpisodeCapture implements Phase 2 §3.5 auto-capture: at the end of a
// successful turn, an LLM (ideally a small/local one — this runs on every
// turn) condenses the exchange into a 1-2 sentence event and stores it as
// episodic memory, so future sessions can recall "what happened" without the
// user ever having asked to save anything.
type EpisodeCapture struct {
	Memory    Memory
	LLM       llm.LLMClient
	ProjectID string
	// Prompt overrides DefaultCapturePrompt (e.g. for localization).
	Prompt string
}

// Capture summarizes one finished turn and stores it as an episodic
// fragment. toolsUsed (may be empty) is recorded in metadata so a recalled
// episode also says how the work was done. Callers typically run this in a
// background goroutine with its own timeout — a capture failure should never
// block or break the turn that just finished.
func (c *EpisodeCapture) Capture(ctx context.Context, userInput, assistantReply string, toolsUsed ...string) error {
	if c == nil || c.Memory == nil || c.LLM == nil {
		return fmt.Errorf("episode capture: memory and llm are required")
	}
	if strings.TrimSpace(userInput) == "" || strings.TrimSpace(assistantReply) == "" {
		return fmt.Errorf("episode capture: nothing to capture")
	}

	prompt := c.Prompt
	if prompt == "" {
		prompt = DefaultCapturePrompt
	}

	transcript := fmt.Sprintf("User: %s\n\nAssistant: %s", userInput, assistantReply)
	if len(transcript) > captureMaxInputChars {
		transcript = transcript[:captureMaxInputChars]
	}

	resp, err := c.LLM.Generate(ctx, llm.CompletionRequest{
		Messages: []llm.Message{
			{Role: llm.RoleSystem, Content: prompt},
			{Role: llm.RoleUser, Content: transcript},
		},
	})
	if err != nil {
		return fmt.Errorf("episode capture: summarize: %w", err)
	}
	summary := strings.TrimSpace(resp.Content)
	if summary == "" {
		return fmt.Errorf("episode capture: empty summary")
	}

	metadata := map[string]string{
		"date": time.Now().Format("2006-01-02"),
	}
	if len(toolsUsed) > 0 {
		metadata["tools"] = strings.Join(toolsUsed, ",")
	}

	return c.Memory.Add(ctx, Fragment{
		Content:   summary,
		Type:      MemoryEpisodic,
		ProjectID: c.ProjectID,
		Metadata:  metadata,
	})
}