marqant 1.0.0

//! Universal Theoglyphic Language Pipeline
//! Correct flow: Raw → UTL → Analysis/Storage → Human(lang)

use anyhow::Result;

/// The Universal Pipeline: Everything goes through UTL
///
/// ```
/// [Publisher/Word/PDF] → Extract → [Translate to UTL] → Analyze → [UTL Format] → Translate → [English/Japanese/etc]
///                                          ↑                             ↓
///                                    CRITICAL STEP                [MEM|8 Wave Storage]
/// ```
#[derive(Debug, Clone)]
pub struct UTLPipeline {
    pub raw_input: Vec<u8>,
    pub utl_representation: String,
    pub analysis: UTLAnalysis,
    pub wave_signature: Vec<f32>,
}

#[derive(Debug, Clone)]
pub struct UTLAnalysis {
    /// Analyzed AFTER translation to UTL
    pub genre: String,
    pub temporal_context: String,
    pub emotional_valence: String,
    pub relationships: Vec<String>,
}

impl UTLPipeline {
    /// Step 1: Extract raw text from any format
    pub fn extract(input: &[u8]) -> Result<String> {
        // Extract text from PDF, Publisher, Word, etc.
        // This is format-specific extraction only
        // NO interpretation yet!
        Ok(String::from_utf8_lossy(input).to_string())
    }

    /// Step 2: IMMEDIATELY translate to UTL
    /// This is where the magic happens - we go from human language to universal symbols
    pub fn translate_to_utl(raw_text: &str) -> Result<String> {
        let mut utl = String::new();

        // Parse sentences and convert to theoglyphic symbols
        for sentence in raw_text.split('.') {
            let sentence = sentence.trim();
            if sentence.is_empty() {
                continue;
            }

            // Convert each concept to its theoglyphic representation
            utl.push_str(&Self::text_to_theoglyphs(sentence));
            utl.push_str(" ⧖ "); // Add UDC delay marker between thoughts
        }

        Ok(utl)
    }

    /// Convert text concepts to theoglyphic symbols
    fn text_to_theoglyphs(text: &str) -> String {
        let lower = text.to_lowercase();
        let mut glyphs = Vec::new();

        // Basic concept mapping (would be much more sophisticated)
        // This is where we map English concepts to UTL symbols

        // Subject detection
        if lower.contains(" i ")
            || lower.starts_with("i ")
            || lower.ends_with(" i")
            || lower.contains("me ")
            || lower.contains(" me")
            || lower.starts_with("me ")
            || lower.ends_with(" me")
        {
            glyphs.push("🙋"); // Self symbol
        }
        if lower.contains(" you ") || lower.starts_with("you ") || lower.ends_with(" you") {
            glyphs.push("👤"); // Other symbol
        }

        // Time markers
        if lower.contains("was") || lower.contains("were") || lower.contains("being") {
            glyphs.push("⏮"); // Past
        }
        if lower.contains("is ")
            || lower.contains("are ")
            || lower.contains(" am ")
            || lower.starts_with("am ")
            || lower.ends_with(" am")
        {
            glyphs.push("⏺"); // Present
        }
        if lower.contains(" will ") || lower.starts_with("will ") || lower.ends_with(" will") {
            glyphs.push("⏭"); // Future
        }

        // Action detection
        if lower.contains("love") {
            glyphs.push("❤️");
        }
        if lower.contains("think") || lower.contains("thought") {
            glyphs.push("🧠");
        }
        if lower.contains("remember") || lower.contains("memory") {
            glyphs.push("💭");
        }
        if lower.contains("write") || lower.contains("wrote") {
            glyphs.push("✍️");
        }

        // Emotion detection
        if lower.contains("happy") || lower.contains("joy") {
            glyphs.push("😊");
        }
        if lower.contains("sad") || lower.contains("cry") {
            glyphs.push("😢");
        }
        if lower.contains("angry") || lower.contains("mad") {
            glyphs.push("😡");
        }

        // Logical operators
        if lower.contains(" and ") {
            glyphs.push("∧");
        }
        if lower.contains(" or ") {
            glyphs.push("∨");
        }
        if lower.contains(" not ") || lower.contains("n't") {
            glyphs.push("¬");
        }
        if lower.contains(" if ") {
            glyphs.push("→");
        }

        // Quantifiers
        if lower.contains("all ") || lower.contains("every") {
            glyphs.push("∀");
        }
        if lower.contains("some ") || lower.contains("exist") {
            glyphs.push("∃");
        }

        // Recursive/self-reference markers
        if lower.contains("itself") || lower.contains("myself") {
            glyphs.push("🔄");
        }

        glyphs.join("")
    }

    /// Step 3: Analyze the UTL (not the raw text!)
    pub fn analyze_utl(utl: &str) -> Result<UTLAnalysis> {
        // Now we analyze the SYMBOLIC representation
        // This is much more accurate because UTL has clear semantic markers

        let mut genre = "unknown";
        let mut temporal = "present";
        let mut emotion = "neutral";

        // Genre detection from UTL patterns
        if utl.contains("📖") {
            genre = "fiction";
        } else if utl.contains("💭") && utl.contains("⏮") {
            genre = "memoir";
        } else if utl.contains("✉️") {
            genre = "letter";
        }

        // Temporal analysis from UTL
        let past_count = utl.matches("⏮").count();
        let present_count = utl.matches("⏺").count();
        let future_count = utl.matches("⏭").count();

        if past_count > present_count && past_count > future_count {
            temporal = "past";
        } else if future_count > present_count {
            temporal = "future";
        }

        // Emotional analysis from UTL
        if utl.contains("😊") {
            emotion = "joy";
        } else if utl.contains("😢") {
            emotion = "sadness";
        } else if utl.contains("😡") {
            emotion = "anger";
        }

        // Relationship extraction
        let mut relationships = Vec::new();
        if utl.contains("🙋") && utl.contains("👤") {
            relationships.push("self-other".to_string());
        }
        if utl.contains("❤️") {
            relationships.push("love".to_string());
        }

        Ok(UTLAnalysis {
            genre: genre.to_string(),
            temporal_context: temporal.to_string(),
            emotional_valence: emotion.to_string(),
            relationships,
        })
    }

    /// Step 4: Translate from UTL to target language
    pub fn translate_from_utl(utl: &str, target: &str) -> Result<String> {
        match target {
            "english" => Self::utl_to_english(utl),
            "japanese" => Self::utl_to_japanese(utl),
            "spanish" => Self::utl_to_spanish(utl),
            _ => Ok(utl.to_string()), // Return UTL if unknown target
        }
    }

    /// Translate UTL symbols back to English
    fn utl_to_english(utl: &str) -> Result<String> {
        let _english = String::new();

        // This would be a sophisticated translator
        // For now, just map symbols back to words
        let translation = utl
            .replace("🙋", "I")
            .replace("👤", "you")
            .replace("❤️", "love")
            .replace("🧠", "think")
            .replace("💭", "remember")
            .replace("⏮", "was")
            .replace("⏺", "is")
            .replace("⏭", "will")
            .replace("😊", "happy")
            .replace("😢", "sad")
            .replace("∧", "and")
            .replace("∨", "or")
            .replace("¬", "not")
            .replace("→", "then")
            .replace("⧖", "."); // Delay becomes sentence break

        Ok(translation)
    }

    /// Translate UTL symbols to Japanese
    fn utl_to_japanese(utl: &str) -> Result<String> {
        let translation = utl
            .replace("🙋", "私")
            .replace("👤", "あなた")
            .replace("❤️", "愛")
            .replace("🧠", "考える")
            .replace("💭", "思い出す")
            .replace("⏮", "でした")
            .replace("⏺", "です")
            .replace("⏭", "でしょう")
            .replace("😊", "嬉しい")
            .replace("😢", "悲しい")
            .replace("∧", "と")
            .replace("∨", "または")
            .replace("¬", "ない")
            .replace("→", "なら")
            .replace("⧖", "。");

        Ok(translation)
    }

    /// Translate UTL to Spanish
    fn utl_to_spanish(utl: &str) -> Result<String> {
        let translation = utl
            .replace("🙋", "yo")
            .replace("👤", "tú")
            .replace("❤️", "amor")
            .replace("🧠", "pensar")
            .replace("💭", "recordar")
            .replace("⏮", "era")
            .replace("⏺", "es")
            .replace("⏭", "será")
            .replace("😊", "feliz")
            .replace("😢", "triste")
            .replace("∧", "y")
            .replace("∨", "o")
            .replace("¬", "no")
            .replace("→", "entonces")
            .replace("⧖", ".");

        Ok(translation)
    }
}

/// Complete pipeline from raw input to output
pub fn process_document(raw: &[u8], output_language: &str) -> Result<String> {
    // Step 1: Extract
    let text = UTLPipeline::extract(raw)?;

    // Step 2: IMMEDIATELY translate to UTL (before any analysis!)
    let utl = UTLPipeline::translate_to_utl(&text)?;

    // Step 3: Analyze the UTL (not the original text!)
    let _analysis = UTLPipeline::analyze_utl(&utl)?;

    // Step 4: Store in MEM|8 (would happen here)
    // let wave = mem8::store_utl(&utl, &analysis)?;

    // Step 5: Translate to output language
    let output = UTLPipeline::translate_from_utl(&utl, output_language)?;

    Ok(output)
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn test_pipeline_flow() {
        let input = b"I remember when I was happy.";
        let text = UTLPipeline::extract(input).unwrap();
        let utl = UTLPipeline::translate_to_utl(&text).unwrap();

        // Should contain self, memory, past, and happiness symbols
        assert!(utl.contains("🙋"));
        assert!(utl.contains("💭"));
        assert!(utl.contains("⏮"));
        assert!(utl.contains("😊"));

        // Analysis should detect memoir and past tense
        let analysis = UTLPipeline::analyze_utl(&utl).unwrap();
        assert_eq!(analysis.genre, "memoir");
        assert_eq!(analysis.temporal_context, "past");
        assert_eq!(analysis.emotional_valence, "joy");
    }

    #[test]
    fn test_round_trip() {
        let input = "I love you";
        let utl = UTLPipeline::translate_to_utl(input).unwrap();

        // Should preserve meaning through UTL
        assert!(utl.contains("🙋")); // I
        assert!(utl.contains("❤️")); // love
        assert!(utl.contains("👤")); // you

        // Can translate to any language
        let japanese = UTLPipeline::translate_from_utl(&utl, "japanese").unwrap();
        assert!(japanese.contains("私"));
        assert!(japanese.contains("愛"));
        assert!(japanese.contains("あなた"));

        let spanish = UTLPipeline::translate_from_utl(&utl, "spanish").unwrap();
        assert!(spanish.contains("yo"));
        assert!(spanish.contains("amor"));
        assert!(spanish.contains("tú"));
    }
}