content: -- harmonia_nexus/src/HarmonizerEngine.hs
  
  -- Define core data types for an Echo and its Emotional Signature
  -- An Echo is a raw narrative fragment, anonymized.
  -- An EmotionalSignature is a structured representation of its core feeling.
  data Echo = Echo {
      echoId :: String,
      rawContent :: String,
      contextTags :: [String] -- e.g., "loss", "triumph", "injustice", "belonging"
  } deriving (Show, Eq, Ord) -- Added Ord for comparison based on echoId
  
  -- A simplified Emotional Signature for demonstration. In reality, this would be
  -- a complex, multi-dimensional vector derived from advanced NLP.
  data EmotionalSignature = EmotionalSignature {
      coreFeeling :: String, -- e.g., "Joy", "Sorrow", "Hope", "Fear"
      intensity :: Float      -- 0.0 to 1.0
  } deriving (Show, Eq)
  
  -- A potential Resonance Path candidate, connecting two Echoes.
  data ResonancePathCandidate = ResonancePathCandidate {
      echoA :: Echo,
      echoB :: Echo,
      sharedSignature :: EmotionalSignature,
      connectionScore :: Float -- How strong is the empathetic link?
  } deriving (Show, Eq)
  
  -- Pseudo-code:
  -- Function: extractSignature
  --   Input: An Echo
  --   Output: Its EmotionalSignature
  --   Process: (Conceptual NLP/ML process) Analyze rawContent and contextTags to derive coreFeeling and intensity.
  extractSignature :: Echo -> EmotionalSignature
  extractSignature echo =
      -- In a real app, this would be a sophisticated NLP model.
      -- For demonstration, let's pretend it magically knows.
      case contextTags echo of
          tags | "joy" `elem` tags -> EmotionalSignature "Joy" 0.9
               | "loss" `elem` tags -> EmotionalSignature "Sorrow" 0.8
               | "hope" `elem` tags -> EmotionalSignature "Hope" 0.7
               | "fear" `elem` tags -> EmotionalSignature "Fear" 0.85
               | otherwise -> EmotionalSignature "Neutral" 0.5
  
  -- Pseudo-code:
  -- Function: calculateResonance
  --   Input: Two EmotionalSignatures
  --   Output: A tuple (SharedSignature, ConnectionScore)
  --   Process: Compare signatures. If coreFeelings are similar and intensities align,
  --            calculate a score. Prioritize connections across diverse contextTags.
  calculateResonance :: EmotionalSignature -> EmotionalSignature -> (EmotionalSignature, Float)
  calculateResonance sigA sigB =
      if coreFeeling sigA == coreFeeling sigB
          then (sigA, 1.0 - abs (intensity sigA - intensity sigB)) -- Closer intensity, higher score
          else (EmotionalSignature "Mismatch" 0.0, 0.0)
  
  -- Helper function to determine if two echoes have diverse contexts.
  -- "Diverse" means they have tags unique to each, indicating different primary contexts,
  -- while also having some shared tags (like the shared emotional feeling itself).
  -- This allows for bridging between different backgrounds while focusing on shared humanity.
  import Data.List ((\), intersect)
  
  areDiverseContexts :: Echo -> Echo -> Bool
  areDiverseContexts e1 e2 =
      let tags1 = contextTags e1
          tags2 = contextTags e2
          uniqueToA = tags1 \\ tags2
          uniqueToB = tags2 \\ tags1
          commonTags = tags1 `intersect` tags2
      in  not (null uniqueToA)        -- Echo A has at least one tag Echo B doesn't
          && not (null uniqueToB)     -- Echo B has at least one tag Echo A doesn't
          && not (null commonTags)    -- They share at least one tag (e.g., the emotional context itself)
  
  -- Pseudo-code:
  -- Function: generateCandidates
  --   Input: List of all Echoes
  --   Output: List of ResonancePathCandidates
  --   Process:
  --     1. For every unique pair of Echoes:
  --     2.   Extract signatures for both.
  --     3.   Calculate resonance between signatures.
  --     4.   If resonance is high AND contextTags are diverse (e.g., different continents, cultures, socio-economic backgrounds):
  --     5.     Create a ResonancePathCandidate.
  --     6. Return all candidates.
  generateCandidates :: [Echo] -> [ResonancePathCandidate]
  generateCandidates allEchoes =
      [ ResonancePathCandidate echo1 echo2 sharedSig score
      | echo1 <- allEchoes
      , echo2 <- allEchoes
      , echoId echo1 < echoId echo2 -- Ensure unique pairs (e.g., (A,B) but not (B,A))
      , let sig1 = extractSignature echo1
      , let sig2 = extractSignature echo2
      , let (sharedSig, score) = calculateResonance sig1 sig2
      , score > 0.7 -- Only consider strong emotional resonance
      , not (null (contextTags echo1)) && not (null (contextTags echo2)) -- Ensure tags exist for diversity check
      , areDiverseContexts echo1 echo2 -- Crucial: Ensure diverse contexts as per project vision
      ]
  
  -- The main Harmonizer function: takes a pool of echoes and harmonizes them.
  harmonizeEchoes :: [Echo] -> [ResonancePathCandidate]
  harmonizeEchoes = generateCandidates
  
  -- Example Usage (in a REPL or test file):
  -- let e1 = Echo "e001" "The quiet despair of a lost crop." ["loss", "agriculture", "rural"]
  -- let e2 = Echo "e002" "The empty feeling after a job layoff." ["loss", "urban", "economic"]
  -- let e3 = Echo "e003" "The joy of seeing my child graduate." ["joy", "family", "education"]
  -- let e4 = Echo "e004" "The silent pride watching my community rebuild after disaster." ["joy", "community", "resilience"]
  -- let e5 = Echo "e005" "The fear of an unknown future." ["fear", "uncertainty"]
  -- let e6 = Echo "e006" "The terror of a sudden, loud noise." ["fear", "trauma"]
  -- let allMyEchoes = [e1, e2, e3, e4, e5, e6]
  -- let paths = harmonizeEchoes allMyEchoes
  -- mapM_ print paths
  