ndisk chatai

local modem = peripheral.find("modem") or error("No modem found")
modem.open(1) -- Open channel 1 for communication

local nodes = {}
local chunkMap = {}

-- Function to load node IDs
local function loadNodeIds()
    nodes = {}
    if fs.exists("ids.txt") then
        local file = fs.open("ids.txt", "r")
        for line in file.readLine do
            local nodeId, hierarchicalNum = line:match("(%d+)%s+(%d+)")
            if nodeId and hierarchicalNum then
                nodes[tonumber(hierarchicalNum)] = tonumber(nodeId)
            end
        end
        file.close()
    end
end

-- Function to load chunk map
local function loadChunkMap()
    chunkMap = {}
    if fs.exists("chunklocation.txt") then
        local file = fs.open("chunklocation.txt", "r")
        for line in file.readLine do
            local filename, chunk, nodeId = line:match("(%S+)%s+(%S+)%s+(%S+)")
            if filename and chunk and nodeId then
                chunkMap[filename] = chunkMap[filename] or {}
                local chunkNum = tonumber(chunk:match("chunk(%d+)"))
                chunkMap[filename][chunkNum] = tonumber(nodeId)
            end
        end
        file.close()
    end
end

loadNodeIds()
local nodeCount = 0
for _ in pairs(nodes) do nodeCount = nodeCount + 1 end
if nodeCount == 0 then
    error("No storage nodes found. Make sure the storage nodes are running and connected.")
end
print("Found " .. nodeCount .. " storage node(s)")
loadChunkMap()



-- Function to send a request to a node
local function sendRequest(nodeId, request)
    request.targetNode = nodeId
    modem.transmit(1, 1, request)
    local timer = os.startTimer(5)
    while true do
        local event, param1, param2, param3, param4, param5 = os.pullEvent()
        if event == "modem_message" and param4.id == request.id then
            return param4.response
        elseif event == "timer" and param1 == timer then
            error("Request timed out for node: " .. nodeId)
        end
    end
end

-- Advanced Dynamic Language Model with Enhanced Spatial AI and Pathfinding for CC: Tweaked

local model = {
    wordTransitions = {},
    layers = {},
    complexIdeas = {},
    selfImprovement = {
        learningRate = 0.1,
        adaptationRate = 0.01
    },
    spatialMemory = {},
    position = {x = 0, y = 0, z = 0},
    orientation = 0,  -- 0: north, 1: east, 2: south, 3: west
    locations = {}
}
local wordList = {}
local memory = {}
local SAVE_FILE = "language_model.dat"
local TRAINING_FILE = "trainingdata.txt"
local exploring = false

local function sendRequest(nodeId, request)
    request.targetNode = nodeId
    modem.transmit(1, 1, request)
    local timer = os.startTimer(5)
    while true do
        local event, param1, param2, param3, param4, param5 = os.pullEvent()
        if event == "modem_message" and param4.id == request.id then
            return param4.response
        elseif event == "timer" and param1 == timer then
            error("Request timed out for node: " .. nodeId)
        end
    end
end

-- Function to load the model from ndisk
local function loadModel()
    if chunkMap[SAVE_FILE] then
        local content = {}
        for chunkNum, nodeId in pairs(chunkMap[SAVE_FILE]) do
            local response = sendRequest(nodeId, {
                id = os.getComputerID() .. "_" .. os.clock(),
                action = "read",
                path = SAVE_FILE,
                chunk = chunkNum
            })
            if response.success then
                content[chunkNum] = response.content
            else
                error("Failed to read chunk " .. chunkNum .. " from node " .. nodeId)
            end
        end
        local data = table.concat(content)
        local loaded = textutils.unserialize(data)
        model.wordTransitions = loaded.wordTransitions or {}
        model.layers = loaded.layers or {}
        model.complexIdeas = loaded.complexIdeas or {}
        model.selfImprovement = loaded.selfImprovement or {learningRate = 0.1, adaptationRate = 0.01}
        model.spatialMemory = loaded.spatialMemory or {}
        model.position = loaded.position or {x = 0, y = 0, z = 0}
        model.orientation = tonumber(loaded.orientation) or 0
        model.locations = loaded.locations or {}
        wordList = loaded.wordList or {}
        memory = loaded.memory or {}
        print("Model loaded from ndisk.")
    else
        print("No existing model found on ndisk. Starting fresh.")
        wordList = {"the", "be", "to", "of", "and", "a", "in", "that", "have", "I"}
    end
end

-- Function to save the model to ndisk
local function saveModel()
    print("Saving model to ndisk...")
    local data = textutils.serialize({
        wordTransitions = model.wordTransitions,
        layers = model.layers,
        complexIdeas = model.complexIdeas,
        selfImprovement = model.selfImprovement,
        spatialMemory = model.spatialMemory,
        position = model.position,
        orientation = model.orientation,
        locations = model.locations,
        wordList = wordList,
        memory = memory
    })

    local nodeCount = 0
    for _ in pairs(nodes) do nodeCount = nodeCount + 1 end
    local chunkSize = math.ceil(#data / nodeCount)
    chunkMap[SAVE_FILE] = {}
    local chunkNum = 1
    for hierarchicalNum, nodeId in pairs(nodes) do
        local start = (chunkNum - 1) * chunkSize + 1
        local chunk = data:sub(start, math.min(start + chunkSize - 1, #data))
        local response = sendRequest(nodeId, {
            id = os.getComputerID() .. "_" .. os.clock(),
            action = "write",
            path = SAVE_FILE,
            chunk = chunkNum,
            content = chunk
        })
        if not response.success then
            error("Failed to write chunk " .. chunkNum .. " to node " .. nodeId)
        end
        chunkMap[SAVE_FILE][chunkNum] = nodeId
        chunkNum = chunkNum + 1
    end

    -- Save updated chunk map
    local file = fs.open("chunklocation.txt", "w")
    for filename, chunks in pairs(chunkMap) do
        for chunkNum, nodeId in pairs(chunks) do
            file.writeLine(filename .. " chunk" .. chunkNum .. " " .. nodeId)
        end
    end
    file.close()

    print("Model saved to ndisk.")
end

-- Function to tokenize input
local function tokenize(input)
    if type(input) ~= "string" then
        return {}
    end
    local words = {}
    for word in input:gmatch("%w+") do
        table.insert(words, word:lower())
    end
    return words
end

-- Function to update the model
local function updateModel(words, modelTable)
    if type(words) ~= "table" or #words == 0 then
        return
    end
    for i = 1, #words - 1 do
        local currentWord = words[i]
        local nextWord = words[i + 1]

        if not modelTable.wordTransitions[currentWord] then
            modelTable.wordTransitions[currentWord] = {}
        end
        modelTable.wordTransitions[currentWord][nextWord] = (modelTable.wordTransitions[currentWord][nextWord] or 0) + 1

        -- Add new words to wordList
        if not table.concat(wordList, " "):find(currentWord) then
            table.insert(wordList, currentWord)
        end
        if not table.concat(wordList, " "):find(nextWord) then
            table.insert(wordList, nextWord)
        end
    end
end

-- Function to generate a response with improved coherence and reduced hallucinations
local function generateResponse(input, modelTable)
    local words = tokenize(input)
    local response = {}
    local currentWord = words[#words] or wordList[math.random(#wordList)]

    local maxWords = math.random(1, 15)  -- Changed minimum to 1
    local context = {}  -- Keep track of recent words for context

    for i = 1, maxWords do
        if modelTable.wordTransitions[currentWord] then
            local totalWeight = 0
            local weightedWords = {}
            for word, count in pairs(modelTable.wordTransitions[currentWord]) do
                totalWeight = totalWeight + (count or 0)
                table.insert(weightedWords, {word = word, weight = count or 0})
            end

            if totalWeight > 0 then
                -- Use context to influence word selection
                local contextInfluence = 0.3  -- Adjust this value to change the influence of context
                local randomWeight = math.random() * (totalWeight + (#context * contextInfluence))
                local cumulativeWeight = 0
                for _, wordData in ipairs(weightedWords) do
                    cumulativeWeight = cumulativeWeight + wordData.weight
                    if context[wordData.word] then
                        cumulativeWeight = cumulativeWeight + contextInfluence
                    end
                    if cumulativeWeight >= randomWeight then
                        currentWord = wordData.word
                        break
                    end
                end
            else
                currentWord = wordList[math.random(#wordList)]
            end
            table.insert(response, currentWord)

            -- Update context
            context[currentWord] = (context[currentWord] or 0) + 1
            if #response > 5 then  -- Keep last 5 words in context
                local oldWord = response[#response - 5]
                context[oldWord] = (context[oldWord] or 1) - 1
                if context[oldWord] <= 0 then
                    context[oldWord] = nil
                end
            end
        else
            currentWord = wordList[math.random(#wordList)]
            table.insert(response, currentWord)
        end
    end

    return table.concat(response, " ")
end

-- Function to analyze patterns and predict improvements
local function analyzePatterns(modelTable)
    local patterns = {}
    for word, transitions in pairs(modelTable.wordTransitions) do
        local sortedTransitions = {}
        for nextWord, weight in pairs(transitions) do
            table.insert(sortedTransitions, {word = nextWord, weight = weight})
        end
        table.sort(sortedTransitions, function(a, b) return a.weight > b.weight end)

        if #sortedTransitions >= 3 then
            patterns[word] = {
                sortedTransitions[1].word,
                sortedTransitions[2].word,
                sortedTransitions[3].word
            }
        end
    end

    modelTable.predictedPatterns = patterns
end
-- Function to delete a saved location
local function deleteLocation(name)
    if model.locations[name] then
        model.locations[name] = nil
        saveModel()  -- Save the model to persist the change
        print("Location '" .. name .. "' has been deleted.")
    else
        print("Location '" .. name .. "' not found.")
    end
end

-- Function for self-improvement with pattern analysis
local function selfImprove()
    model.selfImprovement.learningRate = model.selfImprovement.learningRate * (1 + model.selfImprovement.adaptationRate)
    analyzePatterns(model)

    -- Use predicted patterns to reinforce likely transitions
    for word, likelyNext in pairs(model.predictedPatterns) do
        for _, nextWord in ipairs(likelyNext) do
            if model.wordTransitions[word] and model.wordTransitions[word][nextWord] then
                model.wordTransitions[word][nextWord] = model.wordTransitions[word][nextWord] * 1.1  -- Increase weight by 10%
            end
        end
    end
end

-- Function to get coordinates in front of the turtle
local function getFrontCoords()
    local x, y, z = model.position.x, model.position.y, model.position.z
    if model.orientation == 0 then     -- North
        z = z - 1
    elseif model.orientation == 1 then -- East
        x = x + 1
    elseif model.orientation == 2 then -- South
        z = z + 1
    else                               -- West
        x = x - 1
    end
    return x, y, z
end

-- Function to move the turtle and update its position
local function moveTurtle(direction)
    local success = false
    if direction == "forward" then
        success = turtle.forward()
        if success then
            local x, y, z = getFrontCoords()
            model.position.x, model.position.y, model.position.z = x, y, z
        end
    elseif direction == "back" then
        success = turtle.back()
        if success then
            local x, y, z = getFrontCoords()
            model.position.x, model.position.y, model.position.z = x, y, z
        end
    elseif direction == "up" then
        success = turtle.up()
        if success then
            model.position.y = model.position.y + 1
        end
    elseif direction == "down" then
        success = turtle.down()
        if success then
            model.position.y = model.position.y - 1
        end
    elseif direction == "left" then
        turtle.turnLeft()
        model.orientation = (model.orientation - 1) % 4
        success = true
    elseif direction == "right" then
        turtle.turnRight()
        model.orientation = (model.orientation + 1) % 4
        success = true
    end

    return success
end

-- Function to detect blocks and update spatial memory
local function detectBlocks()
    local success, data = turtle.inspect()
    if success then
        local x, y, z = getFrontCoords()
        local key = x .. "," .. y .. "," .. z
        model.spatialMemory[key] = {
            name = data.name,
            metadata = data.metadata,
            explored = true
        }
    end
end

-- Function to create a new layer in the model
local function createNewLayer(layerName, words, modelTable)
    if not modelTable.layers[layerName] then
        modelTable.layers[layerName] = {}
    end

    for i = 1, #words - 1 do
        local currentWord = words[i]
        local nextWord = words[i + 1]

        if not modelTable.layers[layerName][currentWord] then
            modelTable.layers[layerName][currentWord] = {}
        end
        modelTable.layers[layerName][currentWord][nextWord] = (modelTable.layers[layerName][currentWord][nextWord] or 0) + 1
    end
end

-- Function to remember spatial context
local function rememberSpatialContext()
    local context = {}
    for pos, data in pairs(model.spatialMemory) do
        table.insert(context, pos .. ": " .. data.name)
    end
    return table.concat(context, "\n")
end

-- Function to relate spatial memory to language model
local function relateSpatialToLanguage()
    for pos, data in pairs(model.spatialMemory) do
        local words = tokenize(data.name)
        updateModel(words, model)
        createNewLayer("spatial_" .. pos, words, model)
    end
    print("Spatial data integrated into language model.")
end

-- Function to find unexplored directions
local function findUnexploredDirections()
    local unexplored = {}
    local directions = {"forward", "left", "right", "up", "down"}
    for _, dir in ipairs(directions) do
        local x, y, z
        if dir == "forward" then
            x, y, z = getFrontCoords()
        elseif dir == "up" then
            x, y, z = model.position.x, model.position.y + 1, model.position.z
        elseif dir == "down" then
            x, y, z = model.position.x, model.position.y - 1, model.position.z
        else
            local tempOrientation = dir == "left" and (model.orientation - 1) % 4 or (model.orientation + 1) % 4
            if tempOrientation == 0 then     -- North
                x, y, z = model.position.x, model.position.y, model.position.z - 1
            elseif tempOrientation == 1 then -- East
                x, y, z = model.position.x + 1, model.position.y, model.position.z
            elseif tempOrientation == 2 then -- South
                x, y, z = model.position.x, model.position.y, model.position.z + 1
            else                             -- West
                x, y, z = model.position.x - 1, model.position.y, model.position.z
            end
        end
        local key = x .. "," .. y .. "," .. z
        if not model.spatialMemory[key] or not model.spatialMemory[key].explored then
            table.insert(unexplored, dir)
        end
    end
    return unexplored
end

-- A* Pathfinding Algorithm
local function aStarPath(start, goal)
    local function heuristic(a, b)
        return math.abs(a.x - b.x) + math.abs(a.y - b.y) + math.abs(a.z - b.z)
    end

    local openSet = {}
    local closedSet = {}
    local cameFrom = {}
    local gScore = {[start] = 0}
    local fScore = {[start] = heuristic(start, goal)}

    table.insert(openSet, start)

    while #openSet > 0 do
        local current = openSet[1]
        for i = 2, #openSet do
            if fScore[openSet[i]] < fScore[current] then
                current = openSet[i]
            end
        end

        if current.x == goal.x and current.y == goal.y and current.z == goal.z then
            local path = {}
            while current do
                table.insert(path, 1, current)
                current = cameFrom[current]
            end
            return path
        end

        for i, v in ipairs(openSet) do
            if v == current then
                table.remove(openSet, i)
                break
            end
        end
        table.insert(closedSet, current)

        local neighbors = {
            {x = current.x + 1, y = current.y, z = current.z},
            {x = current.x - 1, y = current.y, z = current.z},
            {x = current.x, y = current.y + 1, z = current.z},
            {x = current.x, y = current.y - 1, z = current.z},
            {x = current.x, y = current.y, z = current.z + 1},
            {x = current.x, y = current.y, z = current.z - 1}
        }

        for _, neighbor in ipairs(neighbors) do
            local inClosedSet = false
            for _, v in ipairs(closedSet) do
                if v.x == neighbor.x and v.y == neighbor.y and v.z == neighbor.z then
                    inClosedSet = true
                    break
                end
            end

            if not inClosedSet then
                local tentative_gScore = gScore[current] + 1

                local inOpenSet = false
                for _, v in ipairs(openSet) do
                    if v.x == neighbor.x and v.y == neighbor.y and v.z == neighbor.z then
                        inOpenSet = true
                        break
                    end
                end

                if not inOpenSet then
                    table.insert(openSet, neighbor)
                elseif tentative_gScore >= (gScore[neighbor] or math.huge) then
                    goto continue
                end

                cameFrom[neighbor] = current
                gScore[neighbor] = tentative_gScore
                fScore[neighbor] = gScore[neighbor] + heuristic(neighbor, goal)

                ::continue::
            end
        end
    end

    return nil -- No path found
end

-- Function to save a location
local function saveLocation(name)
    model.locations[name] = {x = model.position.x, y = model.position.y, z = model.position.z}
    saveModel()  -- Save the model immediately after adding a new location
    print("Location '" .. name .. "' saved.")
end

-- Function to go to a saved location
local function gotoLocation(name)
    local coords = model.locations[name]
    if not coords then
        print("Location '" .. name .. "' not found.")
        return
    end

    local path = aStarPath(model.position, coords)
    if not path then
        print("No path found to '" .. name .. "'.")
        return
    end

    print("Path found. Moving to '" .. name .. "'...")
    for i, step in ipairs(path) do
        local dx = step.x - model.position.x
        local dy = step.y - model.position.y
        local dz = step.z - model.position.z

        -- Determine direction and move
        if dx ~= 0 then
            if dx > 0 then
                while model.orientation ~= 1 do  -- Face East
                    moveTurtle("right")
                end
            else
                while model.orientation ~= 3 do  -- Face West
                    moveTurtle("right")
                end
            end
            moveTurtle("forward")
        elseif dz ~= 0 then
            if dz > 0 then
                while model.orientation ~= 2 do  -- Face South
                    moveTurtle("right")
                end
            else
                while model.orientation ~= 0 do  -- Face North
                    moveTurtle("right")
                end
            end
            moveTurtle("forward")
        elseif dy ~= 0 then
            if dy > 0 then
                moveTurtle("up")
            else
                moveTurtle("down")
            end
        end

        print("Step " .. i .. " of " .. #path .. " completed.")
    end

    print("Arrived at '" .. name .. "'.")
end

-- Function to load training data
local function loadTrainingData()
    if fs.exists(TRAINING_FILE) then
        local f = fs.open(TRAINING_FILE, "r")
        local data = f.readAll()
        f.close()
        if data and data ~= "" then
            local lines = {}
            for line in data:gmatch("[^\r\n]+") do
                table.insert(lines, line)
            end
            for i = 1, #lines, 2 do
                local prompt = lines[i]
                local response = lines[i + 1]
                if prompt and response then
                    local promptWords = tokenize(prompt)
                    local responseWords = tokenize(response)
                    updateModel(promptWords, model)
                    updateModel(responseWords, model)
                    createNewLayer("prompt_" .. i, promptWords, model)
                    createNewLayer("response_" .. i, responseWords, model)
                end
            end
        end
    end
end


-- Function to remember context
local function rememberContext(input)
    table.insert(memory, input)
    if #memory > 10 then
        table.remove(memory, 1)
    end
end

-- Function to handle complex ideas (placeholder implementation)
local function handleComplexIdea(idea, modelTable)
    modelTable.complexIdeas = modelTable.complexIdeas or {}
    modelTable.complexIdeas[idea] = (modelTable.complexIdeas[idea] or 0) + 1
end

-- Function for reinforcement learning
local function reinforcementLearning(rating, modelTable)
    local learningRate = model.selfImprovement.learningRate
    for i = 1, #memory do
        local words = tokenize(memory[i])
        for j = 1, #words - 1 do
            local currentWord = words[j]
            local nextWord = words[j + 1]
            if modelTable.wordTransitions[currentWord] and modelTable.wordTransitions[currentWord][nextWord] then
                modelTable.wordTransitions[currentWord][nextWord] =
                    modelTable.wordTransitions[currentWord][nextWord] * (1 + learningRate * (rating / 10 - 0.5))
            end
        end
    end
end

-- Function to handle math expressions
local function handleMath(input)
    local func, err = load("return " .. input)
    if func then
        local success, result = pcall(func)
        if success then
            return tostring(result)
        end
    end
    return "Error: Invalid math expression."
end

-- Main loop
print("Advanced Dynamic Language Model with Enhanced Spatial AI and Pathfinding")
print("Type 'exit' to quit, 'save' to save the model")

loadNodeIds()
local nodeCount = 0
for _ in pairs(nodes) do nodeCount = nodeCount + 1 end
if nodeCount == 0 then
    error("No storage nodes found. Make sure the storage nodes are running and connected.")
end
print("Found " .. nodeCount .. " storage node(s)")
loadChunkMap()
loadModel()
loadTrainingData()

local function explorationTask()
    while true do
        if exploring then
            local unexploredDirections = findUnexploredDirections()
            if #unexploredDirections > 0 then
                local direction = unexploredDirections[math.random(#unexploredDirections)]
                if moveTurtle(direction) then
                    detectBlocks()
                end
            else
                -- If surrounded by explored blocks, move randomly
                local directions = {"forward", "left", "right", "up", "down"}
                local direction = directions[math.random(#directions)]
                if moveTurtle(direction) then
                    detectBlocks()
                end
            end

            -- Allow other processes to run
            os.sleep(0.1)

            if turtle.getFuelLevel() == 0 then
                print("Out of fuel. Exploration stopped.")
                exploring = false
            end
        else
            os.sleep(0.1)
        end
    end
end
-- Function to list saved locations
local function listLocations()
    if not model.locations or next(model.locations) == nil then
        print("No locations saved.")
        return
    end

    print("Saved locations:")
    local index = 1
    for name, coords in pairs(model.locations) do
        print(index .. ". " .. name .. " (" .. coords.x .. ", " .. coords.y .. ", " .. coords.z .. ")")
        index = index + 1
    end
end

local function mainLoop()
    while true do
        write("> ")
        local input = read()

        if input:lower() == "exit" then
            saveModel()
            print("Goodbye!")
            break
        elseif input:lower() == "save" then
            saveModel()
        elseif input:lower() == "explore" then
            exploring = true
            print("Starting exploration. Type 'stop' to end.")
        elseif input:lower() == "stop" then
            exploring = false
            print("Exploration will stop after the current move.")
        elseif input:lower() == "list locations" then
            listLocations()
        elseif input:match("^save%s+(.+)$") then
            local name = input:match("^save%s+(.+)$")
            saveLocation(name)
        elseif input:match("^goto%s+(.+)$") then
            local name = input:match("^goto%s+(.+)$")
            gotoLocation(name)
        elseif input:match("^delete%s+(.+)$") then
            local name = input:match("^delete%s+(.+)$")
            deleteLocation(name)
        elseif input:match("^rate%s+(%d+)$") then
            local rating = tonumber(input:match("^rate%s+(%d+)$"))
            if rating and rating >= 1 and rating <= 10 then
                reinforcementLearning(rating, model)
                print("Thank you for your rating!")
            else
                print("Invalid rating. Please use a number between 1 and 10.")
            end
        elseif input:match("^%d+[%+%-%*/%^]%d+$") then
            local result = handleMath(input)
            print("Math: " .. result)
        elseif input:match("^move%s+(%w+)$") then
            local direction = input:match("^move%s+(%w+)$")
            if moveTurtle(direction) then
                print("Moved " .. direction)
                detectBlocks()
            else
                print("Failed to move " .. direction)
            end
        elseif input:match("^inspect$") then
            detectBlocks()
            print("Inspected block at current position.")
        elseif input:match("^remember%s+spatial$") then
            local context = rememberSpatialContext()
            print("Spatial Memory:\n" .. context)
        else
            local words = tokenize(input)
            updateModel(words, model)
            rememberContext(input)
            handleComplexIdea(input, model)
            local response = generateResponse(input, model)
            print("Model: " .. response)
            selfImprove()
        end
    end
end

parallel.waitForAny(explorationTask, mainLoop)