fix: add Julia (.jl) support for code indexing with fallback chunking

- Add .jl extension to supported extensions list in tree-sitter/index.ts
- Add .jl to fallbackExtensions array in shared/supported-extensions.ts
- Add comprehensive tests for Julia file parsing and chunking
- Fixes issue where Julia files were not being indexed at all

Resolves #8966

src/services/code-index/processors/__tests__/parser.julia.spec.ts

@@ -0,0 +1,227 @@
+import { describe, it, expect, beforeAll } from "vitest"
+import { CodeParser } from "../parser"
+import { shouldUseFallbackChunking } from "../../shared/supported-extensions"
+import * as path from "path"
+import { initializeTreeSitter } from "../../../tree-sitter/__tests__/helpers"
+
+describe("Julia file parsing", () => {
+	let parser: CodeParser
+
+	beforeAll(async () => {
+		await initializeTreeSitter()
+		parser = new CodeParser()
+	})
+
+	it("should use fallback chunking for Julia files", () => {
+		// Verify that Julia extension is marked for fallback chunking
+		expect(shouldUseFallbackChunking(".jl")).toBe(true)
+	})
+
+	it("should parse Julia files using fallback chunking", async () => {
+		const juliaContent = `# Julia module for data analysis
+module DataAnalytics
+
+using Statistics
+using DataFrames
+
+# Type definition for data points
+struct DataPoint
+    x::Float64
+    y::Float64
+    label::String
+end
+
+# Function to calculate basic statistics
+function calculate_statistics(data::Vector{Float64})
+    return (
+        mean = mean(data),
+        median = median(data),
+        std = std(data),
+        min = minimum(data),
+        max = maximum(data)
+    )
+end
+
+# Filter data by value range
+function filter_data(data::Vector{DataPoint}, min_val::Float64, max_val::Float64)
+    return filter(p -> min_val <= p.x <= max_val, data)
+end
+
+# Process dataset with custom transformation
+function process_dataset(df::DataFrame, transform_func::Function)
+    processed = DataFrame()
+    for col in names(df)
+        if eltype(df[!, col]) <: Number
+            processed[!, col] = transform_func.(df[!, col])
+        else
+            processed[!, col] = df[!, col]
+        end
+    end
+    return processed
+end
+
+# Main analysis pipeline
+function run_analysis(input_file::String, output_file::String)
+    # Load data
+    df = DataFrame(CSV.File(input_file))
+    
+    # Process data
+    processed = process_dataset(df, x -> log(1 + abs(x)))
+    
+    # Calculate statistics for numeric columns
+    stats_dict = Dict{String, Any}()
+    for col in names(processed)
+        if eltype(processed[!, col]) <: Number
+            stats_dict[col] = calculate_statistics(processed[!, col])
+        end
+    end
+    
+    # Save results
+    CSV.write(output_file, processed)
+    
+    return stats_dict
+end
+
+# Export public interface
+export DataPoint, calculate_statistics, filter_data, process_dataset, run_analysis
+
+end # module DataAnalytics
+
+# Usage example
+using .DataAnalytics
+
+# Create sample data
+sample_points = [
+    DataPoint(1.0, 2.0, "A"),
+    DataPoint(3.0, 4.0, "B"),
+    DataPoint(5.0, 6.0, "C")
+]
+
+# Filter data
+filtered = filter_data(sample_points, 2.0, 4.0)
+println("Filtered data: ", filtered)
+
+# Calculate statistics
+values = [p.x for p in sample_points]
+stats = calculate_statistics(values)
+println("Statistics: ", stats)`
+
+		const testFilePath = path.join("/tmp", "test.jl")
+		const result = await parser.parseFile(testFilePath, {
+			content: juliaContent,
+			fileHash: "test-hash",
+		})
+
+		// Should have results from fallback chunking
+		expect(result.length).toBeGreaterThan(0)
+
+		// Check that all blocks are of type 'fallback_chunk'
+		result.forEach((block) => {
+			expect(block.type).toBe("fallback_chunk")
+		})
+
+		// Verify that the content is properly chunked
+		const firstBlock = result[0]
+		expect(firstBlock.file_path).toBe(testFilePath)
+		expect(firstBlock.content).toContain("Julia module")
+		expect(firstBlock.identifier).toBeNull()
+		expect(firstBlock.segmentHash).toMatch(/^[a-f0-9]{64}$/)
+		expect(firstBlock.fileHash).toBe("test-hash")
+	})
+
+	it("should handle small Julia files that don't meet minimum character requirements", async () => {
+		const smallJuliaContent = `# Small Julia file
+x = 1
+y = 2`
+
+		const testFilePath = path.join("/tmp", "small.jl")
+		const result = await parser.parseFile(testFilePath, {
+			content: smallJuliaContent,
+			fileHash: "small-hash",
+		})
+
+		// Should return empty array for files too small to index
+		expect(result.length).toBe(0)
+	})
+
+	it("should chunk large Julia files appropriately", async () => {
+		// Create a large Julia file content with multiple sections
+		const sections: string[] = []
+
+		// Add multiple function definitions to create chunks
+		for (let i = 0; i < 20; i++) {
+			sections.push(`
+# Function ${i} for processing data
+function process_data_${i}(data::Vector{Float64})
+    # This is a longer function with detailed implementation
+    # to ensure we have enough content for chunking
+    
+    # Step 1: Validate input data
+    if isempty(data)
+        throw(ArgumentError("Data cannot be empty"))
+    end
+    
+    # Step 2: Calculate intermediate results
+    intermediate = map(x -> x * 2.0, data)
+    
+    # Step 3: Apply transformation
+    transformed = map(x -> log(1 + abs(x)), intermediate)
+    
+    # Step 4: Compute final result
+    result = sum(transformed) / length(transformed)
+    
+    # Step 5: Return processed value
+    return result
+end
+`)
+		}
+
+		const largeJuliaContent = `# Large Julia module with many functions
+module LargeModule
+
+using Statistics
+using LinearAlgebra
+
+${sections.join("\n")}
+
+# Export all functions
+export ${Array.from({ length: 20 }, (_, i) => `process_data_${i}`).join(", ")}
+
+end # module LargeModule`
+
+		const testFilePath = path.join("/tmp", "large.jl")
+		const result = await parser.parseFile(testFilePath, {
+			content: largeJuliaContent,
+			fileHash: "large-hash",
+		})
+
+		// Should have multiple chunks
+		expect(result.length).toBeGreaterThan(1)
+
+		// All chunks should be fallback chunks
+		result.forEach((block) => {
+			expect(block.type).toBe("fallback_chunk")
+		})
+
+		// Check that chunks have reasonable sizes
+		result.forEach((block) => {
+			// Each chunk should have content
+			expect(block.content.length).toBeGreaterThan(0)
+			// Chunks should not exceed maximum size (with tolerance)
+			expect(block.content.length).toBeLessThanOrEqual(150000) // MAX_BLOCK_CHARS * MAX_CHARS_TOLERANCE_FACTOR
+		})
+	})
+})
+
+describe("Fallback Extensions Configuration for Julia", () => {
+	it("should correctly identify Julia extension for fallback chunking", () => {
+		// Julia should use fallback
+		expect(shouldUseFallbackChunking(".jl")).toBe(true)
+		expect(shouldUseFallbackChunking(".JL")).toBe(true) // Case insensitive
+
+		// Non-Julia extensions should not use fallback (unless they're in the list)
+		expect(shouldUseFallbackChunking(".py")).toBe(false)
+		expect(shouldUseFallbackChunking(".js")).toBe(false)
+		expect(shouldUseFallbackChunking(".ts")).toBe(false)
+	})
+})

src/services/code-index/shared/supported-extensions.ts

@@ -22,6 +22,7 @@ export const fallbackExtensions = [
 	".vb", // Visual Basic .NET - no dedicated WASM parser
 	".scala", // Scala - uses fallback chunking instead of Lua query workaround
 	".swift", // Swift - uses fallback chunking due to parser instability
+	".jl", // Julia - no dedicated WASM parser available
 ]
 
 /**

src/services/tree-sitter/index.ts

@@ -91,6 +91,8 @@ const extensions = [
 	"erb",
 	// Visual Basic .NET
 	"vb",
+	// Julia
+	"jl",
 ].map((e) => `.${e}`)
 
 export { extensions }