Fix build_index

.github/workflows/CI.yml

@@ -11,6 +11,8 @@ concurrency:
   # Cancel intermediate builds: only if it is a pull request build.
   group: ${{ github.workflow }}-${{ github.ref }}
   cancel-in-progress: ${{ startsWith(github.ref, 'refs/pull/') }}
+env:
+  OPENAI_API_KEY: "invalid-key-just-for-testing"
 jobs:
   test:
     name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }} - ${{ github.event_name }}

CHANGELOG.md

@@ -10,6 +10,11 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Fixed
 
+## [0.1.1]
+
+### Fixed
+- Fixed a bug in `build_index` where imports were missing and keywords were not passed properly in all scenarios.
+
 ## [0.1.0]
 
 ### Added

Project.toml

@@ -1,7 +1,7 @@
 name = "AIHelpMe"
 uuid = "01402e1f-dc83-4213-a98b-42887d758baa"
 authors = ["J S <49557684+svilupp@users.noreply.github.com> and contributors"]
-version = "0.1.0"
+version = "0.1.1"
 
 [deps]
 HDF5 = "f67ccb44-e63f-5c2f-98bd-6dc0ccc4ba2f"

src/preparation.jl

@@ -97,16 +97,20 @@ function RT.build_index(mod::Module; verbose::Int = 1, kwargs...)
     ## Extract current configuration
     chunker_kwargs_ = (; sources = all_sources)
     chunker_kwargs = haskey(kwargs, :chunker_kwargs) ?
-                     merge(kwargs.chunker_kwargs, chunker_kwargs_) : chunker_kwargs_
+                     merge(kwargs[:chunker_kwargs], chunker_kwargs_) : chunker_kwargs_
 
     embedder_kwargs_ = RT.getpropertynested(
         RAG_KWARGS[], [:retriever_kwargs], :embedder_kwargs, nothing)
+    # Note: force Matrix{Bool} structure for now, switch to Int8-based binary embeddings with the latest PT
     embedder_kwargs = haskey(kwargs, :embedder_kwargs) ?
-                      merge(kwargs.embedder_kwargs, embedder_kwargs_) : embedder_kwargs_
+                      merge(
+        (; return_type = Matrix{Bool}), embedder_kwargs_, kwargs[:embedder_kwargs]) :
+                      merge((; return_type = Matrix{Bool}), embedder_kwargs_)
 
     new_index = RT.build_index(RAG_CONFIG[].indexer, all_docs;
-        embedder_kwargs, chunker = TextChunker(), chunker_kwargs,
-        verbose, index_id = nameof(mod), kwargs...)
+        kwargs...,
+        embedder_kwargs, chunker = RT.TextChunker(), chunker_kwargs,
+        verbose, index_id = nameof(mod))
 end
 
 """
@@ -124,14 +128,18 @@ function RT.build_index(modules::Vector{Module} = Base.Docs.modules; verbose::In
     ## Extract current configuration
     chunker_kwargs_ = (; sources = all_sources)
     chunker_kwargs = haskey(kwargs, :chunker_kwargs) ?
-                     merge(kwargs.chunker_kwargs, chunker_kwargs_) : chunker_kwargs_
+                     merge(kwargs[:chunker_kwargs], chunker_kwargs_) : chunker_kwargs_
 
+    # Note: force Matrix{Bool} structure for now, switch to Int8-based binary embeddings with the latest PT
     embedder_kwargs_ = RT.getpropertynested(
         RAG_KWARGS[], [:retriever_kwargs], :embedder_kwargs, nothing)
     embedder_kwargs = haskey(kwargs, :embedder_kwargs) ?
-                      merge(kwargs.embedder_kwargs, embedder_kwargs_) : embedder_kwargs_
+                      merge(
+        (; return_type = Matrix{Bool}), embedder_kwargs_, kwargs[:embedder_kwargs]) :
+                      merge((; return_type = Matrix{Bool}), embedder_kwargs_)
 
     new_index = RT.build_index(RAG_CONFIG[].indexer, all_docs;
-        embedder_kwargs, chunker = TextChunker(), chunker_kwargs,
-        verbose, index_id = nameof(mod), kwargs...)
+        kwargs...,
+        embedder_kwargs, chunker = RT.TextChunker(), chunker_kwargs,
+        verbose, index_id = :all_modules)
 end

test/preparation.jl

@@ -1,4 +1,4 @@
-using AIHelpMe: docextract
+using AIHelpMe: docextract, build_index
 
 # create an empty module
 module ABC123
@@ -24,3 +24,72 @@ end
     @test length(all_sources) == 2
     @test occursin("ABC1234", all_sources[2])
 end
+
+@testset "build_index" begin
+    # test with a mock server
+    PORT = rand(9000:31000)
+    PT.register_model!(; name = "mock-emb", schema = PT.CustomOpenAISchema())
+    PT.register_model!(; name = "mock-meta", schema = PT.CustomOpenAISchema())
+    PT.register_model!(; name = "mock-gen", schema = PT.CustomOpenAISchema())
+
+    echo_server = HTTP.serve!(PORT; verbose = -1) do req
+        content = JSON3.read(req.body)
+
+        if content[:model] == "mock-gen"
+            user_msg = last(content[:messages])
+            response = Dict(
+                :choices => [
+                    Dict(:message => user_msg, :finish_reason => "stop")
+                ],
+                :model => content[:model],
+                :usage => Dict(:total_tokens => length(user_msg[:content]),
+                    :prompt_tokens => length(user_msg[:content]),
+                    :completion_tokens => 0))
+        elseif content[:model] == "mock-emb"
+            response = Dict(
+                :data => [Dict(:embedding => ones(Float32, 1536))
+                          for i in 1:length(content[:input])],
+                :usage => Dict(:total_tokens => length(content[:input]),
+                    :prompt_tokens => length(content[:input]),
+                    :completion_tokens => 0))
+        elseif content[:model] == "mock-meta"
+            user_msg = last(content[:messages])
+            response = Dict(
+                :choices => [
+                    Dict(:finish_reason => "stop",
+                    :message => Dict(:tool_calls => [
+                        Dict(:function => Dict(:arguments => JSON3.write(MaybeTags([
+                        Tag("yes", "category")
+                    ]))))]))],
+                :model => content[:model],
+                :usage => Dict(:total_tokens => length(user_msg[:content]),
+                    :prompt_tokens => length(user_msg[:content]),
+                    :completion_tokens => 0))
+        else
+            @info content
+        end
+        return HTTP.Response(200, JSON3.write(response))
+    end
+
+    # One module
+    index = build_index(AIHelpMe; verbose = 2, embedder_kwargs = (; model = "mock-emb"),
+        tagger_kwargs = (; model = "mock-meta"), api_kwargs = (;
+            url = "http://localhost:$(PORT)"))
+    @test index.embeddings == ones(Bool, 1024, length(index.chunks))
+    @test all(x -> occursin("AIHelpMe", x), index.sources)
+    @test index.tags == nothing
+    @test index.tags_vocab == nothing
+
+    # Many modules
+    index = build_index(
+        [AIHelpMe, Test]; verbose = 2, embedder_kwargs = (; model = "mock-emb"),
+        tagger_kwargs = (; model = "mock-meta"), api_kwargs = (;
+            url = "http://localhost:$(PORT)"))
+    @test index.embeddings == ones(Bool, 1024, length(index.chunks))
+    @test all(x -> occursin("AIHelpMe", x) || occursin("Test", x), index.sources)
+    @test index.tags == nothing
+    @test index.tags_vocab == nothing
+
+    # clean up
+    close(echo_server)
+end

test/runtests.jl

@@ -3,6 +3,7 @@ using PromptingTools
 using PromptingTools.Experimental.RAGTools
 const PT = PromptingTools
 const RT = PromptingTools.Experimental.RAGTools
+using PromptingTools: HTTP, JSON3
 using HDF5, Serialization
 using Test
 using Aqua