Finished code cleanup, readme is mostly done.

pkg/llm/llm.go

@@ -18,12 +18,14 @@ const contextKeyLLM contextKey = "llm"
 //go:embed prompts
 var prompts embed.FS
 
+// LLM is responsible for abstracting the configuration and implementations of the LLMs used.
 type LLM struct {
 	code     llms.Model
 	chat     llms.Model
 	embedder embeddings.Embedder
 }
 
+// FromConfig bootstraps the LLM from a passed in configuration.
 func FromConfig(cfg *config.Configuration) (*LLM, error) {
 	embedLLM, err := cfg.Embedding.GetEmbedding()
 	if err != nil {
@@ -52,30 +54,32 @@ func FromConfig(cfg *config.Configuration) (*LLM, error) {
 	}, nil
 }
 
+// FromContext retrieves an LLM from a passed in context wrapped with WrapContext.
 func FromContext(ctx context.Context) *LLM {
 	return ctx.Value(contextKeyLLM).(*LLM)
 }
 
+// WrapContext embeds an LLM inside a context so it can be retrieved with FromContext.
 func WrapContext(ctx context.Context, llmRef *LLM) context.Context {
 	return context.WithValue(ctx, contextKeyLLM, llmRef)
 }
 
-func (llm *LLM) GetEmbedding(ctx context.Context, texts ...string) ([][]float32, error) {
-	return llm.embedder.EmbedDocuments(ctx, texts)
-}
-
+// Embedder gets an embedder that can be used to store and retrieve embeddings.
 func (llm *LLM) Embedder() embeddings.Embedder {
 	return llm.embedder
 }
 
+// CodePrompt passes a prompt to the code LLM and returns the response.
 func (llm *LLM) CodePrompt(ctx context.Context, prompt string) (string, error) {
 	return llm.code.Call(ctx, prompt)
 }
 
+// ChatPrompt passes a prompt to the chat LLM and returns the response.
 func (llm *LLM) ChatPrompt(ctx context.Context, prompt string) (string, error) {
 	return llm.chat.Call(ctx, prompt)
 }
 
+// GetPrompt loads a LLM prompt template and injects variables into it. Uses the go template format.
 func GetPrompt(name string, data any) (string, error) {
 	tmplText, err := prompts.ReadFile("prompts/" + name + ".tmpl")
 	if err != nil {

pkg/llm/relevent_docs.go

@@ -9,6 +9,7 @@ import (
 	"strconv"
 )
 
+// RelevantDocs attempts to find the most relevant file chunks based on context from the prompt.
 type RelevantDocs struct {
 	CallbacksHandler callbacks.Handler
 	db               *database.Database
@@ -17,6 +18,7 @@ type RelevantDocs struct {
 	size             int
 }
 
+// FileChunkID is a pointer to a repository file chunk that has been indexed.
 type FileChunkID struct {
 	Name    string
 	ChunkID int
@@ -26,6 +28,7 @@ type FileChunkID struct {
 	Doc     *schema.Document
 }
 
+// NewGetRelevantDocs creates a new RelevantDocs scanner.
 func NewGetRelevantDocs(db *database.Database, llm *LLM, repoID string, size int) *RelevantDocs {
 	return &RelevantDocs{
 		db:     db,
@@ -35,6 +38,7 @@ func NewGetRelevantDocs(db *database.Database, llm *LLM, repoID string, size int
 	}
 }
 
+// GetRelevantFileChunks will scan for relevant documents based on a prompt.
 func (rd *RelevantDocs) GetRelevantFileChunks(ctx context.Context, query string) ([]*FileChunkID, error) {
 	vectorStore, closeFunc, err := rd.db.GetVectorStore(ctx, rd.llm.Embedder())
 	if err != nil {