warkanum
cfc78e0493
Add a retrieval_mode field ("semantic" or "text") to the output of all
five query-driven tools so callers can distinguish vector search from
Postgres full-text fallback without inspecting server logs.
Tools updated: search_thoughts, recall_context, get_project_context,
summarize_thoughts, and related_thoughts (semantic neighbours only;
omitempty so field is absent when include_semantic is false or no query
is provided for the non-mandatory-query tools).
The shared semanticSearch helper now returns the mode as a third return
value. All callers updated; fixes two compile errors left by the
previous worker (summarize.go and links.go were not capturing the new
return).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
112 lines
3.5 KiB
Go
112 lines
3.5 KiB
Go
package tools
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import (
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"context"
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"fmt"
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"strings"
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"github.com/modelcontextprotocol/go-sdk/mcp"
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"git.warky.dev/wdevs/amcs/internal/ai"
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"git.warky.dev/wdevs/amcs/internal/config"
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"git.warky.dev/wdevs/amcs/internal/session"
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"git.warky.dev/wdevs/amcs/internal/store"
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thoughttypes "git.warky.dev/wdevs/amcs/internal/types"
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)
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type ContextTool struct {
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store *store.DB
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embeddings *ai.EmbeddingRunner
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search config.SearchConfig
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sessions *session.ActiveProjects
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}
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type ProjectContextInput struct {
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Project string `json:"project,omitempty" jsonschema:"project name or id; falls back to the active session project"`
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Query string `json:"query,omitempty" jsonschema:"optional semantic focus for project context"`
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Limit int `json:"limit,omitempty" jsonschema:"maximum number of context items to return"`
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}
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type ContextItem struct {
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ID string `json:"id"`
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Content string `json:"content"`
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Metadata thoughttypes.ThoughtMetadata `json:"metadata"`
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Similarity float64 `json:"similarity,omitempty"`
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Source string `json:"source"`
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}
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type ProjectContextOutput struct {
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Project thoughttypes.Project `json:"project"`
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Context string `json:"context"`
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Items []ContextItem `json:"items"`
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RetrievalMode string `json:"retrieval_mode,omitempty"`
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}
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func NewContextTool(db *store.DB, embeddings *ai.EmbeddingRunner, search config.SearchConfig, sessions *session.ActiveProjects) *ContextTool {
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return &ContextTool{store: db, embeddings: embeddings, search: search, sessions: sessions}
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}
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func (t *ContextTool) Handle(ctx context.Context, req *mcp.CallToolRequest, in ProjectContextInput) (*mcp.CallToolResult, ProjectContextOutput, error) {
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project, err := resolveProject(ctx, t.store, t.sessions, req, in.Project, true)
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if err != nil {
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return nil, ProjectContextOutput{}, err
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}
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limit := normalizeLimit(in.Limit, t.search)
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recent, err := t.store.RecentThoughts(ctx, &project.NumericID, limit, 0)
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if err != nil {
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return nil, ProjectContextOutput{}, err
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}
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items := make([]ContextItem, 0, limit*2)
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seen := map[string]struct{}{}
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for _, thought := range recent {
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key := fmt.Sprint(thought.ID)
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seen[key] = struct{}{}
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items = append(items, ContextItem{
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ID: key,
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Content: thought.Content,
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Metadata: thought.Metadata,
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Source: "recent",
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})
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}
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var retrievalMode string
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query := strings.TrimSpace(in.Query)
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if query != "" {
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semantic, mode, err := semanticSearch(ctx, t.store, t.embeddings, t.search, query, limit, t.search.DefaultThreshold, &project.NumericID, nil)
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if err != nil {
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return nil, ProjectContextOutput{}, err
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}
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retrievalMode = mode
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for _, result := range semantic {
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key := fmt.Sprint(result.ID)
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if _, ok := seen[key]; ok {
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continue
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}
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seen[key] = struct{}{}
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items = append(items, ContextItem{
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ID: key,
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Content: result.Content,
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Metadata: result.Metadata,
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Similarity: result.Similarity,
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Source: "semantic",
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})
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}
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}
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lines := make([]string, 0, len(items))
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for i, item := range items {
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lines = append(lines, thoughtContextLine(i, item.Content, item.Metadata, item.Similarity))
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}
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contextBlock := formatContextBlock(fmt.Sprintf("Project context for %s", project.Name), lines)
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_ = t.store.TouchProject(ctx, project.NumericID)
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return nil, ProjectContextOutput{
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Project: *project,
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Context: contextBlock,
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Items: items,
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RetrievalMode: retrievalMode,
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}, nil
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}
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