searchat 0.2.2

Semantic search and RAG for local AI coding agent conversations

Searchat

Semantic search and RAG-powered Q&A for AI coding agent conversations. Find past solutions by meaning, not just keywords, and ask questions about your conversation history.

Fork of: Process-Point-Technologies-Corporation/searchat

Supported Agents

Agent	Location	Format
Claude Code	~/.claude/projects/**/*.jsonl	JSONL
Mistral Vibe	~/.vibe/logs/session/*.json	JSON
OpenCode	~/.local/share/opencode/storage/session/*/*.json	JSON
OpenAI Codex	~/.codex/sessions/**/rollout-*.jsonl	JSONL
Gemini CLI	~/.gemini/tmp/<project_hash>/chats/*.json	JSON

Features

Core Search

• Hybrid Search — BM25 keyword + FAISS semantic vectors with RRF fusion
• Multi-Agent — Search across Claude Code, Mistral Vibe, and OpenCode sessions
• Tool Filters — Filter results by specific agent (Claude, Vibe, or OpenCode)
• Autocomplete — Smart search suggestions as you type
• Search History — Persistent search history with LocalStorage

AI-Powered Features

• RAG Chat — Ask questions about your conversation history with AI-powered answers
• Semantic Highlights — Optional LLM-generated highlight terms for search results
• Conversation Similarity — Discover related conversations using semantic similarity
• Code Extraction — Extract and view code snippets with syntax highlighting

Organization & Management

• Bookmarks — Save and annotate favorite conversations
• Saved Queries — Save reusable searches (query + filters + mode)
• Dashboards — Build dashboards from saved queries (widgets + auto-refresh)
• Search Analytics — Track search patterns and usage statistics
• Export — Export conversations in JSON/Markdown/Text (optional PDF + Jupyter notebook)
• Bulk Export — Export multiple conversations at once
• Pagination — Navigate large result sets efficiently

Data Safety & Performance

• Live Indexing — Auto-indexes new/modified files (5min debounce)
• Append-Only — Never deletes existing data, safe for long-term use
• Backups — Create and restore backups from UI or API
• Snapshots — Browse backups as read-only datasets ("snapshot" mode)
• Safe Shutdown — Detects ongoing indexing, prevents data corruption
• DuckDB Storage — Efficient Parquet-based storage with fast queries
• FAISS Vectors — High-performance semantic search

User Experience

• Keyboard Shortcuts — Power user navigation and commands
• Cross-Platform — Windows, WSL, Linux, macOS
• Local-First — All data stays on your machine
• Self-Search — Agents can search their own history via API
• Terminal Resume — Resume conversations directly in terminal

Quick Start

git clone https://github.com/Mathews-Tom/searchat.git
cd searchat
pip install -e .

# First-time setup: build search index
python scripts/setup-index

# Start web server
searchat-web

Open http://localhost:8000

The setup script indexes all conversations from supported agents. On subsequent runs, the web server automatically indexes new conversations via live file watching.

Enable Claude Self-Search

Add to ~/.claude/CLAUDE.md:

## Conversation History Search

Search past Claude Code conversations via local API (requires server running).

**Search:**

```bash
curl -s "http://localhost:8000/api/search?q=QUERY&limit=5" | jq '.results[] | {id: .conversation_id, title, snippet}'
```

Get full conversation:

curl -s "http://localhost:8000/api/conversation/CONVERSATION_ID" | jq '.messages[] | {role, content: .content[:500]}'

Ask questions (RAG):

curl -X POST "http://localhost:8000/api/chat" \
  -H "Content-Type: application/json" \
  -d '{"query": "How did we implement authentication?", "model_provider": "openai", "model_name": "gpt-4.1-mini"}'

When to use:

• User asks "did we discuss X before" or "find that conversation about Y"
• Looking for previous solutions to similar problems
• Checking how something was implemented in past sessions
• Asking questions about past work (use RAG chat)

Start server: searchat-web from the searchat directory

See `CLAUDE.example.md` for the full template.

## Usage

### Web UI

```bash
searchat-web

Features:

• Search Modes: hybrid/semantic/keyword with autocomplete
• Filters: project, date range, tool (agent), similarity search
• View Conversations: Full message history with code extraction
• Bookmarks: Save and annotate favorite conversations
• RAG Chat: Ask questions about your conversation history
• Analytics: View search patterns and statistics
• Saved Queries: Save and re-run complex searches
• Dashboards: Create dashboards and widgets from saved queries
• Export: Download conversations in multiple formats
• Backups: Create and restore backups (left sidebar)
• Snapshots: Switch between active index and read-only backup snapshots
• Keyboard Shortcuts: Press ? to see all shortcuts
• Terminal Resume: Resume conversations in terminal
• Helpful Tips: Search tips + API integration sidebars

CLI

searchat  # interactive mode

API

Search & Discovery

# Search
curl "http://localhost:8000/api/search?q=authentication&mode=hybrid&limit=10"

# Search with tool filter (claude, vibe, opencode)
curl "http://localhost:8000/api/search?q=authentication&tool=claude&limit=10"

# Autocomplete suggestions
curl "http://localhost:8000/api/search/suggestions?q=auth&limit=5"

# Find similar conversations
curl "http://localhost:8000/api/conversation/{conversation_id}/similar?limit=5"

# Optional: request highlight terms for the UI (LLM)
curl "http://localhost:8000/api/search?q=auth&mode=hybrid&highlight=true&highlight_provider=ollama"

# Search with pagination
curl "http://localhost:8000/api/search?q=api&limit=20&offset=0"

Conversations

# Get conversation
curl "http://localhost:8000/api/conversation/{conversation_id}"

# List all conversations
curl "http://localhost:8000/api/conversations/all?limit=50"

# Extract code snippets
curl "http://localhost:8000/api/conversation/{conversation_id}/code"

# Code highlighting (Pygments)
curl -X POST "http://localhost:8000/api/code/highlight" \
  -H "Content-Type: application/json" \
  -d '{"blocks":[{"code":"print(123)","language":"python","language_source":"fence"}]}'

# Conversation diff
curl "http://localhost:8000/api/conversation/{conversation_id}/diff?target_id={other_conversation_id}"

# Export conversation
curl "http://localhost:8000/api/conversation/{conversation_id}/export?format=markdown"

# Bulk export
curl -X POST "http://localhost:8000/api/conversations/bulk-export" \
  -H "Content-Type: application/json" \
  -d '{"conversation_ids": ["id1", "id2"], "format": "json"}'

# Resume in terminal
curl -X POST "http://localhost:8000/api/resume?conversation_id={id}"

Bookmarks

# List bookmarks
curl "http://localhost:8000/api/bookmarks"

# Add bookmark
curl -X POST "http://localhost:8000/api/bookmarks" \
  -H "Content-Type: application/json" \
  -d '{"conversation_id": "abc123", "notes": "Important auth solution"}'

# Remove bookmark
curl -X DELETE "http://localhost:8000/api/bookmarks/{conversation_id}"

RAG Chat

# Ask question about conversation history
curl -X POST "http://localhost:8000/api/chat" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "How did we implement authentication?",
    "model_provider": "openai",
    "model_name": "gpt-4.1-mini"
  }'

# Non-streaming RAG response with citations
curl -X POST "http://localhost:8000/api/chat-rag" \
  -H "Content-Type: application/json" \
  -d '{"query":"Summarize how backups work","model_provider":"ollama","model_name":"ollama/gemma3"}'

# Streaming response (default)
curl -X POST "http://localhost:8000/api/chat" \
  -H "Content-Type: application/json" \
  -d '{"query": "Explain the API design", "model_provider": "ollama", "model_name": "llama3"}' \
  --no-buffer

Analytics & Statistics

# Index statistics
curl "http://localhost:8000/api/statistics"

# Search analytics
curl "http://localhost:8000/api/stats/analytics/summary?days=7"

# Top queries / trends
curl "http://localhost:8000/api/stats/analytics/top-queries?limit=10&days=30"
curl "http://localhost:8000/api/stats/analytics/trends?days=30"

# List projects
curl "http://localhost:8000/api/projects"

# Project summary
curl "http://localhost:8000/api/projects/summary"

Saved Queries & Dashboards

# Saved queries
curl "http://localhost:8000/api/queries"

# Dashboards
curl "http://localhost:8000/api/dashboards"

Tech Docs (Optional)

Requires export.enable_tech_docs=true.

curl -X POST "http://localhost:8000/api/docs/summary" \
  -H "Content-Type: application/json" \
  -d '{
    "title": "Searchat Notes",
    "format": "markdown",
    "sections": [
      {"name": "Backups", "query": "backup restore", "mode": "hybrid", "filters": {"project": "myapp"}}
    ]
  }'

Snapshots (Read-only)

# Search within a backup snapshot
curl "http://localhost:8000/api/search?q=auth&snapshot=backup_YYYYMMDD_HHMMSS"

Indexing & Management

# Watcher status
curl "http://localhost:8000/api/watcher/status"

# Index missing conversations (append-only)
curl -X POST "http://localhost:8000/api/index_missing"

# Safe shutdown (checks for ongoing indexing)
curl -X POST "http://localhost:8000/api/shutdown"

# Force shutdown (override safety check)
curl -X POST "http://localhost:8000/api/shutdown?force=true"

Backups

# Create backup
curl -X POST "http://localhost:8000/api/backup/create"

# List backups
curl "http://localhost:8000/api/backup/list"

# Restore backup
curl -X POST "http://localhost:8000/api/backup/restore" \
  -H "Content-Type: application/json" \
  -d '{"name": "backup_YYYYMMDD_HHMMSS"}'

# Delete backup
curl -X DELETE "http://localhost:8000/api/backup/delete/backup_YYYYMMDD_HHMMSS"

Utilities

# Add missing conversations to index
python scripts/index-missing

# Initial setup (interactive, safe options)
python scripts/setup-index

# Convert Vibe plaintext history to searchable sessions
python utils/vibe_converter.py

As Library

from searchat.core.search_engine import SearchEngine
from searchat.config.settings import Config

config = Config.load()
engine = SearchEngine(config.paths.search_directory, config)

results = engine.search("python async", mode="hybrid")
for r in results.results[:5]:
    print(f"{r.title}: {r.score:.3f}")

Architecture

Code Organization:

• src/searchat/api/ - FastAPI app with 13 modular routers (50+ endpoints)
• src/searchat/core/ - Core indexing and search logic
• src/searchat/services/ - Business services (chat, bookmarks, analytics, backup)
• src/searchat/web/ - Modular frontend (HTML + CSS modules + ES6 JS)
• tests/ - Comprehensive test suite (500+ tests)

Data Flow:

~/.claude/projects/**/*.jsonl     (source conversations)
~/.vibe/logs/session/*.json
~/.local/share/opencode/.../*.json
        │
        ▼ index_append_only()
        │
~/.searchat/data/
├── conversations/*.parquet       (DuckDB queryable)
└── indices/
    ├── embeddings.faiss          (semantic vectors)
    ├── embeddings.metadata.parquet
    └── index_metadata.json

Search Flow:

1. Query → BM25 keyword search + FAISS semantic search
2. Results merged via Reciprocal Rank Fusion
3. Hybrid ranking returns best of both approaches
4. Optional: Find similar conversations via vector similarity

RAG Flow:

1. User question → Search for relevant conversations
2. Top results used as context
3. LLM generates answer with conversation references
4. Streaming response to client

Live Watching:

• watchdog monitors conversation directories
• New files → indexed immediately
• Modified files → re-indexed after 5min debounce (configurable)
• index_append_only() adds to existing index
• Never deletes existing data

Documentation:

• docs/features.md - Complete feature list and descriptions
• docs/architecture.md - System design and components
• docs/api-reference.md - Complete API endpoint documentation
• docs/terminal-launching.md - Platform-specific terminal launching

Configuration

Create ~/.searchat/config/settings.toml:

[paths]
search_directory = "~/.searchat"
claude_directory_windows = "~/.claude/projects"
claude_directory_wsl = "//wsl$/Ubuntu/home/{username}/.claude/projects"

[indexing]
batch_size = 1000
auto_index = true
reindex_on_modification = true  # Re-index modified conversations
modification_debounce_minutes = 5  # Wait time before re-indexing
enable_connectors = true
enable_adaptive_indexing = true

[search]
default_mode = "hybrid"
max_results = 100
snippet_length = 200

[embedding]
model = "all-MiniLM-L6-v2"
batch_size = 32
device = "auto"  # auto|cuda|mps|cpu

[llm]
default_provider = "ollama"
openai_model = "gpt-4.1-mini"
ollama_model = "ollama/gemma3"

[chat]
enable_rag = true
enable_citations = true

[analytics]
enabled = false
retention_days = 30

[export]
enable_ipynb = false
enable_pdf = false
enable_tech_docs = false

[dashboards]
enabled = true

[snapshots]
enabled = true

[performance]
memory_limit_mb = 3000
query_cache_size = 100

Or use environment variables:

export SEARCHAT_DATA_DIR=~/.searchat
export SEARCHAT_PORT=8000
export SEARCHAT_EMBEDDING_MODEL=all-MiniLM-L6-v2
export SEARCHAT_REINDEX_ON_MODIFICATION=true
export SEARCHAT_MODIFICATION_DEBOUNCE_MINUTES=5
export SEARCHAT_OPENCODE_DATA_DIR=~/.local/share/opencode
export OPENAI_API_KEY=sk-...  # For RAG chat
export OLLAMA_BASE_URL=http://localhost:11434

Requirements

• Python 3.9+
• ~2-3GB RAM (embeddings model + FAISS index)
• ~10MB disk per 1K conversations
• Optional: OpenAI API key or Ollama for RAG chat

Dependencies

Package	Purpose
sentence-transformers	Embeddings (all-MiniLM-L6-v2)
faiss-cpu	Vector similarity search
pyarrow	Parquet storage
duckdb	SQL queries on parquet
fastapi + uvicorn	Web API
watchdog	File system monitoring
litellm	Multi-provider LLM interface
rich	CLI formatting

Safety

Append-only indexing: Never deletes existing data.

indexer.index_append_only(file_paths)  # Safe: only adds new data
indexer.index_all()                     # Blocked if index exists
indexer.index_all(force=True)           # Explicit override required

Safe shutdown: Detects ongoing indexing operations.

# Check status, wait if indexing in progress
curl -X POST "http://localhost:8000/api/shutdown"

# Override safety check (may corrupt data)
curl -X POST "http://localhost:8000/api/shutdown?force=true"

Backups: Create backups before risky operations.

# Automatic pre-restore backup before any restore operation
curl -X POST "http://localhost:8000/api/backup/restore" -d '{"name": "backup_20260129_120000"}'

Protects against:

• Data loss from deleted/moved source files
• Corrupted Parquet/FAISS files during indexing
• Inconsistent metadata from interrupted operations

Performance

Metric	Value
Search latency	<100ms (hybrid), <50ms (semantic), <30ms (keyword)
Filtered queries	<20ms (DuckDB predicate pushdown)
Index build	~60s per 100K conversations
Embedding	Batched (CPU: 0.1s/conv, GPU: 0.008s/conv)
Memory	~2-3GB
Startup	<3s
RAG chat response	<2s (with OpenAI), <5s (with Ollama)
Code extraction	<50ms per conversation
Similarity search	<100ms (FAISS nearest neighbors)

Testing

pytest                          # Run the full test suite
pytest tests/api/              # Run API tests only
pytest -v                      # Verbose output
pytest -k test_search          # Run specific tests
pytest --cov=searchat          # Coverage report
pytest --cov-report=html       # HTML coverage report

Test Coverage:

• 500+ tests (API, UI contract tests, unit tests, perf gates)
• ~5,900 lines of test code
• Comprehensive coverage of all features
• API endpoint tests, unit tests, integration tests

Troubleshooting

Port in use:

SEARCHAT_PORT=8001 searchat-web

No conversations found:

ls ~/.claude/projects/  # Verify conversations exist

WSL not tracked: Configure claude_directory_wsl in ~/.searchat/config/settings.toml:

claude_directory_wsl = "//wsl.localhost/Ubuntu/home/username/.claude/projects"

Missing conversations after setup:

python scripts/index-missing  # Index files not yet in search index

Slow on WSL: Run from Windows Python or move repo to WSL filesystem (~/projects/).

Import errors:

pip install -e . --force-reinstall

Empty environment variables override config: Remove empty values from ~/.searchat/config/.env or set proper values.

RAG chat not working:

# For OpenAI
export OPENAI_API_KEY=sk-...

# For Ollama (local)
ollama serve  # Start Ollama server
export OLLAMA_BASE_URL=http://localhost:11434

Fork Enhancements

This fork adds significant new features beyond the original:

• RAG Chat - AI-powered Q&A over conversation history
• Bookmarks System - Save and organize favorite conversations
• Search Analytics - Track and analyze search patterns
• Conversation Similarity - Discover related conversations
• Code Extraction - Extract code snippets with syntax highlighting
• Saved Queries - Reusable searches with stored filters
• Dashboards - Builder UI + widgets rendered from saved queries
• Snapshots - Browse backups as read-only datasets
• Export Features - JSON/Markdown/Text exports (optional PDF + Jupyter)
• Bulk Export - Export multiple conversations at once
• Pagination - Efficient navigation of large result sets
• Autocomplete - Smart search suggestions
• Search History - Persistent search history
• Keyboard Shortcuts - Power user shortcuts
• OpenCode Support - Added third agent support
• Tool Filtering - Filter by specific agent
• Modern Typing - Python 3.12 type hints throughout

See docs/features.md for complete feature documentation.

Contributing

See CONTRIBUTING.md for guidelines.

License

MIT