https://github.com/p-funk/fegis
Compile YAML into semantic LLM tools with structured memory and an emergent knowledge graph.
https://github.com/p-funk/fegis
Last synced: 3 months ago
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Compile YAML into semantic LLM tools with structured memory and an emergent knowledge graph.
- Host: GitHub
- URL: https://github.com/p-funk/fegis
- Owner: p-funk
- License: mit
- Created: 2025-04-04T19:02:04.000Z (6 months ago)
- Default Branch: master
- Last Pushed: 2025-05-15T23:52:43.000Z (5 months ago)
- Last Synced: 2025-06-22T18:12:54.609Z (4 months ago)
- Language: Python
- Homepage:
- Size: 1020 KB
- Stars: 16
- Watchers: 1
- Forks: 3
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Fegis
Fegis does 3 things:
1. **Easy to write tools** - Write prompts in YAML format. Tool schemas use flexible natural language instructions.
2. **Structured data from tool calls saved in a vector database** - Every tool use is automatically stored in Qdrant with full context.
3. **Search** - AI can search through all previous tool usage using semantic similarity, filters, or direct lookup.
## Quick Start
```bash
# Install uv
# Windows
winget install --id=astral-sh.uv -e
# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh
# Clone
git clone https://github.com/p-funk/fegis.git
# Start Qdrant
docker run -d --name qdrant -p 6333:6333 -p 6334:6334 qdrant/qdrant:latest
```
## Configure Claude Desktop
Update `claude_desktop_config.json`:
```json
{
"mcpServers": {
"fegis": {
"command": "uv",
"args": [
"--directory",
"/absolute/path/to/fegis",
"run",
"fegis"
],
"env": {
"QDRANT_URL": "http://localhost:6333",
"QDRANT_API_KEY": "",
"COLLECTION_NAME": "fegis_memory",
"EMBEDDING_MODEL": "BAAI/bge-small-en",
"ARCHETYPE_PATH": "/absolute/path/to/fegis-wip/archetypes/default.yaml",
"AGENT_ID": "claude_desktop"
}
}
}
}
```
Restart Claude Desktop. You'll have 7 new tools available including SearchMemory.
## How It Works
### 1. Tools from YAML
```yaml
parameters:
BiasScope:
description: "Range of bias detection to apply"
examples: [confirmation, availability, anchoring, systematic, comprehensive]
IntrospectionDepth:
description: "How deeply to examine internal reasoning processes"
examples: [surface, moderate, deep, exhaustive, meta_recursive]
tools:
BiasDetector:
description: "Identify reasoning blind spots, cognitive biases, and systematic errors in AI thinking patterns through structured self-examination"
parameters:
BiasScope:
IntrospectionDepth:
frames:
identified_biases:
type: List
required: true
reasoning_patterns:
type: List
required: true
alternative_perspectives:
type: List
required: true
```
### 2. Automatic Memory Storage
Every tool invocation gets stored with:
- Tool name and parameters used
- Complete input and output
- Timestamp and session context
- Vector embeddings for semantic search
### 3. SearchMemory Tool
```
"Use SearchMemory and find my analysis of privacy concerns"
"Use SearchMemory and what creative ideas did I generate last week?"
"Use SearchMemory and show me all UncertaintyNavigator results"
"Use SearchMemory and search for memories about decision-making"
```
## Available Archetypes
- `archetypes/default.yaml` - Cognitive analysis tools (UncertaintyNavigator, BiasDetector, etc.)
- `archetypes/simple_example.yaml` - Basic example tools
- `archetypes/emoji_mind.yaml` - Symbolic reasoning with emojis
- `archetypes/slime_mold.yaml` - Network optimization tools
- `archetypes/vibe_surfer.yaml` - Web exploration tools
## Configuration
Required environment variables:
- `ARCHETYPE_PATH` - Path to YAML archetype file
- `QDRANT_URL` - Qdrant database URL (default: http://localhost:6333)
Optional environment variables:
- `COLLECTION_NAME` - Qdrant collection name (default: fegis_memory)
- `AGENT_ID` - Identifier for this agent (default: default-agent)
- `EMBEDDING_MODEL` - Dense embedding model (default: BAAI/bge-small-en)
- `QDRANT_API_KEY` - API key for remote Qdrant (default: empty)
## Requirements
- Python 3.13+
- uv package manager
- Docker (for Qdrant)
- MCP-compatible client
## License
MIT License - see LICENSE file for details.