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CHANGELOG.md
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CHANGELOG.md
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All notable changes to Project Lyra are organized by component.
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All notable changes to Project Lyra are organized by component.
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/)
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/)
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and adheres to [Semantic Versioning](https://semver.org/).
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and adheres to [Semantic Versioning](https://semver.org/).
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# Last Updated: 11-26-25
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# Last Updated: 11-28-25
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---
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---
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## 🧠 Lyra-Core ##############################################################################
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## 🧠 Lyra-Core ##############################################################################
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## [Project Lyra v0.5.0] - 2025-11-28
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### 🔧 Fixed - Critical API Wiring & Integration
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After the major architectural rewire (v0.4.x), this release fixes all critical endpoint mismatches and ensures end-to-end system connectivity.
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#### Cortex → Intake Integration ✅
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- **Fixed** `IntakeClient` to use correct Intake v0.2 API endpoints
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- Changed `GET /context/{session_id}` → `GET /summaries?session_id={session_id}`
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- Updated JSON response parsing to extract `summary_text` field
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- Fixed environment variable name: `INTAKE_API` → `INTAKE_API_URL`
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- Corrected default port: `7083` → `7080`
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- Added deprecation warning to `summarize_turn()` method (endpoint removed in Intake v0.2)
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#### Relay → UI Compatibility ✅
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- **Added** OpenAI-compatible endpoint `POST /v1/chat/completions`
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- Accepts standard OpenAI format with `messages[]` array
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- Returns OpenAI-compatible response structure with `choices[]`
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- Extracts last message content from messages array
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- Includes usage metadata (stub values for compatibility)
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- **Refactored** Relay to use shared `handleChatRequest()` function
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- Both `/chat` and `/v1/chat/completions` use same core logic
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- Eliminates code duplication
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- Consistent error handling across endpoints
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#### Relay → Intake Connection ✅
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- **Fixed** Intake URL fallback in Relay server configuration
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- Corrected port: `7082` → `7080`
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- Updated endpoint: `/summary` → `/add_exchange`
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- Now properly sends exchanges to Intake for summarization
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#### Code Quality & Python Package Structure ✅
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- **Added** missing `__init__.py` files to all Cortex subdirectories
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- `cortex/llm/__init__.py`
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- `cortex/reasoning/__init__.py`
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- `cortex/persona/__init__.py`
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- `cortex/ingest/__init__.py`
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- `cortex/utils/__init__.py`
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- Improves package imports and IDE support
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- **Removed** unused import in `cortex/router.py`: `from unittest import result`
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- **Deleted** empty file `cortex/llm/resolve_llm_url.py` (was 0 bytes, never implemented)
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### ✅ Verified Working
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Complete end-to-end message flow now operational:
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```
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UI → Relay (/v1/chat/completions)
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↓
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Relay → Cortex (/reason)
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↓
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Cortex → Intake (/summaries) [retrieves context]
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↓
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Cortex 4-stage pipeline:
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1. reflection.py → meta-awareness notes
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2. reasoning.py → draft answer
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3. refine.py → polished answer
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4. persona/speak.py → Lyra personality
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↓
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Cortex → Relay (returns persona response)
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↓
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Relay → Intake (/add_exchange) [async summary]
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↓
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Intake → NeoMem (background memory storage)
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↓
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Relay → UI (final response)
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```
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### 📝 Documentation
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- **Added** this CHANGELOG entry with comprehensive v0.5.0 notes
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- **Updated** README.md to reflect v0.5.0 architecture
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- Documented new endpoints
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- Updated data flow diagrams
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- Clarified Intake v0.2 changes
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- Corrected service descriptions
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### 🐛 Issues Resolved
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- ❌ Cortex could not retrieve context from Intake (wrong endpoint)
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- ❌ UI could not send messages to Relay (endpoint mismatch)
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- ❌ Relay could not send summaries to Intake (wrong port/endpoint)
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- ❌ Python package imports were implicit (missing __init__.py)
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### ⚠️ Known Issues (Non-Critical)
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- Session management endpoints not implemented in Relay (`GET/POST /sessions/:id`)
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- RAG service currently disabled in docker-compose.yml
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- Cortex `/ingest` endpoint is a stub returning `{"status": "ok"}`
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### 🎯 Migration Notes
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If upgrading from v0.4.x:
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1. Pull latest changes from git
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2. Verify environment variables in `.env` files:
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- Check `INTAKE_API_URL=http://intake:7080` (not `INTAKE_API`)
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- Verify all service URLs use correct ports
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3. Restart Docker containers: `docker-compose down && docker-compose up -d`
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4. Test with a simple message through the UI
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---
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## [Infrastructure v1.0.0] - 2025-11-26
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## [Infrastructure v1.0.0] - 2025-11-26
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### Changed
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### Changed
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README.md
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README.md
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##### Project Lyra - README v0.3.0 - needs fixing #####
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# Project Lyra - README v0.5.0
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Lyra is a modular persistent AI companion system.
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Lyra is a modular persistent AI companion system with advanced reasoning capabilities.
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It provides memory-backed chat using **NeoMem** + **Relay** + **Persona Sidecar**,
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It provides memory-backed chat using **NeoMem** + **Relay** + **Cortex**,
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with optional subconscious annotation powered by **Cortex VM** running local LLMs.
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with multi-stage reasoning pipeline powered by distributed LLM backends.
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## Mission Statement ##
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## Mission Statement
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The point of project lyra is to give an AI chatbot more abilities than a typical chatbot. typical chat bots are essentially amnesic and forget everything about your project. Lyra helps keep projects organized and remembers everything you have done. Think of her abilities as a notepad/schedule/data base/ co-creator/collaborattor all with its own executive function. Say something in passing, Lyra remembers it then reminds you of it later.
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The point of Project Lyra is to give an AI chatbot more abilities than a typical chatbot. Typical chatbots are essentially amnesic and forget everything about your project. Lyra helps keep projects organized and remembers everything you have done. Think of her abilities as a notepad/schedule/database/co-creator/collaborator all with its own executive function. Say something in passing, Lyra remembers it then reminds you of it later.
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---
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---
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## Structure ##
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## Architecture Overview
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Project Lyra exists as a series of docker containers that run independentally of each other but are all networked together. Think of it as how the brain has regions, Lyra has modules:
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## A. VM 100 - lyra-core:
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1. ** Core v0.3.1 - Docker Stack
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- Relay - (docker container) - The main harness that connects the modules together and accepts input from the user.
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- UI - (HTML) - This is how the user communicates with lyra. ATM its a typical instant message interface, but plans are to make it much more than that.
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- Persona - (docker container) - This is the personality of lyra, set how you want her to behave. Give specific instructions for output. Basically prompt injection.
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- All of this is built and controlled by a single .env and docker-compose.lyra.yml.
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2. **NeoMem v0.1.0 - (docker stack)
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- NeoMem is Lyra's main long term memory data base. It is a fork of mem0 oss. Uses vector databases and graph.
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- NeoMem launches with a single separate docker-compose.neomem.yml.
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## B. VM 101 - lyra - cortex
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Project Lyra operates as a series of Docker containers networked together in a microservices architecture. Like how the brain has regions, Lyra has modules:
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3. ** Cortex - VM containing docker stack
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- This is the working reasoning layer of Lyra.
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- Built to be flexible in deployment. Run it locally or remotely (via wan/lan)
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- Intake v0.1.0 - (docker Container) gives conversations context and purpose
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- Intake takes the last N exchanges and summarizes them into coherrent short term memories.
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- Uses a cascading summarization setup that quantizes the exchanges. Summaries occur at L2, L5, L10, L15, L20 etc.
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- Keeps the bot aware of what is going on with out having to send it the whole chat every time.
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- Cortex - Docker container containing:
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- Reasoning Layer
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- TBD
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- Reflect - (docker continer) - Not yet implemented, road map.
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- Calls back to NeoMem after N exchanges and N summaries and edits memories created during the initial messaging step. This helps contain memories to coherrent thoughts, reduces the noise.
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- Can be done actively and asynchronously, or on a time basis (think human sleep and dreams).
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- This stage is not yet built, this is just an idea.
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## C. Remote LLM APIs:
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### A. VM 100 - lyra-core (Core Services)
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3. **AI Backends
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- Lyra doesnt run models her self, she calls up APIs.
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**1. Relay** (Node.js/Express) - Port 7078
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- Endlessly customizable as long as it outputs to the same schema.
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- Main orchestrator and message router
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- Coordinates all module interactions
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- OpenAI-compatible endpoint: `POST /v1/chat/completions`
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- Internal endpoint: `POST /chat`
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- Routes messages through Cortex reasoning pipeline
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- Manages async calls to Intake and NeoMem
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**2. UI** (Static HTML)
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- Browser-based chat interface with cyberpunk theme
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- Connects to Relay at `http://10.0.0.40:7078`
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- Saves and loads sessions
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- OpenAI-compatible message format
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**3. NeoMem** (Python/FastAPI) - Port 7077
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- Long-term memory database (fork of Mem0 OSS)
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- Vector storage (PostgreSQL + pgvector) + Graph storage (Neo4j)
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||||||
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- RESTful API: `/memories`, `/search`
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- Semantic memory updates and retrieval
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||||||
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- No external SDK dependencies - fully local
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||||||
|
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||||||
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### B. VM 101 - lyra-cortex (Reasoning Layer)
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|
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||||||
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**4. Cortex** (Python/FastAPI) - Port 7081
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|
- Primary reasoning engine with multi-stage pipeline
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|
- **4-Stage Processing:**
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||||||
|
1. **Reflection** - Generates meta-awareness notes about conversation
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||||||
|
2. **Reasoning** - Creates initial draft answer using context
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||||||
|
3. **Refinement** - Polishes and improves the draft
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||||||
|
4. **Persona** - Applies Lyra's personality and speaking style
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||||||
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- Integrates with Intake for short-term context
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||||||
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- Flexible LLM router supporting multiple backends
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||||||
|
|
||||||
|
**5. Intake v0.2** (Python/FastAPI) - Port 7080
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||||||
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- Simplified short-term memory summarization
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||||||
|
- Session-based circular buffer (deque, maxlen=200)
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||||||
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- Single-level simple summarization (no cascading)
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||||||
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- Background async processing with FastAPI BackgroundTasks
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|
- Pushes summaries to NeoMem automatically
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||||||
|
- **API Endpoints:**
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||||||
|
- `POST /add_exchange` - Add conversation exchange
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||||||
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- `GET /summaries?session_id={id}` - Retrieve session summary
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||||||
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- `POST /close_session/{id}` - Close and cleanup session
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|
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||||||
|
### C. LLM Backends (Remote/Local APIs)
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||||||
|
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||||||
|
**Multi-Backend Strategy:**
|
||||||
|
- **PRIMARY**: vLLM on AMD MI50 GPU (`http://10.0.0.43:8000`) - Cortex reasoning, Intake
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||||||
|
- **SECONDARY**: Ollama on RTX 3090 (`http://10.0.0.3:11434`) - Configurable per-module
|
||||||
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- **CLOUD**: OpenAI API (`https://api.openai.com/v1`) - Cortex persona layer
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|
- **FALLBACK**: Local backup (`http://10.0.0.41:11435`) - Emergency fallback
|
||||||
|
|
||||||
---
|
---
|
||||||
|
|
||||||
|
## Data Flow Architecture (v0.5.0)
|
||||||
|
|
||||||
## 🚀 Features ##
|
### Normal Message Flow:
|
||||||
|
|
||||||
# Lyra-Core VM (VM100)
|
```
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||||||
- **Relay **:
|
User (UI) → POST /v1/chat/completions
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- The main harness and orchestrator of Lyra.
|
↓
|
||||||
- OpenAI-compatible endpoint: `POST /v1/chat/completions`
|
Relay (7078)
|
||||||
- Injects persona + relevant memories into every LLM call
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↓ POST /reason
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- Routes all memory storage/retrieval through **NeoMem**
|
Cortex (7081)
|
||||||
- Logs spans (`neomem.add`, `neomem.search`, `persona.fetch`, `llm.generate`)
|
↓ GET /summaries?session_id=xxx
|
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|
Intake (7080) [RETURNS SUMMARY]
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||||||
|
↓
|
||||||
|
Cortex processes (4 stages):
|
||||||
|
1. reflection.py → meta-awareness notes
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||||||
|
2. reasoning.py → draft answer (uses LLM)
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||||||
|
3. refine.py → refined answer (uses LLM)
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||||||
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4. persona/speak.py → Lyra personality (uses LLM)
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||||||
|
↓
|
||||||
|
Returns persona answer to Relay
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||||||
|
↓
|
||||||
|
Relay → Cortex /ingest (async, stub)
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||||||
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Relay → Intake /add_exchange (async)
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||||||
|
↓
|
||||||
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Intake → Background summarize → NeoMem
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||||||
|
↓
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||||||
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Relay → UI (returns final response)
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|
```
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||||||
|
|
||||||
- **NeoMem (Memory Engine)**:
|
### Cortex 4-Stage Reasoning Pipeline:
|
||||||
- Forked from Mem0 OSS and fully independent.
|
|
||||||
- Drop-in compatible API (`/memories`, `/search`).
|
|
||||||
- Local-first: runs on FastAPI with Postgres + Neo4j.
|
|
||||||
- No external SDK dependencies.
|
|
||||||
- Default service: `neomem-api` (port 7077).
|
|
||||||
- Capable of adding new memories and updating previous memories. Compares existing embeddings and performs in place updates when a memory is judged to be a semantic match.
|
|
||||||
|
|
||||||
- **UI**:
|
1. **Reflection** (`reflection.py`) - Cloud backend (OpenAI)
|
||||||
- Lightweight static HTML chat page.
|
- Analyzes user intent and conversation context
|
||||||
- Connects to Relay at `http://<host>:7078`.
|
- Generates meta-awareness notes
|
||||||
- Nice cyberpunk theme!
|
- "What is the user really asking?"
|
||||||
- Saves and loads sessions, which then in turn send to relay.
|
|
||||||
|
2. **Reasoning** (`reasoning.py`) - Primary backend (vLLM)
|
||||||
|
- Retrieves short-term context from Intake
|
||||||
|
- Creates initial draft answer
|
||||||
|
- Integrates context, reflection notes, and user prompt
|
||||||
|
|
||||||
|
3. **Refinement** (`refine.py`) - Primary backend (vLLM)
|
||||||
|
- Polishes the draft answer
|
||||||
|
- Improves clarity and coherence
|
||||||
|
- Ensures factual consistency
|
||||||
|
|
||||||
|
4. **Persona** (`speak.py`) - Cloud backend (OpenAI)
|
||||||
|
- Applies Lyra's personality and speaking style
|
||||||
|
- Natural, conversational output
|
||||||
|
- Final answer returned to user
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Features
|
||||||
|
|
||||||
|
### Lyra-Core (VM 100)
|
||||||
|
|
||||||
|
**Relay**:
|
||||||
|
- Main orchestrator and message router
|
||||||
|
- OpenAI-compatible endpoint: `POST /v1/chat/completions`
|
||||||
|
- Internal endpoint: `POST /chat`
|
||||||
|
- Health check: `GET /_health`
|
||||||
|
- Async non-blocking calls to Cortex and Intake
|
||||||
|
- Shared request handler for code reuse
|
||||||
|
- Comprehensive error handling
|
||||||
|
|
||||||
|
**NeoMem (Memory Engine)**:
|
||||||
|
- Forked from Mem0 OSS - fully independent
|
||||||
|
- Drop-in compatible API (`/memories`, `/search`)
|
||||||
|
- Local-first: runs on FastAPI with Postgres + Neo4j
|
||||||
|
- No external SDK dependencies
|
||||||
|
- Semantic memory updates - compares embeddings and performs in-place updates
|
||||||
|
- Default service: `neomem-api` (port 7077)
|
||||||
|
|
||||||
|
**UI**:
|
||||||
|
- Lightweight static HTML chat interface
|
||||||
|
- Cyberpunk theme
|
||||||
|
- Session save/load functionality
|
||||||
|
- OpenAI message format support
|
||||||
|
|
||||||
|
### Cortex (VM 101)
|
||||||
|
|
||||||
|
**Cortex** (v0.5):
|
||||||
|
- Multi-stage reasoning pipeline (reflection → reasoning → refine → persona)
|
||||||
|
- Flexible LLM backend routing
|
||||||
|
- Per-stage backend selection
|
||||||
|
- Async processing throughout
|
||||||
|
- IntakeClient integration for short-term context
|
||||||
|
- `/reason`, `/ingest` (stub), `/health` endpoints
|
||||||
|
|
||||||
|
**Intake** (v0.2):
|
||||||
|
- Simplified single-level summarization
|
||||||
|
- Session-based circular buffer (200 exchanges max)
|
||||||
|
- Background async summarization
|
||||||
|
- Automatic NeoMem push
|
||||||
|
- No persistent log files (memory-only)
|
||||||
|
- **Breaking change from v0.1**: Removed cascading summaries (L1, L2, L5, L10, L20, L30)
|
||||||
|
|
||||||
|
**LLM Router**:
|
||||||
|
- Dynamic backend selection
|
||||||
|
- Environment-driven configuration
|
||||||
|
- Support for vLLM, Ollama, OpenAI, custom endpoints
|
||||||
|
- Per-module backend preferences
|
||||||
|
|
||||||
# Beta Lyrae (RAG Memory DB) - added 11-3-25
|
# Beta Lyrae (RAG Memory DB) - added 11-3-25
|
||||||
- **RAG Knowledge DB - Beta Lyrae (sheliak)**
|
- **RAG Knowledge DB - Beta Lyrae (sheliak)**
|
||||||
@@ -159,7 +264,85 @@ with optional subconscious annotation powered by **Cortex VM** running local LLM
|
|||||||
└── Future: sends summaries → Cortex for reflection
|
└── Future: sends summaries → Cortex for reflection
|
||||||
|
|
||||||
|
|
||||||
# Additional information available in the trilium docs. #
|
---
|
||||||
|
|
||||||
|
## Version History
|
||||||
|
|
||||||
|
### v0.5.0 (2025-11-28) - Current Release
|
||||||
|
- ✅ Fixed all critical API wiring issues
|
||||||
|
- ✅ Added OpenAI-compatible endpoint to Relay (`/v1/chat/completions`)
|
||||||
|
- ✅ Fixed Cortex → Intake integration
|
||||||
|
- ✅ Added missing Python package `__init__.py` files
|
||||||
|
- ✅ End-to-end message flow verified and working
|
||||||
|
|
||||||
|
### v0.4.x (Major Rewire)
|
||||||
|
- Cortex multi-stage reasoning pipeline
|
||||||
|
- Intake v0.2 simplification
|
||||||
|
- LLM router with multi-backend support
|
||||||
|
- Major architectural restructuring
|
||||||
|
|
||||||
|
### v0.3.x
|
||||||
|
- Beta Lyrae RAG system
|
||||||
|
- NeoMem integration
|
||||||
|
- Basic Cortex reasoning loop
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Known Issues (v0.5.0)
|
||||||
|
|
||||||
|
### Non-Critical
|
||||||
|
- Session management endpoints not fully implemented in Relay
|
||||||
|
- RAG service currently disabled in docker-compose.yml
|
||||||
|
- Cortex `/ingest` endpoint is a stub
|
||||||
|
|
||||||
|
### Future Enhancements
|
||||||
|
- Re-enable RAG service integration
|
||||||
|
- Implement full session persistence
|
||||||
|
- Add request correlation IDs for tracing
|
||||||
|
- Comprehensive health checks
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Quick Start
|
||||||
|
|
||||||
|
### Prerequisites
|
||||||
|
- Docker + Docker Compose
|
||||||
|
- PostgreSQL 13+, Neo4j 4.4+ (for NeoMem)
|
||||||
|
- At least one LLM API endpoint (vLLM, Ollama, or OpenAI)
|
||||||
|
|
||||||
|
### Setup
|
||||||
|
1. Configure environment variables in `.env` files
|
||||||
|
2. Start services: `docker-compose up -d`
|
||||||
|
3. Check health: `curl http://localhost:7078/_health`
|
||||||
|
4. Access UI: `http://localhost:7078`
|
||||||
|
|
||||||
|
### Test
|
||||||
|
```bash
|
||||||
|
curl -X POST http://localhost:7078/v1/chat/completions \
|
||||||
|
-H "Content-Type: application/json" \
|
||||||
|
-d '{
|
||||||
|
"messages": [{"role": "user", "content": "Hello Lyra!"}],
|
||||||
|
"session_id": "test"
|
||||||
|
}'
|
||||||
|
```
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Documentation
|
||||||
|
|
||||||
|
- See [CHANGELOG.md](CHANGELOG.md) for detailed version history
|
||||||
|
- See `ENVIRONMENT_VARIABLES.md` for environment variable reference
|
||||||
|
- Additional information available in the Trilium docs
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## License
|
||||||
|
|
||||||
|
NeoMem is a derivative work based on Mem0 OSS (Apache 2.0).
|
||||||
|
© 2025 Terra-Mechanics / ServersDown Labs. All modifications released under Apache 2.0.
|
||||||
|
|
||||||
|
**Built with Claude Code**
|
||||||
|
|
||||||
---
|
---
|
||||||
|
|
||||||
## 📦 Requirements
|
## 📦 Requirements
|
||||||
|
|||||||
@@ -13,7 +13,7 @@ const PORT = Number(process.env.PORT || 7078);
|
|||||||
// core endpoints
|
// core endpoints
|
||||||
const CORTEX_REASON = process.env.CORTEX_REASON_URL || "http://cortex:7081/reason";
|
const CORTEX_REASON = process.env.CORTEX_REASON_URL || "http://cortex:7081/reason";
|
||||||
const CORTEX_INGEST = process.env.CORTEX_INGEST_URL || "http://cortex:7081/ingest";
|
const CORTEX_INGEST = process.env.CORTEX_INGEST_URL || "http://cortex:7081/ingest";
|
||||||
const INTAKE_URL = process.env.INTAKE_URL || "http://intake:7082/summary";
|
const INTAKE_URL = process.env.INTAKE_URL || "http://intake:7080/add_exchange";
|
||||||
|
|
||||||
// -----------------------------------------------------
|
// -----------------------------------------------------
|
||||||
// Helper request wrapper
|
// Helper request wrapper
|
||||||
@@ -41,6 +41,45 @@ async function postJSON(url, data) {
|
|||||||
return json;
|
return json;
|
||||||
}
|
}
|
||||||
|
|
||||||
|
// -----------------------------------------------------
|
||||||
|
// Shared chat handler logic
|
||||||
|
// -----------------------------------------------------
|
||||||
|
async function handleChatRequest(session_id, user_msg) {
|
||||||
|
// 1. → Cortex.reason
|
||||||
|
let reason;
|
||||||
|
try {
|
||||||
|
reason = await postJSON(CORTEX_REASON, {
|
||||||
|
session_id,
|
||||||
|
user_prompt: user_msg
|
||||||
|
});
|
||||||
|
} catch (e) {
|
||||||
|
console.error("Relay → Cortex.reason error:", e.message);
|
||||||
|
throw new Error(`cortex_reason_failed: ${e.message}`);
|
||||||
|
}
|
||||||
|
|
||||||
|
const persona = reason.final_output || reason.persona || "(no persona text)";
|
||||||
|
|
||||||
|
// 2. → Cortex.ingest (async, non-blocking)
|
||||||
|
postJSON(CORTEX_INGEST, {
|
||||||
|
session_id,
|
||||||
|
user_msg,
|
||||||
|
assistant_msg: persona
|
||||||
|
}).catch(e => console.warn("Relay → Cortex.ingest failed:", e.message));
|
||||||
|
|
||||||
|
// 3. → Intake summary (async, non-blocking)
|
||||||
|
postJSON(INTAKE_URL, {
|
||||||
|
session_id,
|
||||||
|
user_msg,
|
||||||
|
assistant_msg: persona
|
||||||
|
}).catch(e => console.warn("Relay → Intake failed:", e.message));
|
||||||
|
|
||||||
|
// 4. Return result
|
||||||
|
return {
|
||||||
|
session_id,
|
||||||
|
reply: persona
|
||||||
|
};
|
||||||
|
}
|
||||||
|
|
||||||
// -----------------------------------------------------
|
// -----------------------------------------------------
|
||||||
// HEALTHCHECK
|
// HEALTHCHECK
|
||||||
// -----------------------------------------------------
|
// -----------------------------------------------------
|
||||||
@@ -48,6 +87,59 @@ app.get("/_health", (_, res) => {
|
|||||||
res.json({ ok: true });
|
res.json({ ok: true });
|
||||||
});
|
});
|
||||||
|
|
||||||
|
// -----------------------------------------------------
|
||||||
|
// OPENAI-COMPATIBLE ENDPOINT (for UI)
|
||||||
|
// -----------------------------------------------------
|
||||||
|
app.post("/v1/chat/completions", async (req, res) => {
|
||||||
|
try {
|
||||||
|
// Extract from OpenAI format
|
||||||
|
const session_id = req.body.session_id || req.body.user || "default";
|
||||||
|
const messages = req.body.messages || [];
|
||||||
|
const lastMessage = messages[messages.length - 1];
|
||||||
|
const user_msg = lastMessage?.content || "";
|
||||||
|
|
||||||
|
if (!user_msg) {
|
||||||
|
return res.status(400).json({ error: "No message content provided" });
|
||||||
|
}
|
||||||
|
|
||||||
|
console.log(`Relay (v1) → received: "${user_msg}"`);
|
||||||
|
|
||||||
|
// Call the same logic as /chat
|
||||||
|
const result = await handleChatRequest(session_id, user_msg);
|
||||||
|
|
||||||
|
// Return in OpenAI format
|
||||||
|
return res.json({
|
||||||
|
id: `chatcmpl-${Date.now()}`,
|
||||||
|
object: "chat.completion",
|
||||||
|
created: Math.floor(Date.now() / 1000),
|
||||||
|
model: "lyra",
|
||||||
|
choices: [{
|
||||||
|
index: 0,
|
||||||
|
message: {
|
||||||
|
role: "assistant",
|
||||||
|
content: result.reply
|
||||||
|
},
|
||||||
|
finish_reason: "stop"
|
||||||
|
}],
|
||||||
|
usage: {
|
||||||
|
prompt_tokens: 0,
|
||||||
|
completion_tokens: 0,
|
||||||
|
total_tokens: 0
|
||||||
|
}
|
||||||
|
});
|
||||||
|
|
||||||
|
} catch (err) {
|
||||||
|
console.error("Relay v1 endpoint fatal:", err);
|
||||||
|
res.status(500).json({
|
||||||
|
error: {
|
||||||
|
message: err.message || String(err),
|
||||||
|
type: "server_error",
|
||||||
|
code: "relay_failed"
|
||||||
|
}
|
||||||
|
});
|
||||||
|
}
|
||||||
|
});
|
||||||
|
|
||||||
// -----------------------------------------------------
|
// -----------------------------------------------------
|
||||||
// MAIN ENDPOINT (new canonical)
|
// MAIN ENDPOINT (new canonical)
|
||||||
// -----------------------------------------------------
|
// -----------------------------------------------------
|
||||||
@@ -58,39 +150,8 @@ app.post("/chat", async (req, res) => {
|
|||||||
|
|
||||||
console.log(`Relay → received: "${user_msg}"`);
|
console.log(`Relay → received: "${user_msg}"`);
|
||||||
|
|
||||||
// 1. → Cortex.reason
|
const result = await handleChatRequest(session_id, user_msg);
|
||||||
let reason;
|
return res.json(result);
|
||||||
try {
|
|
||||||
reason = await postJSON(CORTEX_REASON, {
|
|
||||||
session_id,
|
|
||||||
user_prompt: user_msg
|
|
||||||
});
|
|
||||||
} catch (e) {
|
|
||||||
console.error("Relay → Cortex.reason error:", e.message);
|
|
||||||
return res.status(500).json({ error: "cortex_reason_failed", detail: e.message });
|
|
||||||
}
|
|
||||||
|
|
||||||
const persona = reason.final_output || reason.persona || "(no persona text)";
|
|
||||||
|
|
||||||
// 2. → Cortex.ingest
|
|
||||||
postJSON(CORTEX_INGEST, {
|
|
||||||
session_id,
|
|
||||||
user_msg,
|
|
||||||
assistant_msg: persona
|
|
||||||
}).catch(e => console.warn("Relay → Cortex.ingest failed:", e.message));
|
|
||||||
|
|
||||||
// 3. → Intake summary
|
|
||||||
postJSON(INTAKE_URL, {
|
|
||||||
session_id,
|
|
||||||
user_msg,
|
|
||||||
assistant_msg: persona
|
|
||||||
}).catch(e => console.warn("Relay → Intake failed:", e.message));
|
|
||||||
|
|
||||||
// 4. → Return to UI
|
|
||||||
return res.json({
|
|
||||||
session_id,
|
|
||||||
reply: persona
|
|
||||||
});
|
|
||||||
|
|
||||||
} catch (err) {
|
} catch (err) {
|
||||||
console.error("Relay fatal:", err);
|
console.error("Relay fatal:", err);
|
||||||
|
|||||||
1
cortex/ingest/__init__.py
Normal file
1
cortex/ingest/__init__.py
Normal file
@@ -0,0 +1 @@
|
|||||||
|
# Ingest module - handles communication with Intake service
|
||||||
@@ -8,9 +8,14 @@ class IntakeClient:
|
|||||||
"""Handles short-term / episodic summaries from Intake service."""
|
"""Handles short-term / episodic summaries from Intake service."""
|
||||||
|
|
||||||
def __init__(self):
|
def __init__(self):
|
||||||
self.base_url = os.getenv("INTAKE_API", "http://intake:7083")
|
self.base_url = os.getenv("INTAKE_API_URL", "http://intake:7080")
|
||||||
|
|
||||||
async def summarize_turn(self, session_id: str, user_msg: str, assistant_msg: Optional[str] = None) -> Dict[str, Any]:
|
async def summarize_turn(self, session_id: str, user_msg: str, assistant_msg: Optional[str] = None) -> Dict[str, Any]:
|
||||||
|
"""
|
||||||
|
DEPRECATED: Intake v0.2 removed the /summarize endpoint.
|
||||||
|
Use add_exchange() instead, which auto-summarizes in the background.
|
||||||
|
This method is kept for backwards compatibility but will fail.
|
||||||
|
"""
|
||||||
payload = {
|
payload = {
|
||||||
"session_id": session_id,
|
"session_id": session_id,
|
||||||
"turns": [{"role": "user", "content": user_msg}]
|
"turns": [{"role": "user", "content": user_msg}]
|
||||||
@@ -24,15 +29,17 @@ class IntakeClient:
|
|||||||
r.raise_for_status()
|
r.raise_for_status()
|
||||||
return r.json()
|
return r.json()
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
logger.warning(f"Intake summarize_turn failed: {e}")
|
logger.warning(f"Intake summarize_turn failed (endpoint removed in v0.2): {e}")
|
||||||
return {}
|
return {}
|
||||||
|
|
||||||
async def get_context(self, session_id: str) -> str:
|
async def get_context(self, session_id: str) -> str:
|
||||||
|
"""Get summarized context for a session from Intake."""
|
||||||
async with httpx.AsyncClient(timeout=15) as client:
|
async with httpx.AsyncClient(timeout=15) as client:
|
||||||
try:
|
try:
|
||||||
r = await client.get(f"{self.base_url}/context/{session_id}")
|
r = await client.get(f"{self.base_url}/summaries", params={"session_id": session_id})
|
||||||
r.raise_for_status()
|
r.raise_for_status()
|
||||||
return r.text
|
data = r.json()
|
||||||
|
return data.get("summary_text", "")
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
logger.warning(f"Intake get_context failed: {e}")
|
logger.warning(f"Intake get_context failed: {e}")
|
||||||
return ""
|
return ""
|
||||||
|
|||||||
1
cortex/llm/__init__.py
Normal file
1
cortex/llm/__init__.py
Normal file
@@ -0,0 +1 @@
|
|||||||
|
# LLM module - provides LLM routing and backend abstraction
|
||||||
1
cortex/persona/__init__.py
Normal file
1
cortex/persona/__init__.py
Normal file
@@ -0,0 +1 @@
|
|||||||
|
# Persona module - applies Lyra's personality and speaking style
|
||||||
1
cortex/reasoning/__init__.py
Normal file
1
cortex/reasoning/__init__.py
Normal file
@@ -0,0 +1 @@
|
|||||||
|
# Reasoning module - multi-stage reasoning pipeline
|
||||||
@@ -1,6 +1,5 @@
|
|||||||
# router.py
|
# router.py
|
||||||
|
|
||||||
from unittest import result
|
|
||||||
from fastapi import APIRouter, HTTPException
|
from fastapi import APIRouter, HTTPException
|
||||||
from pydantic import BaseModel
|
from pydantic import BaseModel
|
||||||
|
|
||||||
|
|||||||
1
cortex/utils/__init__.py
Normal file
1
cortex/utils/__init__.py
Normal file
@@ -0,0 +1 @@
|
|||||||
|
# Utilities module
|
||||||
484
intake/intake.py
484
intake/intake.py
@@ -1,430 +1,160 @@
|
|||||||
from fastapi import FastAPI, Body, Query, BackgroundTasks
|
from fastapi import FastAPI, Body, Query, BackgroundTasks
|
||||||
from collections import deque
|
from collections import deque
|
||||||
from datetime import datetime
|
from datetime import datetime
|
||||||
|
from uuid import uuid4
|
||||||
import requests
|
import requests
|
||||||
import os
|
import os
|
||||||
import sys
|
import sys
|
||||||
import asyncio
|
|
||||||
from dotenv import load_dotenv
|
|
||||||
|
|
||||||
# ───────────────────────────────────────────────
|
|
||||||
# 🔧 Load environment variables
|
|
||||||
# ───────────────────────────────────────────────
|
|
||||||
load_dotenv()
|
|
||||||
|
|
||||||
|
# ─────────────────────────────
|
||||||
|
# Config
|
||||||
|
# ─────────────────────────────
|
||||||
SUMMARY_MODEL = os.getenv("SUMMARY_MODEL_NAME", "mistral-7b-instruct-v0.2.Q4_K_M.gguf")
|
SUMMARY_MODEL = os.getenv("SUMMARY_MODEL_NAME", "mistral-7b-instruct-v0.2.Q4_K_M.gguf")
|
||||||
SUMMARY_URL = os.getenv("SUMMARY_API_URL", "http://localhost:8080/v1/completions")
|
SUMMARY_URL = os.getenv("SUMMARY_API_URL", "http://localhost:8080/v1/completions")
|
||||||
SUMMARY_MAX_TOKENS = int(os.getenv("SUMMARY_MAX_TOKENS", "200"))
|
SUMMARY_MAX_TOKENS = int(os.getenv("SUMMARY_MAX_TOKENS", "200"))
|
||||||
SUMMARY_TEMPERATURE = float(os.getenv("SUMMARY_TEMPERATURE", "0.3"))
|
SUMMARY_TEMPERATURE = float(os.getenv("SUMMARY_TEMPERATURE", "0.3"))
|
||||||
|
|
||||||
# ───────────────────────────────────────────────
|
|
||||||
# 🧠 NeoMem connection (session-aware)
|
|
||||||
# ───────────────────────────────────────────────
|
|
||||||
from uuid import uuid4
|
|
||||||
|
|
||||||
NEOMEM_API = os.getenv("NEOMEM_API")
|
NEOMEM_API = os.getenv("NEOMEM_API")
|
||||||
NEOMEM_KEY = os.getenv("NEOMEM_KEY")
|
NEOMEM_KEY = os.getenv("NEOMEM_KEY")
|
||||||
|
|
||||||
def push_summary_to_neomem(summary_text: str, level: str, session_id: str):
|
# ─────────────────────────────
|
||||||
"""Send summarized text to NeoMem, tagged by session_id."""
|
# App + session buffer
|
||||||
if not NEOMEM_API:
|
# ─────────────────────────────
|
||||||
print("⚠️ NEOMEM_API not set, skipping NeoMem push")
|
app = FastAPI()
|
||||||
return
|
SESSIONS = {}
|
||||||
|
|
||||||
payload = {
|
@app.on_event("startup")
|
||||||
"messages": [
|
def banner():
|
||||||
{"role": "assistant", "content": summary_text}
|
print("🧩 Intake v0.2 booting...")
|
||||||
],
|
print(f" Model: {SUMMARY_MODEL}")
|
||||||
"user_id": "brian",
|
print(f" API: {SUMMARY_URL}")
|
||||||
# optional: uncomment if you want sessions tracked in NeoMem natively
|
sys.stdout.flush()
|
||||||
# "run_id": session_id,
|
|
||||||
"metadata": {
|
# ─────────────────────────────
|
||||||
"source": "intake",
|
# Helper: summarize exchanges
|
||||||
"type": "summary",
|
# ─────────────────────────────
|
||||||
"level": level,
|
def llm(prompt: str):
|
||||||
"session_id": session_id,
|
try:
|
||||||
"cortex": {}
|
resp = requests.post(
|
||||||
}
|
SUMMARY_URL,
|
||||||
}
|
json={
|
||||||
|
"model": SUMMARY_MODEL,
|
||||||
|
"prompt": prompt,
|
||||||
|
"max_tokens": SUMMARY_MAX_TOKENS,
|
||||||
|
"temperature": SUMMARY_TEMPERATURE,
|
||||||
|
},
|
||||||
|
timeout=30,
|
||||||
|
)
|
||||||
|
resp.raise_for_status()
|
||||||
|
return resp.json().get("choices", [{}])[0].get("text", "").strip()
|
||||||
|
except Exception as e:
|
||||||
|
return f"[Error summarizing: {e}]"
|
||||||
|
|
||||||
|
def summarize_simple(exchanges):
|
||||||
|
"""Simple factual summary of recent exchanges."""
|
||||||
|
text = ""
|
||||||
|
for e in exchanges:
|
||||||
|
text += f"User: {e['user_msg']}\nAssistant: {e['assistant_msg']}\n\n"
|
||||||
|
|
||||||
|
prompt = f"""
|
||||||
|
Summarize the following conversation between Brian (user) and Lyra (assistant).
|
||||||
|
Focus only on factual content. Avoid names, examples, story tone, or invented details.
|
||||||
|
|
||||||
|
{text}
|
||||||
|
|
||||||
|
Summary:
|
||||||
|
"""
|
||||||
|
return llm(prompt)
|
||||||
|
|
||||||
|
# ─────────────────────────────
|
||||||
|
# NeoMem push
|
||||||
|
# ─────────────────────────────
|
||||||
|
def push_to_neomem(summary: str, session_id: str):
|
||||||
|
if not NEOMEM_API:
|
||||||
|
return
|
||||||
|
|
||||||
headers = {"Content-Type": "application/json"}
|
headers = {"Content-Type": "application/json"}
|
||||||
if NEOMEM_KEY:
|
if NEOMEM_KEY:
|
||||||
headers["Authorization"] = f"Bearer {NEOMEM_KEY}"
|
headers["Authorization"] = f"Bearer {NEOMEM_KEY}"
|
||||||
|
|
||||||
|
payload = {
|
||||||
|
"messages": [{"role": "assistant", "content": summary}],
|
||||||
|
"user_id": "brian",
|
||||||
|
"metadata": {
|
||||||
|
"source": "intake",
|
||||||
|
"session_id": session_id
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
try:
|
try:
|
||||||
r = requests.post(f"{NEOMEM_API}/memories", json=payload, headers=headers, timeout=25)
|
requests.post(
|
||||||
r.raise_for_status()
|
f"{NEOMEM_API}/memories",
|
||||||
print(f"🧠 NeoMem updated ({level}, {session_id}, {len(summary_text)} chars)")
|
json=payload,
|
||||||
|
headers=headers,
|
||||||
|
timeout=20
|
||||||
|
).raise_for_status()
|
||||||
|
print(f"🧠 NeoMem updated for {session_id}")
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
print(f"❌ NeoMem push failed ({level}, {session_id}): {e}")
|
print(f"NeoMem push failed: {e}")
|
||||||
|
|
||||||
|
# ─────────────────────────────
|
||||||
# ───────────────────────────────────────────────
|
# Background summarizer
|
||||||
# ⚙️ FastAPI + buffer setup
|
# ─────────────────────────────
|
||||||
# ───────────────────────────────────────────────
|
def bg_summarize(session_id: str):
|
||||||
app = FastAPI()
|
|
||||||
|
|
||||||
# Multiple rolling buffers keyed by session_id
|
|
||||||
SESSIONS = {}
|
|
||||||
|
|
||||||
|
|
||||||
# Summary trigger points
|
|
||||||
# → low-tier: quick factual recaps
|
|
||||||
# → mid-tier: “Reality Check” reflections
|
|
||||||
# → high-tier: rolling continuity synthesis
|
|
||||||
LEVELS = [1, 2, 5, 10, 20, 30]
|
|
||||||
|
|
||||||
@app.on_event("startup")
|
|
||||||
def show_boot_banner():
|
|
||||||
print("🧩 Intake booting...")
|
|
||||||
print(f" Model: {SUMMARY_MODEL}")
|
|
||||||
print(f" API: {SUMMARY_URL}")
|
|
||||||
print(f" Max tokens: {SUMMARY_MAX_TOKENS}, Temp: {SUMMARY_TEMPERATURE}")
|
|
||||||
sys.stdout.flush()
|
|
||||||
|
|
||||||
# ───────────────────────────────────────────────
|
|
||||||
# 🧠 Hierarchical Summarizer (L10→L20→L30 cascade)
|
|
||||||
# ───────────────────────────────────────────────
|
|
||||||
SUMMARIES_CACHE = {"L10": [], "L20": [], "L30": []}
|
|
||||||
|
|
||||||
def summarize(exchanges, level):
|
|
||||||
"""Hierarchical summarizer: builds local and meta summaries."""
|
|
||||||
# Join exchanges into readable text
|
|
||||||
text = "\n".join(
|
|
||||||
f"User: {e['turns'][0]['content']}\nAssistant: {e['turns'][1]['content']}"
|
|
||||||
for e in exchanges
|
|
||||||
)
|
|
||||||
|
|
||||||
def query_llm(prompt: str):
|
|
||||||
try:
|
|
||||||
resp = requests.post(
|
|
||||||
SUMMARY_URL,
|
|
||||||
json={
|
|
||||||
"model": SUMMARY_MODEL,
|
|
||||||
"prompt": prompt,
|
|
||||||
"max_tokens": SUMMARY_MAX_TOKENS,
|
|
||||||
"temperature": SUMMARY_TEMPERATURE,
|
|
||||||
},
|
|
||||||
timeout=180,
|
|
||||||
)
|
|
||||||
resp.raise_for_status()
|
|
||||||
data = resp.json()
|
|
||||||
return data.get("choices", [{}])[0].get("text", "").strip()
|
|
||||||
except Exception as e:
|
|
||||||
return f"[Error summarizing: {e}]"
|
|
||||||
|
|
||||||
# ───── L10: local “Reality Check” block ─────
|
|
||||||
if level == 10:
|
|
||||||
prompt = f"""
|
|
||||||
You are Lyra Intake performing a 'Reality Check' for the last {len(exchanges)} exchanges.
|
|
||||||
Summarize this block as one coherent paragraph describing the user’s focus, progress, and tone.
|
|
||||||
Avoid bullet points.
|
|
||||||
|
|
||||||
Exchanges:
|
|
||||||
{text}
|
|
||||||
|
|
||||||
Reality Check Summary:
|
|
||||||
"""
|
|
||||||
summary = query_llm(prompt)
|
|
||||||
SUMMARIES_CACHE["L10"].append(summary)
|
|
||||||
|
|
||||||
# ───── L20: merge L10s ─────
|
|
||||||
elif level == 20:
|
|
||||||
# 1️⃣ create fresh L10 for 11–20
|
|
||||||
l10_prompt = f"""
|
|
||||||
You are Lyra Intake generating a second Reality Check for the most recent {len(exchanges)} exchanges.
|
|
||||||
Summarize them as one paragraph describing what's new or changed since the last block.
|
|
||||||
Avoid bullet points.
|
|
||||||
|
|
||||||
Exchanges:
|
|
||||||
{text}
|
|
||||||
|
|
||||||
Reality Check Summary:
|
|
||||||
"""
|
|
||||||
new_l10 = query_llm(l10_prompt)
|
|
||||||
SUMMARIES_CACHE["L10"].append(new_l10)
|
|
||||||
|
|
||||||
# 2️⃣ merge all L10s into a Session Overview
|
|
||||||
joined_l10s = "\n\n".join(SUMMARIES_CACHE["L10"])
|
|
||||||
l20_prompt = f"""
|
|
||||||
You are Lyra Intake merging multiple 'Reality Checks' into a single Session Overview.
|
|
||||||
Summarize the following Reality Checks into one short paragraph capturing the ongoing goals,
|
|
||||||
patterns, and overall progress.
|
|
||||||
|
|
||||||
Reality Checks:
|
|
||||||
{joined_l10s}
|
|
||||||
|
|
||||||
Session Overview:
|
|
||||||
"""
|
|
||||||
l20_summary = query_llm(l20_prompt)
|
|
||||||
SUMMARIES_CACHE["L20"].append(l20_summary)
|
|
||||||
summary = new_l10 + "\n\n" + l20_summary
|
|
||||||
|
|
||||||
# ───── L30: continuity synthesis ─────
|
|
||||||
elif level == 30:
|
|
||||||
# 1️⃣ create new L10 for 21–30
|
|
||||||
new_l10 = query_llm(f"""
|
|
||||||
You are Lyra Intake creating a new Reality Check for exchanges 21–30.
|
|
||||||
Summarize this block in one cohesive paragraph, describing any shifts in focus or tone.
|
|
||||||
|
|
||||||
Exchanges:
|
|
||||||
{text}
|
|
||||||
|
|
||||||
Reality Check Summary:
|
|
||||||
""")
|
|
||||||
|
|
||||||
SUMMARIES_CACHE["L10"].append(new_l10)
|
|
||||||
|
|
||||||
# 2️⃣ merge all lower levels for continuity
|
|
||||||
joined = "\n\n".join(SUMMARIES_CACHE["L10"] + SUMMARIES_CACHE["L20"])
|
|
||||||
continuity_prompt = f"""
|
|
||||||
You are Lyra Intake performing a 'Continuity Report' — a high-level reflection combining all Reality Checks
|
|
||||||
and Session Overviews so far. Describe how the conversation has evolved, the key insights, and remaining threads.
|
|
||||||
|
|
||||||
Reality Checks and Overviews:
|
|
||||||
{joined}
|
|
||||||
|
|
||||||
Continuity Report:
|
|
||||||
"""
|
|
||||||
l30_summary = query_llm(continuity_prompt)
|
|
||||||
SUMMARIES_CACHE["L30"].append(l30_summary)
|
|
||||||
summary = new_l10 + "\n\n" + l30_summary
|
|
||||||
|
|
||||||
# ───── L1–L5 (standard factual summaries) ─────
|
|
||||||
else:
|
|
||||||
prompt = f"""
|
|
||||||
You are Lyra Intake, a background summarization module for an AI assistant.
|
|
||||||
|
|
||||||
Your job is to compress recent chat exchanges between a user and an assistant
|
|
||||||
into a short, factual summary. The user's name is Brian, and the assistant's name is Lyra.
|
|
||||||
Focus only on the real conversation content.
|
|
||||||
Do NOT invent names, people, or examples. Avoid speculation or storytelling.
|
|
||||||
|
|
||||||
Summarize clearly what topics were discussed and what conclusions were reached.
|
|
||||||
Avoid speculation, names, or bullet points.
|
|
||||||
|
|
||||||
Exchanges:
|
|
||||||
{text}
|
|
||||||
|
|
||||||
Summary:
|
|
||||||
"""
|
|
||||||
summary = query_llm(prompt)
|
|
||||||
|
|
||||||
return f"[L{level} Summary of {len(exchanges)} exchanges]: {summary}"
|
|
||||||
|
|
||||||
from datetime import datetime
|
|
||||||
|
|
||||||
LOG_DIR = "/app/logs"
|
|
||||||
os.makedirs(LOG_DIR, exist_ok=True)
|
|
||||||
|
|
||||||
def log_to_file(level: str, summary: str):
|
|
||||||
"""Append each summary to a persistent .txt log file."""
|
|
||||||
timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
|
|
||||||
filename = os.path.join(LOG_DIR, "summaries.log")
|
|
||||||
with open(filename, "a", encoding="utf-8") as f:
|
|
||||||
f.write(f"[{timestamp}] {level}\n{summary}\n{'='*60}\n\n")
|
|
||||||
|
|
||||||
# ───────────────────────────────────────────────
|
|
||||||
# 🔁 Background summarization helper
|
|
||||||
# ───────────────────────────────────────────────
|
|
||||||
def run_summarization_task(exchange, session_id):
|
|
||||||
"""Async-friendly wrapper for slow summarization work."""
|
|
||||||
try:
|
try:
|
||||||
hopper = SESSIONS.get(session_id)
|
hopper = SESSIONS.get(session_id)
|
||||||
if not hopper:
|
if not hopper:
|
||||||
print(f"⚠️ No hopper found for {session_id}")
|
|
||||||
return
|
return
|
||||||
|
|
||||||
buffer = hopper["buffer"]
|
buf = list(hopper["buffer"])
|
||||||
count = len(buffer)
|
summary = summarize_simple(buf)
|
||||||
summaries = {}
|
push_to_neomem(summary, session_id)
|
||||||
|
|
||||||
if count < 30:
|
|
||||||
for lvl in LEVELS:
|
|
||||||
if lvl <= count:
|
|
||||||
s_text = summarize(list(buffer)[-lvl:], lvl)
|
|
||||||
log_to_file(f"L{lvl}", s_text)
|
|
||||||
push_summary_to_neomem(s_text, f"L{lvl}", session_id)
|
|
||||||
summaries[f"L{lvl}"] = s_text
|
|
||||||
else:
|
|
||||||
# optional: include your existing 30+ logic here
|
|
||||||
pass
|
|
||||||
|
|
||||||
if summaries:
|
|
||||||
print(f"🧩 [BG] Summaries generated asynchronously at count={count}: {list(summaries.keys())}")
|
|
||||||
|
|
||||||
|
print(f"🧩 Summary generated for {session_id}")
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
print(f"💥 [BG] Async summarization failed: {e}")
|
print(f"Summarizer error: {e}")
|
||||||
|
|
||||||
|
# ─────────────────────────────
|
||||||
|
# Routes
|
||||||
|
# ─────────────────────────────
|
||||||
|
|
||||||
# ───────────────────────────────────────────────
|
|
||||||
# 📨 Routes
|
|
||||||
# ───────────────────────────────────────────────
|
|
||||||
@app.post("/add_exchange")
|
@app.post("/add_exchange")
|
||||||
def add_exchange(exchange: dict = Body(...), background_tasks: BackgroundTasks = None):
|
def add_exchange(exchange: dict = Body(...), background_tasks: BackgroundTasks = None):
|
||||||
|
|
||||||
session_id = exchange.get("session_id") or f"sess-{uuid4().hex[:8]}"
|
session_id = exchange.get("session_id") or f"sess-{uuid4().hex[:8]}"
|
||||||
exchange["session_id"] = session_id
|
exchange["session_id"] = session_id
|
||||||
|
exchange["timestamp"] = datetime.now().isoformat()
|
||||||
|
|
||||||
if session_id not in SESSIONS:
|
if session_id not in SESSIONS:
|
||||||
SESSIONS[session_id] = {"buffer": deque(maxlen=100), "last_update": datetime.now()}
|
SESSIONS[session_id] = {
|
||||||
|
"buffer": deque(maxlen=200),
|
||||||
|
"created_at": datetime.now()
|
||||||
|
}
|
||||||
print(f"🆕 Hopper created: {session_id}")
|
print(f"🆕 Hopper created: {session_id}")
|
||||||
|
|
||||||
hopper = SESSIONS[session_id]
|
SESSIONS[session_id]["buffer"].append(exchange)
|
||||||
hopper["buffer"].append(exchange)
|
|
||||||
hopper["last_update"] = datetime.now()
|
|
||||||
count = len(hopper["buffer"])
|
|
||||||
|
|
||||||
# 🚀 queue background summarization
|
|
||||||
if background_tasks:
|
if background_tasks:
|
||||||
background_tasks.add_task(run_summarization_task, exchange, session_id)
|
background_tasks.add_task(bg_summarize, session_id)
|
||||||
print(f"⏩ Queued async summarization for {session_id}")
|
print(f"⏩ Summarization queued for {session_id}")
|
||||||
|
|
||||||
return {"ok": True, "exchange_count": count, "queued": True}
|
return {"ok": True, "session_id": session_id}
|
||||||
|
|
||||||
|
|
||||||
# # ── Normal tiered behavior up to 30 ── commented out for aysnc addon
|
|
||||||
# if count < 30:
|
|
||||||
# if count in LEVELS:
|
|
||||||
# for lvl in LEVELS:
|
|
||||||
# if lvl <= count:
|
|
||||||
# summaries[f"L{lvl}"] = summarize(list(buffer)[-lvl:], lvl)
|
|
||||||
# log_to_file(f"L{lvl}", summaries[f"L{lvl}"])
|
|
||||||
# push_summary_to_neomem(summaries[f"L{lvl}"], f"L{lvl}", session_id)
|
|
||||||
|
|
||||||
# # 🚀 Launch summarization in the background (non-blocking)
|
|
||||||
# if background_tasks:
|
|
||||||
# background_tasks.add_task(run_summarization_task, exchange, session_id)
|
|
||||||
# print(f"⏩ Queued async summarization for {session_id}")
|
|
||||||
|
|
||||||
|
|
||||||
# # ── Beyond 30: keep summarizing every +15 exchanges ──
|
|
||||||
# else:
|
|
||||||
# # Find next milestone after 30 (45, 60, 75, ...)
|
|
||||||
# milestone = 30 + ((count - 30) // 15) * 15
|
|
||||||
# if count == milestone:
|
|
||||||
# summaries[f"L{milestone}"] = summarize(list(buffer)[-15:], milestone)
|
|
||||||
# log_to_file(f"L{milestone}", summaries[f"L{milestone}"])
|
|
||||||
# push_summary_to_neomem(summaries[f"L{milestone}"], f"L{milestone}", session_id)
|
|
||||||
|
|
||||||
# # Optional: merge all continuity summaries so far into a running meta-summary
|
|
||||||
# joined = "\n\n".join(
|
|
||||||
# [s for key, s in summaries.items() if key.startswith("L")]
|
|
||||||
# )
|
|
||||||
# meta_prompt = f"""
|
|
||||||
# You are Lyra Intake composing an 'Ongoing Continuity Report' that merges
|
|
||||||
# all prior continuity summaries into one living narrative.
|
|
||||||
# Focus on major themes, changes, and lessons so far.
|
|
||||||
|
|
||||||
# Continuity Summaries:
|
|
||||||
# {joined}
|
|
||||||
|
|
||||||
# Ongoing Continuity Report:
|
|
||||||
# """
|
|
||||||
# meta_summary = f"[L∞ Ongoing Continuity Report]: {query_llm(meta_prompt)}"
|
|
||||||
# summaries["L∞"] = meta_summary
|
|
||||||
# log_to_file("L∞", meta_summary)
|
|
||||||
# push_summary_to_neomem(meta_summary, "L∞", session_id)
|
|
||||||
|
|
||||||
# print(f"🌀 L{milestone} continuity summary created (messages {count-14}-{count})")
|
|
||||||
|
|
||||||
# # ── Log summaries ──
|
|
||||||
# if summaries:
|
|
||||||
# print(f"🧩 Summaries generated at count={count}: {list(summaries.keys())}")
|
|
||||||
|
|
||||||
# return {
|
|
||||||
# "ok": True,
|
|
||||||
# "exchange_count": len(buffer),
|
|
||||||
# "queued": True
|
|
||||||
# }
|
|
||||||
|
|
||||||
# ───────────────────────────────────────────────
|
|
||||||
# Clear rubbish from hopper.
|
|
||||||
# ───────────────────────────────────────────────
|
|
||||||
def close_session(session_id: str):
|
|
||||||
"""Run a final summary for the given hopper, post it to NeoMem, then delete it."""
|
|
||||||
hopper = SESSIONS.get(session_id)
|
|
||||||
if not hopper:
|
|
||||||
print(f"⚠️ No active hopper for {session_id}")
|
|
||||||
return
|
|
||||||
|
|
||||||
buffer = hopper["buffer"]
|
|
||||||
if not buffer:
|
|
||||||
print(f"⚠️ Hopper {session_id} is empty, skipping closure")
|
|
||||||
del SESSIONS[session_id]
|
|
||||||
return
|
|
||||||
|
|
||||||
try:
|
|
||||||
print(f"🔒 Closing hopper {session_id} ({len(buffer)} exchanges)")
|
|
||||||
|
|
||||||
# Summarize everything left in the buffer
|
|
||||||
final_summary = summarize(list(buffer), 30) # level 30 = continuity synthesis
|
|
||||||
log_to_file("LFinal", final_summary)
|
|
||||||
push_summary_to_neomem(final_summary, "LFinal", session_id)
|
|
||||||
|
|
||||||
# Optionally: mark this as a special 'closure' memory
|
|
||||||
closure_note = f"[Session {session_id} closed with {len(buffer)} exchanges]"
|
|
||||||
push_summary_to_neomem(closure_note, "LFinalNote", session_id)
|
|
||||||
|
|
||||||
print(f"🧹 Hopper {session_id} closed and deleted")
|
|
||||||
except Exception as e:
|
|
||||||
print(f"💥 Error closing hopper {session_id}: {e}")
|
|
||||||
finally:
|
|
||||||
del SESSIONS[session_id]
|
|
||||||
|
|
||||||
@app.post("/close_session/{session_id}")
|
@app.post("/close_session/{session_id}")
|
||||||
def close_session_endpoint(session_id: str):
|
def close_session(session_id: str):
|
||||||
close_session(session_id)
|
if session_id in SESSIONS:
|
||||||
|
del SESSIONS[session_id]
|
||||||
return {"ok": True, "closed": session_id}
|
return {"ok": True, "closed": session_id}
|
||||||
|
|
||||||
# ───────────────────────────────────────────────
|
|
||||||
# 🧾 Provide recent summary for Cortex /reason calls
|
|
||||||
# ───────────────────────────────────────────────
|
|
||||||
@app.get("/summaries")
|
@app.get("/summaries")
|
||||||
def get_summary(session_id: str = Query(..., description="Active session ID")):
|
def get_summary(session_id: str = Query(...)):
|
||||||
"""
|
hopper = SESSIONS.get(session_id)
|
||||||
Return the most recent summary (L10→L30→LFinal) for a given session.
|
if not hopper:
|
||||||
If none exist yet, return a placeholder summary.
|
return {"summary_text": "(none)", "session_id": session_id}
|
||||||
"""
|
|
||||||
try:
|
|
||||||
# Find the most recent file entry in summaries.log
|
|
||||||
log_path = os.path.join(LOG_DIR, "summaries.log")
|
|
||||||
if not os.path.exists(log_path):
|
|
||||||
return {
|
|
||||||
"summary_text": "(none)",
|
|
||||||
"last_message_ts": datetime.now().isoformat(),
|
|
||||||
"session_id": session_id,
|
|
||||||
"exchange_count": 0,
|
|
||||||
}
|
|
||||||
|
|
||||||
with open(log_path, "r", encoding="utf-8") as f:
|
summary = summarize_simple(list(hopper["buffer"]))
|
||||||
lines = f.readlines()
|
return {"summary_text": summary, "session_id": session_id}
|
||||||
|
|
||||||
# Grab the last summary section that mentions this session_id
|
|
||||||
recent_lines = [ln for ln in lines if session_id in ln or ln.startswith("[L")]
|
|
||||||
if recent_lines:
|
|
||||||
# Find the last non-empty summary text
|
|
||||||
snippet = "".join(recent_lines[-8:]).strip()
|
|
||||||
else:
|
|
||||||
snippet = "(no summaries yet)"
|
|
||||||
|
|
||||||
return {
|
|
||||||
"summary_text": snippet[-1000:], # truncate to avoid huge block
|
|
||||||
"last_message_ts": datetime.now().isoformat(),
|
|
||||||
"session_id": session_id,
|
|
||||||
"exchange_count": len(SESSIONS.get(session_id, {}).get("buffer", [])),
|
|
||||||
}
|
|
||||||
|
|
||||||
except Exception as e:
|
|
||||||
print(f"⚠️ /summaries failed for {session_id}: {e}")
|
|
||||||
return {
|
|
||||||
"summary_text": f"(error fetching summaries: {e})",
|
|
||||||
"last_message_ts": datetime.now().isoformat(),
|
|
||||||
"session_id": session_id,
|
|
||||||
"exchange_count": 0,
|
|
||||||
}
|
|
||||||
|
|
||||||
# ───────────────────────────────────────────────
|
|
||||||
# ✅ Health check
|
|
||||||
# ───────────────────────────────────────────────
|
|
||||||
@app.get("/health")
|
@app.get("/health")
|
||||||
def health():
|
def health():
|
||||||
return {"ok": True, "model": SUMMARY_MODEL, "url": SUMMARY_URL}
|
return {"ok": True, "model": SUMMARY_MODEL, "url": SUMMARY_URL}
|
||||||
|
|||||||
Reference in New Issue
Block a user