Replace the silent placeholder-UUID fallback in
_GraphNamespace.add_batch with logger.exception(...) + raise so
embedder misconfiguration (404 unknown model, connection refused, etc.)
fails the surrounding graph-build Task with a visible error instead of
producing a Task that looks completed while the graph stays empty.
Document the existing-but-undocumented Ollama embedder configuration
in .env.example, CLAUDE.md, README.md, and docker-compose.yml.
mxbai-embed-large is the recommended local model because its 1024-dim
output matches Graphiti's default EMBEDDING_DIM. Adds a curl smoke
test to verify embedder reachability before the first graph build.
No new env var or provider literal: Ollama is reached through the
existing openai-provider branch by setting EMBEDDING_BASE_URL,
EMBEDDING_API_KEY, and EMBEDDING_MODEL.
Closes#18
Adds a Neo4j service to docker-compose so `docker compose up -d` works
on a clean checkout, and unhardcodes Graphiti's LLM/embedder so the
documented default provider (Qwen via Dashscope) actually works.
- docker-compose: neo4j:5-community service with cypher-shell
healthcheck, named volumes, and `depends_on: service_healthy` on the
app container; in-Docker NEO4J_URI override leaves the host-mode
default untouched.
- Config: new GRAPHITI_LLM_PROVIDER (openai|gemini, default openai) plus
optional EMBEDDING_API_KEY / EMBEDDING_BASE_URL that fall back to the
chat LLM credentials.
- graphiti_adapter: provider switch inside the singleton factory with
lazy per-provider imports; Gemini path is preserved exactly. The
no-op `_GeminiReranker` becomes a provider-agnostic
`_PassthroughReranker`, still injected explicitly so Graphiti does
not fall back to its OpenAI-only default reranker.
- Drop the ignored `reranker=` kwarg from `_GraphNamespace.search` and
the misleading callers in `zep_tools.py` and
`oasis_profile_generator.py`.
- Refresh `.env.example` to mirror the README env section.
Spec, requirements, and design under
`.kiro/specs/graphiti-neo4j-finalize/`.
Closes#1
- Deleted docker-compose.yml, backend Dockerfile, frontend Dockerfile, and nginx configuration to streamline project setup.
- Updated .env.example to reorganize LLM and ZEP API configurations for clarity and ease of use.
- Enhanced README.md to reflect changes in project structure and provide clearer setup instructions.
- Updated .env.example to reflect new LLM configuration with Aliyun's API.
- Enhanced .gitignore to include additional files and directories for better exclusion of sensitive and build artifacts.
- Added docker-compose.yml for streamlined deployment of backend and frontend services.
- Introduced Dockerfiles for both backend and frontend to facilitate containerized builds.
- Created README.md to provide comprehensive project documentation and setup instructions.
- Established nginx configuration for frontend to support API proxying and static file serving.
Dominik Seemann
666ghj