CalvinBackup/fuzzforge_ai
1
0
Fork 0
mirror of https://github.com/FuzzingLabs/fuzzforge_ai.git synced 2026-05-26 06:47:46 +02:00
Code Issues Packages Projects Releases Wiki Activity

Store Cognee datasets in the projects bucket

Browse Source
This commit is contained in:
Songbird
2025-11-07 17:29:37 +01:00
parent 3ef6bf2437
commit 44d61ad4bf
9 changed files with 23 additions and 18 deletions
Download Patch File Download Diff File Expand all files Collapse all files
docs/docs/ai/a2a-services.md
+1 -1
View File
@@ -12,7 +12,7 @@ Run the command from a project directory that already contains `.fuzzforge/`. Th
**Default directories / services**
- Logs: `.fuzzforge/logs/cognee.log`
- Cognee datasets: hosted by the shared Cognee service (`COGNEE_SERVICE_URL`) inside the configured MinIO/S3 bucket. Local mode falls back to `.fuzzforge/cognee/project_<id>/{data,system}`. Uploads dropped into `s3://cognee/projects/<project-id>/...` are ingested automatically via RabbitMQ + the dispatcher.
- Cognee datasets: hosted by the shared Cognee service (`COGNEE_SERVICE_URL`) inside the configured MinIO/S3 bucket. Local mode falls back to `.fuzzforge/cognee/project_<id>/{data,system}`. Uploads dropped into `s3://projects/<project-id>/...` are ingested automatically via RabbitMQ + the dispatcher.
- Artifact cache: `.fuzzforge/artifacts`
## HTTP Endpoints
docs/docs/ai/architecture.md
+1 -1
View File
@@ -92,7 +92,7 @@ The CLI surface mirrors these helpers as natural-language prompts (`You> run fuz
## Knowledge & Ingestion
- The `fuzzforge ingest` and `fuzzforge rag ingest` commands call into `ai/src/fuzzforge_ai/ingest_utils.py`, which filters file types, ignores caches, and streams files to the Cognee service where they are stored under `s3://<bucket>/<prefix>/project_<id>/`. When files land directly in `s3://cognee/projects/<project-id>/<category>/...`, the dispatcher performs the same workflow automatically via RabbitMQ events.
- The `fuzzforge ingest` and `fuzzforge rag ingest` commands call into `ai/src/fuzzforge_ai/ingest_utils.py`, which filters file types, ignores caches, and streams files to the Cognee service where they are stored under `s3://projects/<project-id>/`. When files land directly in `s3://projects/<project-id>/<category>/...`, the dispatcher performs the same workflow automatically via RabbitMQ events.
- Runtime queries hit `query_project_knowledge_api` on the executor, which defers to `cognee_service` for dataset lookup and semantic search. When Cognee credentials are absent the tools return a friendly "not configured" response.
## Artifact Pipeline
docs/docs/ai/ingestion.md
+1 -1
View File
@@ -102,7 +102,7 @@ Add comments or project-specific overrides as needed; the agent reads these vari
## Event-Driven Ingestion
Uploading files directly into MinIO triggers Cognee automatically. The dispatcher watches `s3://cognee/projects/<project-id>/...` and translates the top-level folder into a dataset:
Uploading files directly into MinIO triggers Cognee automatically. The dispatcher watches `s3://projects/<project-id>/...` and translates the top-level folder into a dataset:
| Prefix | Dataset name |
|-----------|---------------------------------------|
docs/docs/how-to/docker-setup.md
+1 -1
View File
@@ -243,7 +243,7 @@ This spins up the Cognee API on `http://localhost:18000`, publishes it to the ho
### RabbitMQ + Dispatcher
`docker-compose.yml` also launches RabbitMQ (`http://localhost:15672`, ingest/ingest) and the `ingestion-dispatcher` container. MinIO publishes `PUT` events from `s3://cognee/projects/<project-id>/...` to the `cognee-ingest` exchange, and the dispatcher downloads the object and calls Cognee’s REST API. That means any rsync/upload into the projects bucket automatically becomes a dataset.
`docker-compose.yml` also launches RabbitMQ (`http://localhost:15672`, ingest/ingest) and the `ingestion-dispatcher` container. MinIO publishes `PUT` events from `s3://projects/<project-id>/...` to the `cognee-ingest` exchange, and the dispatcher downloads the object and calls Cognee’s REST API. That means any rsync/upload into the projects bucket automatically becomes a dataset.
---