feat: per-caller Bearer token auth and new query tools for MCP server (#984)

Replace the broken GATEWAY_SECRET auth (token was sent as a query
parameter, silently ignored by the gateway) with end-to-end Bearer
token forwarding.  Each MCP caller gets a dedicated WebSocket
authenticated via the gateway's in-band first-frame protocol, with
whoami verification on first connect.

Also fix and extend the tool surface:
- embeddings: accept list of texts (was single string)
- triples_query: use Term wire format with compact keys (was legacy
  Value format), add collection and graph parameters
- sparql_query: new tool for SPARQL SELECT/ASK/CONSTRUCT/DESCRIBE
- graphql_query: new tool for structured data (rows) GraphQL queries
- all tools: add optional workspace parameter

README.md

@@ -11,11 +11,11 @@
 
 <a href="https://trendshift.io/repositories/17291" target="_blank"><img src="https://trendshift.io/api/badge/repositories/17291" alt="trustgraph-ai%2Ftrustgraph | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
 
-# The agent runtime platform
+# The semantic deployment platform
 
 </div>
 
-TrustGraph is an agent runtime platform built around context graphs — structured, queryable representations of your domain knowledge that ground every agent query in verified, explainable facts in private deployments with sovereign control. The platform is the full stack for agentic systems: context graphs, memory, retrieval, orchestration, and inference for precision-critical agent workloads.
+TrustGraph is a comprehensive semantic infrastructure for agents built around context graphs — structured, queryable representations of your domain knowledge that ground every agent query in verified, explainable facts in private deployments with sovereign control. The platform is the full stack for agentic systems: context graphs, memory, retrieval, orchestration, and inference for deterministic agent workloads.
 
 The platform:
 - [x] Multi-model and multimodal database system
@@ -99,23 +99,21 @@ For a browser based configuration, try the [Configuration Terminal](https://conf
 - [**Developer APIs and CLI**](https://docs.trustgraph.ai/reference)
 - [**Deployment Guides**](https://docs.trustgraph.ai/deployment)
 
-## Workbench
+## Context Graph UI
 
-The **Workbench** provides tools for all major features of TrustGraph. The **Workbench** is on port `8888` by default.
+<img width="1389" height="961" alt="Image" src="https://github.com/user-attachments/assets/35c9250d-0f01-40cb-9294-1ee8fd9a1b56" />
 
-- **Vector Search**: Search the installed knowledge bases
-- **Agentic, GraphRAG and LLM Chat**: Chat interface for agents, GraphRAG queries, or direct to LLMs
-- **Relationships**: Analyze deep relationships in the installed knowledge bases
-- **Graph Visualizer**: 3D GraphViz of the installed knowledge bases
-- **Library**: Staging area for installing knowledge bases
-- **Flow Classes**: Workflow preset configurations
-- **Flows**: Create custom workflows and adjust LLM parameters during runtime
-- **Knowledge Cores**: Manage resuable knowledge bases
-- **Prompts**: Manage and adjust prompts during runtime
-- **Schemas**: Define custom schemas for structured data knowledge bases
-- **Ontologies**: Define custom ontologies for unstructured data knowledge bases
-- **Agent Tools**: Define tools with collections, knowledge cores, MCP connections, and tool groups
-- **MCP Tools**: Connect to MCP servers
+The UI provides tools for all major features of TrustGraph. The UI deploys on port `8888` by default.
+
+- **Agent Console** — Query your agents directly with streaming responses and live explainability event tracking, so you can watch reasoning unfold in real time
+- **GraphRAG View** — Interactive graph RAG queries with a visual explainability DAG and inline provenance display, making it easy to see exactly where answers came from
+- **Context Explorer** — An interactive 3D context graph explorer with dynamic graph loading, BFS neighborhood extraction, edge pulse animation, and multiple navigation views
+- **Document Ingestion** — A complete upload and submission workflow with page and chunk inspection and document structure browsing
+- **Ontology Workbench** — A full ontology editor with class and property trees, OWL/XML and Turtle import/export with round-trip fidelity, circular dependency detection, and safe-delete confirmation dialogs
+- **Schema Workbench** — Interactive schema management with list, create, edit, and delete operations including field and index management
+- **Flow Management** — Flow creation and detail views with configurable parameters, temperature controls, and grouped storage layout
+- **Workspace UX** — Workspace selection and management surfaced directly in the interface
+- **Prompt Editor** — A dedicated prompt editing workflow
 
 ## TypeScript Library for UIs
 

docs/tech-specs/knowledge-core-completeness.md

@@ -0,0 +1,535 @@
+---
+layout: default
+title: "Knowledge Core Completeness"
+parent: "Tech Specs"
+---
+
+# Knowledge Core Completeness
+
+## Overview
+
+Knowledge cores are portable snapshots of extracted knowledge: triples, graph
+embeddings, and document embeddings stored in Cassandra's `knowledge` keyspace.
+They can be downloaded as files, transferred between TrustGraph instances, and
+loaded back into vector and graph stores.
+
+Recent additions to TrustGraph — explainability/provenance and named graphs —
+were not carried through to the knowledge core system. This means that
+exporting and re-importing a core loses provenance links, graph assignments,
+and source material, breaking the explainability chain.
+
+This specification addresses three gaps:
+
+1. **Named graphs not stored** — The `g` (graph name) field on triples is
+   silently dropped when writing to the core store and comes back as `None`
+   on read.
+2. **Provenance triples not captured** — Provenance triples (PROV-O) are
+   generated during extraction and flow to graph stores, but never enter
+   the knowledge core store. It is unclear whether they arrive at the store
+   in the correct form.
+3. **Source material not included** — Documents, text pages, and chunks in
+   the librarian's bucket store are not part of the core. After loading a
+   core on a different instance, provenance links to source material point
+   at nothing.
+
+## Goals
+
+- **Self-contained cores**: A downloaded knowledge core file contains
+  everything needed to reconstruct the full knowledge graph including
+  provenance and source attribution on a fresh instance.
+- **Named graph preservation**: Round-tripping a core preserves graph
+  assignments on all triples.
+- **Backward compatibility**: Existing core files (without graph names or
+  source material) can still be uploaded and loaded. New fields are optional
+  on import.
+- **No change to core identity**: A core is still identified by its document
+  ID. The additional data is associated with the same core ID.
+- **Minimal file format changes**: Extend the existing msgpack record format
+  with new record types rather than restructuring existing ones.
+
+## Background
+
+### Current Lifecycle
+
+```
+Extraction pipeline
+    │
+    ├─ triples ──────────────────► knowledge core store (Cassandra)
+    ├─ graph embeddings ─────────► knowledge core store (Cassandra)
+    ├─ document embeddings ──────► knowledge core store (Cassandra)
+    ├─ provenance triples ───────► graph store (only)
+    └─ source documents ─────────► librarian bucket store (only)
+
+Download:  Cassandra ──► knowledge manager ──► API gateway ──► client file
+Upload:    client file ──► API gateway ──► knowledge manager ──► Cassandra
+Load:      Cassandra ──► knowledge manager ──► Pulsar topics ──► graph/vector stores
+```
+
+### Current Core File Format (msgpack)
+
+A core file is a sequence of concatenated msgpack records. Each record is a
+2-element tuple: `(type_tag, payload)`.
+
+| Type tag | Payload | Description |
+|----------|---------|-------------|
+| `"t"` | `{"m": {id, root, collection}, "t": [triple_dicts]}` | Triple batch |
+| `"ge"` | `{"m": {id, root, collection}, "e": [{entity, vector}]}` | Graph embedding batch |
+
+### What's Missing
+
+#### Named Graphs
+
+The `Triple` dataclass has a `g: str | None` field (graph name IRI), used to
+separate provenance graphs (`urn:graph:source`, `urn:graph:retrieval`) from
+the default graph. However:
+
+- **Cassandra schema** (`knowledge.triples` table): stores a 6-tuple per
+  triple `(s_val, s_is_uri, p_val, p_is_uri, o_val, o_is_uri)` — no graph
+  field.
+- **`add_triples()`** (`tables/knowledge.py:231`): destructures only `s`,
+  `p`, `o` — `g` is discarded.
+- **`get_triples()`** (`tables/knowledge.py:396`): reconstructs `Triple`
+  with `g` defaulting to `None`.
+- **Core file format**: triple dicts do not include a graph field.
+
+#### Provenance Triples
+
+Provenance triples are generated in the extraction pipeline
+(`trustgraph-base/trustgraph/provenance/triples.py`) and published to graph
+store topics. They use named graphs (`urn:graph:source`,
+`urn:graph:retrieval`) and PROV-O vocabulary.
+
+The knowledge core store processor (`storage/knowledge/store.py`) listens on
+`triples-input` and `graph-embeddings-input`. Whether provenance triples
+arrive on the same `triples-input` topic or a separate one needs
+verification. Even if they do arrive, the graph name would be lost (per
+above).
+
+#### Source Material
+
+The librarian stores the full document hierarchy in a separate system:
+
+- **Blob store** (S3/MinIO): original documents, text pages, chunks —
+  keyed by object UUID under `doc/{object_id}`.
+- **Cassandra `library` keyspace**: document metadata including `id`,
+  `kind` (MIME type), `title`, `parent_id`, `document_type`
+  (`source`/`extracted`), `object_id` (blob reference).
+
+Provenance triples link extracted facts back to chunk/page/document IDs.
+Those IDs resolve through the librarian. When a core is loaded on a
+different instance, the librarian has no matching documents, so the entire
+provenance chain is broken.
+
+### Key Source Files
+
+| Component | File | Purpose |
+|-----------|------|---------|
+| Core Cassandra schema | `trustgraph-flow/trustgraph/tables/knowledge.py` | Table definitions, read/write |
+| Core manager | `trustgraph-flow/trustgraph/cores/knowledge.py` | API operations, load-to-store |
+| Core store processor | `trustgraph-flow/trustgraph/storage/knowledge/store.py` | Extraction → Cassandra |
+| CLI download | `trustgraph-cli/trustgraph/cli/get_kg_core.py` | Core → msgpack file |
+| CLI upload | `trustgraph-cli/trustgraph/cli/put_kg_core.py` | Msgpack file → core |
+| CLI load | `trustgraph-cli/trustgraph/cli/load_kg_core.py` | Core → graph/vector stores |
+| API client | `trustgraph-base/trustgraph/api/knowledge.py` | Client-side knowledge API |
+| Triple schema | `trustgraph-base/trustgraph/schema/core/primitives.py` | Triple dataclass with `g` field |
+| Provenance generation | `trustgraph-base/trustgraph/provenance/triples.py` | PROV-O triple creation |
+| Librarian | `trustgraph-flow/trustgraph/librarian/librarian.py` | Document storage service |
+| Library tables | `trustgraph-flow/trustgraph/tables/library.py` | Document metadata in Cassandra |
+| Blob store | `trustgraph-flow/trustgraph/librarian/blob_store.py` | S3/MinIO object storage |
+
+## Technical Design
+
+### Change 1: Named Graph Field in Core Storage
+
+#### Cassandra Schema
+
+Extend the `triples` tuple from 6 to 7 elements, adding the graph name:
+
+```
+triples list<tuple<
+    text, boolean,       -- s_val, s_is_uri
+    text, boolean,       -- p_val, p_is_uri
+    text, boolean,       -- o_val, o_is_uri
+    text                 -- graph name (empty string = default graph)
+>>
+```
+
+**Migration**: The schema change uses `ALTER TABLE` or is handled by
+creating a new table version. Existing rows with 6-element tuples must be
+handled gracefully on read — if the tuple has 6 elements, treat graph as
+default.
+
+#### Write Path (`add_triples`)
+
+Change `tables/knowledge.py:add_triples()` to include `triple.g`:
+
+```python
+triples = [
+    (
+        *term_to_tuple(v.s), *term_to_tuple(v.p), *term_to_tuple(v.o),
+        v.g or ""
+    )
+    for v in m.triples
+]
+```
+
+#### Read Path (`get_triples`)
+
+Change `tables/knowledge.py:get_triples()` to restore the graph name:
+
+```python
+Triple(
+    s = tuple_to_term(elt[0], elt[1]),
+    p = tuple_to_term(elt[2], elt[3]),
+    o = tuple_to_term(elt[4], elt[5]),
+    g = elt[6] if len(elt) > 6 and elt[6] else None,
+)
+```
+
+The `len(elt) > 6` guard provides backward compatibility with existing
+6-element rows.
+
+#### Core File Format
+
+Extend triple dicts in the `"t"` record to include the graph name:
+
+```python
+# In get_kg_core.py write_triple — each triple dict gains "g" key
+{"s": ..., "p": ..., "o": ..., "g": "urn:graph:source"}
+```
+
+On read (`put_kg_core.py`), treat missing `"g"` key as default graph for
+backward compatibility with old core files.
+
+### Change 2: Provenance Triples in Cores
+
+#### Investigation Required
+
+Before implementation, verify:
+
+1. Whether provenance triples arrive on the `triples-input` topic that the
+   knowledge core store processor already listens on.
+2. If not, which topic they use, and whether the store processor should
+   subscribe to it.
+
+#### If provenance triples already arrive at the store
+
+The only change needed is Change 1 (named graphs) — the provenance triples
+are already being stored, just without their graph name. Once graph names
+are preserved, provenance triples will round-trip correctly.
+
+#### If provenance triples do NOT arrive at the store
+
+Two options:
+
+**Option A — Route provenance to the existing store topic**: Configure the
+flow so provenance triples are published to the same `triples-input` topic.
+This is the simpler approach and keeps the store processor unchanged.
+
+**Option B — Add a subscription**: Add a new `ConsumerSpec` in the store
+processor for the provenance topic. This keeps provenance routing
+independent but adds complexity.
+
+Recommendation: Option A, unless there is a reason provenance triples are
+intentionally kept off the core store topic.
+
+### Change 3: Source Material in Cores
+
+This is the largest change. The goal is that when a core is loaded on a
+fresh instance, provenance links to source material resolve.
+
+#### Architecture
+
+Source material is **not stored in the knowledge core tables**. It lives in
+the librarian (Cassandra `library` keyspace + S3/MinIO blob store) and is
+fetched on demand via the librarian's existing service API.
+
+The knowledge manager acts as a **client of the librarian service** — it
+calls the librarian's request/response API over pub/sub to retrieve document
+metadata and content. It does not access the library's Cassandra tables or
+blob store directly.
+
+#### Transport
+
+The librarian's pub/sub API already handles chunking of large documents.
+This chunking is designed to be websocket-friendly, so library content
+flowing through the API gateway to external clients does not require
+re-chunking. The API gateway remains a transport layer.
+
+```
+Download:
+  Knowledge manager ──pub/sub──► Librarian (fetch metadata + content)
+  Knowledge manager ──pub/sub──► API gateway ──websocket──► Client
+
+Upload:
+  Client ──websocket──► API gateway ──pub/sub──► Knowledge manager
+  Knowledge manager ──pub/sub──► Librarian (store metadata + content)
+```
+
+#### What to Include
+
+The provenance chain links facts → chunks → pages → documents. For the
+chain to resolve, the core must include:
+
+1. **Document metadata** — the library record for each document in the
+   hierarchy (id, kind, title, parent_id, document_type, etc.)
+2. **Document content** — the blob data for each document (original file,
+   extracted text pages, text chunks)
+
+Including the full hierarchy is necessary because:
+- A user viewing provenance needs to traverse fact → chunk → page → document
+- The chunk text is needed to show what text a fact was extracted from
+- The page text provides broader context
+- The original document is needed for full source attribution
+
+#### Size Implications
+
+Source material will significantly increase core file sizes. A rough model:
+
+| Component | Typical size per document |
+|-----------|-------------------------|
+| Triples + embeddings (current) | 1-10 MB |
+| Chunk text (all chunks) | ~same as original document |
+| Page text (all pages) | ~same as original document |
+| Original document (PDF, etc.) | Varies widely (KB to hundreds of MB) |
+
+For a 10 MB PDF, the core could grow from ~5 MB to ~25 MB (original +
+derived text + existing data). For large document sets, cores could become
+very large.
+
+**Decision needed**: Whether to include original documents or just derived
+text (pages + chunks). Including only derived text still allows provenance
+display but loses the ability to serve the original file.
+
+#### New Core File Record Types
+
+Add new msgpack record types for library content:
+
+| Type tag | Payload | Description |
+|----------|---------|-------------|
+| `"lm"` | `{"id", "kind", "title", "parent_id", "document_type", "comments", "tags", "metadata"}` | Library document metadata |
+| `"lb"` | `{"id", "data"}` | Library document blob content (chunked by pub/sub layer) |
+
+These are emitted after the existing `"t"` and `"ge"` records during
+download and processed during upload.
+
+#### Download Path
+
+Extend `KnowledgeManager.get_kg_core()` to:
+
+1. Stream triples and graph embeddings from the core store (existing
+   behavior).
+2. Use the librarian service API to retrieve documents associated with
+   this core ID:
+   a. Fetch the root document metadata and content.
+   b. Use `list-children` to discover child documents (pages, chunks).
+   c. Recursively fetch metadata and content for each child.
+3. Stream each document as `"lm"` (metadata) and `"lb"` (content) records.
+
+The knowledge manager gains the librarian service as a pub/sub dependency.
+Large document content is chunked by the librarian's existing pub/sub
+transport — the knowledge manager receives and forwards these chunks without
+buffering the full blob in memory.
+
+#### Upload Path
+
+Extend `KnowledgeManager.put_kg_core()` to handle the new record types:
+
+1. For `"lm"` records: call the librarian service API to create/update
+   the document metadata.
+2. For `"lb"` records: call the librarian service API to store the
+   document content.
+
+Parent-child relationships are preserved because `parent_id` is stored in
+the metadata. Documents should be processed in hierarchy order (parent
+before child) to satisfy any ordering constraints.
+
+#### Load Path
+
+The load path (`_load_kg_core`) publishes triples and embeddings to Pulsar
+topics for ingestion into graph/vector stores. Source material does not need
+to flow through the load path — it is already in the librarian after the
+upload step and can be accessed directly by services that need it.
+
+No changes to the load path for source material.
+
+#### CLI Changes
+
+**`tg-get-kg-core`**: Add handling for `"lm"` and `"lb"` record types in
+the file writer.
+
+**`tg-put-kg-core`**: Add handling for `"lm"` and `"lb"` record types in
+the file reader. Send library records to the knowledge manager alongside
+triple/embedding records.
+
+#### Associating Documents with Cores
+
+The core ID is `metadata.root`, which is the root document ID from the
+librarian. This provides a natural join: the core's root document and all
+its children (pages, chunks) are the source material for that core.
+
+The librarian's `list-children` API provides the child documents. A
+recursive traversal from the root document collects the full hierarchy.
+
+### API Changes
+
+#### KnowledgeResponse Schema
+
+Add optional fields to `KnowledgeResponse` for library data:
+
+```python
+@dataclass
+class KnowledgeResponse:
+    error: Error | None = None
+    ids: list | None = None
+    eos: bool = False
+    triples: Triples | None = None
+    graph_embeddings: GraphEmbeddings | None = None
+    document_embeddings: DocumentEmbeddings | None = None
+    library_metadata: LibraryMetadata | None = None    # new
+    library_blob: LibraryBlob | None = None            # new
+```
+
+#### New Schema Types
+
+```python
+@dataclass
+class LibraryMetadata:
+    id: str
+    kind: str | None = None
+    title: str | None = None
+    parent_id: str | None = None
+    document_type: str | None = None
+    comments: str | None = None
+    tags: list[str] | None = None
+    metadata: list[Triple] | None = None
+
+@dataclass
+class LibraryBlob:
+    id: str
+    data: bytes
+```
+
+#### Socket API
+
+The existing streaming protocol for `get-kg-core` / `put-kg-core` carries
+these new fields naturally — responses already stream multiple record types.
+
+### Dependencies Between Changes
+
+```
+Change 1 (named graphs)  ◄── Change 2 depends on this
+         │
+         └── Change 2 (provenance triples)
+                      │
+                      └── Change 3 (source material) is independent
+```
+
+Change 1 is a prerequisite for Change 2 (provenance triples use named
+graphs). Change 3 is independent and can be implemented in parallel.
+
+## Security Considerations
+
+- **Workspace isolation**: Core download/upload must respect workspace
+  boundaries. Source material from the librarian must only be included if
+  it belongs to the same workspace as the core. This is already enforced
+  by the existing workspace-scoped queries.
+- **Large blob transfer**: Streaming large documents through the API
+  is handled by the librarian's existing pub/sub chunking, which is
+  designed to be websocket-friendly. No additional chunking layer is
+  needed.
+- **Cross-instance trust**: When uploading a core from an external source,
+  the library content should be treated as untrusted input. Document
+  metadata and blob content should be validated before insertion.
+
+## Performance Considerations
+
+- **Core file size**: Including source material will significantly increase
+  core file sizes. Consider adding a flag to download/upload commands to
+  optionally exclude source material for use cases where only the knowledge
+  graph is needed.
+- **Streaming**: All paths already use streaming (paged Cassandra queries,
+  msgpack record-at-a-time). Library content should follow the same pattern.
+- **Cassandra schema migration**: Changing the tuple width in the `triples`
+  table requires careful handling. Cassandra frozen tuples cannot be altered
+  in place — a migration strategy is needed (see Migration Plan).
+
+## Testing Strategy
+
+- **Unit tests**: Triple round-trip with graph name (write → read →
+  verify `g` field preserved). Backward compatibility with 6-element tuples.
+- **Integration tests**: Full lifecycle — extract with provenance → download
+  core → upload to fresh instance → load → verify provenance chain resolves.
+- **File format tests**: Read old-format core files (no graph name, no
+  library records) and verify they load without error.
+- **Library inclusion tests**: Download core with source material → upload →
+  verify documents accessible through librarian.
+
+## Migration Plan
+
+### Cassandra Schema
+
+The `triples` table stores tuples in a `list<tuple<...>>` column. Cassandra
+does not support altering the type of an existing column. Options:
+
+**Option A — New table**: Create a `triples_v2` table with the 7-element
+tuple. Migrate data from `triples` to `triples_v2`. The read path checks
+both tables during a transition period, then the old table is dropped.
+
+**Option B — Dual read**: Keep the existing table. The read path handles
+both 6-element and 7-element tuples by checking length. New writes use
+7-element tuples. This works if Cassandra accepts variable-length tuples in
+a list — **needs verification**.
+
+**Option C — Separate graph column**: Instead of extending the tuple, add a
+parallel `graphs list<text>` column where `graphs[i]` corresponds to
+`triples[i]`. This avoids tuple migration entirely but requires keeping the
+two lists in sync.
+
+Recommendation: Verify Option B first (simplest). Fall back to Option A if
+Cassandra rejects mixed tuple lengths.
+
+### Core File Format
+
+Backward compatible by design:
+- Old files lack `"g"` in triple dicts and have no `"lm"`/`"lb"` records →
+  handled by defaults.
+- New files read by old code → old code ignores unknown record types (the
+  existing `read_message` raises on unknown types, so this needs a small
+  fix to skip unknown types gracefully).
+
+## Open Questions
+
+1. **Provenance topic routing**: Do provenance triples currently arrive at
+   the `triples-input` topic consumed by the knowledge core store? If not,
+   what topic are they on?
+
+2. **Include original documents?**: Should cores include the original
+   uploaded document (e.g. PDF), or only derived text (pages + chunks)?
+   Including originals makes cores fully self-contained but potentially
+   very large. Excluding them preserves provenance text display but loses
+   the ability to serve the original file.
+
+3. **Optional source material**: Should there be a flag on download/upload
+   to include or exclude source material? This would let users choose
+   between compact cores (knowledge only) and complete cores (knowledge +
+   sources).
+
+4. **Cassandra tuple migration**: Can Cassandra handle mixed-length tuples
+   in a `list<tuple<...>>` column, or is a table migration required?
+
+5. **Document embedding cores**: DE cores are managed alongside KG cores.
+   Do they need the same treatment (source material inclusion)?  The
+   document embeddings reference chunk IDs — the same provenance chain
+   applies.
+
+6. **Core versioning**: Should the core file include a version marker so
+   readers can distinguish old-format from new-format files without
+   trial-and-error parsing?
+
+## References
+
+- Extraction-time provenance: `docs/tech-specs/extraction-time-provenance.md`
+- Query-time explainability: `docs/tech-specs/query-time-explainability.md`
+- Agent explainability: `docs/tech-specs/agent-explainability.md`
+- Data ownership model: `docs/tech-specs/data-ownership-model.md`

tests/unit/test_base/test_cassandra_config.py

@@ -409,4 +409,57 @@ class TestEdgeCases:
         
         assert hosts == ['mixed-host']
         assert username is None  # Stays None
-        assert password == 'mixed-pass'
+        assert password == 'mixed-pass'
+
+
+class TestReplicationFactorParamPath:
+
+    def test_explicit_kwarg(self):
+        with patch.dict(os.environ, {}, clear=True):
+            _, _, _, _, rf = resolve_cassandra_config(
+                replication_factor=3,
+            )
+            assert rf == 3
+
+    def test_kwarg_overrides_env(self):
+        with patch.dict(os.environ, {'CASSANDRA_REPLICATION_FACTOR': '5'}, clear=True):
+            _, _, _, _, rf = resolve_cassandra_config(
+                replication_factor=3,
+            )
+            assert rf == 3
+
+    def test_env_fallback_when_kwarg_none(self):
+        with patch.dict(os.environ, {'CASSANDRA_REPLICATION_FACTOR': '5'}, clear=True):
+            _, _, _, _, rf = resolve_cassandra_config(
+                replication_factor=None,
+            )
+            assert rf == 5
+
+    def test_default_when_no_kwarg_no_env(self):
+        with patch.dict(os.environ, {}, clear=True):
+            _, _, _, _, rf = resolve_cassandra_config()
+            assert rf == 1
+
+    def test_params_dict_path(self):
+        with patch.dict(os.environ, {}, clear=True):
+            params = {'cassandra_replication_factor': 3}
+            _, _, _, _, rf = resolve_cassandra_config(
+                replication_factor=params.get('cassandra_replication_factor'),
+            )
+            assert rf == 3
+
+    def test_params_dict_overrides_env(self):
+        with patch.dict(os.environ, {'CASSANDRA_REPLICATION_FACTOR': '5'}, clear=True):
+            params = {'cassandra_replication_factor': 3}
+            _, _, _, _, rf = resolve_cassandra_config(
+                replication_factor=params.get('cassandra_replication_factor'),
+            )
+            assert rf == 3
+
+    def test_params_dict_missing_falls_to_env(self):
+        with patch.dict(os.environ, {'CASSANDRA_REPLICATION_FACTOR': '5'}, clear=True):
+            params = {}
+            _, _, _, _, rf = resolve_cassandra_config(
+                replication_factor=params.get('cassandra_replication_factor'),
+            )
+            assert rf == 5

tests/unit/test_base/test_qdrant_config.py

@@ -0,0 +1,136 @@
+
+import os
+import pytest
+from unittest.mock import patch
+
+from trustgraph.base.qdrant_config import (
+    get_qdrant_defaults,
+    resolve_qdrant_config,
+)
+
+
+class TestGetQdrantDefaults:
+
+    def test_defaults_with_no_env_vars(self):
+        with patch.dict(os.environ, {}, clear=True):
+            defaults = get_qdrant_defaults()
+            assert defaults['url'] == 'http://localhost:6333'
+            assert defaults['api_key'] is None
+            assert defaults['replication_factor'] == 1
+            assert defaults['shard_number'] == 1
+
+    def test_defaults_from_env(self):
+        env = {
+            'QDRANT_URL': 'http://qdrant:6333',
+            'QDRANT_API_KEY': 'secret',
+            'QDRANT_REPLICATION_FACTOR': '3',
+            'QDRANT_SHARD_NUMBER': '5',
+        }
+        with patch.dict(os.environ, env, clear=True):
+            defaults = get_qdrant_defaults()
+            assert defaults['url'] == 'http://qdrant:6333'
+            assert defaults['api_key'] == 'secret'
+            assert defaults['replication_factor'] == 3
+            assert defaults['shard_number'] == 5
+
+
+class TestResolveQdrantConfig:
+
+    def test_defaults(self):
+        with patch.dict(os.environ, {}, clear=True):
+            url, api_key, rf, sn = resolve_qdrant_config()
+            assert url == 'http://localhost:6333'
+            assert api_key is None
+            assert rf == 1
+            assert sn == 1
+
+    def test_explicit_kwargs(self):
+        with patch.dict(os.environ, {}, clear=True):
+            url, api_key, rf, sn = resolve_qdrant_config(
+                url='http://custom:6333',
+                api_key='key',
+                replication_factor=3,
+                shard_number=5,
+            )
+            assert url == 'http://custom:6333'
+            assert api_key == 'key'
+            assert rf == 3
+            assert sn == 5
+
+    def test_kwargs_override_env(self):
+        env = {
+            'QDRANT_URL': 'http://env:6333',
+            'QDRANT_REPLICATION_FACTOR': '10',
+            'QDRANT_SHARD_NUMBER': '10',
+        }
+        with patch.dict(os.environ, env, clear=True):
+            url, _, rf, sn = resolve_qdrant_config(
+                url='http://explicit:6333',
+                replication_factor=3,
+                shard_number=5,
+            )
+            assert url == 'http://explicit:6333'
+            assert rf == 3
+            assert sn == 5
+
+    def test_env_fallback_when_kwargs_none(self):
+        env = {
+            'QDRANT_URL': 'http://env:6333',
+            'QDRANT_REPLICATION_FACTOR': '3',
+            'QDRANT_SHARD_NUMBER': '5',
+        }
+        with patch.dict(os.environ, env, clear=True):
+            url, _, rf, sn = resolve_qdrant_config()
+            assert url == 'http://env:6333'
+            assert rf == 3
+            assert sn == 5
+
+    def test_params_dict_path(self):
+        with patch.dict(os.environ, {}, clear=True):
+            params = {
+                'store_uri': 'http://params:6333',
+                'api_key': 'pkey',
+                'qdrant_replication_factor': 3,
+                'qdrant_shard_number': 5,
+            }
+            url, api_key, rf, sn = resolve_qdrant_config(
+                url=params.get('store_uri'),
+                api_key=params.get('api_key'),
+                replication_factor=params.get('qdrant_replication_factor'),
+                shard_number=params.get('qdrant_shard_number'),
+            )
+            assert url == 'http://params:6333'
+            assert api_key == 'pkey'
+            assert rf == 3
+            assert sn == 5
+
+    def test_params_dict_overrides_env(self):
+        env = {
+            'QDRANT_REPLICATION_FACTOR': '10',
+            'QDRANT_SHARD_NUMBER': '10',
+        }
+        with patch.dict(os.environ, env, clear=True):
+            params = {
+                'qdrant_replication_factor': 3,
+                'qdrant_shard_number': 5,
+            }
+            _, _, rf, sn = resolve_qdrant_config(
+                replication_factor=params.get('qdrant_replication_factor'),
+                shard_number=params.get('qdrant_shard_number'),
+            )
+            assert rf == 3
+            assert sn == 5
+
+    def test_params_dict_missing_falls_to_env(self):
+        env = {
+            'QDRANT_REPLICATION_FACTOR': '3',
+            'QDRANT_SHARD_NUMBER': '5',
+        }
+        with patch.dict(os.environ, env, clear=True):
+            params = {}
+            _, _, rf, sn = resolve_qdrant_config(
+                replication_factor=params.get('qdrant_replication_factor'),
+                shard_number=params.get('qdrant_shard_number'),
+            )
+            assert rf == 3
+            assert sn == 5

tests/unit/test_cores/test_knowledge_manager.py

@@ -11,7 +11,12 @@ from unittest.mock import AsyncMock, Mock, patch, MagicMock
 from unittest.mock import call
 
 from trustgraph.cores.knowledge import KnowledgeManager
-from trustgraph.schema import KnowledgeResponse, Triples, GraphEmbeddings, Metadata, Triple, Term, EntityEmbeddings, IRI, LITERAL
+from trustgraph.schema import (
+    KnowledgeResponse, Triples, GraphEmbeddings, Metadata, Triple, Term,
+    EntityEmbeddings, IRI, LITERAL,
+    LibraryMetadata, LibraryBlob,
+    LibrarianResponse, DocumentMetadata,
+)
 
 
 @pytest.fixture
@@ -373,11 +378,252 @@ class TestKnowledgeManagerOtherMethods:
         mock_respond = AsyncMock()
 
         await knowledge_manager.delete_kg_core(mock_request, mock_respond, "test-user")
-        
+
         # Verify table store was called correctly
         knowledge_manager.table_store.delete_kg_core.assert_called_once_with("test-user", "test-doc-id")
-        
+
         # Verify response
         mock_respond.assert_called_once()
         response = mock_respond.call_args[0][0]
-        assert response.error is None
+        assert response.error is None
+
+
+class TestKnowledgeManagerLibraryDownload:
+    """Test get_kg_core streaming of library documents."""
+
+    @pytest.fixture
+    def manager_with_librarian(self, mock_flow_config):
+        with patch('trustgraph.cores.knowledge.KnowledgeTableStore'):
+            mock_librarian = AsyncMock()
+            manager = KnowledgeManager(
+                cassandra_host=["localhost"],
+                cassandra_username="test_user",
+                cassandra_password="test_pass",
+                keyspace="test_keyspace",
+                flow_config=mock_flow_config,
+                librarian=mock_librarian,
+            )
+            manager.table_store = AsyncMock()
+            return manager
+
+    @pytest.mark.asyncio
+    async def test_get_kg_core_streams_library_docs(self, manager_with_librarian):
+        mock_request = Mock()
+        mock_request.id = "root-doc"
+        mock_respond = AsyncMock()
+
+        manager_with_librarian.table_store.get_triples = AsyncMock()
+        manager_with_librarian.table_store.get_graph_embeddings = AsyncMock()
+
+        root_meta = DocumentMetadata(
+            id="root-doc", kind="application/pdf", title="Test PDF",
+            document_type="source",
+        )
+        child_meta = DocumentMetadata(
+            id="chunk-1", kind="text/plain", title="Chunk 1",
+            parent_id="root-doc", document_type="chunk",
+        )
+
+        manager_with_librarian.librarian.fetch_document_metadata.return_value = root_meta
+        manager_with_librarian.librarian.request.return_value = LibrarianResponse(
+            document_metadatas=[child_meta],
+        )
+        manager_with_librarian.librarian.fetch_document_content.side_effect = [
+            b"cm9vdCBjb250ZW50",
+            b"Y2h1bmsgY29udGVudA==",
+        ]
+
+        await manager_with_librarian.get_kg_core(
+            mock_request, mock_respond, "test-user"
+        )
+
+        responses = [c[0][0] for c in mock_respond.call_args_list]
+
+        lm_responses = [r for r in responses if r.library_metadata is not None]
+        lb_responses = [r for r in responses if r.library_blob is not None]
+        eos_responses = [r for r in responses if r.eos is True]
+
+        assert len(lm_responses) == 2
+        assert lm_responses[0].library_metadata.id == "root-doc"
+        assert lm_responses[0].library_metadata.document_type == "source"
+        assert lm_responses[1].library_metadata.id == "chunk-1"
+        assert lm_responses[1].library_metadata.parent_id == "root-doc"
+
+        assert len(lb_responses) == 2
+        assert lb_responses[0].library_blob.id == "root-doc"
+        assert lb_responses[0].library_blob.data == b"cm9vdCBjb250ZW50"
+        assert lb_responses[1].library_blob.id == "chunk-1"
+
+        assert len(eos_responses) == 1
+
+    @pytest.mark.asyncio
+    async def test_get_kg_core_no_librarian_skips_library(self, mock_flow_config):
+        with patch('trustgraph.cores.knowledge.KnowledgeTableStore'):
+            manager = KnowledgeManager(
+                cassandra_host=["localhost"],
+                cassandra_username="u", cassandra_password="p",
+                keyspace="ks", flow_config=mock_flow_config,
+            )
+            manager.table_store = AsyncMock()
+            manager.table_store.get_triples = AsyncMock()
+            manager.table_store.get_graph_embeddings = AsyncMock()
+
+        mock_request = Mock()
+        mock_request.id = "doc-1"
+        mock_respond = AsyncMock()
+
+        await manager.get_kg_core(mock_request, mock_respond, "w")
+
+        responses = [c[0][0] for c in mock_respond.call_args_list]
+        assert all(r.library_metadata is None for r in responses)
+        assert all(r.library_blob is None for r in responses)
+
+    @pytest.mark.asyncio
+    async def test_get_kg_core_librarian_metadata_failure_is_graceful(
+        self, manager_with_librarian,
+    ):
+        mock_request = Mock()
+        mock_request.id = "missing-doc"
+        mock_respond = AsyncMock()
+
+        manager_with_librarian.table_store.get_triples = AsyncMock()
+        manager_with_librarian.table_store.get_graph_embeddings = AsyncMock()
+        manager_with_librarian.librarian.fetch_document_metadata.side_effect = (
+            RuntimeError("not found")
+        )
+
+        await manager_with_librarian.get_kg_core(
+            mock_request, mock_respond, "test-user"
+        )
+
+        responses = [c[0][0] for c in mock_respond.call_args_list]
+        assert all(r.library_metadata is None for r in responses)
+        assert any(r.eos for r in responses)
+
+
+class TestKnowledgeManagerLibraryUpload:
+    """Test put_kg_core handling of library metadata and blob records."""
+
+    @pytest.fixture
+    def manager_with_librarian(self, mock_flow_config):
+        with patch('trustgraph.cores.knowledge.KnowledgeTableStore'):
+            mock_librarian = AsyncMock()
+            manager = KnowledgeManager(
+                cassandra_host=["localhost"],
+                cassandra_username="u", cassandra_password="p",
+                keyspace="ks", flow_config=mock_flow_config,
+                librarian=mock_librarian,
+            )
+            manager.table_store = AsyncMock()
+            return manager
+
+    @pytest.mark.asyncio
+    async def test_put_metadata_then_blob_calls_librarian(
+        self, manager_with_librarian,
+    ):
+        mock_respond = AsyncMock()
+        manager_with_librarian.librarian.request.return_value = LibrarianResponse()
+
+        # First call: metadata
+        req_meta = Mock()
+        req_meta.triples = None
+        req_meta.graph_embeddings = None
+        req_meta.library_metadata = LibraryMetadata(
+            id="doc-1", kind="application/pdf", title="Test",
+            document_type="source",
+        )
+        req_meta.library_blob = None
+        await manager_with_librarian.put_kg_core(req_meta, mock_respond, "ws")
+
+        # Metadata is buffered, librarian not called yet
+        manager_with_librarian.librarian.request.assert_not_called()
+
+        # Second call: blob
+        req_blob = Mock()
+        req_blob.triples = None
+        req_blob.graph_embeddings = None
+        req_blob.library_metadata = None
+        req_blob.library_blob = LibraryBlob(
+            id="doc-1", data=b"dGVzdA==",
+        )
+        await manager_with_librarian.put_kg_core(req_blob, mock_respond, "ws")
+
+        # Now librarian should have been called with add-document
+        manager_with_librarian.librarian.request.assert_called_once()
+        call_args = manager_with_librarian.librarian.request.call_args[0][0]
+        assert call_args.operation == "add-document"
+        assert call_args.document_metadata.id == "doc-1"
+        assert call_args.document_metadata.kind == "application/pdf"
+        assert call_args.content == b"dGVzdA=="
+
+    @pytest.mark.asyncio
+    async def test_put_child_document_uses_add_child_operation(
+        self, manager_with_librarian,
+    ):
+        mock_respond = AsyncMock()
+        manager_with_librarian.librarian.request.return_value = LibrarianResponse()
+
+        req_meta = Mock()
+        req_meta.triples = None
+        req_meta.graph_embeddings = None
+        req_meta.library_metadata = LibraryMetadata(
+            id="chunk-1", kind="text/plain", title="Chunk",
+            parent_id="doc-1", document_type="chunk",
+        )
+        req_meta.library_blob = None
+        await manager_with_librarian.put_kg_core(req_meta, mock_respond, "ws")
+
+        req_blob = Mock()
+        req_blob.triples = None
+        req_blob.graph_embeddings = None
+        req_blob.library_metadata = None
+        req_blob.library_blob = LibraryBlob(id="chunk-1", data=b"Y2h1bms=")
+        await manager_with_librarian.put_kg_core(req_blob, mock_respond, "ws")
+
+        call_args = manager_with_librarian.librarian.request.call_args[0][0]
+        assert call_args.operation == "add-child-document"
+        assert call_args.document_metadata.parent_id == "doc-1"
+
+    @pytest.mark.asyncio
+    async def test_put_blob_without_metadata_logs_warning(
+        self, manager_with_librarian,
+    ):
+        mock_respond = AsyncMock()
+
+        req_blob = Mock()
+        req_blob.triples = None
+        req_blob.graph_embeddings = None
+        req_blob.library_metadata = None
+        req_blob.library_blob = LibraryBlob(id="orphan", data=b"data")
+        await manager_with_librarian.put_kg_core(req_blob, mock_respond, "ws")
+
+        # Librarian should not be called for orphan blob
+        manager_with_librarian.librarian.request.assert_not_called()
+
+    @pytest.mark.asyncio
+    async def test_put_existing_document_is_graceful(
+        self, manager_with_librarian,
+    ):
+        mock_respond = AsyncMock()
+        manager_with_librarian.librarian.request.side_effect = RuntimeError(
+            "Document already exists"
+        )
+
+        req_meta = Mock()
+        req_meta.triples = None
+        req_meta.graph_embeddings = None
+        req_meta.library_metadata = LibraryMetadata(
+            id="doc-1", kind="application/pdf", title="Test",
+            document_type="source",
+        )
+        req_meta.library_blob = None
+        await manager_with_librarian.put_kg_core(req_meta, mock_respond, "ws")
+
+        req_blob = Mock()
+        req_blob.triples = None
+        req_blob.graph_embeddings = None
+        req_blob.library_metadata = None
+        req_blob.library_blob = LibraryBlob(id="doc-1", data=b"data")
+        await manager_with_librarian.put_kg_core(req_blob, mock_respond, "ws")
+
+        # Should not raise — "already exists" is handled gracefully

tests/unit/test_decoding/test_pdf_decoder.py

@@ -49,7 +49,7 @@ class TestPdfDecoderProcessor(IsolatedAsyncioTestCase):
     async def test_on_message_success(self, mock_pdf_loader_class, mock_producer, mock_consumer):
         """Test successful PDF processing"""
         # Mock PDF content
-        pdf_content = b"fake pdf content"
+        pdf_content = b"%PDF-1.7\nfake pdf content"
         pdf_base64 = base64.b64encode(pdf_content).decode('utf-8')
 
         # Mock PyPDFLoader
@@ -88,13 +88,55 @@ class TestPdfDecoderProcessor(IsolatedAsyncioTestCase):
         # Verify triples were sent for each page (provenance)
         assert mock_triples_flow.send.call_count == 2
 
+    @patch('trustgraph.base.librarian_client.Consumer')
+    @patch('trustgraph.base.librarian_client.Producer')
+    @patch('trustgraph.decoding.pdf.pdf_decoder.PyPDFLoader')
+    @patch('trustgraph.base.async_processor.AsyncProcessor', MockAsyncProcessor)
+    async def test_on_message_rejects_librarian_content_that_is_not_pdf(self, mock_pdf_loader_class, mock_producer, mock_consumer):
+        """Test rejecting non-PDF content before invoking the PDF loader"""
+        html_content = b"<html><body>Not found</body></html>"
+        html_base64 = base64.b64encode(html_content)
+
+        mock_metadata = Metadata(id="test-doc")
+        mock_document = Document(metadata=mock_metadata, document_id="doc-123")
+        mock_msg = MagicMock()
+        mock_msg.value.return_value = mock_document
+
+        mock_output_flow = AsyncMock()
+        mock_triples_flow = AsyncMock()
+        mock_flow = MagicMock(side_effect=lambda name: {
+            "output": mock_output_flow,
+            "triples": mock_triples_flow,
+        }.get(name))
+        mock_flow.librarian.fetch_document_metadata = AsyncMock(
+            return_value=MagicMock(kind="application/pdf")
+        )
+        mock_flow.librarian.fetch_document_content = AsyncMock(
+            return_value=html_base64
+        )
+        mock_flow.librarian.save_child_document = AsyncMock()
+
+        config = {
+            'id': 'test-pdf-decoder',
+            'taskgroup': AsyncMock()
+        }
+
+        processor = Processor(**config)
+
+        await processor.on_message(mock_msg, None, mock_flow)
+
+        mock_pdf_loader_class.assert_not_called()
+        mock_output_flow.send.assert_not_called()
+        mock_triples_flow.send.assert_not_called()
+        mock_flow.librarian.save_child_document.assert_not_called()
+
     @patch('trustgraph.base.librarian_client.Consumer')
     @patch('trustgraph.base.librarian_client.Producer')
     @patch('trustgraph.decoding.pdf.pdf_decoder.PyPDFLoader')
     @patch('trustgraph.base.async_processor.AsyncProcessor', MockAsyncProcessor)
     async def test_on_message_empty_pdf(self, mock_pdf_loader_class, mock_producer, mock_consumer):
         """Test handling of empty PDF"""
-        pdf_content = b"fake pdf content"
+        pdf_content = b"%PDF-1.7\nfake pdf content"
         pdf_base64 = base64.b64encode(pdf_content).decode('utf-8')
 
         mock_loader = MagicMock()
@@ -126,7 +168,7 @@ class TestPdfDecoderProcessor(IsolatedAsyncioTestCase):
     @patch('trustgraph.base.async_processor.AsyncProcessor', MockAsyncProcessor)
     async def test_on_message_unicode_content(self, mock_pdf_loader_class, mock_producer, mock_consumer):
         """Test handling of unicode content in PDF"""
-        pdf_content = b"fake pdf content"
+        pdf_content = b"%PDF-1.7\nfake pdf content"
         pdf_base64 = base64.b64encode(pdf_content).decode('utf-8')
 
         mock_loader = MagicMock()

tests/unit/test_query/test_rows_cassandra_query.py

@@ -333,8 +333,8 @@ class TestUnifiedTableQueries:
     """Test queries against the unified rows table"""
 
     @pytest.mark.asyncio
-    @patch('trustgraph.query.rows.cassandra.service.async_execute', new_callable=AsyncMock)
-    async def test_query_with_index_match(self, mock_async_execute):
+    @patch('trustgraph.query.rows.cassandra.service.async_execute_paged', new_callable=AsyncMock)
+    async def test_query_with_index_match(self, mock_async_execute_paged):
         """Test query execution with matching index"""
         processor = MagicMock()
         processor.session = MagicMock()
@@ -344,10 +344,10 @@ class TestUnifiedTableQueries:
         processor.find_matching_index = Processor.find_matching_index.__get__(processor, Processor)
         processor.query_cassandra = Processor.query_cassandra.__get__(processor, Processor)
 
-        # Mock async_execute to return test data
+        # Mock async_execute_paged to return test data (list of pages)
         mock_row = MagicMock()
         mock_row.data = {"id": "123", "name": "Test Product", "category": "electronics"}
-        mock_async_execute.return_value = [mock_row]
+        mock_async_execute_paged.return_value = [[mock_row]]
 
         schema = RowSchema(
             name="products",
@@ -370,10 +370,10 @@ class TestUnifiedTableQueries:
 
         # Verify Cassandra was connected and queried
         processor.connect_cassandra.assert_called_once()
-        mock_async_execute.assert_called_once()
+        mock_async_execute_paged.assert_called_once()
 
         # Verify query structure - should query unified rows table
-        call_args = mock_async_execute.call_args
+        call_args = mock_async_execute_paged.call_args
         query = call_args[0][1]
         params = call_args[0][2]
 
@@ -394,8 +394,8 @@ class TestUnifiedTableQueries:
         assert results[0]["category"] == "electronics"
 
     @pytest.mark.asyncio
-    @patch('trustgraph.query.rows.cassandra.service.async_execute', new_callable=AsyncMock)
-    async def test_query_without_index_match(self, mock_async_execute):
+    @patch('trustgraph.query.rows.cassandra.service.async_scan', new_callable=AsyncMock)
+    async def test_query_without_index_match(self, mock_async_scan):
         """Test query execution without matching index (scan mode)"""
         processor = MagicMock()
         processor.session = MagicMock()
@@ -406,12 +406,10 @@ class TestUnifiedTableQueries:
         processor._matches_filters = Processor._matches_filters.__get__(processor, Processor)
         processor.query_cassandra = Processor.query_cassandra.__get__(processor, Processor)
 
-        # Mock async_execute to return test data
+        # Mock async_scan to return filtered test data
         mock_row1 = MagicMock()
         mock_row1.data = {"id": "1", "name": "Product A", "price": "100"}
-        mock_row2 = MagicMock()
-        mock_row2.data = {"id": "2", "name": "Product B", "price": "200"}
-        mock_async_execute.return_value = [mock_row1, mock_row2]
+        mock_async_scan.return_value = [mock_row1]
 
         schema = RowSchema(
             name="products",
@@ -432,13 +430,16 @@ class TestUnifiedTableQueries:
             limit=10
         )
 
-        # Query should use ALLOW FILTERING for scan
-        call_args = mock_async_execute.call_args
+        # Verify async_scan was called
+        mock_async_scan.assert_called_once()
+
+        # Verify query structure
+        call_args = mock_async_scan.call_args
         query = call_args[0][1]
 
         assert "ALLOW FILTERING" in query
 
-        # Should post-filter results
+        # Should return filtered results
         assert len(results) == 1
         assert results[0]["name"] == "Product A"
 

tests/unit/test_reliability/test_null_embedding_protection.py

@@ -259,6 +259,8 @@ class TestGraphEmbeddingsNullProtection:
         proc.collection_exists = MagicMock(return_value=True)
         proc._cache_lock = asyncio.Lock()
         proc._known_collections = set()
+        proc.replication_factor = 1
+        proc.shard_number = 1
 
         msg = MagicMock()
         msg.metadata.collection = "graphs"

tests/unit/test_tables/test_knowledge_table_store.py

@@ -155,7 +155,7 @@ class TestGetTriples:
     @pytest.mark.asyncio
     @patch('trustgraph.tables.knowledge.async_execute_paged', new_callable=AsyncMock)
     async def test_row_converts_to_triples(self, mock_async_execute_paged):
-        # row[3] is a list of (s_val, s_uri, p_val, p_uri, o_val, o_uri)
+        # row[3] is a list of (s_val, s_uri, p_val, p_uri, o_val, o_uri, graph)
         fake_row = (
             None, None, None,
             [
@@ -163,6 +163,7 @@ class TestGetTriples:
                     "http://example.org/alice", True,
                     "http://example.org/knows", True,
                     "http://example.org/bob", True,
+                    "urn:graph:source",
                 ),
             ],
         )
@@ -191,3 +192,33 @@ class TestGetTriples:
         assert t.s.iri == "http://example.org/alice"
         assert t.p.iri == "http://example.org/knows"
         assert t.o.iri == "http://example.org/bob"
+        assert t.g == "urn:graph:source"
+
+    @pytest.mark.asyncio
+    @patch('trustgraph.tables.knowledge.async_execute_paged', new_callable=AsyncMock)
+    async def test_empty_graph_name_becomes_none(self, mock_async_execute_paged):
+        fake_row = (
+            None, None, None,
+            [
+                (
+                    "http://example.org/alice", True,
+                    "http://example.org/knows", True,
+                    "http://example.org/bob", True,
+                    "",
+                ),
+            ],
+        )
+
+        store = _make_store()
+        store.cassandra = Mock()
+        store.get_triples_stmt = Mock()
+        mock_async_execute_paged.return_value = [[fake_row]]
+
+        received = []
+
+        async def receiver(msg):
+            received.append(msg)
+
+        await store.get_triples("w", "d", receiver)
+
+        assert received[0].triples[0].g is None

tests/unit/test_translators/test_knowledge_translator_roundtrip.py

@@ -1,5 +1,6 @@
 """
-Round-trip unit tests for KnowledgeRequestTranslator.
+Round-trip unit tests for KnowledgeRequestTranslator and
+KnowledgeResponseTranslator.
 
 Regression coverage: a previous version of the decode side constructed
 EntityEmbeddings(vectors=...) — the schema field is `vector` (singular),
@@ -15,9 +16,13 @@ Triples breaks the test.
 
 import pytest
 
-from trustgraph.messaging.translators.knowledge import KnowledgeRequestTranslator
+from trustgraph.messaging.translators.knowledge import (
+    KnowledgeRequestTranslator,
+    KnowledgeResponseTranslator,
+)
 from trustgraph.schema import (
     KnowledgeRequest,
+    KnowledgeResponse,
     GraphEmbeddings,
     EntityEmbeddings,
     Triples,
@@ -25,6 +30,8 @@ from trustgraph.schema import (
     Metadata,
     Term,
     IRI,
+    LibraryMetadata,
+    LibraryBlob,
 )
 
 
@@ -145,3 +152,161 @@ class TestKnowledgeRequestTranslatorTriples:
         assert t.s.iri == "http://example.org/alice"
         assert t.p.iri == "http://example.org/knows"
         assert t.o.iri == "http://example.org/bob"
+
+
+class TestKnowledgeRequestTranslatorLibrary:
+
+    def test_roundtrip_preserves_library_metadata(self, translator):
+        request = KnowledgeRequest(
+            operation="put-kg-core",
+            id="doc-1",
+            library_metadata=LibraryMetadata(
+                id="doc-1",
+                kind="application/pdf",
+                title="Test Document",
+                parent_id="",
+                document_type="source",
+                comments="test comments",
+                tags=["tag1", "tag2"],
+            ),
+        )
+
+        encoded = translator.encode(request)
+        assert "library-metadata" in encoded
+        lm = encoded["library-metadata"]
+        assert lm["id"] == "doc-1"
+        assert lm["kind"] == "application/pdf"
+        assert lm["title"] == "Test Document"
+        assert lm["parent-id"] == ""
+        assert lm["document-type"] == "source"
+        assert lm["comments"] == "test comments"
+        assert lm["tags"] == ["tag1", "tag2"]
+
+        decoded = translator.decode(encoded)
+        assert decoded.library_metadata is not None
+        assert decoded.library_metadata.id == "doc-1"
+        assert decoded.library_metadata.kind == "application/pdf"
+        assert decoded.library_metadata.title == "Test Document"
+        assert decoded.library_metadata.parent_id == ""
+        assert decoded.library_metadata.document_type == "source"
+        assert decoded.library_metadata.comments == "test comments"
+        assert decoded.library_metadata.tags == ["tag1", "tag2"]
+
+    def test_roundtrip_preserves_child_document_metadata(self, translator):
+        request = KnowledgeRequest(
+            operation="put-kg-core",
+            id="doc-1",
+            library_metadata=LibraryMetadata(
+                id="chunk-1",
+                kind="text/plain",
+                title="Chunk 1",
+                parent_id="doc-1",
+                document_type="chunk",
+            ),
+        )
+
+        encoded = translator.encode(request)
+        decoded = translator.decode(encoded)
+
+        assert decoded.library_metadata.parent_id == "doc-1"
+        assert decoded.library_metadata.document_type == "chunk"
+
+    def test_roundtrip_preserves_library_blob(self, translator):
+        request = KnowledgeRequest(
+            operation="put-kg-core",
+            id="doc-1",
+            library_blob=LibraryBlob(
+                id="doc-1",
+                data=b"SGVsbG8gV29ybGQ=",
+            ),
+        )
+
+        encoded = translator.encode(request)
+        assert "library-blob" in encoded
+        assert encoded["library-blob"]["id"] == "doc-1"
+        assert encoded["library-blob"]["data"] == "SGVsbG8gV29ybGQ="
+
+        decoded = translator.decode(encoded)
+        assert decoded.library_blob is not None
+        assert decoded.library_blob.id == "doc-1"
+        assert decoded.library_blob.data == "SGVsbG8gV29ybGQ="
+
+    def test_absent_library_fields_decode_as_none(self, translator):
+        decoded = translator.decode({
+            "operation": "get-kg-core",
+            "id": "doc-1",
+        })
+        assert decoded.library_metadata is None
+        assert decoded.library_blob is None
+
+
+class TestKnowledgeResponseTranslatorLibrary:
+
+    @pytest.fixture
+    def response_translator(self):
+        return KnowledgeResponseTranslator()
+
+    def test_encode_library_metadata(self, response_translator):
+        response = KnowledgeResponse(
+            ids=None,
+            library_metadata=LibraryMetadata(
+                id="doc-1",
+                kind="application/pdf",
+                title="Test",
+                parent_id="",
+                document_type="source",
+                comments="",
+                tags=[],
+            ),
+        )
+        encoded = response_translator.encode(response)
+        assert "library-metadata" in encoded
+        assert encoded["library-metadata"]["id"] == "doc-1"
+        assert encoded["library-metadata"]["kind"] == "application/pdf"
+        assert encoded["library-metadata"]["document-type"] == "source"
+
+    def test_encode_library_blob_bytes_to_string(self, response_translator):
+        response = KnowledgeResponse(
+            ids=None,
+            library_blob=LibraryBlob(
+                id="doc-1",
+                data=b"dGVzdCBkYXRh",
+            ),
+        )
+        encoded = response_translator.encode(response)
+        assert "library-blob" in encoded
+        assert encoded["library-blob"]["id"] == "doc-1"
+        assert encoded["library-blob"]["data"] == "dGVzdCBkYXRh"
+        assert isinstance(encoded["library-blob"]["data"], str)
+
+    def test_encode_library_blob_string_passthrough(self, response_translator):
+        response = KnowledgeResponse(
+            ids=None,
+            library_blob=LibraryBlob(
+                id="doc-1",
+                data="already-a-string",
+            ),
+        )
+        encoded = response_translator.encode(response)
+        assert encoded["library-blob"]["data"] == "already-a-string"
+
+    def test_library_metadata_is_not_final(self, response_translator):
+        response = KnowledgeResponse(
+            ids=None,
+            library_metadata=LibraryMetadata(id="doc-1"),
+        )
+        _, is_final = response_translator.encode_with_completion(response)
+        assert is_final is False
+
+    def test_library_blob_is_not_final(self, response_translator):
+        response = KnowledgeResponse(
+            ids=None,
+            library_blob=LibraryBlob(id="doc-1", data=b"data"),
+        )
+        _, is_final = response_translator.encode_with_completion(response)
+        assert is_final is False
+
+    def test_eos_is_final(self, response_translator):
+        response = KnowledgeResponse(eos=True)
+        _, is_final = response_translator.encode_with_completion(response)
+        assert is_final is True

trustgraph-base/trustgraph/api/socket_client.py

@@ -502,6 +502,7 @@ class SocketClient:
 
     def put_kg_core(
         self, id: str, triples=None, graph_embeddings=None,
+        library_metadata=None, library_blob=None,
     ) -> Dict[str, Any]:
         request = {
             "operation": "put-kg-core",
@@ -512,6 +513,10 @@ class SocketClient:
             request["triples"] = triples
         if graph_embeddings is not None:
             request["graph-embeddings"] = graph_embeddings
+        if library_metadata is not None:
+            request["library-metadata"] = library_metadata
+        if library_blob is not None:
+            request["library-blob"] = library_blob
         return self._send_request_sync("knowledge", None, request)
 
     def get_de_core(self, id: str) -> Iterator[Dict[str, Any]]:

trustgraph-base/trustgraph/base/cassandra_config.py

@@ -103,35 +103,19 @@ def resolve_cassandra_config(
     host: Optional[str] = None,
     username: Optional[str] = None,
     password: Optional[str] = None,
-    default_keyspace: Optional[str] = None
+    default_keyspace: Optional[str] = None,
+    replication_factor: Optional[int] = None,
 ) -> Tuple[List[str], Optional[str], Optional[str], Optional[str], int]:
-    """
-    Resolve Cassandra configuration from various sources.
-
-    Can accept either argparse args object or explicit parameters.
-    Converts host string to list format for Cassandra driver.
-
-    Args:
-        args: Optional argparse namespace with cassandra_host, cassandra_username, cassandra_password, cassandra_keyspace, cassandra_replication_factor
-        host: Optional explicit host parameter (overrides args)
-        username: Optional explicit username parameter (overrides args)
-        password: Optional explicit password parameter (overrides args)
-        default_keyspace: Optional default keyspace if not specified elsewhere
-
-    Returns:
-        tuple: (hosts_list, username, password, keyspace, replication_factor)
-    """
-    # If args provided, extract values
     keyspace = None
-    replication_factor = 1
     if args is not None:
         host = host or getattr(args, 'cassandra_host', None)
         username = username or getattr(args, 'cassandra_username', None)
         password = password or getattr(args, 'cassandra_password', None)
         keyspace = getattr(args, 'cassandra_keyspace', None)
-        replication_factor = getattr(args, 'cassandra_replication_factor', 1)
+        replication_factor = replication_factor or getattr(
+            args, 'cassandra_replication_factor', None
+        )
 
-    # Apply defaults if still None
     defaults = get_cassandra_defaults()
     host = host or defaults['host']
     username = username or defaults['username']

trustgraph-base/trustgraph/base/qdrant_config.py

@@ -0,0 +1,87 @@
+
+import os
+import argparse
+from typing import Optional, Any, Tuple
+
+
+def get_qdrant_defaults() -> dict:
+    return {
+        'url': os.getenv('QDRANT_URL', 'http://localhost:6333'),
+        'api_key': os.getenv('QDRANT_API_KEY'),
+        'replication_factor': int(os.getenv('QDRANT_REPLICATION_FACTOR', '1')),
+        'shard_number': int(os.getenv('QDRANT_SHARD_NUMBER', '1')),
+    }
+
+
+def add_qdrant_args(parser: argparse.ArgumentParser) -> None:
+    defaults = get_qdrant_defaults()
+
+    url_help = f"Qdrant URL (default: {defaults['url']})"
+    if 'QDRANT_URL' in os.environ:
+        url_help += " [from QDRANT_URL]"
+
+    api_key_help = "Qdrant API key"
+    if defaults['api_key']:
+        api_key_help += " (default: <set>)"
+        if 'QDRANT_API_KEY' in os.environ:
+            api_key_help += " [from QDRANT_API_KEY]"
+
+    replication_help = f"Qdrant collection replication factor (default: {defaults['replication_factor']})"
+    if 'QDRANT_REPLICATION_FACTOR' in os.environ:
+        replication_help += " [from QDRANT_REPLICATION_FACTOR]"
+
+    shard_help = f"Qdrant collection shard number (default: {defaults['shard_number']})"
+    if 'QDRANT_SHARD_NUMBER' in os.environ:
+        shard_help += " [from QDRANT_SHARD_NUMBER]"
+
+    parser.add_argument(
+        '--store-uri',
+        default=defaults['url'],
+        help=url_help,
+    )
+
+    parser.add_argument(
+        '--api-key',
+        default=defaults['api_key'],
+        help=api_key_help,
+    )
+
+    parser.add_argument(
+        '--qdrant-replication-factor',
+        type=int,
+        default=defaults['replication_factor'],
+        help=replication_help,
+    )
+
+    parser.add_argument(
+        '--qdrant-shard-number',
+        type=int,
+        default=defaults['shard_number'],
+        help=shard_help,
+    )
+
+
+def resolve_qdrant_config(
+    args: Optional[Any] = None,
+    url: Optional[str] = None,
+    api_key: Optional[str] = None,
+    replication_factor: Optional[int] = None,
+    shard_number: Optional[int] = None,
+) -> Tuple[str, Optional[str], int, int]:
+    if args is not None:
+        url = url or getattr(args, 'store_uri', None)
+        api_key = api_key or getattr(args, 'api_key', None)
+        replication_factor = replication_factor or getattr(
+            args, 'qdrant_replication_factor', None
+        )
+        shard_number = shard_number or getattr(
+            args, 'qdrant_shard_number', None
+        )
+
+    defaults = get_qdrant_defaults()
+    url = url or defaults['url']
+    api_key = api_key or defaults['api_key']
+    replication_factor = replication_factor or defaults['replication_factor']
+    shard_number = shard_number or defaults['shard_number']
+
+    return url, api_key, replication_factor, shard_number

trustgraph-base/trustgraph/messaging/translators/knowledge.py

@@ -2,7 +2,8 @@ from typing import Dict, Any, Tuple, Optional
 from ...schema import (
     KnowledgeRequest, KnowledgeResponse, Triples, GraphEmbeddings,
     DocumentEmbeddings, ChunkEmbeddings,
-    Metadata, EntityEmbeddings
+    Metadata, EntityEmbeddings,
+    LibraryMetadata, LibraryBlob,
 )
 from .base import MessageTranslator
 from .primitives import ValueTranslator, SubgraphTranslator
@@ -61,6 +62,27 @@ class KnowledgeRequestTranslator(MessageTranslator):
                 ]
             )
 
+        library_metadata = None
+        if "library-metadata" in data:
+            lm = data["library-metadata"]
+            library_metadata = LibraryMetadata(
+                id=lm.get("id", ""),
+                kind=lm.get("kind", ""),
+                title=lm.get("title", ""),
+                parent_id=lm.get("parent-id", ""),
+                document_type=lm.get("document-type", ""),
+                comments=lm.get("comments", ""),
+                tags=lm.get("tags", []),
+            )
+
+        library_blob = None
+        if "library-blob" in data:
+            lb = data["library-blob"]
+            library_blob = LibraryBlob(
+                id=lb.get("id", ""),
+                data=lb.get("data", b""),
+            )
+
         return KnowledgeRequest(
             operation=data.get("operation"),
             id=data.get("id"),
@@ -69,6 +91,8 @@ class KnowledgeRequestTranslator(MessageTranslator):
             triples=triples,
             graph_embeddings=graph_embeddings,
             document_embeddings=document_embeddings,
+            library_metadata=library_metadata,
+            library_blob=library_blob,
         )
 
     def encode(self, obj: KnowledgeRequest) -> Dict[str, Any]:
@@ -125,6 +149,26 @@ class KnowledgeRequestTranslator(MessageTranslator):
                 ],
             }
 
+        if obj.library_metadata:
+            result["library-metadata"] = {
+                "id": obj.library_metadata.id,
+                "kind": obj.library_metadata.kind,
+                "title": obj.library_metadata.title,
+                "parent-id": obj.library_metadata.parent_id,
+                "document-type": obj.library_metadata.document_type,
+                "comments": obj.library_metadata.comments,
+                "tags": obj.library_metadata.tags,
+            }
+
+        if obj.library_blob:
+            data = obj.library_blob.data
+            if isinstance(data, bytes):
+                data = data.decode("utf-8")
+            result["library-blob"] = {
+                "id": obj.library_blob.id,
+                "data": data,
+            }
+
         return result
 
 
@@ -194,6 +238,32 @@ class KnowledgeResponseTranslator(MessageTranslator):
                 }
             }
 
+        # Streaming library metadata response
+        if obj.library_metadata:
+            return {
+                "library-metadata": {
+                    "id": obj.library_metadata.id,
+                    "kind": obj.library_metadata.kind,
+                    "title": obj.library_metadata.title,
+                    "parent-id": obj.library_metadata.parent_id,
+                    "document-type": obj.library_metadata.document_type,
+                    "comments": obj.library_metadata.comments,
+                    "tags": obj.library_metadata.tags,
+                }
+            }
+
+        # Streaming library blob response
+        if obj.library_blob:
+            data = obj.library_blob.data
+            if isinstance(data, bytes):
+                data = data.decode("utf-8")
+            return {
+                "library-blob": {
+                    "id": obj.library_blob.id,
+                    "data": data,
+                }
+            }
+
         # End of stream marker
         if obj.eos is True:
             return {"eos": True}
@@ -209,7 +279,9 @@ class KnowledgeResponseTranslator(MessageTranslator):
         is_final = (
             obj.ids is not None or  # List response
             obj.eos is True or      # End of stream
-            (not obj.triples and not obj.graph_embeddings and not obj.document_embeddings)  # Empty response
+            (not obj.triples and not obj.graph_embeddings
+             and not obj.document_embeddings
+             and not obj.library_metadata and not obj.library_blob)  # Empty response
         )
         
         return response, is_final

trustgraph-base/trustgraph/schema/knowledge/knowledge.py

@@ -21,6 +21,21 @@ from .embeddings import GraphEmbeddings, DocumentEmbeddings
 #   <- ()
 #   <- (error)
 
+@dataclass
+class LibraryMetadata:
+    id: str = ""
+    kind: str = ""
+    title: str = ""
+    parent_id: str = ""
+    document_type: str = ""
+    comments: str = ""
+    tags: list[str] = field(default_factory=list)
+
+@dataclass
+class LibraryBlob:
+    id: str = ""
+    data: bytes = b""
+
 @dataclass
 class KnowledgeRequest:
     # get-kg-core, delete-kg-core, list-kg-cores, put-kg-core
@@ -44,6 +59,10 @@ class KnowledgeRequest:
     # put-de-core
     document_embeddings: DocumentEmbeddings | None = None
 
+    # put-kg-core (source material)
+    library_metadata: LibraryMetadata | None = None
+    library_blob: LibraryBlob | None = None
+
 @dataclass
 class KnowledgeResponse:
     error: Error | None = None
@@ -52,6 +71,8 @@ class KnowledgeResponse:
     triples: Triples | None = None
     graph_embeddings: GraphEmbeddings | None = None
     document_embeddings: DocumentEmbeddings | None = None
+    library_metadata: LibraryMetadata | None = None
+    library_blob: LibraryBlob | None = None
 
 knowledge_request_queue = queue('knowledge', cls='request')
 knowledge_response_queue = queue('knowledge', cls='response')

trustgraph-cli/trustgraph/cli/get_kg_core.py

@@ -47,6 +47,31 @@ def write_ge(f, data):
     )
     f.write(msgpack.packb(msg, use_bin_type=True))
 
+def write_library_metadata(f, data):
+    msg = (
+        "lm",
+        {
+            "i": data["id"],
+            "k": data.get("kind", ""),
+            "t": data.get("title", ""),
+            "p": data.get("parent-id", ""),
+            "d": data.get("document-type", ""),
+            "c": data.get("comments", ""),
+            "g": data.get("tags", []),
+        }
+    )
+    f.write(msgpack.packb(msg, use_bin_type=True))
+
+def write_library_blob(f, data):
+    msg = (
+        "lb",
+        {
+            "i": data["id"],
+            "d": data.get("data", b""),
+        }
+    )
+    f.write(msgpack.packb(msg, use_bin_type=True))
+
 def fetch(url, workspace, id, output, token=None):
 
     api = Api(url=url, token=token, workspace=workspace)
@@ -55,6 +80,8 @@ def fetch(url, workspace, id, output, token=None):
     try:
         ge = 0
         t = 0
+        lm = 0
+        lb = 0
 
         with open(output, "wb") as f:
 
@@ -68,7 +95,15 @@ def fetch(url, workspace, id, output, token=None):
                     ge += 1
                     write_ge(f, response["graph-embeddings"])
 
-        print(f"Got: {t} triple, {ge} GE messages.")
+                if "library-metadata" in response:
+                    lm += 1
+                    write_library_metadata(f, response["library-metadata"])
+
+                if "library-blob" in response:
+                    lb += 1
+                    write_library_blob(f, response["library-blob"])
+
+        print(f"Got: {t} triple, {ge} GE, {lm} library metadata, {lb} library blob messages.")
 
     finally:
         socket.close()

trustgraph-cli/trustgraph/cli/load_structured_data.py

@@ -78,7 +78,7 @@ def load_structured_data(
         logger.info("Step 1: Analyzing data to discover best matching schema...")
         
         # Step 1: Auto-discover schema (reuse discover_schema logic)
-        discovered_schema = _auto_discover_schema(api_url, input_file, sample_chars, flow, logger, workspace=workspace)
+        discovered_schema = _auto_discover_schema(api_url, input_file, sample_chars, flow, logger, token=token, workspace=workspace)
         if not discovered_schema:
             logger.error("Failed to discover suitable schema automatically")
             print("❌ Could not automatically determine the best schema for your data.")
@@ -90,7 +90,7 @@ def load_structured_data(
         
         # Step 2: Auto-generate descriptor
         logger.info("Step 2: Generating descriptor configuration...")
-        auto_descriptor = _auto_generate_descriptor(api_url, input_file, discovered_schema, sample_chars, flow, logger, workspace=workspace)
+        auto_descriptor = _auto_generate_descriptor(api_url, input_file, discovered_schema, sample_chars, flow, logger, token=token, workspace=workspace)
         if not auto_descriptor:
             logger.error("Failed to generate descriptor automatically")
             print("❌ Could not automatically generate descriptor configuration.")
@@ -172,7 +172,7 @@ def load_structured_data(
         logger.info(f"Sample chars: {sample_chars} characters")
         
         # Use the helper function to discover schema (get raw response for display)
-        response = _auto_discover_schema(api_url, input_file, sample_chars, flow, logger, return_raw_response=True, workspace=workspace)
+        response = _auto_discover_schema(api_url, input_file, sample_chars, flow, logger, return_raw_response=True, token=token, workspace=workspace)
         
         if response:
             # Debug: print response type and content 
@@ -203,7 +203,7 @@ def load_structured_data(
         # If no schema specified, discover it first
         if not schema_name:
             logger.info("No schema specified, auto-discovering...")
-            schema_name = _auto_discover_schema(api_url, input_file, sample_chars, flow, logger, workspace=workspace)
+            schema_name = _auto_discover_schema(api_url, input_file, sample_chars, flow, logger, token=token, workspace=workspace)
             if not schema_name:
                 print("Error: Could not determine schema automatically.")
                 print("Please specify a schema using --schema-name or run --discover-schema first.")
@@ -213,7 +213,7 @@ def load_structured_data(
             logger.info(f"Target schema: {schema_name}")
         
         # Generate descriptor using helper function
-        descriptor = _auto_generate_descriptor(api_url, input_file, schema_name, sample_chars, flow, logger, workspace=workspace)
+        descriptor = _auto_generate_descriptor(api_url, input_file, schema_name, sample_chars, flow, logger, token=token, workspace=workspace)
         
         if descriptor:
             # Output the generated descriptor
@@ -603,7 +603,7 @@ def _send_to_trustgraph(rows, api_url, flow, batch_size=1000, token=None, worksp
 
 
 # Helper functions for auto mode
-def _auto_discover_schema(api_url, input_file, sample_chars, flow, logger, return_raw_response=False, workspace="default"):
+def _auto_discover_schema(api_url, input_file, sample_chars, flow, logger, return_raw_response=False, token=None, workspace="default"):
     """Auto-discover the best matching schema for the input data
     
     Args:
@@ -626,7 +626,7 @@ def _auto_discover_schema(api_url, input_file, sample_chars, flow, logger, retur
         # Import API modules
         from trustgraph.api import Api
         from trustgraph.api.types import ConfigKey
-        api = Api(api_url, workspace=workspace)
+        api = Api(api_url, token=token, workspace=workspace)
         config_api = api.config()
         
         # Get available schemas
@@ -707,7 +707,7 @@ def _auto_discover_schema(api_url, input_file, sample_chars, flow, logger, retur
         return None
 
 
-def _auto_generate_descriptor(api_url, input_file, schema_name, sample_chars, flow, logger, workspace="default"):
+def _auto_generate_descriptor(api_url, input_file, schema_name, sample_chars, flow, logger, token=None, workspace="default"):
     """Auto-generate descriptor configuration for the discovered schema"""
     try:
         # Read sample data
@@ -717,7 +717,7 @@ def _auto_generate_descriptor(api_url, input_file, schema_name, sample_chars, fl
         # Import API modules
         from trustgraph.api import Api
         from trustgraph.api.types import ConfigKey
-        api = Api(api_url, workspace=workspace)
+        api = Api(api_url, token=token, workspace=workspace)
         config_api = api.config()
         
         # Get schema definition

trustgraph-cli/trustgraph/cli/put_kg_core.py

@@ -40,6 +40,23 @@ def read_message(unpacked, id):
             },
             "triples": msg["t"],
         }
+    elif unpacked[0] == "lm":
+        msg = unpacked[1]
+        return "lm", {
+            "id": msg["i"],
+            "kind": msg.get("k", ""),
+            "title": msg.get("t", ""),
+            "parent-id": msg.get("p", ""),
+            "document-type": msg.get("d", ""),
+            "comments": msg.get("c", ""),
+            "tags": msg.get("g", []),
+        }
+    elif unpacked[0] == "lb":
+        msg = unpacked[1]
+        return "lb", {
+            "id": msg["i"],
+            "data": msg.get("d", b""),
+        }
     else:
         raise RuntimeError("Unpacked unexpected messsage type", unpacked[0])
 
@@ -51,6 +68,8 @@ def put(url, workspace, id, input, token=None):
     try:
         ge = 0
         t = 0
+        lm = 0
+        lb = 0
 
         with open(input, "rb") as f:
 
@@ -73,10 +92,18 @@ def put(url, workspace, id, input, token=None):
                     t += 1
                     socket.put_kg_core(id, triples=msg)
 
+                elif kind == "lm":
+                    lm += 1
+                    socket.put_kg_core(id, library_metadata=msg)
+
+                elif kind == "lb":
+                    lb += 1
+                    socket.put_kg_core(id, library_blob=msg)
+
                 else:
                     raise RuntimeError("Unexpected message kind", kind)
 
-        print(f"Put: {t} triple, {ge} GE messages.")
+        print(f"Put: {t} triple, {ge} GE, {lm} library metadata, {lb} library blob messages.")
 
     finally:
         socket.close()

trustgraph-flow/trustgraph/config/service/service.py

@@ -83,7 +83,8 @@ class Processor(AsyncProcessor):
             host=cassandra_host,
             username=cassandra_username,
             password=cassandra_password,
-            default_keyspace="config"
+            default_keyspace="config",
+            replication_factor=params.get("cassandra_replication_factor"),
         )
 
         # Store resolved configuration

trustgraph-flow/trustgraph/cores/knowledge.py

@@ -1,6 +1,7 @@
 
 from .. schema import KnowledgeResponse, Error, Triples, GraphEmbeddings
-from .. schema import DocumentEmbeddings
+from .. schema import DocumentEmbeddings, LibraryMetadata, LibraryBlob
+from .. schema import LibrarianRequest, DocumentMetadata
 from .. knowledge import hash
 from .. exceptions import RequestError
 from .. tables.knowledge import KnowledgeTableStore
@@ -18,7 +19,7 @@ class KnowledgeManager:
 
     def __init__(
             self, cassandra_host, cassandra_username, cassandra_password,
-            keyspace, flow_config, replication_factor=1,
+            keyspace, flow_config, librarian=None, replication_factor=1,
     ):
 
         self.table_store = KnowledgeTableStore(
@@ -26,6 +27,9 @@ class KnowledgeManager:
             replication_factor
         )
 
+        self.librarian = librarian
+        self._pending_library_metadata = {}
+
         self.loader_queue = asyncio.Queue(maxsize=20)
         self.background_task = None
         self.flow_config = flow_config
@@ -86,6 +90,9 @@ class KnowledgeManager:
             publish_ge,
         )
 
+        if self.librarian:
+            await self._stream_library_docs(request.id, respond)
+
         logger.debug("Knowledge core retrieval complete")
 
         await respond(
@@ -122,6 +129,12 @@ class KnowledgeManager:
                 workspace, request.graph_embeddings
             )
 
+        if request.library_metadata and self.librarian:
+            await self._put_library_metadata(request.library_metadata, workspace)
+
+        if request.library_blob and self.librarian:
+            await self._put_library_blob(request.library_blob, workspace)
+
         await respond(
             KnowledgeResponse(
                 error = None,
@@ -250,6 +263,112 @@ class KnowledgeManager:
 
         await self.loader_queue.put((request, respond, workspace))
 
+    async def _stream_library_docs(self, document_id, respond):
+
+        try:
+            root_meta = await self.librarian.fetch_document_metadata(
+                document_id
+            )
+        except Exception as e:
+            logger.warning(f"Could not fetch library metadata for {document_id}: {e}")
+            return
+
+        if root_meta is None:
+            return
+
+        await self._stream_one_doc(root_meta, respond)
+
+        try:
+            resp = await self.librarian.request(
+                LibrarianRequest(
+                    operation="list-children",
+                    document_id=document_id,
+                )
+            )
+        except Exception as e:
+            logger.warning(f"Could not list children for {document_id}: {e}")
+            return
+
+        for child_meta in resp.document_metadatas:
+            await self._stream_one_doc(child_meta, respond)
+
+    async def _stream_one_doc(self, doc_meta, respond):
+
+        lm = LibraryMetadata(
+            id=doc_meta.id,
+            kind=doc_meta.kind,
+            title=doc_meta.title,
+            parent_id=doc_meta.parent_id,
+            document_type=doc_meta.document_type,
+            comments=doc_meta.comments,
+            tags=doc_meta.tags or [],
+        )
+
+        await respond(
+            KnowledgeResponse(library_metadata=lm)
+        )
+
+        try:
+            content = await self.librarian.fetch_document_content(
+                doc_meta.id
+            )
+        except Exception as e:
+            logger.warning(f"Could not fetch content for {doc_meta.id}: {e}")
+            return
+
+        await respond(
+            KnowledgeResponse(
+                library_blob=LibraryBlob(
+                    id=doc_meta.id,
+                    data=content,
+                )
+            )
+        )
+
+    async def _put_library_metadata(self, lm, workspace):
+        self._pending_library_metadata[lm.id] = lm
+
+    async def _put_library_blob(self, lb, workspace):
+
+        lm = self._pending_library_metadata.pop(lb.id, None)
+        if lm is None:
+            logger.warning(
+                f"Received library blob for {lb.id} with no preceding metadata"
+            )
+            return
+
+        doc_meta = DocumentMetadata(
+            id=lm.id,
+            kind=lm.kind,
+            title=lm.title,
+            parent_id=lm.parent_id,
+            document_type=lm.document_type,
+            comments=lm.comments,
+            tags=lm.tags or [],
+        )
+
+        if lm.parent_id:
+            operation = "add-child-document"
+        else:
+            operation = "add-document"
+
+        try:
+            await self.librarian.request(
+                LibrarianRequest(
+                    operation=operation,
+                    document_id=lm.id,
+                    document_metadata=doc_meta,
+                    content=lb.data,
+                )
+            )
+        except RuntimeError as e:
+            if "already exists" in str(e):
+                logger.debug(f"Library document {lm.id} already exists, skipping")
+            else:
+                logger.warning(f"Could not save library document {lm.id}: {e}")
+        except Exception as e:
+            logger.warning(f"Could not save library document {lm.id}: {e}")
+
     async def core_loader(self):
 
         logger.info("Knowledge background processor running...")

trustgraph-flow/trustgraph/cores/service.py

@@ -12,6 +12,7 @@ import logging
 from .. base import WorkspaceProcessor, Consumer, Producer, Publisher, Subscriber
 from .. base import ConsumerMetrics, ProducerMetrics
 from .. base.cassandra_config import add_cassandra_args, resolve_cassandra_config
+from .. base import LibrarianClient
 
 from .. schema import KnowledgeRequest, KnowledgeResponse, Error
 from .. schema import knowledge_request_queue, knowledge_response_queue
@@ -60,7 +61,8 @@ class Processor(WorkspaceProcessor):
             host=cassandra_host,
             username=cassandra_username,
             password=cassandra_password,
-            default_keyspace="knowledge"
+            default_keyspace="knowledge",
+            replication_factor=params.get("cassandra_replication_factor"),
         )
 
         self.cassandra_host = hosts
@@ -77,12 +79,17 @@ class Processor(WorkspaceProcessor):
             }
         )
 
+        self.librarian_client = LibrarianClient(
+            id=id, backend=self.pubsub, taskgroup=self.taskgroup,
+        )
+
         self.knowledge = KnowledgeManager(
             cassandra_host = self.cassandra_host,
             cassandra_username = self.cassandra_username,
             cassandra_password = self.cassandra_password,
             keyspace = keyspace,
             flow_config = self,
+            librarian = self.librarian_client,
             replication_factor = replication_factor,
         )
 
@@ -156,6 +163,7 @@ class Processor(WorkspaceProcessor):
     async def start(self):
 
         await super(Processor, self).start()
+        await self.librarian_client.start()
 
     async def on_knowledge_config(self, workspace, config, version):
 

trustgraph-flow/trustgraph/decoding/pdf/pdf_decoder.py

@@ -32,6 +32,10 @@ logger = logging.getLogger(__name__)
 default_ident = "document-decoder"
 
 
+def _looks_like_pdf(content):
+    return content.lstrip().startswith(b"%PDF-")
+
+
 class Processor(FlowProcessor):
 
     def __init__(self, **params):
@@ -94,33 +98,37 @@ class Processor(FlowProcessor):
                 )
                 return
 
-        with tempfile.NamedTemporaryFile(delete_on_close=False, suffix='.pdf') as fp:
+        # Check if we should fetch from librarian or use inline data
+        if v.document_id:
+            # Fetch from librarian via Pulsar
+            logger.info(f"Fetching document {v.document_id} from librarian...")
+
+            content = await flow.librarian.fetch_document_content(
+                document_id=v.document_id,
+
+            )
+
+            # Content is base64 encoded
+            if isinstance(content, str):
+                content = content.encode('utf-8')
+            decoded_content = base64.b64decode(content)
+
+            logger.info(f"Fetched {len(decoded_content)} bytes from librarian")
+        else:
+            # Use inline data (backward compatibility)
+            decoded_content = base64.b64decode(v.data)
+
+        if not _looks_like_pdf(decoded_content):
+            logger.error(
+                f"Document {v.metadata.id} is not valid PDF content. "
+                f"Ignoring document."
+            )
+            return
+
+        with tempfile.NamedTemporaryFile(delete=False, suffix='.pdf') as fp:
             temp_path = fp.name
-
-            # Check if we should fetch from librarian or use inline data
-            if v.document_id:
-                # Fetch from librarian via Pulsar
-                logger.info(f"Fetching document {v.document_id} from librarian...")
-                fp.close()
-
-                content = await flow.librarian.fetch_document_content(
-                    document_id=v.document_id,
-    
-                )
-
-                # Content is base64 encoded
-                if isinstance(content, str):
-                    content = content.encode('utf-8')
-                decoded_content = base64.b64decode(content)
-
-                with open(temp_path, 'wb') as f:
-                    f.write(decoded_content)
-
-                logger.info(f"Fetched {len(decoded_content)} bytes from librarian")
-            else:
-                # Use inline data (backward compatibility)
-                fp.write(base64.b64decode(v.data))
-                fp.close()
+            fp.write(decoded_content)
+            fp.close()
 
             global PyPDFLoader
             if PyPDFLoader is None:

trustgraph-flow/trustgraph/direct/cassandra_kg.py

@@ -6,7 +6,7 @@ import logging
 from cassandra.cluster import Cluster
 from cassandra.auth import PlainTextAuthProvider
 from cassandra.query import BatchStatement, SimpleStatement
-from ssl import SSLContext, PROTOCOL_TLSv1_2
+import ssl
 
 from ..tables.cassandra_async import async_execute
 
@@ -41,13 +41,15 @@ class KnowledgeGraph:
 
     def __init__(
             self, hosts=None,
-            keyspace="trustgraph", username=None, password=None
+            keyspace="trustgraph", username=None, password=None,
+            replication_factor=1,
     ):
 
         if hosts is None:
             hosts = ["localhost"]
 
         self.keyspace = keyspace
+        self.replication_factor = replication_factor
         self.username = username
 
         # 7-table schema for quads with full query pattern support
@@ -68,7 +70,7 @@ class KnowledgeGraph:
         self.collection_metadata_table = "collection_metadata"
 
         if username and password:
-            ssl_context = SSLContext(PROTOCOL_TLSv1_2)
+            ssl_context = ssl.create_default_context()
             auth_provider = PlainTextAuthProvider(username=username, password=password)
             self.cluster = Cluster(hosts, auth_provider=auth_provider, ssl_context=ssl_context)
         else:
@@ -92,7 +94,7 @@ class KnowledgeGraph:
             create keyspace if not exists {self.keyspace}
                 with replication = {{
                    'class' : 'SimpleStrategy',
-                   'replication_factor' : 1
+                   'replication_factor' : {self.replication_factor}
                 }};
         """)
 
@@ -539,13 +541,15 @@ class EntityCentricKnowledgeGraph:
 
     def __init__(
             self, hosts=None,
-            keyspace="trustgraph", username=None, password=None
+            keyspace="trustgraph", username=None, password=None,
+            replication_factor=1,
     ):
 
         if hosts is None:
             hosts = ["localhost"]
 
         self.keyspace = keyspace
+        self.replication_factor = replication_factor
         self.username = username
 
         # 2-table entity-centric schema
@@ -556,7 +560,7 @@ class EntityCentricKnowledgeGraph:
         self.collection_metadata_table = "collection_metadata"
 
         if username and password:
-            ssl_context = SSLContext(PROTOCOL_TLSv1_2)
+            ssl_context = ssl.create_default_context()
             auth_provider = PlainTextAuthProvider(username=username, password=password)
             self.cluster = Cluster(hosts, auth_provider=auth_provider, ssl_context=ssl_context)
         else:
@@ -580,7 +584,7 @@ class EntityCentricKnowledgeGraph:
             create keyspace if not exists {self.keyspace}
                 with replication = {{
                    'class' : 'SimpleStrategy',
-                   'replication_factor' : 1
+                   'replication_factor' : {self.replication_factor}
                 }};
         """)
 

trustgraph-flow/trustgraph/gateway/dispatch/core_export.py

@@ -73,6 +73,39 @@ class CoreExport:
                     enc = msgpack.packb(msg)
                     await response.write(enc)
 
+                if "library-metadata" in resp:
+
+                    data = resp["library-metadata"]
+                    msg = (
+                        "lm",
+                        {
+                            "i": data["id"],
+                            "k": data.get("kind", ""),
+                            "t": data.get("title", ""),
+                            "p": data.get("parent-id", ""),
+                            "d": data.get("document-type", ""),
+                            "c": data.get("comments", ""),
+                            "g": data.get("tags", []),
+                        }
+                    )
+
+                    enc = msgpack.packb(msg)
+                    await response.write(enc)
+
+                if "library-blob" in resp:
+
+                    data = resp["library-blob"]
+                    msg = (
+                        "lb",
+                        {
+                            "i": data["id"],
+                            "d": data.get("data", b""),
+                        }
+                    )
+
+                    enc = msgpack.packb(msg, use_bin_type=True)
+                    await response.write(enc)
+
             await kr.process(
                 {
                     "operation": "get-kg-core",

trustgraph-flow/trustgraph/gateway/dispatch/core_import.py

@@ -79,6 +79,39 @@ class CoreImport:
 
                         await kr.process(msg)
 
+                    elif unpacked[0] == "lm":
+                        msg = unpacked[1]
+                        msg = {
+                            "operation": "put-kg-core",
+                            "workspace": workspace,
+                            "id": id,
+                            "library-metadata": {
+                                "id": msg["i"],
+                                "kind": msg.get("k", ""),
+                                "title": msg.get("t", ""),
+                                "parent-id": msg.get("p", ""),
+                                "document-type": msg.get("d", ""),
+                                "comments": msg.get("c", ""),
+                                "tags": msg.get("g", []),
+                            }
+                        }
+
+                        await kr.process(msg)
+
+                    elif unpacked[0] == "lb":
+                        msg = unpacked[1]
+                        msg = {
+                            "operation": "put-kg-core",
+                            "workspace": workspace,
+                            "id": id,
+                            "library-blob": {
+                                "id": msg["i"],
+                                "data": msg.get("d", b""),
+                            }
+                        }
+
+                        await kr.process(msg)
+
         except Exception as e:
             logger.error(f"Core import exception: {e}", exc_info=True)
             await error(str(e))

trustgraph-flow/trustgraph/gateway/dispatch/mux.py

@@ -4,6 +4,8 @@ import queue
 import uuid
 import logging
 
+from ..capabilities import PUBLIC, AUTHENTICATED
+
 # Module logger
 logger = logging.getLogger(__name__)
 
@@ -156,37 +158,41 @@ class Mux:
                 })
                 return
 
-            # Resolve workspace first (default-fill from the caller's
-            # bound workspace), then ask the regime to authorise the
-            # service-level capability against the matched
-            # operation's resource shape.
+            # Resolve workspace (default-fill from the caller's
+            # bound workspace).  Workspace resolution applies to all
+            # operations regardless of capability level.
             try:
                 await enforce_workspace(data, self.identity, self.auth)
                 if isinstance(inner, dict):
                     await enforce_workspace(inner, self.identity, self.auth)
 
-                if data.get("flow"):
-                    resource = {
-                        "workspace": data.get("workspace", ""),
-                        "flow": data.get("flow", ""),
-                    }
-                    parameters = {}
-                else:
-                    # Build a minimal RequestContext so the matched
-                    # operation's own extractors decide resource and
-                    # parameters — same path the HTTP endpoints take.
-                    from ..registry import RequestContext
-                    ctx = RequestContext(
-                        body=inner if isinstance(inner, dict) else {},
-                        match_info={},
-                        identity=self.identity,
-                    )
-                    resource = op.extract_resource(ctx)
-                    parameters = op.extract_parameters(ctx)
+                # Authorisation: capability sentinels short-circuit
+                # the regime call; capability strings go through
+                # authorise().
+                if op.capability not in (PUBLIC, AUTHENTICATED):
+                    if data.get("flow"):
+                        resource = {
+                            "workspace": data.get("workspace", ""),
+                            "flow": data.get("flow", ""),
+                        }
+                        parameters = {}
+                    else:
+                        # Build a minimal RequestContext so the matched
+                        # operation's own extractors decide resource
+                        # and parameters — same path the HTTP
+                        # endpoints take.
+                        from ..registry import RequestContext
+                        ctx = RequestContext(
+                            body=inner if isinstance(inner, dict) else {},
+                            match_info={},
+                            identity=self.identity,
+                        )
+                        resource = op.extract_resource(ctx)
+                        parameters = op.extract_parameters(ctx)
 
-                await self.auth.authorise(
-                    self.identity, op.capability, resource, parameters,
-                )
+                    await self.auth.authorise(
+                        self.identity, op.capability, resource, parameters,
+                    )
             except _web.HTTPNotFound:
                 await self.ws.send_json({
                     "id": request_id,

trustgraph-flow/trustgraph/iam/service/service.py

@@ -101,6 +101,7 @@ class Processor(AsyncProcessor):
             username=cassandra_username,
             password=cassandra_password,
             default_keyspace="iam",
+            replication_factor=params.get("cassandra_replication_factor"),
         )
 
         self.cassandra_host = hosts

trustgraph-flow/trustgraph/librarian/service.py

@@ -8,6 +8,7 @@ import asyncio
 import base64
 import json
 import logging
+import os
 from datetime import datetime
 
 from .. base import WorkspaceProcessor, Consumer, Producer, Publisher, Subscriber
@@ -54,6 +55,16 @@ default_object_store_access_key = "object-user"
 default_object_store_secret_key = "object-password"
 default_object_store_use_ssl = False
 default_object_store_region = None
+
+# Environment variables consulted as a fallback when the
+# corresponding params field is not set in the processor-group YAML
+# or via CLI.  Intended for K8s Secret / env-var injection so
+# credentials never have to live in the YAML (and thus in git).
+ENV_OBJECT_STORE_ENDPOINT = "OBJECT_STORE_ENDPOINT"
+ENV_OBJECT_STORE_ACCESS_KEY = "OBJECT_STORE_ACCESS_KEY"
+ENV_OBJECT_STORE_SECRET_KEY = "OBJECT_STORE_SECRET_KEY"
+ENV_OBJECT_STORE_USE_SSL = "OBJECT_STORE_USE_SSL"
+ENV_OBJECT_STORE_REGION = "OBJECT_STORE_REGION"
 default_cassandra_host = "cassandra"
 default_min_chunk_size = 1  # No minimum by default (for Garage)
 
@@ -89,22 +100,36 @@ class Processor(WorkspaceProcessor):
             "config_response_queue", default_config_response_queue
         )
 
-        object_store_endpoint = params.get("object_store_endpoint", default_object_store_endpoint)
-        object_store_access_key = params.get(
-            "object_store_access_key",
-            default_object_store_access_key
+        # Resolve object-store config.  Precedence: explicit params
+        # (CLI / processor-group YAML) → environment variable →
+        # hardcoded default.  The env-var path lets K8s Secrets feed
+        # credentials without them appearing in the YAML.
+        object_store_endpoint = (
+            params.get("object_store_endpoint")
+            or os.environ.get(ENV_OBJECT_STORE_ENDPOINT)
+            or default_object_store_endpoint
         )
-        object_store_secret_key = params.get(
-            "object_store_secret_key",
-            default_object_store_secret_key
+        object_store_access_key = (
+            params.get("object_store_access_key")
+            or os.environ.get(ENV_OBJECT_STORE_ACCESS_KEY)
+            or default_object_store_access_key
         )
-        object_store_use_ssl = params.get(
-            "object_store_use_ssl",
-            default_object_store_use_ssl
+        object_store_secret_key = (
+            params.get("object_store_secret_key")
+            or os.environ.get(ENV_OBJECT_STORE_SECRET_KEY)
+            or default_object_store_secret_key
         )
-        object_store_region = params.get(
-            "object_store_region",
-            default_object_store_region
+        object_store_use_ssl = params.get("object_store_use_ssl")
+        if object_store_use_ssl is None:
+            env_ssl = os.environ.get(ENV_OBJECT_STORE_USE_SSL)
+            if env_ssl is not None:
+                object_store_use_ssl = env_ssl.lower() in ("true", "1", "yes")
+            else:
+                object_store_use_ssl = default_object_store_use_ssl
+        object_store_region = (
+            params.get("object_store_region")
+            or os.environ.get(ENV_OBJECT_STORE_REGION)
+            or default_object_store_region
         )
 
         min_chunk_size = params.get(
@@ -121,7 +146,8 @@ class Processor(WorkspaceProcessor):
             host=cassandra_host,
             username=cassandra_username,
             password=cassandra_password,
-            default_keyspace="librarian"
+            default_keyspace="librarian",
+            replication_factor=params.get("cassandra_replication_factor"),
         )
 
         # Store resolved configuration

trustgraph-flow/trustgraph/query/doc_embeddings/qdrant/service.py

@@ -12,31 +12,33 @@ from qdrant_client import QdrantClient
 from .... schema import DocumentEmbeddingsResponse, ChunkMatch
 from .... schema import Error
 from .... base import DocumentEmbeddingsQueryService
+from .... base.qdrant_config import add_qdrant_args, resolve_qdrant_config
 
 # Module logger
 logger = logging.getLogger(__name__)
 
 default_ident = "doc-embeddings-query"
 
-default_store_uri = 'http://localhost:6333'
-
 class Processor(DocumentEmbeddingsQueryService):
 
     def __init__(self, **params):
 
-        store_uri = params.get("store_uri", default_store_uri)
+        store_uri = params.get("store_uri")
+        api_key = params.get("api_key")
 
-        #optional api key
-        api_key = params.get("api_key", None)
+        url, api_key, _, _ = resolve_qdrant_config(
+            url=store_uri,
+            api_key=api_key,
+        )
 
         super(Processor, self).__init__(
             **params | {
-                "store_uri": store_uri,
+                "store_uri": url,
                 "api_key": api_key,
             }
         )
 
-        self.qdrant = QdrantClient(url=store_uri, api_key=api_key)
+        self.qdrant = QdrantClient(url=url, api_key=api_key)
 
     async def query_document_embeddings(self, workspace, msg):
 
@@ -85,18 +87,7 @@ class Processor(DocumentEmbeddingsQueryService):
     def add_args(parser):
 
         DocumentEmbeddingsQueryService.add_args(parser)
-
-        parser.add_argument(
-            '-t', '--store-uri',
-            default=default_store_uri,
-            help=f'Qdrant store URI (default: {default_store_uri})'
-        )
-        
-        parser.add_argument(
-            '-k', '--api-key',
-            default=None,
-            help=f'API key for qdrant (default: None)'
-        )
+        add_qdrant_args(parser)
 
 def run():
 

trustgraph-flow/trustgraph/query/graph_embeddings/qdrant/service.py

@@ -12,31 +12,32 @@ from qdrant_client import QdrantClient
 from .... schema import GraphEmbeddingsResponse, EntityMatch
 from .... schema import Error, Term, IRI, LITERAL
 from .... base import GraphEmbeddingsQueryService
+from .... base.qdrant_config import add_qdrant_args, resolve_qdrant_config
 
 # Module logger
 logger = logging.getLogger(__name__)
 
 default_ident = "graph-embeddings-query"
 
-default_store_uri = 'http://localhost:6333'
-
 class Processor(GraphEmbeddingsQueryService):
 
     def __init__(self, **params):
 
-        store_uri = params.get("store_uri", default_store_uri)
+        store_uri = params.get("store_uri")
+        api_key = params.get("api_key")
 
-        #optional api key
-        api_key = params.get("api_key", None)
+        url, api_key, _, _ = resolve_qdrant_config(
+            url=store_uri, api_key=api_key,
+        )
 
         super(Processor, self).__init__(
             **params | {
-                "store_uri": store_uri,
+                "store_uri": url,
                 "api_key": api_key,
             }
         )
 
-        self.qdrant = QdrantClient(url=store_uri, api_key=api_key)
+        self.qdrant = QdrantClient(url=url, api_key=api_key)
 
     def create_value(self, ent):
         if ent.startswith("http://") or ent.startswith("https://"):
@@ -104,18 +105,7 @@ class Processor(GraphEmbeddingsQueryService):
     def add_args(parser):
 
         GraphEmbeddingsQueryService.add_args(parser)
-
-        parser.add_argument(
-            '-t', '--store-uri',
-            default=default_store_uri,
-            help=f'Qdrant store URI (default: {default_store_uri})'
-        )
-        
-        parser.add_argument(
-            '-k', '--api-key',
-            default=None,
-            help=f'API key for qdrant (default: None)'
-        )
+        add_qdrant_args(parser)
 
 def run():
 

trustgraph-flow/trustgraph/query/ontology/sparql_cassandra.py

@@ -116,7 +116,7 @@ class CassandraTripleStore(Store if RDFLIB_AVAILABLE else object):
         # Create keyspace
         self.session.execute(f"""
             CREATE KEYSPACE IF NOT EXISTS {self.keyspace}
-            WITH replication = {{'class': 'SimpleStrategy', 'replication_factor': 1}}
+            WITH replication = {{'class': 'SimpleStrategy', 'replication_factor': {self.cassandra_config.get('replication_factor', 1)}}}
         """)
 
         # Create triples table optimized for SPARQL queries

trustgraph-flow/trustgraph/query/row_embeddings/qdrant/service.py

@@ -19,12 +19,12 @@ from .... schema import (
     RowIndexMatch, Error
 )
 from .... base import FlowProcessor, ConsumerSpec, ProducerSpec
+from .... base.qdrant_config import add_qdrant_args, resolve_qdrant_config
 
 # Module logger
 logger = logging.getLogger(__name__)
 
 default_ident = "row-embeddings-query"
-default_store_uri = 'http://localhost:6333'
 default_concurrency = 10
 
 
@@ -35,13 +35,17 @@ class Processor(FlowProcessor):
         id = params.get("id", default_ident)
         concurrency = params.get("concurrency", default_concurrency)
 
-        store_uri = params.get("store_uri", default_store_uri)
-        api_key = params.get("api_key", None)
+        store_uri = params.get("store_uri")
+        api_key = params.get("api_key")
+
+        url, api_key, _, _ = resolve_qdrant_config(
+            url=store_uri, api_key=api_key,
+        )
 
         super(Processor, self).__init__(
             **params | {
                 "id": id,
-                "store_uri": store_uri,
+                "store_uri": url,
                 "api_key": api_key,
             }
         )
@@ -62,7 +66,7 @@ class Processor(FlowProcessor):
             )
         )
 
-        self.qdrant = QdrantClient(url=store_uri, api_key=api_key)
+        self.qdrant = QdrantClient(url=url, api_key=api_key)
 
     def sanitize_name(self, name: str) -> str:
         """Sanitize names for Qdrant collection naming"""
@@ -192,21 +196,9 @@ class Processor(FlowProcessor):
 
     @staticmethod
     def add_args(parser):
-        """Add command-line arguments"""
 
         FlowProcessor.add_args(parser)
-
-        parser.add_argument(
-            '-t', '--store-uri',
-            default=default_store_uri,
-            help=f'Qdrant store URI (default: {default_store_uri})'
-        )
-
-        parser.add_argument(
-            '-k', '--api-key',
-            default=None,
-            help='API key for Qdrant (default: None)'
-        )
+        add_qdrant_args(parser)
 
         parser.add_argument(
             '-c', '--concurrency',

trustgraph-flow/trustgraph/query/rows/cassandra/service.py

@@ -24,7 +24,7 @@ from .... schema import RowsQueryRequest, RowsQueryResponse, GraphQLError
 from .... schema import Error, RowSchema, Field as SchemaField
 from .... base import FlowProcessor, ConsumerSpec, ProducerSpec
 from .... base.cassandra_config import add_cassandra_args, resolve_cassandra_config
-from .... tables.cassandra_async import async_execute
+from .... tables.cassandra_async import async_execute, async_execute_paged, async_scan
 
 from ... graphql import GraphQLSchemaBuilder, SortDirection
 
@@ -180,7 +180,7 @@ class Processor(FlowProcessor):
                         description=field_def.get("description", ""),
                         required=field_def.get("required", False),
                         enum_values=field_def.get("enum", []),
-                        indexed=field_def.get("indexed", False)
+                        indexed=field_def.get("indexed", False),
                     )
                     fields.append(field)
 
@@ -232,6 +232,8 @@ class Processor(FlowProcessor):
         for index_name in index_names:
             if index_name in filters:
                 value = filters[index_name]
+                if value == "" or value is None:
+                    continue
                 # Single field index -> single element list
                 index_value = [str(value)]
                 return (index_name, index_value)
@@ -282,11 +284,13 @@ class Processor(FlowProcessor):
                 query += f" LIMIT {limit}"
 
             try:
-                rows = await async_execute(self.session, query, params)
-                for row in rows:
-                    # Convert data map to dict with proper field names
-                    row_dict = dict(row.data) if row.data else {}
-                    results.append(row_dict)
+                pages = await async_execute_paged(
+                    self.session, query, params
+                )
+                for page in pages:
+                    for row in page:
+                        row_dict = dict(row.data) if row.data else {}
+                        results.append(row_dict)
             except Exception as e:
                 logger.error(f"Failed to query rows: {e}", exc_info=True)
                 raise
@@ -308,8 +312,6 @@ class Processor(FlowProcessor):
             # Query using the first index (arbitrary choice for scan)
             primary_index = index_names[0]
 
-            # We need to scan all values for this index
-            # This requires ALLOW FILTERING or a different approach
             query = f"""
             SELECT data, source FROM {safe_keyspace}.rows
             WHERE collection = %s
@@ -320,17 +322,18 @@ class Processor(FlowProcessor):
             params = [collection, schema_name, primary_index]
 
             try:
-                rows = await async_execute(self.session, query, params)
-
-                for row in rows:
+                def row_filter(row):
                     row_dict = dict(row.data) if row.data else {}
+                    return self._matches_filters(row_dict, filters, row_schema)
 
-                    # Apply post-filters
-                    if self._matches_filters(row_dict, filters, row_schema):
-                        results.append(row_dict)
-
-                        if limit and len(results) >= limit:
-                            break
+                matched_rows = await async_scan(
+                    self.session, query, params,
+                    row_filter=row_filter,
+                    limit=limit,
+                )
+                for row in matched_rows:
+                    row_dict = dict(row.data) if row.data else {}
+                    results.append(row_dict)
 
             except Exception as e:
                 logger.error(f"Failed to scan rows: {e}", exc_info=True)
@@ -363,7 +366,7 @@ class Processor(FlowProcessor):
             # Parse filter key for operator
             if '_' in filter_key:
                 parts = filter_key.rsplit('_', 1)
-                if parts[1] in ['gt', 'gte', 'lt', 'lte', 'contains', 'in']:
+                if parts[1] in ['gt', 'gte', 'lt', 'lte', 'contains', 'in', 'not', 'startsWith', 'endsWith', 'not_in']:
                     field_name = parts[0]
                     operator = parts[1]
                 else:
@@ -400,6 +403,18 @@ class Processor(FlowProcessor):
                 elif operator == 'in':
                     if str(row_value) not in [str(v) for v in filter_value]:
                         return False
+                elif operator == 'not':
+                    if str(row_value) == str(filter_value):
+                        return False
+                elif operator == 'startsWith':
+                    if not str(row_value).startswith(str(filter_value)):
+                        return False
+                elif operator == 'endsWith':
+                    if not str(row_value).endswith(str(filter_value)):
+                        return False
+                elif operator == 'not_in':
+                    if str(row_value) in [str(v) for v in filter_value]:
+                        return False
             except (ValueError, TypeError):
                 return False
 

trustgraph-flow/trustgraph/storage/doc_embeddings/qdrant/write.py

@@ -14,29 +14,36 @@ from qdrant_client.models import Distance, VectorParams
 from .... base import DocumentEmbeddingsStoreService, CollectionConfigHandler
 from .... base import AsyncProcessor, Consumer, Producer
 from .... base import ConsumerMetrics, ProducerMetrics
+from .... base.qdrant_config import add_qdrant_args, resolve_qdrant_config
 
 # Module logger
 logger = logging.getLogger(__name__)
 
 default_ident = "doc-embeddings-write"
 
-default_store_uri = 'http://localhost:6333'
-
 class Processor(CollectionConfigHandler, DocumentEmbeddingsStoreService):
 
     def __init__(self, **params):
 
-        store_uri = params.get("store_uri", default_store_uri)
-        api_key = params.get("api_key", None)
+        store_uri = params.get("store_uri")
+        api_key = params.get("api_key")
+
+        url, api_key, replication_factor, shard_number = resolve_qdrant_config(
+            url=store_uri, api_key=api_key,
+            replication_factor=params.get("qdrant_replication_factor"),
+            shard_number=params.get("qdrant_shard_number"),
+        )
 
         super(Processor, self).__init__(
             **params | {
-                "store_uri": store_uri,
+                "store_uri": url,
                 "api_key": api_key,
             }
         )
 
-        self.qdrant = QdrantClient(url=store_uri, api_key=api_key)
+        self.qdrant = QdrantClient(url=url, api_key=api_key)
+        self.replication_factor = replication_factor
+        self.shard_number = shard_number
         self._cache_lock = asyncio.Lock()
         self._known_collections: set[str] = set()
 
@@ -61,6 +68,8 @@ class Processor(CollectionConfigHandler, DocumentEmbeddingsStoreService):
                     vectors_config=VectorParams(
                         size=dim, distance=Distance.COSINE
                     ),
+                    replication_factor=self.replication_factor,
+                    shard_number=self.shard_number,
                 )
             self._known_collections.add(collection_name)
 
@@ -109,18 +118,7 @@ class Processor(CollectionConfigHandler, DocumentEmbeddingsStoreService):
     def add_args(parser):
 
         DocumentEmbeddingsStoreService.add_args(parser)
-
-        parser.add_argument(
-            '-t', '--store-uri',
-            default=default_store_uri,
-            help=f'Qdrant URI (default: {default_store_uri})'
-        )
-        
-        parser.add_argument(
-            '-k', '--api-key',
-            default=None,
-            help=f'Qdrant API key (default: None)'
-        )
+        add_qdrant_args(parser)
 
     async def create_collection(self, workspace: str, collection: str, metadata: dict):
         """

trustgraph-flow/trustgraph/storage/graph_embeddings/qdrant/write.py

@@ -14,6 +14,7 @@ from qdrant_client.models import Distance, VectorParams
 from .... base import GraphEmbeddingsStoreService, CollectionConfigHandler
 from .... base import AsyncProcessor, Consumer, Producer
 from .... base import ConsumerMetrics, ProducerMetrics
+from .... base.qdrant_config import add_qdrant_args, resolve_qdrant_config
 from .... schema import IRI, LITERAL
 
 # Module logger
@@ -29,29 +30,34 @@ def get_term_value(term):
     elif term.type == LITERAL:
         return term.value
     else:
-        # For blank nodes or other types, use id or value
         return term.id or term.value
 
 
 default_ident = "graph-embeddings-write"
 
-default_store_uri = 'http://localhost:6333'
-
 class Processor(CollectionConfigHandler, GraphEmbeddingsStoreService):
 
     def __init__(self, **params):
 
-        store_uri = params.get("store_uri", default_store_uri)
-        api_key = params.get("api_key", None)
+        store_uri = params.get("store_uri")
+        api_key = params.get("api_key")
+
+        url, api_key, replication_factor, shard_number = resolve_qdrant_config(
+            url=store_uri, api_key=api_key,
+            replication_factor=params.get("qdrant_replication_factor"),
+            shard_number=params.get("qdrant_shard_number"),
+        )
 
         super(Processor, self).__init__(
             **params | {
-                "store_uri": store_uri,
+                "store_uri": url,
                 "api_key": api_key,
             }
         )
 
-        self.qdrant = QdrantClient(url=store_uri, api_key=api_key)
+        self.qdrant = QdrantClient(url=url, api_key=api_key)
+        self.replication_factor = replication_factor
+        self.shard_number = shard_number
         self._cache_lock = asyncio.Lock()
         self._known_collections: set[str] = set()
 
@@ -76,6 +82,8 @@ class Processor(CollectionConfigHandler, GraphEmbeddingsStoreService):
                     vectors_config=VectorParams(
                         size=dim, distance=Distance.COSINE
                     ),
+                    replication_factor=self.replication_factor,
+                    shard_number=self.shard_number,
                 )
             self._known_collections.add(collection_name)
 
@@ -128,18 +136,7 @@ class Processor(CollectionConfigHandler, GraphEmbeddingsStoreService):
     def add_args(parser):
 
         GraphEmbeddingsStoreService.add_args(parser)
-
-        parser.add_argument(
-            '-t', '--store-uri',
-            default=default_store_uri,
-            help=f'Qdrant store URI (default: {default_store_uri})'
-        )
-        
-        parser.add_argument(
-            '-k', '--api-key',
-            default=None,
-            help=f'Qdrant API key'
-        )
+        add_qdrant_args(parser)
 
     async def create_collection(self, workspace: str, collection: str, metadata: dict):
         """

trustgraph-flow/trustgraph/storage/knowledge/store.py

@@ -27,7 +27,8 @@ class Processor(FlowProcessor):
             host=params.get("cassandra_host"),
             username=params.get("cassandra_username"),
             password=params.get("cassandra_password"),
-            default_keyspace='knowledge'
+            default_keyspace='knowledge',
+            replication_factor=params.get("cassandra_replication_factor"),
         )
 
         super(Processor, self).__init__(

trustgraph-flow/trustgraph/storage/row_embeddings/qdrant/write.py

@@ -27,12 +27,12 @@ from qdrant_client.models import PointStruct, Distance, VectorParams
 from .... schema import RowEmbeddings
 from .... base import FlowProcessor, ConsumerSpec
 from .... base import CollectionConfigHandler
+from .... base.qdrant_config import add_qdrant_args, resolve_qdrant_config
 
 # Module logger
 logger = logging.getLogger(__name__)
 
 default_ident = "row-embeddings-write"
-default_store_uri = 'http://localhost:6333'
 
 
 class Processor(CollectionConfigHandler, FlowProcessor):
@@ -41,13 +41,19 @@ class Processor(CollectionConfigHandler, FlowProcessor):
 
         id = params.get("id", default_ident)
 
-        store_uri = params.get("store_uri", default_store_uri)
-        api_key = params.get("api_key", None)
+        store_uri = params.get("store_uri")
+        api_key = params.get("api_key")
+
+        url, api_key, replication_factor, shard_number = resolve_qdrant_config(
+            url=store_uri, api_key=api_key,
+            replication_factor=params.get("qdrant_replication_factor"),
+            shard_number=params.get("qdrant_shard_number"),
+        )
 
         super(Processor, self).__init__(
             **params | {
                 "id": id,
-                "store_uri": store_uri,
+                "store_uri": url,
                 "api_key": api_key,
             }
         )
@@ -63,7 +69,9 @@ class Processor(CollectionConfigHandler, FlowProcessor):
         # Register config handler for collection management
         self.register_config_handler(self.on_collection_config, types=["collection"])
 
-        self.qdrant = QdrantClient(url=store_uri, api_key=api_key)
+        self.qdrant = QdrantClient(url=url, api_key=api_key)
+        self.replication_factor = replication_factor
+        self.shard_number = shard_number
         self._cache_lock = asyncio.Lock()
         self._known_collections: set[str] = set()
 
@@ -103,6 +111,8 @@ class Processor(CollectionConfigHandler, FlowProcessor):
                         size=dimension,
                         distance=Distance.COSINE
                     ),
+                    replication_factor=self.replication_factor,
+                    shard_number=self.shard_number,
                 )
             self._known_collections.add(collection_name)
 
@@ -249,21 +259,9 @@ class Processor(CollectionConfigHandler, FlowProcessor):
 
     @staticmethod
     def add_args(parser):
-        """Add command-line arguments"""
 
         FlowProcessor.add_args(parser)
-
-        parser.add_argument(
-            '-t', '--store-uri',
-            default=default_store_uri,
-            help=f'Qdrant URI (default: {default_store_uri})'
-        )
-
-        parser.add_argument(
-            '-k', '--api-key',
-            default=None,
-            help='Qdrant API key (default: None)'
-        )
+        add_qdrant_args(parser)
 
 
 def run():

trustgraph-flow/trustgraph/storage/rows/cassandra/write.py

@@ -47,16 +47,18 @@ class Processor(CollectionConfigHandler, FlowProcessor):
         cassandra_password = params.get("cassandra_password")
 
         # Resolve configuration with environment variable fallback
-        hosts, username, password, keyspace, _ = resolve_cassandra_config(
+        hosts, username, password, keyspace, replication_factor = resolve_cassandra_config(
             host=cassandra_host,
             username=cassandra_username,
-            password=cassandra_password
+            password=cassandra_password,
+            replication_factor=params.get("cassandra_replication_factor"),
         )
 
         # Store resolved configuration with proper names
         self.cassandra_host = hosts  # Store as list
         self.cassandra_username = username
         self.cassandra_password = password
+        self.replication_factor = replication_factor
 
         # Config key for schemas
         self.config_key = params.get("config_type", "schema")
@@ -170,7 +172,7 @@ class Processor(CollectionConfigHandler, FlowProcessor):
                         description=field_def.get("description", ""),
                         required=field_def.get("required", False),
                         enum_values=field_def.get("enum", []),
-                        indexed=field_def.get("indexed", False)
+                        indexed=field_def.get("indexed", False),
                     )
                     fields.append(field)
 
@@ -232,7 +234,7 @@ class Processor(CollectionConfigHandler, FlowProcessor):
         CREATE KEYSPACE IF NOT EXISTS {safe_keyspace}
         WITH REPLICATION = {{
             'class': 'SimpleStrategy',
-            'replication_factor': 1
+            'replication_factor': {self.replication_factor}
         }}
         """
 

trustgraph-flow/trustgraph/tables/cassandra_async.py

@@ -80,14 +80,14 @@ def _set_exception_if_pending(fut, exc):
         fut.set_exception(exc)
 
 
-async def async_execute_paged(session, query, parameters=None, fetch_size=100):
+async def async_execute_paged(session, query, parameters=None, fetch_size=5000):
     """Execute a CQL query with page-by-page iteration.
 
     Uses synchronous session.execute() inside run_in_executor so that
     the driver's ResultSet paging works correctly without materialising
     the entire result set in memory.
 
-    Yields one page of rows at a time (as a list).
+    Returns all pages as a list of lists.
     """
     loop = asyncio.get_running_loop()
 
@@ -111,3 +111,50 @@ async def async_execute_paged(session, query, parameters=None, fetch_size=100):
     return await loop.run_in_executor(
         None, _fetch_all_pages
     )
+
+
+async def async_scan(
+    session, query, parameters=None, row_filter=None,
+    limit=None, fetch_size=5000,
+):
+    """Scan a CQL query page-by-page, applying a filter and limit.
+
+    Only matching rows accumulate in memory.  Each page is discarded
+    after processing, so peak memory is bounded by fetch_size plus
+    the number of matching rows (capped by limit).
+
+    Args:
+        session: cassandra.cluster.Session
+        query: CQL statement string
+        parameters: bind params
+        row_filter: callable(row) -> bool, or None to accept all
+        limit: max results to return, or None for unlimited
+        fetch_size: rows per Cassandra page fetch
+
+    Returns:
+        List of matching rows.
+    """
+    loop = asyncio.get_running_loop()
+
+    if isinstance(query, str):
+        stmt = SimpleStatement(query, fetch_size=fetch_size)
+    else:
+        stmt = query
+        stmt.fetch_size = fetch_size
+
+    def _scan():
+        results = []
+        result_set = session.execute(stmt, parameters)
+        while True:
+            for row in result_set.current_rows:
+                if row_filter is None or row_filter(row):
+                    results.append(row)
+                    if limit and len(results) >= limit:
+                        return results
+            if result_set.has_more_pages:
+                result_set.fetch_next_page()
+            else:
+                break
+        return results
+
+    return await loop.run_in_executor(None, _scan)

trustgraph-flow/trustgraph/tables/config.py

@@ -4,7 +4,7 @@ from .. schema import Metadata, GraphEmbeddings
 
 from cassandra.cluster import Cluster
 from cassandra.auth import PlainTextAuthProvider
-from ssl import SSLContext, PROTOCOL_TLSv1_2
+import ssl
 
 import uuid
 import time
@@ -33,7 +33,7 @@ class ConfigTableStore:
             cassandra_host = [h.strip() for h in cassandra_host.split(',')]
 
         if cassandra_username and cassandra_password:
-            ssl_context = SSLContext(PROTOCOL_TLSv1_2)
+            ssl_context = ssl.create_default_context()
             auth_provider = PlainTextAuthProvider(
                 username=cassandra_username, password=cassandra_password
             )

trustgraph-flow/trustgraph/tables/iam.py

@@ -15,7 +15,7 @@ import logging
 
 from cassandra.cluster import Cluster
 from cassandra.auth import PlainTextAuthProvider
-from ssl import SSLContext, PROTOCOL_TLSv1_2
+import ssl
 
 from . cassandra_async import async_execute
 
@@ -39,7 +39,7 @@ class IamTableStore:
             cassandra_host = [h.strip() for h in cassandra_host.split(",")]
 
         if cassandra_username and cassandra_password:
-            ssl_context = SSLContext(PROTOCOL_TLSv1_2)
+            ssl_context = ssl.create_default_context()
             auth_provider = PlainTextAuthProvider(
                 username=cassandra_username, password=cassandra_password,
             )

trustgraph-flow/trustgraph/tables/knowledge.py

@@ -23,7 +23,7 @@ def tuple_to_term(value, is_uri):
     else:
         return Term(type=LITERAL, value=value)
 from cassandra.auth import PlainTextAuthProvider
-from ssl import SSLContext, PROTOCOL_TLSv1_2
+import ssl
 
 import uuid
 import time
@@ -50,7 +50,7 @@ class KnowledgeTableStore:
             cassandra_host = [h.strip() for h in cassandra_host.split(',')]
 
         if cassandra_username and cassandra_password:
-            ssl_context = SSLContext(PROTOCOL_TLSv1_2)
+            ssl_context = ssl.create_default_context()
             auth_provider = PlainTextAuthProvider(
                 username=cassandra_username, password=cassandra_password
             )
@@ -98,7 +98,8 @@ class KnowledgeTableStore:
                     text, boolean, text, boolean, text, boolean
                 >>,
                 triples list<tuple<
-                    text, boolean, text, boolean, text, boolean
+                    text, boolean, text, boolean, text, boolean,
+                    text
                 >>,
                 PRIMARY KEY ((workspace, document_id), id)
             );
@@ -234,7 +235,8 @@ class KnowledgeTableStore:
 
         triples = [
             (
-                *term_to_tuple(v.s), *term_to_tuple(v.p), *term_to_tuple(v.o)
+                *term_to_tuple(v.s), *term_to_tuple(v.p), *term_to_tuple(v.o),
+                v.g or ""
             )
             for v in m.triples
         ]
@@ -416,6 +418,7 @@ class KnowledgeTableStore:
                             s = tuple_to_term(elt[0], elt[1]),
                             p = tuple_to_term(elt[2], elt[3]),
                             o = tuple_to_term(elt[4], elt[5]),
+                            g = elt[6] if elt[6] else None,
                         )
                         for elt in row[3]
                     ]

trustgraph-flow/trustgraph/tables/library.py

@@ -24,7 +24,7 @@ from .. exceptions import RequestError
 from cassandra.cluster import Cluster
 from cassandra.auth import PlainTextAuthProvider
 from cassandra.query import BatchStatement
-from ssl import SSLContext, PROTOCOL_TLSv1_2
+import ssl
 
 import uuid
 import time
@@ -53,7 +53,7 @@ class LibraryTableStore:
             cassandra_host = [h.strip() for h in cassandra_host.split(',')]
 
         if cassandra_username and cassandra_password:
-            ssl_context = SSLContext(PROTOCOL_TLSv1_2)
+            ssl_context = ssl.create_default_context()
             auth_provider = PlainTextAuthProvider(
                 username=cassandra_username, password=cassandra_password
             )

trustgraph-mcp/trustgraph/mcp_server/tg_socket.py

@@ -1,49 +1,110 @@
 
-from dataclasses import dataclass
 from websockets.asyncio.client import connect
-from urllib.parse import urlencode, urlparse, urlunparse, parse_qs
 import asyncio
 import logging
 import json
 import uuid
-import time
+import hashlib
+
+logger = logging.getLogger(__name__)
+
+
+def _token_key(token):
+    """Derive a dict key from a token without storing the raw secret."""
+    return hashlib.sha256(token.encode()).hexdigest()[:16]
+
 
 class WebSocketManager:
+    """Manages an authenticated WebSocket connection to the TrustGraph
+    gateway on behalf of a single caller.
 
-    def __init__(self, url, token=None):
+    Each caller token gets its own WebSocketManager so that gateway-side
+    identity, workspace, and capability scoping are preserved end-to-end.
+    """
+
+    def __init__(self, url, token):
         self.url = url
+        # ── Security boundary: token storage ──
+        # This is the MCP caller's Bearer token, forwarded verbatim to
+        # the gateway.  It MUST NOT be logged, persisted, or shared
+        # across callers.  It is held only for the lifetime of this
+        # connection so that re-auth (e.g. after a reconnect) is
+        # possible.
         self.token = token
         self.socket = None
-
-    # FIXME: authentication is broken. The /api/v1/socket endpoint uses
-    # in-band auth (first-frame protocol via the Mux dispatcher), not
-    # query-parameter tokens. This query-string token is silently ignored.
-    # Fix: after connect(), send an auth frame with the bearer token as
-    # the first message, matching the gateway's in-band auth protocol.
-    def _build_url(self):
-        if not self.token:
-            return self.url
-        parsed = urlparse(self.url)
-        params = parse_qs(parsed.query)
-        params["token"] = [self.token]
-        new_query = urlencode(params, doseq=True)
-        return urlunparse(parsed._replace(query=new_query))
+        self.identity = None
+        self.last_used = None
 
     async def start(self):
-        self.socket = await connect(self._build_url())
+        """Connect and authenticate via the gateway's in-band auth
+        protocol.  Raises on auth failure."""
+
+        # ── Security boundary: MCP server → gateway ──
+        # The WebSocket connects to the gateway and authenticates using
+        # the caller's Bearer token via the in-band first-frame auth
+        # protocol.  The token belongs to the MCP client — we forward
+        # it as-is and never interpret its contents.
+        self.socket = await connect(self.url)
         self.pending_requests = {}
         self.running = True
+
+        await self._authenticate()
+
         self.reader_task = asyncio.create_task(self.reader())
 
+    async def _authenticate(self):
+        """Send in-band auth frame and wait for auth-ok / auth-failed.
+
+        The gateway expects ``{"type": "auth", "token": "..."}`` as the
+        first frame on a new WebSocket.  Any service frame sent before
+        auth-ok is rejected.
+        """
+        await self.socket.send(json.dumps({
+            "type": "auth",
+            "token": self.token,
+        }))
+
+        response_text = await asyncio.wait_for(self.socket.recv(), 10)
+        response = json.loads(response_text)
+
+        if response.get("type") == "auth-ok":
+            logger.info(
+                "WebSocket authenticated, default workspace: %s",
+                response.get("workspace"),
+            )
+            return
+
+        # Auth failed — close immediately, do not leave an
+        # unauthenticated socket open.
+        await self.socket.close()
+        self.socket = None
+
+        if response.get("type") == "auth-failed":
+            raise RuntimeError(
+                "Gateway rejected the authentication token"
+            )
+
+        raise RuntimeError(
+            f"Unexpected auth response type: {response.get('type')}"
+        )
+
+    async def whoami(self):
+        """Verify the token by calling the gateway's whoami endpoint.
+        Returns the identity dict and caches it on ``self.identity``.
+        """
+        gen = self.request("iam", {"operation": "whoami"}, flow_id=None)
+        async for response in gen:
+            self.identity = response
+            return response
+
     async def stop(self):
         self.running = False
-        await self.reader_task
+        if hasattr(self, "reader_task"):
+            await self.reader_task
 
     async def reader(self):
-        """
-        Background task to read websocket responses and route to correct
-        request
-        """
+        """Background task: read WebSocket frames and route them to the
+        correct pending-request queue by ``id``."""
 
         while self.running:
             try:
@@ -59,23 +120,21 @@ class WebSocketManager:
 
                 request_id = response.get("id")
                 if request_id and request_id in self.pending_requests:
-                    # Put the response in the queue
                     queue = self.pending_requests[request_id]
                     await queue.put(response)
                 else:
-                    logging.warning(
-                        f"Response for unknown request ID: {request_id}"
+                    logger.warning(
+                        "Response for unknown request ID: %s", request_id
                     )
 
             except Exception as e:
 
-                logging.error(f"Error in websocket reader: {e}")
+                logger.error("Error in websocket reader: %s", e)
 
-                # Put error in all pending queues
                 for queue in self.pending_requests.values():
                     try:
                         await queue.put({"error": str(e)})
-                    except:
+                    except Exception:
                         pass
 
                 self.pending_requests.clear()
@@ -86,25 +145,29 @@ class WebSocketManager:
 
     async def request(
             self, service, request_data, flow_id="default",
+            workspace=None,
     ):
-        """
-        Send a request via websocket and handle single or streaming responses
+        """Send a request via WebSocket and yield responses.
+
+        Args:
+            service: Gateway service name (e.g. "graph-rag", "config").
+            request_data: Inner request payload.
+            flow_id: Optional flow identifier.  ``None`` omits the field
+                (workspace-level services don't use flows).
+            workspace: Optional workspace override.  When ``None`` the
+                gateway uses the caller's default workspace.
         """
 
-        # Generate unique request ID
+        import time
+        self.last_used = time.monotonic()
+
         request_id = f"{uuid.uuid4()}"
 
-        # Determine if this service streams responses
-        streaming_services = {"agent"}
-        is_streaming = service in streaming_services
-
-        # Create a queue for all responses (streaming and single)
         response_queue = asyncio.Queue()
         self.pending_requests[request_id] = response_queue
 
         try:
 
-            # Build request message
             message = {
                 "id": request_id,
                 "service": service,
@@ -114,7 +177,16 @@ class WebSocketManager:
             if flow_id is not None:
                 message["flow"] = flow_id
 
-            # Send request
+            # ── Security boundary: workspace scoping ──
+            # When the caller supplies a workspace, we set it on the
+            # message envelope.  The gateway's enforce_workspace()
+            # validates that the authenticated identity is permitted
+            # to access the target workspace — we MUST NOT skip or
+            # override that check.  When workspace is None, the
+            # gateway default-fills from the identity's bound workspace.
+            if workspace is not None:
+                message["workspace"] = workspace
+
             await self.socket.send(json.dumps(message))
 
             while self.running:
@@ -127,19 +199,17 @@ class WebSocketManager:
                     continue
 
                 if "error" in response:
-                    if "message" in response["error"]:
-                        raise RuntimeError(response["error"]["text"])
+                    if isinstance(response["error"], dict):
+                        raise RuntimeError(
+                            response["error"].get("message", str(response["error"]))
+                        )
                     else:
                         raise RuntimeError(str(response["error"]))
 
                 yield response["response"]
 
-                if "complete" in response:
-                    if response["complete"]:
-                        break
+                if response.get("complete"):
+                    break
 
-        except Exception as e:
-            # Clean up on error
+        finally:
             self.pending_requests.pop(request_id, None)
-            raise e
-