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tisnik merged 1 commit into from
Jun 3, 2026
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LCORE-2086: Reformat tables #1841

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30 changes: 15 additions & 15 deletions docs/ARCHITECTURE.md
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Expand Up @@ -44,7 +44,7 @@ To enhance LLM responses, LCore leverages **RAG (Retrieval-Augmented Generation)
```
┌─────────────────────────────────────────────────────────┐
│ Client Applications │
│ (Web UI, CLI, VS Code Extension, Mobile Apps, etc.) │
│ (Web UI, CLI, VS Code Extension, Mobile Apps, etc.) │
└────────────────────┬────────────────────────────────────┘
│ REST/A2A/JSON-RPC
▼
Expand Down Expand Up @@ -150,14 +150,14 @@ LCore requires two main configuration files:

**Authentication Providers:**

| Provider | Use Case | Token Handling |
|----------|----------|----------------|
| **No Auth** | Development, testing | No token (empty string) |
| **No Auth + Token** | Testing with token passthrough | Bearer token passed through |
| **Kubernetes** | K8s service accounts | K8s service account token validated and forwarded |
| **Red Hat SSO** | Red Hat environments | X-RH-Identity header (no separate token) |
| **API Key** | API key authentication | API key from Authorization header |
| **JWK/JWT** | JWT tokens | JWT validated and forwarded |
| Provider | Use Case | Token Handling |
|---------------------|--------------------------------|---------------------------------------------------|
| **No Auth** | Development, testing | No token (empty string) |
| **No Auth + Token** | Testing with token passthrough | Bearer token passed through |
| **Kubernetes** | K8s service accounts | K8s service account token validated and forwarded |
| **Red Hat SSO** | Red Hat environments | X-RH-Identity header (no separate token) |
| **API Key** | API key authentication | API key from Authorization header |
| **JWK/JWT** | JWT tokens | JWT validated and forwarded |

**Authentication Result (AuthTuple):**

Expand Down Expand Up @@ -427,12 +427,12 @@ LCore uses a multi-database strategy to optimize for different data access patte

The system uses **4 separate databases** for different purposes:

| Database | Purpose | Technology | Size |
|----------|---------|------------|------|
| **User DB** | Conversation metadata | SQLAlchemy ORM | Small |
| **Cache DB** | Full conversation transcripts | psycopg2/sqlite3 | Large |
| **Quota DB** | Token usage and limits | psycopg2/sqlite3 | Medium |
| **A2A DB** | Agent-to-agent protocol state | SQLAlchemy async | Small |
| Database | Purpose | Technology | Size |
|--------------|-------------------------------|------------------|--------|
| **User DB** | Conversation metadata | SQLAlchemy ORM | Small |
| **Cache DB** | Full conversation transcripts | psycopg2/sqlite3 | Large |
| **Quota DB** | Token usage and limits | psycopg2/sqlite3 | Medium |
| **A2A DB** | Agent-to-agent protocol state | SQLAlchemy async | Small |

### 4.2 Why Separate Databases?

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22 changes: 11 additions & 11 deletions docs/a2a_protocol.md
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Expand Up @@ -354,14 +354,14 @@ A2A Request

### Task States

| State | Description |
|-------|-------------|
| `submitted` | Task has been received and queued |
| `working` | Task is being processed |
| `completed` | Task finished successfully |
| `failed` | Task failed with an error |
| State | Description |
|------------------|--------------------------------------------|
| `submitted` | Task has been received and queued |
| `working` | Task is being processed |
| `completed` | Task finished successfully |
| `failed` | Task failed with an error |
| `input_required` | Agent needs additional input from the user |
| `auth_required` | Authentication is required to continue |
| `auth_required` | Authentication is required to continue |

### Multi-Turn Conversations

Expand Down Expand Up @@ -527,10 +527,10 @@ curl -X POST http://localhost:8090/a2a \

A2A messages support an optional `metadata` field that can be used to pass additional parameters to control request routing and behavior. The following metadata fields are supported:

| Field | Type | Description |
|-------|------|-------------|
| `model` | `string` | Specify the LLM model to use for this request (e.g., `"gpt-4"`, `"llama3.1"`) |
| `provider` | `string` | Specify the LLM provider to use (e.g., `"openai"`, `"watsonx"`) |
| Field | Type | Description |
|--------------------|----------------|--------------------------------------------------------------------------------------------------------|
| `model` | `string` | Specify the LLM model to use for this request (e.g., `"gpt-4"`, `"llama3.1"`) |
| `provider` | `string` | Specify the LLM provider to use (e.g., `"openai"`, `"watsonx"`) |
| `vector_store_ids` | `list[string]` | Specify which vector stores to query for RAG. If not provided, all available vector stores are queried |

#### Example: Using Metadata
Expand Down
26 changes: 13 additions & 13 deletions docs/byok_guide.md
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Expand Up @@ -191,15 +191,15 @@ byok_rag:

**`byok_rag` field reference:**

| Field | Required | Default | Description |
|-------|----------|---------|-------------|
| `rag_id` | Yes | — | Unique identifier for the knowledge source |
| `rag_type` | No | `inline::faiss` | Vector store provider type |
| `embedding_model` | No | `sentence-transformers/all-mpnet-base-v2` | Embedding model identifier or path |
| `embedding_dimension` | No | `768` | Embedding vector dimensionality |
| `vector_db_id` | Yes | — | Vector store ID generated by rag-content (e.g. `vs_8c94967b-81cc-4028-a294-9cfac6fd9ae2`) |
| `db_path` | Yes | — | Path to the vector database file |
| `score_multiplier` | No | `1.0` | Weight for Inline RAG ranking (values > 1.0 boost; < 1.0 reduce) |
| Field | Required | Default | Description |
|-----------------------|----------|-------------------------------------------|-------------------------------------------------------------------------------------------|
| `rag_id` | Yes | — | Unique identifier for the knowledge source |
| `rag_type` | No | `inline::faiss` | Vector store provider type |
| `embedding_model` | No | `sentence-transformers/all-mpnet-base-v2` | Embedding model identifier or path |
| `embedding_dimension` | No | `768` | Embedding vector dimensionality |
| `vector_db_id` | Yes | — | Vector store ID generated by rag-content (e.g. `vs_8c94967b-81cc-4028-a294-9cfac6fd9ae2`) |
| `db_path` | Yes | — | Path to the vector database file |
| `score_multiplier` | No | `1.0` | Weight for Inline RAG ranking (values > 1.0 boost; < 1.0 reduce) |

**Multiple knowledge sources:**

Expand Down Expand Up @@ -251,10 +251,10 @@ okp:

Both modes can be enabled simultaneously. Choose based on your latency and control preferences:

| Mode | When context is fetched | Tool call needed | score_multiplier |
|------|------------------------|------------------|-----------------|
| Inline RAG | With every query | No | Yes (BYOK only) |
| Tool RAG | On LLM demand | Yes | No |
| Mode | When context is fetched | Tool call needed | score_multiplier |
|------------|-------------------------|------------------|------------------|
| Inline RAG | With every query | No | Yes (BYOK only) |
| Tool RAG | On LLM demand | Yes | No |

> [!TIP]
> A ready-to-use example combining BYOK and OKP is available at
Expand Down
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