docs(research): add farsi embedding model research knowledge base

Body:
        Why:
        - Insurance RAG pipeline needs Farsi-optimized embeddings
        - Current local baseline (Nomic Embed) is English-only

        Changes:
        - 8 cloud model profiles with curl + python test commands
        - 5 local model profiles with VRAM, serving platform notes
        - Persian benchmark landscape (MIRACL-Fa, mMARCO, FaMTE, MTEB)
        - Decision report with ranked options and recommendations
        - Full comparison table (15 models × 10 columns)

        Impact:
        - Knowledge base for embedding model selection
        - Top picks: BGE-M3 (local), Cohere embed-v4.0 (cloud)
        - Critical: Nomic Embed must be replaced (English-only)

embedding_models/jina.md

@@ -0,0 +1,111 @@
+---
+last_updated: 2026-07-20
+tags: [embedding, jina, cloud, local, farsi, insurance, rag, cheap]
+source: import-knowledge
+---
+
+# Jina AI — jina-embeddings-v3
+
+## Overview
+
+Available as both cloud API and local model. Cheapest cloud option with explicit Farsi support. **⚠️ Local model has non-commercial license (CC-BY-NC-4.0).**
+
+## Cloud API
+
+- **Type**: Cloud
+- **Provider**: Jina AI
+- **Price**: ~$0.02 per 1M tokens ([source](https://jina.ai/pricing/))
+- **Max input tokens**: 8,192
+- **Embedding dimensions**: 1024 (Matryoshka — resizable)
+- **Language coverage**: 89 languages including Farsi
+- **Persian benchmark**: No public Persian-specific scores. Strong MTEB multilingual.
+
+## Local Model
+
+- **Parameters**: ~568M
+- **VRAM (fp16)**: ~1.1 GB
+- **License**: CC-BY-NC-4.0 ⚠️ (non-commercial!) — **verify for enterprise use**
+- **Model card**: https://huggingface.co/jinaai/jina-embeddings-v3
+
+## Pros
+
+- Cheapest cloud option: ~$0.02/1M tokens
+- 89 languages including Farsi
+- Task-specific adapters (retrieval, clustering, classification)
+- Matryoshka support (resizable dimensions)
+- 8K context
+- ColBERT/late interaction support
+
+## Cons
+
+- Local model is CC-BY-NC (non-commercial) — verify for enterprise
+- Smaller company — less enterprise track record
+- Pricing page not transparent (SPA, not standard display)
+
+## API Test — Curl
+
+**Endpoint**: `POST https://api.jina.ai/v1/embeddings`
+**Auth**: `Authorization: Bearer $JINA_API_KEY`
+**Get key**: https://jina.ai/api-keys
+
+### For queries
+
+```bash
+curl -s https://api.jina.ai/v1/embeddings   -H "Content-Type: application/json"   -H "Authorization: Bearer $JINA_API_KEY"   -d '{
+    "model": "jina-embeddings-v3",
+    "input": ["بیمه نامه شخص ثالث چیست؟"],
+    "task": "retrieval.query"
+  }' | python3 -m json.tool
+```
+
+### For document chunks (indexing)
+
+```bash
+curl -s https://api.jina.ai/v1/embeddings   -H "Content-Type: application/json"   -H "Authorization: Bearer $JINA_API_KEY"   -d '{
+    "model": "jina-embeddings-v3",
+    "input": ["بیمه نامه شخص ثالث شامل پوشش خسارات مالی و جانی است."],
+    "task": "retrieval.passage"
+  }' | python3 -m json.tool
+```
+
+### With Matryoshka dimension reduction
+
+```bash
+curl -s https://api.jina.ai/v1/embeddings   -H "Content-Type: application/json"   -H "Authorization: Bearer $JINA_API_KEY"   -d '{
+    "model": "jina-embeddings-v3",
+    "input": ["بیمه نامه شخص ثالث چیست؟"],
+    "task": "retrieval.query",
+    "dimensions": 512
+  }' | python3 -c "import sys,json; d=json.load(sys.stdin); print(f'dims={len(d["data"][0]["embedding"])}')"
+```
+
+**Key differences from OpenAI**:
+- Use `task: "retrieval.query"` for queries, `task: "retrieval.passage"` for chunks
+- Optional `dimensions` param for Matryoshka truncation
+- Optional `late_chunking: true` for late-interaction-style results
+
+**Response shape**: `data[0].embedding` = float array, `usage.total_tokens` = token count
+
+## API Test — Python
+
+```python
+from jina import Client
+
+client = Client(api_key="YOUR_JINA_API_KEY")  # or uses JINA_API_KEY env var
+
+result = client.embed(
+    inputs=["بیمه نامه شخص ثالث چیست?"],
+    model="jina-embeddings-v3",
+    task="retrieval.query"
+)
+
+embedding = result.embeddings[0].embedding
+print(f"Dimensions: {len(embedding)}")
+```
+
+## TODO
+
+- [ ] Verify enterprise licensing terms for local model (CC-BY-NC)
+- [ ] Test cloud API with 100-question eval set
+- [ ] Benchmark on MIRACL-Farsi subset
+- [ ] Compare with OpenAI and Cohere on Farsi queries