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/cohere.md

@@ -0,0 +1,98 @@
+---
+last_updated: 2026-07-20
+tags: [embedding, cohere, cloud, farsi, insurance, rag, enterprise]
+source: import-knowledge
+---
+
+# Cohere — embed-v4.0
+
+## Overview
+
+- **Type**: Cloud
+- **Provider**: Cohere
+- **Price**: Enterprise only (Model Vault: ~$4.00–$5.00/hr dedicated instance) — legacy embed-multilingual-v3 was ~$0.10/1M tokens ([source](https://cohere.com/pricing))
+- **Max input tokens**: 512,000
+- **Embedding dimensions**: 256, 512, 1024, or 1536 (configurable)
+- **Language coverage**: 100+ languages including Farsi
+- **Persian benchmark**: Cohere models score well on MIRACL-Farsi on the MTEB leaderboard. No isolated Farsi numbers published by Cohere.
+
+## Why It's #1 Cloud Pick
+
+**512K context window** — largest of any embedding API. Can embed full insurance documents without chunking. Strong Farsi support (100+ languages). MIRACL-Farsi scores on MTEB leaderboard.
+
+**Caveat**: Enterprise-only pricing. No public per-token API anymore.
+
+## Pros
+
+- 100+ languages with explicit Farsi support
+- 512K context — can embed full documents, no chunking needed
+- Strong MIRACL-Farsi scores
+- v2 API with input_type distinction (search_query vs search_document)
+- Configurable dimensions (256–1536)
+
+## Cons
+
+- Enterprise-only pricing (Model Vault: ~$4–5/hr dedicated instance)
+- No public per-token API pricing — requires sales engagement
+- Smaller ecosystem than OpenAI
+
+## API Test — Curl
+
+**Endpoint**: `POST https://api.cohere.ai/v2/embed`
+**Auth**: `Authorization: Bearer $COHERE_API_KEY`
+**Get key**: https://dashboard.cohere.com/api-keys
+
+```bash
+curl -s https://api.cohere.ai/v2/embed   -H "Content-Type: application/json"   -H "Authorization: Bearer $COHERE_API_KEY"   -d '{
+    "model": "embed-v4.0",
+    "texts": ["بیمه نامه شخص ثالث چیست؟"],
+    "input_type": "search_query",
+    "embedding_types": ["float"]
+  }' | python3 -m json.tool
+```
+
+### ⚠️ Key Differences from OpenAI
+
+| Aspect | OpenAI | Cohere |
+|--------|--------|--------|
+| Input field | `"input"` (string/array) | `"texts"` (array) |
+| Input type | N/A | Required: `"search_query"` or `"search_document"` |
+| Output format | `data[0].embedding` | `data.embeddings.float[0]` |
+| Token count | `usage.total_tokens` | `meta.billed_units.input_tokens` |
+
+### Indexing Documents (use search_document)
+
+```bash
+curl -s https://api.cohere.ai/v2/embed   -H "Content-Type: application/json"   -H "Authorization: Bearer $COHERE_API_KEY"   -d '{
+    "model": "embed-v4.0",
+    "texts": ["بیمه نامه شخص ثالث شامل پوشش خسارات مالی و جانی است."],
+    "input_type": "search_document",
+    "embedding_types": ["float"]
+  }' | python3 -c "import sys,json; d=json.load(sys.stdin); print(f'dims={len(d["data"]["embeddings"]["float"][0])}, tokens={d["meta"]["billed_units"]["input_tokens"]}')"
+```
+
+## API Test — Python
+
+```python
+import cohere
+
+co = cohere.ClientV2(api_key="YOUR_COHERE_API_KEY")  # or use COHERE_API_KEY env var
+
+response = co.embed(
+    model="embed-v4.0",
+    input_type="search_query",
+    texts=["بیمه نامه شخص ثالث چیست؟"],
+    embedding_types=["float"],
+    output_dimension=1024
+)
+
+embedding = response.embeddings.float[0]
+print(f"Dimensions: {len(embedding)}")
+```
+
+## TODO
+
+- [ ] Contact Cohere sales for enterprise pricing
+- [ ] Benchmark on MIRACL-Farsi subset
+- [ ] Compare with OpenAI text-embedding-3-large on Farsi queries
+- [ ] Verify on-premises deployment options