Merge pull request #32 from SecrinLabs/ronaldo

chore: update default Ollama completion model to qwen2.5-coder and em…

Author: jenilsavani9

README.md

@@ -88,8 +88,8 @@ poetry run python scripts/verify.py
 
 ```bash
 # Install Ollama → https://ollama.com
-ollama pull llama3               # completion model
-ollama pull nomic-embed-text     # embedding model (768d)
+ollama pull qwen2.5-coder:0.5b               # completion model
+ollama pull mxbai-embed-large     # embedding model (768d)
 ```
 
 ### Cloud LLM
@@ -119,8 +119,8 @@ then writes `.secrin.yml`. Commit this file so teammates share the same defaults
 ```
 ? LLM provider (ollama / openai / anthropic): ollama
 ? Ollama host [http://localhost:11434]:
-? Ollama model [llama3]:
-? Embed model [nomic-embed-text]:
+? Ollama model [qwen2.5-coder:0.5b]:
+? Embed model [mxbai-embed-large]:
 ? Neo4j URI [bolt://localhost:7687]:
 ? Neo4j username [neo4j]:
 ? Neo4j password:
@@ -130,7 +130,7 @@ then writes `.secrin.yml`. Commit this file so teammates share the same defaults
 ✓ Created .secrin.yml
 ✓ Updated .env  (NEO4J_PASS)
 ✓ Connected to Neo4j  (0 nodes found)
-✓ Connected to Ollama  (llama3 available)
+✓ Connected to Ollama  (qwen2.5-coder:0.5b available)
 
 Run `secrin graph build --repo <url-or-path>` to index your repo.
 ```
@@ -154,8 +154,8 @@ secrin analyze
 Runs in two phases:
 
 ```
-⠋ [Phase 1] Summarizing  ollama / llama3  Function 48  Class 12  File 21
-⠋ [Phase 2] Embedding    nomic-embed-text  Function 48  Class 12  File 21
+⠋ [Phase 1] Summarizing  ollama / qwen2.5-coder:0.5b  Function 48  Class 12  File 21
+⠋ [Phase 2] Embedding    mxbai-embed-large  Function 48  Class 12  File 21
 
 ╭─ Analysis Results ────────────────────────╮
 │ Label      Summarized   Embedded           │
@@ -220,7 +220,7 @@ Coverage       98% summarized  ·  96% embedded
 Last analyzed  2 hours ago  (main @ a3f9c12)
 Neo4j          ● connected  bolt://localhost:7687
 Wiki           docs/wiki/  ·  47 pages
-.secrin.yml    ✓  ollama / llama3
+.secrin.yml    ✓  ollama / qwen2.5-coder:0.5b
 ──────────────────────────────────────────────────────────────
 ```
 
@@ -233,8 +233,8 @@ Wiki           docs/wiki/  ·  47 pages
 ```yaml
 llm:
   provider: ollama          # ollama | openai | anthropic
-  model: llama3
-  embed_model: nomic-embed-text
+  model: qwen2.5-coder:0.5b
+  embed_model: mxbai-embed-large
   base_url: http://localhost:11434   # Ollama only; omitted for cloud providers
 
 neo4j:
@@ -260,7 +260,7 @@ ANTHROPIC_API_KEY=sk-ant-...
 # Optional overrides (if you don't use .secrin.yml)
 LLM_PROVIDER=ollama
 LLM_MODEL_OLLAMA=qwen2.5-coder:0.5b
-OLLAMA_EMBEDDING_MODEL=nomic-embed-text
+OLLAMA_EMBEDDING_MODEL=mxbai-embed-large
 EMBEDDING_DIMENSION=768
 ```
 

packages/arc42gen/providers/ollama_provider.py

@@ -23,10 +23,10 @@ class OllamaProvider(BaseLLMProvider):
     No API key required - models run on the local machine.
     """
 
-    DEFAULT_MODEL = "llama3"
+    DEFAULT_MODEL = "qwen2.5-coder:0.5b"
     MODEL_ALIASES = {
         "codellama": "codellama:7b",
-        "llama3": "qwen2.5-coder:0.5b",
+        "qwen2.5-coder:0.5b": "qwen2.5-coder:0.5b",
         "mistral": "mistral:7b",
     }
 

packages/cli/agents/llm_client.py

@@ -26,7 +26,7 @@
 ---------------------------------
 Anthropic does not expose an embeddings API.  When provider="anthropic",
 embed() uses Ollama (base_url + embed_model).  Ensure Ollama is running
-and embed_model is set to a local embedding model (e.g. nomic-embed-text).
+and embed_model is set to a local embedding model (e.g. mxbai-embed-large).
 """
 from __future__ import annotations
 
@@ -43,15 +43,15 @@
 # ---------------------------------------------------------------------------
 
 _DEFAULT_MODELS: dict[str, str] = {
-    "ollama":    "llama3",
+    "ollama":    "qwen2.5-coder:0.5b",
     "openai":    "gpt-4o-mini",
     "anthropic": "claude-haiku-4-5-20251001",
 }
 
 _DEFAULT_EMBED_MODELS: dict[str, str] = {
-    "ollama":    "nomic-embed-text",
+    "ollama":    "mxbai-embed-large",
     "openai":    "text-embedding-3-small",
-    "anthropic": "nomic-embed-text",  # via Ollama
+    "anthropic": "mxbai-embed-large",  # via Ollama
 }
 
 

packages/cli/commands/init.py

@@ -9,8 +9,8 @@
 ----------------
   ? LLM provider (ollama / openai / anthropic): ollama
   ? Ollama host [http://localhost:11434]:
-  ? Ollama model [llama3]:
-  ? Embed model [nomic-embed-text]:
+  ? Ollama model [qwen2.5-coder:0.5b]:
+  ? Embed model [mxbai-embed-large]:
   ? Neo4j URI [bolt://localhost:7687]:
   ? Neo4j username [neo4j]:
   ? Neo4j password:
@@ -20,7 +20,7 @@
   ✓ Created .secrin.yml
   ✓ Updated .env  (NEO4J_PASS)
   ✓ Connected to Neo4j  (42 nodes found)
-  ✓ Connected to Ollama  (llama3 available)
+  ✓ Connected to Ollama  (qwen2.5-coder:0.5b available)
 
   Run `secrin graph build --repo <url-or-path>` to index your repo.
 
@@ -52,14 +52,14 @@
 
 # Provider → default completion model
 _COMPLETION_DEFAULTS: dict[str, str] = {
-    "ollama":    "llama3",
+    "ollama":    "qwen2.5-coder:0.5b",
     "openai":    "gpt-4o-mini",
     "anthropic": "claude-haiku-4-5-20251001",
 }
 
 # Provider → default embed model
 _EMBED_DEFAULTS: dict[str, str] = {
-    "ollama":    "nomic-embed-text",
+    "ollama":    "mxbai-embed-large",
     "openai":    "text-embedding-3-small",
     "anthropic": "nomic-embed-text",  # via Ollama
 }

packages/cli/commands/status.py

@@ -19,7 +19,7 @@
 Last analyzed  2 hours ago  (main @ a3f9c12)
 Neo4j          ● connected  bolt://localhost:7687
 Wiki           docs/wiki/  ·  47 pages
-.secrin.yml    ✓  ollama / llama3
+.secrin.yml    ✓  ollama / qwen2.5-coder:0.5b
 ──────────────────────────────────────────────────────────────
 """
 from __future__ import annotations

packages/cli/core/secrin_yml.py

@@ -9,8 +9,8 @@
 ------
 llm:
   provider: ollama          # ollama | openai | anthropic
-  model: llama3
-  embed_model: nomic-embed-text
+  model: qwen2.5-coder:0.5b
+  embed_model: mxbai-embed-large
   base_url: http://localhost:11434   # Ollama only
 
 neo4j:
@@ -38,8 +38,8 @@
 class SecrinYml:
     # LLM
     provider:        str        = "ollama"
-    model:           str        = "llama3"
-    embed_model:     str        = "nomic-embed-text"
+    model:           str        = "qwen2.5-coder:0.5b"
+    embed_model:     str        = "mxbai-embed-large"
     base_url:        str        = "http://localhost:11434"  # Ollama host
 
     # Neo4j
@@ -72,8 +72,8 @@ def load(cwd: Path) -> Optional[SecrinYml]:
 
     return SecrinYml(
         provider        = llm.get("provider",   "ollama"),
-        model           = llm.get("model",       "llama3"),
-        embed_model     = llm.get("embed_model", "nomic-embed-text"),
+        model           = llm.get("model",       "qwen2.5-coder:0.5b"),
+        embed_model     = llm.get("embed_model", "mxbai-embed-large"),
         base_url        = llm.get("base_url",    "http://localhost:11434"),
         neo4j_uri       = neo4j.get("uri",       "bolt://localhost:7687"),
         neo4j_user      = neo4j.get("username",  "neo4j"),