Upgrade MiniMax default model to MiniMax-M3 in dagworks RAG examples (#1620)

* Upgrade MiniMax model default to MiniMax-M3 in dagworks RAG modules

Updates the default model returned by `model__minimax()` in the
`conversational_rag` and `faiss_rag` dataflows from `MiniMax-M2.7`
to `MiniMax-M3`. The base URL (`https://api.minimax.io/v1`) and the
OpenAI-compatible client wiring stay the same; only the model ID
constant and its references in tests/README change.

- contrib/hamilton/contrib/dagworks/conversational_rag/__init__.py:
  `model__minimax()` now returns `MiniMax-M3`.
- contrib/hamilton/contrib/dagworks/faiss_rag/__init__.py:
  `model__minimax()` now returns `MiniMax-M3`.
- Unit tests updated to assert the new model constant and to pass
  `MiniMax-M3` into mocked chat completion calls.
- README config tables and "uses the [MiniMax-...] model" lines
  refreshed to reference MiniMax-M3.

Co-Authored-By: Octopus <liyuan851277048@icloud.com>
Signed-off-by: Octopus <liyuan851277048@icloud.com>

* docs: correct MiniMax context window (M3=512K, M2.7=192K; was mistakenly 1M)

* docs: correct MiniMax context window (M3=512K, M2.7=192K; was mistakenly 1M)

---------

Signed-off-by: Octopus <liyuan851277048@icloud.com>

Author: octo-patch

contrib/hamilton/contrib/dagworks/conversational_rag/README.md

@@ -130,7 +130,7 @@ result = dr.execute(
 )
 print(result)
 ```
-MiniMax uses the [MiniMax-M2.7](https://www.minimax.io/) model with a 1M token context window
+MiniMax uses the [MiniMax-M3](https://www.minimax.io/) model with a 512K context context window
 via an OpenAI-compatible API endpoint.
 
 # How to extend this module
@@ -150,7 +150,7 @@ With (3) you can add more functions that create parts of the prompt.
 
 | Config Key | Values | Description |
 |-----------|--------|-------------|
-| `provider` | `"minimax"` | Use MiniMax M2.7 as the LLM. Requires `MINIMAX_API_KEY` env var. |
+| `provider` | `"minimax"` | Use MiniMax M3 as the LLM. Requires `MINIMAX_API_KEY` env var. |
 | *(empty)* | | Default: uses OpenAI. Requires `OPENAI_API_KEY` env var. |
 
 # Limitations

contrib/hamilton/contrib/dagworks/conversational_rag/__init__.py

@@ -148,7 +148,7 @@ def model__openai() -> str:
 @config.when(provider="minimax")
 def model__minimax() -> str:
     """The model to use for MiniMax."""
-    return "MiniMax-M2.7"
+    return "MiniMax-M3"
 
 
 def conversational_rag_response(answer_prompt: str, llm_client: openai.OpenAI, model: str) -> str:

contrib/hamilton/contrib/dagworks/conversational_rag/test_conversational_rag.py

@@ -80,8 +80,8 @@ class TestModelConfig:
     def test_model_openai_returns_gpt35(self):
         assert conversational_rag.model__openai() == "gpt-3.5-turbo"
 
-    def test_model_minimax_returns_m27(self):
-        assert conversational_rag.model__minimax() == "MiniMax-M2.7"
+    def test_model_minimax_returns_m3(self):
+        assert conversational_rag.model__minimax() == "MiniMax-M3"
 
 
 class TestOpenAIProvider:
@@ -153,11 +153,11 @@ def test_standalone_question_with_minimax_model(self):
         result = conversational_rag.standalone_question(
             standalone_question_prompt="test prompt",
             llm_client=mock_client,
-            model="MiniMax-M2.7",
+            model="MiniMax-M3",
         )
         assert result == "standalone question"
         call_args = mock_client.chat.completions.create.call_args
-        assert call_args.kwargs["model"] == "MiniMax-M2.7"
+        assert call_args.kwargs["model"] == "MiniMax-M3"
 
     def test_rag_response_with_minimax_model(self):
         mock_client = MagicMock(spec=openai.OpenAI)
@@ -169,11 +169,11 @@ def test_rag_response_with_minimax_model(self):
         result = conversational_rag.conversational_rag_response(
             answer_prompt="Where did stefan work?",
             llm_client=mock_client,
-            model="MiniMax-M2.7",
+            model="MiniMax-M3",
         )
         assert result == "MiniMax answer"
         call_args = mock_client.chat.completions.create.call_args
-        assert call_args.kwargs["model"] == "MiniMax-M2.7"
+        assert call_args.kwargs["model"] == "MiniMax-M3"
 
 
 class TestHamiltonDriverConfig:
@@ -293,7 +293,7 @@ def test_minimax_standalone_question_real_api(self, minimax_api_key):
                 "Follow Up Input: Where did he work?\n"
                 "Standalone question:",
                 llm_client=client,
-                model="MiniMax-M2.7",
+                model="MiniMax-M3",
             )
             assert isinstance(result, str)
             assert len(result) > 0
@@ -306,7 +306,7 @@ def test_minimax_conversational_rag_response_real_api(self, minimax_api_key):
                 "Stefan worked at Stitch Fix.\n\n"
                 "Question: Where did Stefan work?",
                 llm_client=client,
-                model="MiniMax-M2.7",
+                model="MiniMax-M3",
             )
             assert isinstance(result, str)
             assert len(result) > 0

contrib/hamilton/contrib/dagworks/faiss_rag/README.md

@@ -102,7 +102,7 @@ result = dr.execute(
 )
 print(result)
 ```
-MiniMax uses the [MiniMax-M2.7](https://www.minimax.io/) model with a 1M token context window
+MiniMax uses the [MiniMax-M3](https://www.minimax.io/) model with a 512K context context window
 via an OpenAI-compatible API endpoint.
 
 # How to extend this module
@@ -122,7 +122,7 @@ With (3) you can add more functions that create parts of the prompt.
 
 | Config Key | Values | Description |
 |-----------|--------|-------------|
-| `provider` | `"minimax"` | Use MiniMax M2.7 as the LLM. Requires `MINIMAX_API_KEY` env var. |
+| `provider` | `"minimax"` | Use MiniMax M3 as the LLM. Requires `MINIMAX_API_KEY` env var. |
 | *(empty)* | | Default: uses OpenAI. Requires `OPENAI_API_KEY` env var. |
 
 # Limitations

contrib/hamilton/contrib/dagworks/faiss_rag/__init__.py

@@ -108,7 +108,7 @@ def model__openai() -> str:
 @config.when(provider="minimax")
 def model__minimax() -> str:
     """The model to use for MiniMax."""
-    return "MiniMax-M2.7"
+    return "MiniMax-M3"
 
 
 def rag_response(rag_prompt: str, llm_client: openai.OpenAI, model: str) -> str:

contrib/hamilton/contrib/dagworks/faiss_rag/test_faiss_rag.py

@@ -65,8 +65,8 @@ class TestModelConfig:
     def test_model_openai_returns_gpt35(self):
         assert faiss_rag.model__openai() == "gpt-3.5-turbo"
 
-    def test_model_minimax_returns_m27(self):
-        assert faiss_rag.model__minimax() == "MiniMax-M2.7"
+    def test_model_minimax_returns_m3(self):
+        assert faiss_rag.model__minimax() == "MiniMax-M3"
 
 
 class TestOpenAIProvider:
@@ -116,7 +116,7 @@ def test_llm_client_minimax_uses_env_api_key(self):
             assert client.api_key == "my-secret-key"
 
     def test_rag_response_with_minimax_model(self):
-        """Test that rag_response works with MiniMax-M2.7 model."""
+        """Test that rag_response works with MiniMax-M3 model."""
         mock_client = MagicMock(spec=openai.OpenAI)
         mock_response = MagicMock()
         mock_response.choices = [MagicMock()]
@@ -126,12 +126,12 @@ def test_rag_response_with_minimax_model(self):
         result = faiss_rag.rag_response(
             rag_prompt="Where did stefan work?",
             llm_client=mock_client,
-            model="MiniMax-M2.7",
+            model="MiniMax-M3",
         )
 
         assert result == "Stitch Fix"
         mock_client.chat.completions.create.assert_called_once_with(
-            model="MiniMax-M2.7",
+            model="MiniMax-M3",
             messages=[{"role": "user", "content": "Where did stefan work?"}],
         )
 
@@ -243,7 +243,7 @@ def test_minimax_rag_response_real_api(self, minimax_api_key):
                 "Stefan worked at Stitch Fix.\n\n"
                 "Question: Where did Stefan work?",
                 llm_client=client,
-                model="MiniMax-M2.7",
+                model="MiniMax-M3",
             )
             assert isinstance(result, str)
             assert len(result) > 0