fireworks[minor]: remove default model and temperature (#30965)

`mixtral-8x-7b-instruct` was recently retired from Fireworks Serverless.

Here we remove the default model altogether, so that the model must be
explicitly specified on init:
```python
ChatFireworks(model="accounts/fireworks/models/llama-v3p1-70b-instruct")  # for example
```

We also set a null default for `temperature`, which previously defaulted
to 0.0. This parameter will no longer be included in request payloads
unless it is explicitly provided.

docs/docs/integrations/llms/fireworks.ipynb

@@ -90,7 +90,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "d285fd7f",
    "metadata": {},
    "outputs": [],
@@ -99,7 +99,7 @@
     "\n",
     "# Initialize a Fireworks model\n",
     "llm = Fireworks(\n",
-    "    model=\"accounts/fireworks/models/mixtral-8x7b-instruct\",\n",
+    "    model=\"accounts/fireworks/models/llama-v3p1-8b-instruct\",\n",
     "    base_url=\"https://api.fireworks.ai/inference/v1/completions\",\n",
     ")"
    ]
@@ -176,7 +176,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "id": "b801c20d",
    "metadata": {},
    "outputs": [
@@ -192,7 +192,7 @@
    "source": [
     "# Setting additional parameters: temperature, max_tokens, top_p\n",
     "llm = Fireworks(\n",
-    "    model=\"accounts/fireworks/models/mixtral-8x7b-instruct\",\n",
+    "    model=\"accounts/fireworks/models/llama-v3p1-8b-instruct\",\n",
     "    temperature=0.7,\n",
     "    max_tokens=15,\n",
     "    top_p=1.0,\n",
@@ -218,7 +218,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "id": "fd2c6bc1",
    "metadata": {},
    "outputs": [
@@ -235,7 +235,7 @@
     "from langchain_fireworks import Fireworks\n",
     "\n",
     "llm = Fireworks(\n",
-    "    model=\"accounts/fireworks/models/mixtral-8x7b-instruct\",\n",
+    "    model=\"accounts/fireworks/models/llama-v3p1-8b-instruct\",\n",
     "    temperature=0.7,\n",
     "    max_tokens=15,\n",
     "    top_p=1.0,\n",

libs/partners/fireworks/README.md

@@ -39,7 +39,7 @@ import os
 
 # Initialize a Fireworks model
 llm = Fireworks(
-    model="accounts/fireworks/models/mixtral-8x7b-instruct",
+    model="accounts/fireworks/models/llama-v3p1-8b-instruct",
     base_url="https://api.fireworks.ai/inference/v1/completions",
 )
 ```

libs/partners/fireworks/langchain_fireworks/chat_models.py

@@ -279,7 +279,7 @@ class ChatFireworks(BaseChatModel):
 
             from langchain_fireworks.chat_models import ChatFireworks
             fireworks = ChatFireworks(
-                model_name="accounts/fireworks/models/mixtral-8x7b-instruct")
+                model_name="accounts/fireworks/models/llama-v3p1-8b-instruct")
     """
 
     @property
@@ -306,11 +306,9 @@ class ChatFireworks(BaseChatModel):
 
     client: Any = Field(default=None, exclude=True)  #: :meta private:
     async_client: Any = Field(default=None, exclude=True)  #: :meta private:
-    model_name: str = Field(
-        default="accounts/fireworks/models/mixtral-8x7b-instruct", alias="model"
-    )
+    model_name: str = Field(alias="model")
     """Model name to use."""
-    temperature: float = 0.0
+    temperature: Optional[float] = None
     """What sampling temperature to use."""
     stop: Optional[Union[str, list[str]]] = Field(default=None, alias="stop_sequences")
     """Default stop sequences."""
@@ -397,10 +395,11 @@ class ChatFireworks(BaseChatModel):
             "model": self.model_name,
             "stream": self.streaming,
             "n": self.n,
-            "temperature": self.temperature,
             "stop": self.stop,
             **self.model_kwargs,
         }
+        if self.temperature is not None:
+            params["temperature"] = self.temperature
         if self.max_tokens is not None:
             params["max_tokens"] = self.max_tokens
         return params

libs/partners/fireworks/tests/integration_tests/test_chat_models.py

@@ -13,54 +13,13 @@ from typing_extensions import TypedDict
 
 from langchain_fireworks import ChatFireworks
 
-
-def test_chat_fireworks_call() -> None:
-    """Test valid call to fireworks."""
-    llm = ChatFireworks(  # type: ignore[call-arg]
-        model="accounts/fireworks/models/llama-v3p1-70b-instruct", temperature=0
-    )
-
-    resp = llm.invoke("Hello!")
-    assert isinstance(resp, AIMessage)
-
-    assert len(resp.content) > 0
-
-
-def test_tool_choice() -> None:
-    """Test that tool choice is respected."""
-    llm = ChatFireworks(  # type: ignore[call-arg]
-        model="accounts/fireworks/models/llama-v3p1-70b-instruct", temperature=0
-    )
-
-    class MyTool(BaseModel):
-        name: str
-        age: int
-
-    with_tool = llm.bind_tools([MyTool], tool_choice="MyTool")
-
-    resp = with_tool.invoke("Who was the 27 year old named Erick?")
-    assert isinstance(resp, AIMessage)
-    assert resp.content == ""  # should just be tool call
-    tool_calls = resp.additional_kwargs["tool_calls"]
-    assert len(tool_calls) == 1
-    tool_call = tool_calls[0]
-    assert tool_call["function"]["name"] == "MyTool"
-    assert json.loads(tool_call["function"]["arguments"]) == {
-        "age": 27,
-        "name": "Erick",
-    }
-    assert tool_call["type"] == "function"
-    assert isinstance(resp.tool_calls, list)
-    assert len(resp.tool_calls) == 1
-    tool_call = resp.tool_calls[0]
-    assert tool_call["name"] == "MyTool"
-    assert tool_call["args"] == {"age": 27, "name": "Erick"}
+_MODEL = "accounts/fireworks/models/llama-v3p1-8b-instruct"
 
 
 def test_tool_choice_bool() -> None:
     """Test that tool choice is respected just passing in True."""
 
-    llm = ChatFireworks(  # type: ignore[call-arg]
+    llm = ChatFireworks(
         model="accounts/fireworks/models/llama-v3p1-70b-instruct", temperature=0
     )
 
@@ -84,17 +43,9 @@ def test_tool_choice_bool() -> None:
     assert tool_call["type"] == "function"
 
 
-def test_stream() -> None:
-    """Test streaming tokens from ChatFireworks."""
-    llm = ChatFireworks()  # type: ignore[call-arg]
-
-    for token in llm.stream("I'm Pickle Rick"):
-        assert isinstance(token.content, str)
-
-
 async def test_astream() -> None:
     """Test streaming tokens from ChatFireworks."""
-    llm = ChatFireworks()  # type: ignore[call-arg]
+    llm = ChatFireworks(model=_MODEL)
 
     full: Optional[BaseMessageChunk] = None
     chunks_with_token_counts = 0
@@ -125,18 +76,9 @@ async def test_astream() -> None:
     assert full.response_metadata["model_name"]
 
 
-async def test_abatch() -> None:
-    """Test abatch tokens from ChatFireworks."""
-    llm = ChatFireworks()  # type: ignore[call-arg]
-
-    result = await llm.abatch(["I'm Pickle Rick", "I'm not Pickle Rick"])
-    for token in result:
-        assert isinstance(token.content, str)
-
-
 async def test_abatch_tags() -> None:
     """Test batch tokens from ChatFireworks."""
-    llm = ChatFireworks()  # type: ignore[call-arg]
+    llm = ChatFireworks(model=_MODEL)
 
     result = await llm.abatch(
         ["I'm Pickle Rick", "I'm not Pickle Rick"], config={"tags": ["foo"]}
@@ -145,18 +87,9 @@ async def test_abatch_tags() -> None:
         assert isinstance(token.content, str)
 
 
-def test_batch() -> None:
-    """Test batch tokens from ChatFireworks."""
-    llm = ChatFireworks()  # type: ignore[call-arg]
-
-    result = llm.batch(["I'm Pickle Rick", "I'm not Pickle Rick"])
-    for token in result:
-        assert isinstance(token.content, str)
-
-
 async def test_ainvoke() -> None:
     """Test invoke tokens from ChatFireworks."""
-    llm = ChatFireworks()  # type: ignore[call-arg]
+    llm = ChatFireworks(model=_MODEL)
 
     result = await llm.ainvoke("I'm Pickle Rick", config={"tags": ["foo"]})
     assert isinstance(result.content, str)
@@ -164,7 +97,7 @@ async def test_ainvoke() -> None:
 
 def test_invoke() -> None:
     """Test invoke tokens from ChatFireworks."""
-    llm = ChatFireworks()  # type: ignore[call-arg]
+    llm = ChatFireworks(model=_MODEL)
 
     result = llm.invoke("I'm Pickle Rick", config=dict(tags=["foo"]))
     assert isinstance(result.content, str)

libs/partners/fireworks/tests/unit_tests/__snapshots__/test_standard.ambr

@@ -17,11 +17,12 @@
       }),
       'max_retries': 2,
       'max_tokens': 100,
-      'model_name': 'accounts/fireworks/models/mixtral-8x7b-instruct',
+      'model_name': 'accounts/fireworks/models/llama-v3p1-70b-instruct',
       'n': 1,
       'request_timeout': 60.0,
       'stop': list([
       ]),
+      'temperature': 0.0,
     }),
     'lc': 1,
     'name': 'ChatFireworks',

libs/partners/fireworks/tests/unit_tests/test_standard.py

@@ -15,7 +15,10 @@ class TestFireworksStandard(ChatModelUnitTests):
 
     @property
     def chat_model_params(self) -> dict:
-        return {"api_key": "test_api_key"}
+        return {
+            "model": "accounts/fireworks/models/llama-v3p1-70b-instruct",
+            "api_key": "test_api_key",
+        }
 
     @property
     def init_from_env_params(self) -> tuple[dict, dict, dict]:
@@ -24,7 +27,9 @@ class TestFireworksStandard(ChatModelUnitTests):
                 "FIREWORKS_API_KEY": "api_key",
                 "FIREWORKS_API_BASE": "https://base.com",
             },
-            {},
+            {
+                "model": "accounts/fireworks/models/llama-v3p1-70b-instruct",
+            },
             {
                 "fireworks_api_key": "api_key",
                 "fireworks_api_base": "https://base.com",