[feat] Added backwards compatibility for OllamaEmbeddings initialization (migration from langchain_community.embeddings to langchain_ollama.embeddings (#29296)

- [feat] **Added backwards compatibility for OllamaEmbeddings
initialization (migration from `langchain_community.embeddings` to
`langchain_ollama.embeddings`**: "langchain_ollama"
- **Description:** Given that `OllamaEmbeddings` from
`langchain_community.embeddings` is deprecated, code is being shifted to
``langchain_ollama.embeddings`. However, this does not offer backward
compatibility of initializing the parameters and `OllamaEmbeddings`
object.
    - **Issue:** #29294 
    - **Dependencies:** None
    - **Twitter handle:** @BaqarAbbas2001


## Additional Information
Previously, `OllamaEmbeddings` from `langchain_community.embeddings`
used to support the following options:

https://github.com/langchain-ai/langchain/blob/e9abe583b2efe80b4c38f4b7548a473bcca4dde5/libs/community/langchain_community/embeddings/ollama.py#L125-L139

However, in the new package `from langchain_ollama import
OllamaEmbeddings`, there is no method to set these options. I have added
these parameters to resolve this issue.

This issue was also discussed in
https://github.com/langchain-ai/langchain/discussions/29113

Author: SyedBaqarAbbas

libs/partners/ollama/langchain_ollama/embeddings.py

@@ -1,9 +1,6 @@
 """Ollama embeddings models."""
 
-from typing import (
-    List,
-    Optional,
-)
+from typing import Any, Dict, List, Optional
 
 from langchain_core.embeddings import Embeddings
 from ollama import AsyncClient, Client
@@ -144,10 +141,89 @@ class OllamaEmbeddings(BaseModel, Embeddings):
     The async client to use for making requests.
     """
 
+    mirostat: Optional[int] = None
+    """Enable Mirostat sampling for controlling perplexity.
+    (default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)"""
+
+    mirostat_eta: Optional[float] = None
+    """Influences how quickly the algorithm responds to feedback
+    from the generated text. A lower learning rate will result in
+    slower adjustments, while a higher learning rate will make
+    the algorithm more responsive. (Default: 0.1)"""
+
+    mirostat_tau: Optional[float] = None
+    """Controls the balance between coherence and diversity
+    of the output. A lower value will result in more focused and
+    coherent text. (Default: 5.0)"""
+
+    num_ctx: Optional[int] = None
+    """Sets the size of the context window used to generate the
+    next token. (Default: 2048)	"""
+
+    num_gpu: Optional[int] = None
+    """The number of GPUs to use. On macOS it defaults to 1 to
+    enable metal support, 0 to disable."""
+
+    num_thread: Optional[int] = None
+    """Sets the number of threads to use during computation.
+    By default, Ollama will detect this for optimal performance.
+    It is recommended to set this value to the number of physical
+    CPU cores your system has (as opposed to the logical number of cores)."""
+
+    repeat_last_n: Optional[int] = None
+    """Sets how far back for the model to look back to prevent
+    repetition. (Default: 64, 0 = disabled, -1 = num_ctx)"""
+
+    repeat_penalty: Optional[float] = None
+    """Sets how strongly to penalize repetitions. A higher value (e.g., 1.5)
+    will penalize repetitions more strongly, while a lower value (e.g., 0.9)
+    will be more lenient. (Default: 1.1)"""
+
+    temperature: Optional[float] = None
+    """The temperature of the model. Increasing the temperature will
+    make the model answer more creatively. (Default: 0.8)"""
+
+    stop: Optional[List[str]] = None
+    """Sets the stop tokens to use."""
+
+    tfs_z: Optional[float] = None
+    """Tail free sampling is used to reduce the impact of less probable
+    tokens from the output. A higher value (e.g., 2.0) will reduce the
+    impact more, while a value of 1.0 disables this setting. (default: 1)"""
+
+    top_k: Optional[int] = None
+    """Reduces the probability of generating nonsense. A higher value (e.g. 100)
+    will give more diverse answers, while a lower value (e.g. 10)
+    will be more conservative. (Default: 40)"""
+
+    top_p: Optional[float] = None
+    """Works together with top-k. A higher value (e.g., 0.95) will lead
+    to more diverse text, while a lower value (e.g., 0.5) will
+    generate more focused and conservative text. (Default: 0.9)"""
+
     model_config = ConfigDict(
         extra="forbid",
     )
 
+    @property
+    def _default_params(self) -> Dict[str, Any]:
+        """Get the default parameters for calling Ollama."""
+        return {
+            "mirostat": self.mirostat,
+            "mirostat_eta": self.mirostat_eta,
+            "mirostat_tau": self.mirostat_tau,
+            "num_ctx": self.num_ctx,
+            "num_gpu": self.num_gpu,
+            "num_thread": self.num_thread,
+            "repeat_last_n": self.repeat_last_n,
+            "repeat_penalty": self.repeat_penalty,
+            "temperature": self.temperature,
+            "stop": self.stop,
+            "tfs_z": self.tfs_z,
+            "top_k": self.top_k,
+            "top_p": self.top_p,
+        }
+
     @model_validator(mode="after")
     def _set_clients(self) -> Self:
         """Set clients to use for ollama."""
@@ -158,7 +234,9 @@ def _set_clients(self) -> Self:
 
     def embed_documents(self, texts: List[str]) -> List[List[float]]:
         """Embed search docs."""
-        embedded_docs = self._client.embed(self.model, texts)["embeddings"]
+        embedded_docs = self._client.embed(
+            self.model, texts, options=self._default_params
+        )["embeddings"]
         return embedded_docs
 
     def embed_query(self, text: str) -> List[float]: