improve llamacpp embeddings (#12972)

- **Description:**
Improve llamacpp embedding class by adding the `device` parameter so it
can be passed to the model and used with `gpu`, `cpu` or Apple metal
(`mps`).
Improve performance by making use of the bulk client api to compute
embeddings in batches.
  
  - **Dependencies:** none
  - **Tag maintainer:** 
@hwchase17

---------

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Chester Curme <chester.curme@gmail.com>

libs/community/langchain_community/embeddings/llamacpp.py

@@ -57,6 +57,9 @@ class LlamaCppEmbeddings(BaseModel, Embeddings):
     verbose: bool = Field(True, alias="verbose")
     """Print verbose output to stderr."""
 
+    device: Optional[str] = Field(None, alias="device")
+    """Device type to use and pass to the model"""
+
     class Config:
         extra = "forbid"
 
@@ -75,6 +78,7 @@ class LlamaCppEmbeddings(BaseModel, Embeddings):
             "n_threads",
             "n_batch",
             "verbose",
+            "device",
         ]
         model_params = {k: values[k] for k in model_param_names}
         # For backwards compatibility, only include if non-null.
@@ -108,8 +112,8 @@ class LlamaCppEmbeddings(BaseModel, Embeddings):
         Returns:
             List of embeddings, one for each text.
         """
-        embeddings = [self.client.embed(text) for text in texts]
-        return [list(map(float, e)) for e in embeddings]
+        embeddings = self.client.create_embedding(texts)
+        return [list(map(float, e["embedding"])) for e in embeddings["data"]]
 
     def embed_query(self, text: str) -> List[float]:
         """Embed a query using the Llama model.