Add support of Cohere Embed v3 (#12940)

Cohere released the new embedding API (Embed v3:
https://txt.cohere.com/introducing-embed-v3/) that treats document and
query embeddings differently. This PR updated the `CohereEmbeddings` to
use them appropriately. It also works with the old models.

libs/langchain/langchain/embeddings/cohere.py

@@ -87,7 +87,10 @@ class CohereEmbeddings(BaseModel, Embeddings):
             List of embeddings, one for each text.
         """
         embeddings = self.client.embed(
-            model=self.model, texts=texts, truncate=self.truncate
+            model=self.model,
+            texts=texts,
+            input_type="search_document",
+            truncate=self.truncate,
         ).embeddings
         return [list(map(float, e)) for e in embeddings]
 
@@ -101,7 +104,10 @@ class CohereEmbeddings(BaseModel, Embeddings):
             List of embeddings, one for each text.
         """
         embeddings = await self.async_client.embed(
-            model=self.model, texts=texts, truncate=self.truncate
+            model=self.model,
+            texts=texts,
+            input_type="search_document",
+            truncate=self.truncate,
         )
         return [list(map(float, e)) for e in embeddings.embeddings]
 
@@ -114,7 +120,13 @@ class CohereEmbeddings(BaseModel, Embeddings):
         Returns:
             Embeddings for the text.
         """
-        return self.embed_documents([text])[0]
+        embeddings = self.client.embed(
+            model=self.model,
+            texts=[text],
+            input_type="search_query",
+            truncate=self.truncate,
+        ).embeddings
+        return [list(map(float, e)) for e in embeddings][0]
 
     async def aembed_query(self, text: str) -> List[float]:
         """Async call out to Cohere's embedding endpoint.
@@ -125,5 +137,10 @@ class CohereEmbeddings(BaseModel, Embeddings):
         Returns:
             Embeddings for the text.
         """
-        embeddings = await self.aembed_documents([text])
-        return embeddings[0]
+        embeddings = await self.async_client.embed(
+            model=self.model,
+            texts=[text],
+            input_type="search_query",
+            truncate=self.truncate,
+        )
+        return [list(map(float, e)) for e in embeddings.embeddings][0]