Fix LLM types so that they can be loaded from config dicts (#6235)

LLM configurations can be loaded from a Python dict (or JSON file
deserialized as dict) using the
[load_llm_from_config](8e1a7a8646/langchain/llms/loading.py (L12))
function.

However, the type string in the `type_to_cls_dict` lookup dict differs
from the type string defined in some LLM classes. This means that the
LLM object can be saved, but not loaded again, because the type strings
differ.

langchain/llms/aleph_alpha.py

@@ -23,7 +23,7 @@ class AlephAlpha(LLM):
         .. code-block:: python
 
             from langchain.llms import AlephAlpha
-            alpeh_alpha = AlephAlpha(aleph_alpha_api_key="my-api-key")
+            aleph_alpha = AlephAlpha(aleph_alpha_api_key="my-api-key")
     """
 
     client: Any  #: :meta private:
@@ -199,7 +199,7 @@ class AlephAlpha(LLM):
     @property
     def _llm_type(self) -> str:
         """Return type of llm."""
-        return "alpeh_alpha"
+        return "aleph_alpha"
 
     def _call(
         self,
@@ -220,7 +220,7 @@ class AlephAlpha(LLM):
         Example:
             .. code-block:: python
 
-                response = alpeh_alpha("Tell me a joke.")
+                response = aleph_alpha("Tell me a joke.")
         """
         from aleph_alpha_client import CompletionRequest, Prompt
 

langchain/llms/bananadev.py

@@ -80,7 +80,7 @@ class Banana(LLM):
     @property
     def _llm_type(self) -> str:
         """Return type of llm."""
-        return "banana"
+        return "bananadev"
 
     def _call(
         self,

langchain/llms/huggingface_text_gen_inference.py

@@ -106,7 +106,7 @@ class HuggingFaceTextGenInference(LLM):
     @property
     def _llm_type(self) -> str:
         """Return type of llm."""
-        return "hf_textgen_inference"
+        return "huggingface_textgen_inference"
 
     def _call(
         self,

langchain/llms/llamacpp.py

@@ -168,7 +168,7 @@ class LlamaCpp(LLM):
     @property
     def _llm_type(self) -> str:
         """Return type of llm."""
-        return "llama.cpp"
+        return "llamacpp"
 
     def _get_parameters(self, stop: Optional[List[str]] = None) -> Dict[str, Any]:
         """

langchain/llms/mosaicml.py

@@ -86,7 +86,7 @@ class MosaicML(LLM):
     @property
     def _llm_type(self) -> str:
         """Return type of llm."""
-        return "mosaicml"
+        return "mosaic"
 
     def _transform_prompt(self, prompt: str) -> str:
         """Transform prompt."""

langchain/llms/rwkv.py

@@ -140,7 +140,7 @@ class RWKV(LLM, BaseModel):
     @property
     def _llm_type(self) -> str:
         """Return the type of llm."""
-        return "rwkv-4"
+        return "rwkv"
 
     def run_rnn(self, _tokens: List[str], newline_adj: int = 0) -> Any:
         AVOID_REPEAT_TOKENS = []