feat(model): support InternLM

pilot/componet.py

@@ -1,7 +1,8 @@
 from __future__ import annotations
 
 from abc import ABC, abstractmethod
-from typing import Type, Dict, TypeVar, Optional, TYPE_CHECKING
+from typing import Type, Dict, TypeVar, Optional, Union, TYPE_CHECKING
+from enum import Enum
 import asyncio
 
 # Checking for type hints during runtime
@@ -37,6 +38,10 @@ class LifeCycle:
         pass
 
 
+class ComponetType(str, Enum):
+    WORKER_MANAGER = "dbgpt_worker_manager"
+
+
 class BaseComponet(LifeCycle, ABC):
     """Abstract Base Component class. All custom components should extend this."""
 
@@ -80,11 +85,20 @@ class SystemApp(LifeCycle):
 
     def register_instance(self, instance: T):
         """Register an already initialized component."""
-        self.componets[instance.name] = instance
+        name = instance.name
+        if isinstance(name, ComponetType):
+            name = name.value
+        if name in self.componets:
+            raise RuntimeError(
+                f"Componse name {name} already exists: {self.componets[name]}"
+            )
+        self.componets[name] = instance
         instance.init_app(self)
 
-    def get_componet(self, name: str, componet_type: Type[T]) -> T:
+    def get_componet(self, name: Union[str, ComponetType], componet_type: Type[T]) -> T:
         """Retrieve a registered component by its name and type."""
+        if isinstance(name, ComponetType):
+            name = name.value
         component = self.componets.get(name)
         if not component:
             raise ValueError(f"No component found with name {name}")

pilot/configs/model_config.py

@@ -69,6 +69,9 @@ LLM_MODEL_CONFIG = {
     # (Llama2 based) We only support WizardLM-13B-V1.2 for now, which is trained from Llama-2 13b, see https://huggingface.co/WizardLM/WizardLM-13B-V1.2
     "wizardlm-13b": os.path.join(MODEL_PATH, "WizardLM-13B-V1.2"),
     "llama-cpp": os.path.join(MODEL_PATH, "ggml-model-q4_0.bin"),
+    # https://huggingface.co/internlm/internlm-chat-7b-v1_1, 7b vs 7b-v1.1: https://github.com/InternLM/InternLM/issues/288
+    "internlm-7b": os.path.join(MODEL_PATH, "internlm-chat-7b-v1_1"),
+    "internlm-7b-8k": os.path.join(MODEL_PATH, "internlm-chat-7b-8k"),
 }
 
 EMBEDDING_MODEL_CONFIG = {

pilot/model/adapter.py

@@ -411,6 +411,29 @@ class LlamaCppAdapater(BaseLLMAdaper):
         return model, tokenizer
 
 
+class InternLMAdapter(BaseLLMAdaper):
+    """The model adapter for internlm/internlm-chat-7b"""
+
+    def match(self, model_path: str):
+        return "internlm" in model_path.lower()
+
+    def loader(self, model_path: str, from_pretrained_kwargs: dict):
+        revision = from_pretrained_kwargs.get("revision", "main")
+        model = AutoModelForCausalLM.from_pretrained(
+            model_path,
+            low_cpu_mem_usage=True,
+            trust_remote_code=True,
+            **from_pretrained_kwargs,
+        )
+        model = model.eval()
+        if "8k" in model_path.lower():
+            model.config.max_sequence_length = 8192
+        tokenizer = AutoTokenizer.from_pretrained(
+            model_path, use_fast=False, trust_remote_code=True, revision=revision
+        )
+        return model, tokenizer
+
+
 register_llm_model_adapters(VicunaLLMAdapater)
 register_llm_model_adapters(ChatGLMAdapater)
 register_llm_model_adapters(GuanacoAdapter)
@@ -421,6 +444,7 @@ register_llm_model_adapters(Llama2Adapter)
 register_llm_model_adapters(BaichuanAdapter)
 register_llm_model_adapters(WizardLMAdapter)
 register_llm_model_adapters(LlamaCppAdapater)
+register_llm_model_adapters(InternLMAdapter)
 # TODO Default support vicuna, other model need to tests and Evaluate
 
 # just for test_py, remove this later

pilot/model/conversation.py

@@ -2,6 +2,8 @@
 Fork from fastchat: https://github.com/lm-sys/FastChat/blob/main/fastchat/conversation.py
 
 Conversation prompt templates.
+
+TODO Using fastchat core package
 """
 
 import dataclasses
@@ -366,4 +368,21 @@ register_conv_template(
     )
 )
 
+# Internlm-chat template
+register_conv_template(
+    Conversation(
+        name="internlm-chat",
+        system="A chat between a curious <|User|> and an <|Bot|>. The <|Bot|> gives helpful, detailed, and polite answers to the <|User|>'s questions.\n\n",
+        roles=("<|User|>", "<|Bot|>"),
+        messages=(),
+        offset=0,
+        sep_style=SeparatorStyle.CHATINTERN,
+        sep="<eoh>",
+        sep2="<eoa>",
+        stop_token_ids=[1, 103028],
+        stop_str="<eoa>",
+    )
+)
+
+
 # TODO Support other model conversation template

pilot/server/chat_adapter.py

@@ -247,6 +247,16 @@ class LlamaCppChatAdapter(BaseChatAdpter):
         return generate_stream
 
 
+class InternLMChatAdapter(BaseChatAdpter):
+    """The model adapter for internlm/internlm-chat-7b"""
+
+    def match(self, model_path: str):
+        return "internlm" in model_path.lower()
+
+    def get_conv_template(self, model_path: str) -> Conversation:
+        return get_conv_template("internlm-chat")
+
+
 register_llm_model_chat_adapter(VicunaChatAdapter)
 register_llm_model_chat_adapter(ChatGLMChatAdapter)
 register_llm_model_chat_adapter(GuanacoChatAdapter)
@@ -257,6 +267,7 @@ register_llm_model_chat_adapter(Llama2ChatAdapter)
 register_llm_model_chat_adapter(BaichuanChatAdapter)
 register_llm_model_chat_adapter(WizardLMChatAdapter)
 register_llm_model_chat_adapter(LlamaCppChatAdapter)
+register_llm_model_chat_adapter(InternLMChatAdapter)
 
 # Proxy model for test and develop, it's cheap for us now.
 register_llm_model_chat_adapter(ProxyllmChatAdapter)