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-rw-r--r--continuedev/src/continuedev/core/config.py2
-rw-r--r--continuedev/src/continuedev/core/sdk.py16
-rw-r--r--continuedev/src/continuedev/libs/llm/anthropic.py81
-rw-r--r--continuedev/src/continuedev/steps/chat.py2
4 files changed, 98 insertions, 3 deletions
diff --git a/continuedev/src/continuedev/core/config.py b/continuedev/src/continuedev/core/config.py
index 6e430c04..05ba48c6 100644
--- a/continuedev/src/continuedev/core/config.py
+++ b/continuedev/src/continuedev/core/config.py
@@ -76,7 +76,7 @@ class ContinueConfig(BaseModel):
server_url: Optional[str] = None
allow_anonymous_telemetry: Optional[bool] = True
default_model: Literal["gpt-3.5-turbo", "gpt-3.5-turbo-16k",
- "gpt-4"] = 'gpt-4'
+ "gpt-4", "claude-2"] = 'gpt-4'
custom_commands: Optional[List[CustomCommand]] = [CustomCommand(
name="test",
description="This is an example custom command. Use /config to edit it and create more",
diff --git a/continuedev/src/continuedev/core/sdk.py b/continuedev/src/continuedev/core/sdk.py
index d73561d2..28487600 100644
--- a/continuedev/src/continuedev/core/sdk.py
+++ b/continuedev/src/continuedev/core/sdk.py
@@ -11,6 +11,7 @@ from ..models.filesystem_edit import FileEdit, FileSystemEdit, AddFile, DeleteFi
from ..models.filesystem import RangeInFile
from ..libs.llm.hf_inference_api import HuggingFaceInferenceAPI
from ..libs.llm.openai import OpenAI
+from ..libs.llm.anthropic import Anthropic
from .observation import Observation
from ..server.ide_protocol import AbstractIdeProtocolServer
from .main import Context, ContinueCustomException, History, Step, ChatMessage
@@ -26,7 +27,7 @@ ModelProvider = Literal["openai", "hf_inference_api", "ggml", "anthropic"]
MODEL_PROVIDER_TO_ENV_VAR = {
"openai": "OPENAI_API_KEY",
"hf_inference_api": "HUGGING_FACE_TOKEN",
- "anthropic": "ANTHROPIC_API_KEY"
+ "anthropic": "ANTHROPIC_API_KEY",
}
@@ -40,6 +41,9 @@ class Models:
@classmethod
async def create(cls, sdk: "ContinueSDK", with_providers: List[ModelProvider] = ["openai"]) -> "Models":
+ if sdk.config.default_model == "claude-2":
+ with_providers.append("anthropic")
+
models = Models(sdk, with_providers)
for provider in with_providers:
if provider in MODEL_PROVIDER_TO_ENV_VAR:
@@ -59,6 +63,14 @@ class Models:
api_key = self.provider_keys["hf_inference_api"]
return HuggingFaceInferenceAPI(api_key=api_key, model=model)
+ def __load_anthropic_model(self, model: str) -> Anthropic:
+ api_key = self.provider_keys["anthropic"]
+ return Anthropic(api_key=api_key, model=model)
+
+ @cached_property
+ def claude2(self):
+ return self.__load_anthropic_model("claude-2")
+
@cached_property
def starcoder(self):
return self.__load_hf_inference_api_model("bigcode/starcoder")
@@ -88,6 +100,8 @@ class Models:
return self.gpt3516k
elif model_name == "gpt-4":
return self.gpt4
+ elif model_name == "claude-2":
+ return self.claude2
else:
raise Exception(f"Unknown model {model_name}")
diff --git a/continuedev/src/continuedev/libs/llm/anthropic.py b/continuedev/src/continuedev/libs/llm/anthropic.py
new file mode 100644
index 00000000..2b8831f0
--- /dev/null
+++ b/continuedev/src/continuedev/libs/llm/anthropic.py
@@ -0,0 +1,81 @@
+
+from functools import cached_property
+import time
+from typing import Any, Coroutine, Dict, Generator, List, Union
+from ...core.main import ChatMessage
+from anthropic import Anthropic, HUMAN_PROMPT, AI_PROMPT
+from ..llm import LLM
+from ..util.count_tokens import DEFAULT_MAX_TOKENS, compile_chat_messages, CHAT_MODELS, DEFAULT_ARGS, count_tokens, prune_raw_prompt_from_top
+
+
+class AnthropicLLM(LLM):
+ api_key: str
+ default_model: str
+ anthropic: Anthropic
+
+ def __init__(self, api_key: str, default_model: str, system_message: str = None):
+ self.api_key = api_key
+ self.default_model = default_model
+ self.system_message = system_message
+
+ self.anthropic = Anthropic(api_key)
+
+ @cached_property
+ def name(self):
+ return self.default_model
+
+ @property
+ def default_args(self):
+ return {**DEFAULT_ARGS, "model": self.default_model}
+
+ def count_tokens(self, text: str):
+ return count_tokens(self.default_model, text)
+
+ def __messages_to_prompt(self, messages: List[ChatMessage]) -> str:
+ prompt = ""
+ for msg in messages:
+ prompt += f"{HUMAN_PROMPT if msg.role == 'user' else AI_PROMPT} {msg.content} "
+
+ return prompt
+
+ async def stream_complete(self, prompt, with_history: List[ChatMessage] = [], **kwargs) -> Generator[Union[Any, List, Dict], None, None]:
+ args = self.default_args.copy()
+ args.update(kwargs)
+ args["stream"] = True
+
+ async for chunk in await self.anthropic.completions.create(
+ model=args["model"],
+ max_tokens_to_sample=args["max_tokens"],
+ prompt=f"{HUMAN_PROMPT} {prompt} {AI_PROMPT}",
+ **args
+ ):
+ yield chunk.completion
+
+ async def stream_chat(self, messages: List[ChatMessage] = [], **kwargs) -> Generator[Union[Any, List, Dict], None, None]:
+ args = self.default_args.copy()
+ args.update(kwargs)
+ args["stream"] = True
+
+ messages = compile_chat_messages(
+ args["model"], messages, args["max_tokens"], functions=args.get("functions", None))
+ async for chunk in await self.anthropic.completions.create(
+ model=args["model"],
+ max_tokens_to_sample=args["max_tokens"],
+ prompt=self.__messages_to_prompt(messages),
+ **args
+ ):
+ yield chunk.completion
+
+ async def complete(self, prompt: str, with_history: List[ChatMessage] = [], **kwargs) -> Coroutine[Any, Any, str]:
+ args = {**self.default_args, **kwargs}
+
+ messages = compile_chat_messages(
+ args["model"], with_history, args["max_tokens"], prompt, functions=None)
+ resp = (await self.anthropic.completions.create(
+ model=args["model"],
+ max_tokens_to_sample=args["max_tokens"],
+ prompt=self.__messages_to_prompt(messages),
+ **args
+ )).completion
+
+ return resp
diff --git a/continuedev/src/continuedev/steps/chat.py b/continuedev/src/continuedev/steps/chat.py
index 14a1cd41..3751dec2 100644
--- a/continuedev/src/continuedev/steps/chat.py
+++ b/continuedev/src/continuedev/steps/chat.py
@@ -28,7 +28,7 @@ class SimpleChatStep(Step):
completion = ""
messages = self.messages or await sdk.get_chat_context()
- generator = sdk.models.gpt4.stream_chat(messages, temperature=0.5)
+ generator = sdk.models.default.stream_chat(messages, temperature=0.5)
try:
async for chunk in generator:
if sdk.current_step_was_deleted():