1 files changed, 156 insertions, 0 deletions
diff --git a/server/continuedev/libs/llm/openai.py b/server/continuedev/libs/llm/openai.py
new file mode 100644
index 00000000..ba29279b
--- /dev/null
+++ b/server/continuedev/libs/llm/openai.py
@@ -0,0 +1,156 @@
+from typing import Callable, List, Literal, Optional
+
+import certifi
+import openai
+from pydantic import Field
+
+from ...core.main import ChatMessage
+from .base import LLM
+
+CHAT_MODELS = {
+    "gpt-3.5-turbo",
+    "gpt-3.5-turbo-16k",
+    "gpt-4",
+    "gpt-3.5-turbo-0613",
+    "gpt-4-32k",
+}
+MAX_TOKENS_FOR_MODEL = {
+    "gpt-3.5-turbo": 4096,
+    "gpt-3.5-turbo-0613": 4096,
+    "gpt-3.5-turbo-16k": 16_384,
+    "gpt-4": 8192,
+    "gpt-35-turbo-16k": 16_384,
+    "gpt-35-turbo-0613": 4096,
+    "gpt-35-turbo": 4096,
+    "gpt-4-32k": 32_768,
+}
+
+
+class OpenAI(LLM):
+    """
+    The OpenAI class can be used to access OpenAI models like gpt-4 and gpt-3.5-turbo.
+
+    If you are locally serving a model that uses an OpenAI-compatible server, you can simply change the `api_base` in the `OpenAI` class like this:
+
+    ```python title="~/.continue/config.py"
+    from continuedev.libs.llm.openai import OpenAI
+
+    config = ContinueConfig(
+        ...
+        models=Models(
+            default=OpenAI(
+                api_key="EMPTY",
+                model="<MODEL_NAME>",
+                api_base="http://localhost:8000", # change to your server
+            )
+        )
+    )
+    ```
+
+    Options for serving models locally with an OpenAI-compatible server include:
+
+    - [text-gen-webui](https://github.com/oobabooga/text-generation-webui/tree/main/extensions/openai#setup--installation)
+    - [FastChat](https://github.com/lm-sys/FastChat/blob/main/docs/openai_api.md)
+    - [LocalAI](https://localai.io/basics/getting_started/)
+    - [llama-cpp-python](https://github.com/abetlen/llama-cpp-python#web-server)
+    """
+
+    api_key: str = Field(
+        ...,
+        description="OpenAI API key",
+    )
+
+    proxy: Optional[str] = Field(None, description="Proxy URL to use for requests.")
+
+    api_base: Optional[str] = Field(None, description="OpenAI API base URL.")
+
+    api_type: Optional[Literal["azure", "openai"]] = Field(
+        None, description="OpenAI API type."
+    )
+
+    api_version: Optional[str] = Field(
+        None, description="OpenAI API version. For use with Azure OpenAI Service."
+    )
+
+    engine: Optional[str] = Field(
+        None, description="OpenAI engine. For use with Azure OpenAI Service."
+    )
+
+    async def start(
+        self, unique_id: Optional[str] = None, write_log: Callable[[str], None] = None
+    ):
+        await super().start(write_log=write_log, unique_id=unique_id)
+
+        if self.context_length is None:
+            self.context_length = MAX_TOKENS_FOR_MODEL.get(self.model, 4096)
+
+        openai.api_key = self.api_key
+        if self.api_type is not None:
+            openai.api_type = self.api_type
+        if self.api_base is not None:
+            openai.api_base = self.api_base
+        if self.api_version is not None:
+            openai.api_version = self.api_version
+
+        if self.verify_ssl is not None and self.verify_ssl is False:
+            openai.verify_ssl_certs = False
+
+        if self.proxy is not None:
+            openai.proxy = self.proxy
+
+        openai.ca_bundle_path = self.ca_bundle_path or certifi.where()
+
+    def collect_args(self, options):
+        args = super().collect_args(options)
+        if self.engine is not None:
+            args["engine"] = self.engine
+
+        if not args["model"].endswith("0613") and "functions" in args:
+            del args["functions"]
+
+        return args
+
+    async def _stream_complete(self, prompt, options):
+        args = self.collect_args(options)
+        args["stream"] = True
+
+        if args["model"] in CHAT_MODELS:
+            async for chunk in await openai.ChatCompletion.acreate(
+                messages=[{"role": "user", "content": prompt}],
+                **args,
+                headers=self.headers,
+            ):
+                if len(chunk.choices) > 0 and "content" in chunk.choices[0].delta:
+                    yield chunk.choices[0].delta.content
+        else:
+            async for chunk in await openai.Completion.acreate(prompt=prompt, **args, headers=self.headers):
+                if len(chunk.choices) > 0:
+                    yield chunk.choices[0].text
+
+    async def _stream_chat(self, messages: List[ChatMessage], options):
+        args = self.collect_args(options)
+
+        async for chunk in await openai.ChatCompletion.acreate(
+            messages=messages,
+            stream=True,
+            **args,
+            headers=self.headers,
+        ):
+            if not hasattr(chunk, "choices") or len(chunk.choices) == 0:
+                continue
+            yield chunk.choices[0].delta
+
+    async def _complete(self, prompt: str, options):
+        args = self.collect_args(options)
+
+        if args["model"] in CHAT_MODELS:
+            resp = await openai.ChatCompletion.acreate(
+                messages=[{"role": "user", "content": prompt}],
+                **args,
+                headers=self.headers,
+            )
+            return resp.choices[0].message.content
+        else:
+            return (
+                (await openai.Completion.acreate(prompt=prompt, **args, headers=self.headers)).choices[0].text
+            )