1 files changed, 50 insertions, 0 deletions
diff --git a/server/continuedev/libs/llm/google_palm_api.py b/server/continuedev/libs/llm/google_palm_api.py
new file mode 100644
index 00000000..3379fefe
--- /dev/null
+++ b/server/continuedev/libs/llm/google_palm_api.py
@@ -0,0 +1,50 @@
+from typing import List
+
+import requests
+from pydantic import Field
+
+from ...core.main import ChatMessage
+from .base import LLM
+
+
+class GooglePaLMAPI(LLM):
+    """
+    The Google PaLM API is currently in public preview, so production applications are not supported yet. However, you can [create an API key in Google MakerSuite](https://makersuite.google.com/u/2/app/apikey) and begin trying out the `chat-bison-001` model. Change `~/.continue/config.py` to look like this:
+
+    ```python title="~/.continue/config.py"
+    from continuedev.core.models import Models
+    from continuedev.libs.llm.hf_inference_api import GooglePaLMAPI
+
+    config = ContinueConfig(
+        ...
+        models=Models(
+            default=GooglePaLMAPI(
+                model="chat-bison-001"
+                api_key="<MAKERSUITE_API_KEY>",
+        )
+    )
+    ```
+    """
+
+    api_key: str = Field(..., description="Google PaLM API key")
+
+    model: str = "chat-bison-001"
+
+    async def _stream_complete(self, prompt, options):
+        api_url = f"https://generativelanguage.googleapis.com/v1beta2/models/{self.model}:generateMessage?key={self.api_key}"
+        body = {"prompt": {"messages": [{"content": prompt}]}}
+        response = requests.post(api_url, json=body)
+        yield response.json()["candidates"][0]["content"]
+
+    async def _stream_chat(self, messages: List[ChatMessage], options):
+        msg_lst = []
+        for message in messages:
+            msg_lst.append({"content": message["content"]})
+
+        api_url = f"https://generativelanguage.googleapis.com/v1beta2/models/{self.model}:generateMessage?key={self.api_key}"
+        body = {"prompt": {"messages": msg_lst}}
+        response = requests.post(api_url, json=body)
+        yield {
+            "content": response.json()["candidates"][0]["content"],
+            "role": "assistant",
+        }