diff --git a/minichain/backend.py b/minichain/backend.py
index ebae501..2292588 100644
--- a/minichain/backend.py
+++ b/minichain/backend.py
@@ -4,7 +4,8 @@
 from dataclasses import dataclass
 from types import TracebackType
 from typing import TYPE_CHECKING, Any, Dict, Iterator, List, Optional, Tuple
-
+import litellm
+from litellm import completion, embedding
 from eliot import start_action, to_file
 
 if TYPE_CHECKING:
@@ -190,29 +191,13 @@ def run(self, request: str) -> str:
         import manifest
 
         chat = {"gpt-4", "gpt-3.5-turbo"}
-        manifest = manifest.Manifest(
-            client_name="openaichat" if self.model in chat else "openai",
-            max_tokens=self.options["max_tokens"],
-            cache_name="sqlite",
-            cache_connection=f"{MinichainContext.name}",
-        )
+        messages=[{"role": "user", "content": request}]
+        ans = completion(model=self.model, messages=messages, stop=self.stop)
 
-        ans = manifest.run(
-            request,
-            stop_sequences=self.stop,
-        )
-        return str(ans)
+        return ans["choices"][0]["messages"]["content"]
 
     def run_stream(self, prompt: str) -> Iterator[str]:
-        import openai
-
-        self.api_key = os.environ.get("OPENAI_API_KEY")
-        assert (
-            self.api_key
-        ), "Need an OPENAI_API_KEY. Get one here https://openai.com/api/"
-        openai.api_key = self.api_key
-
-        for chunk in openai.ChatCompletion.create(
+        for chunk in completion(
             model=self.model,
             messages=[{"role": "user", "content": prompt}],
             stream=True,
@@ -233,14 +218,13 @@ def __init__(self, model: str = "text-embedding-ada-002", **kwargs: Any) -> None
     def run(self, request: str) -> str:
         import openai
 
-        self.api_key = os.environ.get("OPENAI_API_KEY")
+        litellm.openai_key = os.environ.get("OPENAI_API_KEY")
         assert (
-            self.api_key
+            litellm.openai_key
         ), "Need an OPENAI_API_KEY. Get one here https://openai.com/api/"
-        openai.api_key = self.api_key
 
-        ans = openai.Embedding.create(
-            engine=self.model,
+        ans = embedding(
+            model=self.model,
             input=request,
         )
         return ans["data"][0]["embedding"]  # type: ignore