diff --git a/README.md b/README.md
index 93bb986..dd48779 100644
--- a/README.md
+++ b/README.md
@@ -6,8 +6,8 @@
 
 Originally based on [Tom Dörr's `fish.codex` repository](https://github.com/tom-doerr/codex.fish),
 but with some additional functionality. It uses the [chat completions API endpoint](https://platform.openai.com/docs/api-reference/chat/create)
-and can be hooked up to OpenAI, Azure OpenAI or a self-hosted LLM behind any
-OpenAI-compatible API.
+and can be hooked up to Google, OpenAI, Azure OpenAI or a self-hosted LLM
+behind any OpenAI-compatible API.
 
 Continuous integration is performed against Azure OpenAI.
 
@@ -60,6 +60,17 @@ model = <your deployment name>
 api_key = <your API key>
 ```
 
+If you use [Gemini](https://deepmind.google/technologies/gemini):
+
+```ini
+[fish-ai]
+configuration = gemini
+
+[gemini]
+provider = google
+api_key = <your API key>
+```
+
 ### Install `fish-ai`
 
 Install the plugin. You can install it using [`fisher`](https://github.com/jorgebucaran/fisher).
diff --git a/conf.d/fish_ai.fish b/conf.d/fish_ai.fish
index 57d73c8..624bc67 100644
--- a/conf.d/fish_ai.fish
+++ b/conf.d/fish_ai.fish
@@ -24,11 +24,11 @@ end
 ##
 function _fish_ai_install --on-event fish_ai_install
     python3 -m venv ~/.fish-ai
-    ~/.fish-ai/bin/pip install -qq openai
+    ~/.fish-ai/bin/pip install -qq openai google-generativeai
 end
 
 function _fish_ai_update --on-event fish_ai_update
-    ~/.fish-ai/bin/pip install -qq --upgrade openai
+    ~/.fish-ai/bin/pip install -qq --upgrade openai google-generativeai
 end
 
 function __fish_ai_uninstall --on-event fish_ai_uninstall
diff --git a/functions/_fish_ai_engine.py b/functions/_fish_ai_engine.py
index 25c06e2..099bcf7 100644
--- a/functions/_fish_ai_engine.py
+++ b/functions/_fish_ai_engine.py
@@ -2,6 +2,7 @@
 
 from openai import OpenAI
 from openai import AzureOpenAI
+import google.generativeai as genai
 from configparser import ConfigParser
 from os import path
 import logging
@@ -49,7 +50,7 @@ def get_config(key):
     return config.get(section=active_section, option=key)
 
 
-def get_client():
+def get_openai_client():
     if (get_config('provider') == 'azure'):
         return AzureOpenAI(
             azure_endpoint=get_config('server'),
@@ -72,18 +73,55 @@ def get_client():
                         .format(get_config('provider')))
 
 
+def create_message_history(messages):
+    """
+    Create message history which can be used with Gemini.
+    Google uses a different chat history format than OpenAI.
+    The message content should be put in a parts array and
+    system messages are not supported.
+    """
+    outputs = []
+    system_messages = []
+    for message in messages:
+        if message.get('role') == 'system':
+            system_messages.append(message.get('content'))
+    for i in range(len(messages) - 1):
+        message = messages[i]
+        if message.get('role') == 'user':
+            outputs.append({
+                'role': 'user',
+                'parts': system_messages + [message.get('content')] if i == 0
+                else [message.get('content')]
+            })
+        elif message.get('role') == 'assistant':
+            outputs.append({
+                'role': 'model',
+                'parts': [message.get('content')]
+            })
+    return outputs
+
+
 def get_response(messages):
     start_time = time_ns()
-    completions = get_client().chat.completions.create(
-        model=get_config('model'),
-        max_tokens=4096,
-        messages=messages,
-        stream=False,
-        temperature=float(get_config('temperature') or '0.2'),
-        n=1,
-    )
+
+    if get_config('provider') == 'google':
+        genai.configure(api_key=get_config('api_key'))
+        model = genai.GenerativeModel(get_config('model') or 'gemini-pro')
+        chat = model.start_chat(history=create_message_history(messages))
+        response = (chat.send_message(messages[-1].get('content'))
+                    .text.strip(' `'))
+    else:
+        completions = get_openai_client().chat.completions.create(
+            model=get_config('model'),
+            max_tokens=4096,
+            messages=messages,
+            stream=False,
+            temperature=float(get_config('temperature') or '0.2'),
+            n=1,
+        )
+        response = completions.choices[0].message.content.strip(' `')
+
     end_time = time_ns()
-    response = completions.choices[0].message.content.strip(' `')
     get_logger().debug('Response received from backend: ' + response)
     get_logger().debug('Processing time: ' +
                        str(round((end_time - start_time) / 1000000)) + ' ms.')