diff --git a/config.example.json b/config.example.json
index 7c51646..f4bfb7a 100644
--- a/config.example.json
+++ b/config.example.json
@@ -20,6 +20,7 @@
   "scraper_timeout": 300,
   "outreach_message_subject": "I have a question...",
   "outreach_message_body_file": "outreach_message.html",
+  "gemini_api_key": "",
   "assembly_ai_api_key": "",
   "font": "bold_font.ttf",
   "imagemagick_path": "Path to magick.exe or on linux/macOS just /usr/bin/convert"
diff --git a/docs/AffiliateMarketing.md b/docs/AffiliateMarketing.md
index e7c803e..53c82ca 100644
--- a/docs/AffiliateMarketing.md
+++ b/docs/AffiliateMarketing.md
@@ -1,6 +1,6 @@
 # AFM
 
-This class is responsible for the Affiliate Marketing part of MPV2. It uses the `g4f` package (as all other classes) as it's way to utilize the power of LLMs, in this case, to generate tweets, based on information about an **Amazon Product**. MPV2 will scrape the page of the product, and save the **product title**, and **product features**, thus having enough information to be able to create a pitch for the product, and post it on Twitter.
+This class is responsible for the Affiliate Marketing part of MPV2. It uses the `g4f` or `google_gen_ai` package (as all other classes) as it's way to utilize the power of LLMs, in this case, to generate tweets, based on information about an **Amazon Product**. MPV2 will scrape the page of the product, and save the **product title**, and **product features**, thus having enough information to be able to create a pitch for the product, and post it on Twitter.
 
 ## Relevant Configuration
 
diff --git a/docs/Configuration.md b/docs/Configuration.md
index 0658032..c0dfe92 100644
--- a/docs/Configuration.md
+++ b/docs/Configuration.md
@@ -14,6 +14,7 @@ All your configurations will be in a file in the root directory, called `config.
     * `llama2_13b`
     * `llama2_70b`
     * `mixtral_8x7b`
+    *  `google`
 - `image_prompt_llm`: `string` - The Large Language Model that will be used to generate image prompts. If left empty, the default model (`gpt35_turbo`) will be used. Here are your choices:
     * `gpt4`
     * `gpt35_turbo`
@@ -45,6 +46,7 @@ All your configurations will be in a file in the root directory, called `config.
 - `scraper_timeout`: `number` - The timeout for the Google Maps scraper.
 - `outreach_message_subject`: `string` - The subject of your outreach message. `{{COMPANY_NAME}}` will be replaced with the company name.
 - `outreach_message_body_file`: `string` - The file that contains the body of your outreach message, should be HTML. `{{COMPANY_NAME}}` will be replaced with the company name.
+- `gemini_api_key`: `string` - Your Google Gemini API key. Get yours from [here](https://ai.google.dev)
 - `assembly_ai_api_key`: `string` - Your Assembly AI API key. Get yours from [here](https://www.assemblyai.com/app/).
 - `font`: `string` - The font that will be used to generate images. This should be a `.ttf` file in the `fonts/` directory.
 - `imagemagick_path`: `string` - The path to the ImageMagick binary. This is used by MoviePy to manipulate images. Install ImageMagick from [here](https://imagemagick.org/script/download.php) and set the path to the `magick.exe` on Windows, or on Linux/MacOS the path to `convert` (usually /usr/bin/convert).
diff --git a/requirements.txt b/requirements.txt
index de671b3..fcf52ac 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -14,3 +14,4 @@ assemblyai
 srt_equalizer
 undetected_chromedriver
 platformdirs
+google-generativeai
diff --git a/src/classes/AFM.py b/src/classes/AFM.py
index 044934f..168a781 100644
--- a/src/classes/AFM.py
+++ b/src/classes/AFM.py
@@ -99,6 +99,17 @@ def generate_response(self, prompt: str) -> str:
         Returns:
             response (str): The response for the user.
         """
+        if get_model() == "google":
+            import google.generativeai as genai
+
+            genai.configure(api_key=get_gemini_api_key())
+
+            model = genai.GenerativeModel('gemini-pro')
+
+            response: str = model.generate_content(prompt).text
+
+            return response
+
         # Generate the response
         response: str = g4f.ChatCompletion.create(
             model=parse_model(get_model()),
diff --git a/src/classes/Twitter.py b/src/classes/Twitter.py
index 020122f..de5a85c 100644
--- a/src/classes/Twitter.py
+++ b/src/classes/Twitter.py
@@ -175,15 +175,24 @@ def generate_post(self) -> str:
         Returns:
             post (str): The post
         """
-        completion = g4f.ChatCompletion.create(
-            model=parse_model(get_model()),
-            messages=[
-                {
-                    "role": "user",
-                    "content": f"Generate a Twitter post about: {self.topic} in {get_twitter_language()}. The Limit is 2 sentences. Choose a specific sub-topic of the provided topic."
-                }
-            ]
-        )
+        if get_model() == "google":
+            import google.generativeai as genai
+
+            genai.configure(api_key=get_gemini_api_key())
+            prompt = f"Generate a Twitter post about: {self.topic} in {get_twitter_language()}. The Limit is 2 sentences. Choose a specific sub-topic of the provided topic."
+            model = genai.GenerativeModel('gemini-pro')
+
+            completion = model.generate_content(prompt).text
+        else:
+            completion = g4f.ChatCompletion.create(
+                model=parse_model(get_model()),
+                messages=[
+                    {
+                        "role": "user",
+                        "content": f"Generate a Twitter post about: {self.topic} in {get_twitter_language()}. The Limit is 2 sentences. Choose a specific sub-topic of the provided topic."
+                    }
+                ]
+            )
 
         if get_verbose():
             info("Generating a post...")
diff --git a/src/classes/YouTube.py b/src/classes/YouTube.py
index 8250278..aa069cc 100644
--- a/src/classes/YouTube.py
+++ b/src/classes/YouTube.py
@@ -112,6 +112,17 @@ def generate_response(self, prompt: str, model: any = None) -> str:
         Returns:
             response (str): The generated AI Repsonse.
         """
+        if get_model() == "google":
+            import google.generativeai as genai
+
+            genai.configure(api_key=get_gemini_api_key())
+
+            model = genai.GenerativeModel('gemini-pro')
+
+            response: str = model.generate_content(prompt).text
+
+            return response
+
         if not model:
             return g4f.ChatCompletion.create(
                 model=parse_model(get_model()),
diff --git a/src/config.py b/src/config.py
index 17c8790..7e2821f 100644
--- a/src/config.py
+++ b/src/config.py
@@ -188,6 +188,15 @@ def get_outreach_message_body_file() -> str:
     """
     with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
         return json.load(file)["outreach_message_body_file"]
+def get_gemini_api_key() -> str:
+    """
+    Gets the Google Gemini API key.
+
+    Returns:
+        key (str): The Gemini API key
+    """
+    with open(os.path.join(ROOT_DIR, "config.json"), "r") as file:
+        return json.load(file)["gemini_api_key"]
 
 def get_assemblyai_api_key() -> str:
     """