diff --git a/main.py b/main.py
index d5ac0b2b..45b5c7ac 100644
--- a/main.py
+++ b/main.py
@@ -94,6 +94,15 @@ def flatten_structure(self, structure):
                 sections.extend(self.flatten_structure(content))
         return sections
 
+    def reset_content(self, title):
+        self.contents[title] = ""
+
+    def get_content(self, title):
+        try:
+            return self.contents[title]
+        except KeyError as e:
+            pass
+
     def update_content(self, title, new_content):
         try:
             self.contents[title] += new_content
@@ -253,6 +262,37 @@ def generate_section(transcript: str, existing_notes: str, section: str, model:
             statistics_to_return = GenerationStatistics(input_time=usage.prompt_time, output_time=usage.completion_time, input_tokens=usage.prompt_tokens, output_tokens=usage.completion_tokens, total_time=usage.total_time, model_name=model)
             yield statistics_to_return
 
+def translate_content(text: str, language: str, model: str = "llama3-8b-8192"):
+    stream = st.session_state.groq.chat.completions.create(
+        model=model,
+        messages=[
+            {
+                "role": "system",
+                "content": f"You are an expert Translator. Your sole objective is to Translate the input English TEXT into {language}. DO NOT PROVIDE ANYTHING ELSE EXCEPT THE TRANSLATION."
+            },
+            {
+                "role": "user",
+                "content": f"### TEXT\n\n{text}\n\n### Translation to {language}:"
+            }
+        ],
+        temperature=0.3,
+        max_tokens=8000,
+        top_p=1,
+        stream=True,
+        stop=None,
+    )
+
+    for chunk in stream:
+        tokens = chunk.choices[0].delta.content
+        if tokens:
+            yield tokens
+        if x_groq := chunk.x_groq:
+            if not x_groq.usage:
+                continue
+            usage = x_groq.usage
+            statistics_to_return = GenerationStatistics(input_time=usage.prompt_time, output_time=usage.completion_time, input_tokens=usage.prompt_tokens, output_tokens=usage.completion_tokens, total_time=usage.total_time, model_name=model)
+            yield statistics_to_return
+
 # Initialize
 if 'button_disabled' not in st.session_state:
     st.session_state.button_disabled = False
@@ -322,11 +362,13 @@ def empty_st():
         st.write(f"---")
 
         st.write("# Customization Settings\n🧪 These settings are experimental.\n")
-        st.write(f"By default, GroqNotes uses Llama3-70b for generating the notes outline and Llama3-8b for the content. This balances quality with speed and rate limit usage. You can customize these selections below.")
+        st.write(f"By default, GroqNotes uses Llama3-70b for generating the notes outline and Llama3-8b for the content and translation. This balances quality with speed and rate limit usage. You can customize these selections below.")
         outline_model_options = ["llama3-70b-8192", "llama3-8b-8192", "mixtral-8x7b-32768", "gemma-7b-it"]
         outline_selected_model = st.selectbox("Outline generation:", outline_model_options)
         content_model_options = ["llama3-8b-8192", "llama3-70b-8192", "mixtral-8x7b-32768", "gemma-7b-it", "gemma2-9b-it"]
         content_selected_model = st.selectbox("Content generation:", content_model_options)
+        target_language_options = ["English", "Spanish", "French"]
+        target_language_selected = st.selectbox("Target language:", target_language_options)
 
         
         # Add note about rate limits
@@ -452,7 +494,7 @@ def display_statistics():
             total_generation_statistics = GenerationStatistics(model_name=str(content_selected_model))
             clear_status()
 
-
+            print("Target language: ", target_language_selected)
             try:
                 notes_structure_json = json.loads(notes_structure)
                 notes = NoteSection(structure=notes_structure_json,transcript=transcription_text)
@@ -476,6 +518,21 @@ def stream_section_content(sections):
                                     display_statistics()
                                 elif chunk is not None:
                                     st.session_state.notes.update_content(title, chunk)
+                            if target_language_selected != "English":
+                                translated_content_stream = translate_content(text=st.session_state.notes.get_content(title), language=target_language_selected, model=content_selected_model)
+                                # Reset content to empty string for translation
+                                st.session_state.notes.reset_content(title)
+                                for chunk in translated_content_stream:
+                                    # Check if GenerationStatistics data is returned instead of str tokens
+                                    chunk_data = chunk
+                                    if type(chunk_data) == GenerationStatistics:
+                                        total_generation_statistics.add(chunk_data)
+                                        
+                                        st.session_state.statistics_text = str(total_generation_statistics)
+                                        display_statistics()
+                                    elif chunk is not None:
+                                        st.session_state.notes.update_content(title, chunk)
+                                    
                         elif isinstance(content, dict):
                             stream_section_content(content)