plot with the image

.gitignore

@@ -3,4 +3,5 @@
 gen-lang-client-0065207637-eaf8e92995b6.json
 
 *.wav
-prompt.txt
+prompt.txt
+plot.png

gemini_call.py

@@ -1,5 +1,7 @@
 import google.generativeai as genai
 import os
+import re
+import matplotlib.pyplot as plt
 
 final_prompt = f'''Task:
 
@@ -39,11 +41,6 @@ final_prompt = f'''Task:
     Sentence 3: -3
     Sentence 4: +3
 
-    Histogram:
-    | Sentence 1 | Sentence 2 | Sentence 3 | Sentence 4 |
-    |------------|------------|------------|------------|
-    |     -9     |     -7     |     -3     |     +3     |
-
     Conclusion:
 
     After analyzing all sentences, provide a conclusion about the overall sentiment of the conversation.
@@ -71,12 +68,41 @@ api_key = os.getenv("GOOGLE_API_KEY")
 genai.configure(api_key=api_key)
 model = genai.GenerativeModel("gemini-2.0-flash-exp" , system_instruction=final_prompt)
 
+def extract_histogram_data(text):
+    # Regex to match the sentences and their sentiment score
+    histogram_pattern = r"Sentence (\d+): (-?\+?\d+)"
+    
+    # Find all matches
+    matches = re.findall(histogram_pattern, text)
+    
+    # Convert matches into two lists: sentence numbers and sentiment scores
+    sentences = [int(match[0]) for match in matches]
+    sentiment_scores = [int(match[1]) for match in matches]
+    
+    return sentences, sentiment_scores
+
+def plot_histogram(sentences, sentiment_scores):
+    plt.figure(figsize=(6, 4))
+    plt.bar(sentences, sentiment_scores, color='skyblue')
+    plt.xlabel('Sentence Number')
+    plt.ylabel('Sentiment Score')
+    plt.title('Sentiment Analysis Histogram')
+    plt.ylim(-12, 12)  # Set y-axis limits for better visualization
+    plt.grid(True, linestyle='--', alpha=0.5)
+    plt.savefig("plot.png" , format="png")
+    plt.close()
+
 def ask_gemini(prompt:str) ->str:
     
     
     response = model.generate_content(prompt)
+    
+    sentences, sentiment_scores = extract_histogram_data(response.text)
+
+    plot_histogram(sentences, sentiment_scores)
+    
     return response.text
 
 if __name__=="__main__":
-    response = model.generate_content("I hated every minute of my experience with you guys. You are straight garbage. But i love the way you look")
-    print(response.text)
+    response = ask_gemini("I hated every minute of my experience with you guys. You are straight garbage. But i love the way you look")
+    print(response)

sentiment_analysis.py

@@ -13,5 +13,6 @@ def get_analysis(file_path)->str:
     return transcript , analysis
 
 if __name__ == "__main__":
-    file_path = "harvard.wav"
-    print(f'Analysis result {get_analysis(file_path)}')
+    file_path = "recorded_audio.wav"
+    transcript , analysis = get_analysis(file_path)
+    print(f'Analysis result {analysis}')

streamlit_app.py

@@ -4,6 +4,7 @@ from streamlit_mic_recorder import mic_recorder
 import wave
 import pyaudio
 from sentiment_analysis import get_analysis
+from PIL import Image
 
 def save_audio(audio_data, filename):
     """Save the recorded audio in .wav format"""
@@ -14,6 +15,19 @@ def save_audio(audio_data, filename):
         wf.setframerate(44100)  # Sample rate (44100 Hz)
         wf.writeframes(audio_data)  # Write audio data to file
 
+def display_message(role, content, image_path=None):
+    if role == "user":
+        st.chat_message(role).markdown(f"**User:** {content}")
+    elif role == "gemini":
+        st.chat_message(role).markdown(f"**Gemini:** {content}")
+        if image_path:
+            # Display the image if it exists
+            try:
+                img = Image.open(image_path)
+                st.image(img, caption="Generated Image", use_column_width=True)
+            except Exception as e:
+                st.error(f"Error loading image: {e}")
+
 def main():
     st.title("Streamlit Voice Recorder")
 
@@ -46,14 +60,15 @@ def main():
             user_message, gemini_response = get_analysis("recorded_audio.wav")
 
         st.session_state.messages.append({"role": "user", "content": user_message})
-        st.session_state.messages.append({"role": "gemini", "content": gemini_response})
+        st.session_state.messages.append({"role": "gemini", "content": gemini_response, "image_url": "plot.png"})
 
     # Display the chat history
     for msg in st.session_state.messages:
+        # Check if the message is from Gemini and display the image accordingly
         if msg["role"] == "user":
-            st.chat_message(msg["role"]).markdown(f"**User:** {msg['content']}")
+            display_message(msg["role"], msg["content"])
         elif msg["role"] == "gemini":
-            st.chat_message(msg["role"]).markdown(f"**Gemini:** {msg['content']}")
+            display_message(msg["role"], msg["content"], msg.get("image_url"))
     
     time.sleep(0.1)