Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -15,28 +15,30 @@ from transformers import (
|
|
15 |
st.set_page_config(
|
16 |
page_icon="π§",
|
17 |
layout="wide",
|
18 |
-
page_title="Radio Imaging Audio Generator - Llama
|
19 |
initial_sidebar_state="expanded",
|
20 |
)
|
21 |
|
22 |
# ---------------------------------------------------------------------
|
23 |
-
# Custom CSS for a
|
24 |
# ---------------------------------------------------------------------
|
25 |
CUSTOM_CSS = """
|
26 |
<style>
|
27 |
body {
|
28 |
-
background-color: #
|
29 |
color: #1F2937;
|
30 |
font-family: 'Segoe UI', Tahoma, sans-serif;
|
31 |
}
|
32 |
h1, h2, h3, h4, h5, h6 {
|
33 |
color: #3B82F6;
|
|
|
34 |
}
|
35 |
.stButton>button {
|
36 |
background-color: #3B82F6 !important;
|
37 |
color: #FFFFFF !important;
|
38 |
border-radius: 8px !important;
|
39 |
font-size: 16px !important;
|
|
|
40 |
}
|
41 |
.sidebar .sidebar-content {
|
42 |
background: #E0F2FE;
|
@@ -63,9 +65,10 @@ st.markdown(CUSTOM_CSS, unsafe_allow_html=True)
|
|
63 |
# ---------------------------------------------------------------------
|
64 |
st.markdown(
|
65 |
"""
|
66 |
-
<h1
|
67 |
<p style='font-size:18px;'>
|
68 |
-
Generate custom radio
|
|
|
69 |
</p>
|
70 |
""",
|
71 |
unsafe_allow_html=True
|
@@ -73,20 +76,21 @@ st.markdown(
|
|
73 |
st.markdown("---")
|
74 |
|
75 |
# ---------------------------------------------------------------------
|
76 |
-
# Instructions Section
|
77 |
# ---------------------------------------------------------------------
|
78 |
with st.expander("π How to Use This Web App"):
|
79 |
st.markdown(
|
80 |
"""
|
81 |
-
1. **Enter
|
82 |
-
2. **
|
83 |
-
3. **
|
84 |
-
4. **
|
|
|
85 |
|
86 |
-
**
|
87 |
-
-
|
88 |
-
-
|
89 |
-
-
|
90 |
"""
|
91 |
)
|
92 |
|
@@ -94,36 +98,59 @@ with st.expander("π How to Use This Web App"):
|
|
94 |
# Sidebar: Model Selection & Options
|
95 |
# ---------------------------------------------------------------------
|
96 |
with st.sidebar:
|
97 |
-
st.header("π§ Model Config")
|
98 |
-
|
|
|
99 |
llama_model_id = st.text_input(
|
100 |
-
"Llama
|
101 |
-
value="meta-llama/Llama-
|
102 |
-
help="
|
103 |
)
|
|
|
104 |
device_option = st.selectbox(
|
105 |
"Hardware Device",
|
106 |
["auto", "cpu"],
|
107 |
-
help="If running locally with a GPU, choose 'auto'.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
108 |
)
|
109 |
|
110 |
# ---------------------------------------------------------------------
|
111 |
# Prompt Input
|
112 |
# ---------------------------------------------------------------------
|
113 |
-
st.markdown("## βπ» Write Your Brief
|
114 |
prompt = st.text_area(
|
115 |
-
"Describe the radio imaging or jingle you want to create.
|
116 |
-
placeholder="e.g. 'An energetic 15-second pop jingle for a morning radio show
|
117 |
)
|
118 |
|
119 |
# ---------------------------------------------------------------------
|
120 |
-
# Text Generation with Llama
|
121 |
# ---------------------------------------------------------------------
|
122 |
@st.cache_resource
|
123 |
def load_llama_pipeline(model_id: str, device: str):
|
124 |
"""
|
125 |
Load the Llama or other open-source model as a text-generation pipeline.
|
126 |
-
|
|
|
127 |
"""
|
128 |
tokenizer = AutoTokenizer.from_pretrained(model_id)
|
129 |
model = AutoModelForCausalLM.from_pretrained(
|
@@ -139,49 +166,51 @@ def load_llama_pipeline(model_id: str, device: str):
|
|
139 |
)
|
140 |
return gen_pipeline
|
141 |
|
142 |
-
def generate_description(user_prompt: str, pipeline_gen):
|
143 |
"""
|
144 |
-
Use the pipeline to create a refined description for MusicGen
|
|
|
145 |
"""
|
146 |
-
# Instruction
|
147 |
-
# or simpler prompt if it's not a chat model
|
148 |
system_prompt = (
|
149 |
-
"You are a
|
150 |
-
"Refine the user's
|
151 |
-
"
|
152 |
)
|
153 |
-
|
154 |
-
#
|
155 |
-
combined_prompt =
|
156 |
-
|
157 |
-
|
|
|
|
|
|
|
|
|
158 |
result = pipeline_gen(
|
159 |
combined_prompt,
|
160 |
-
max_new_tokens=
|
161 |
do_sample=True,
|
162 |
-
temperature=0.
|
163 |
)
|
164 |
-
# Extract generated text (some models output extra tokens or the entire prompt again)
|
165 |
generated_text = result[0]["generated_text"]
|
166 |
-
|
167 |
-
# Attempt to
|
168 |
-
# Just a heuristic: find the last occurrence of "script:" or any relevant marker
|
169 |
if "script:" in generated_text.lower():
|
170 |
-
generated_text = generated_text.split("script:")[-1].strip()
|
171 |
|
172 |
-
#
|
173 |
-
generated_text += "\n\n(Generated by Radio Imaging Audio Generator - Llama
|
174 |
return generated_text
|
175 |
|
176 |
# Button: Generate Description
|
177 |
-
if st.button("π Refine Description with Llama"):
|
178 |
if not prompt.strip():
|
179 |
-
st.error("Please provide a
|
180 |
else:
|
181 |
with st.spinner("Generating a refined description..."):
|
182 |
try:
|
183 |
pipeline_llama = load_llama_pipeline(llama_model_id, device_option)
|
184 |
-
refined_text = generate_description(prompt, pipeline_llama)
|
185 |
st.session_state['refined_prompt'] = refined_text
|
186 |
st.success("Description successfully refined!")
|
187 |
st.write(refined_text)
|
@@ -191,7 +220,7 @@ if st.button("π Refine Description with Llama"):
|
|
191 |
file_name="refined_description.txt"
|
192 |
)
|
193 |
except Exception as e:
|
194 |
-
st.error(f"Error while generating with Llama: {e}")
|
195 |
|
196 |
st.markdown("---")
|
197 |
|
@@ -207,30 +236,43 @@ def load_musicgen_model():
|
|
207 |
|
208 |
if st.button("βΆ Generate Audio with MusicGen"):
|
209 |
if 'refined_prompt' not in st.session_state or not st.session_state['refined_prompt']:
|
210 |
-
st.error("Please generate or have a refined
|
211 |
else:
|
212 |
descriptive_text = st.session_state['refined_prompt']
|
213 |
-
with st.spinner("Generating your audio...
|
214 |
try:
|
215 |
musicgen_model, processor = load_musicgen_model()
|
216 |
-
|
|
|
|
|
|
|
|
|
217 |
inputs = processor(
|
218 |
-
text=[
|
219 |
padding=True,
|
220 |
return_tensors="pt"
|
221 |
)
|
222 |
-
|
|
|
223 |
sampling_rate = musicgen_model.config.audio_encoder.sampling_rate
|
224 |
|
225 |
# Save & display the audio
|
226 |
-
audio_filename = "
|
227 |
scipy.io.wavfile.write(
|
228 |
audio_filename,
|
229 |
rate=sampling_rate,
|
230 |
data=audio_values[0, 0].numpy()
|
231 |
)
|
|
|
232 |
st.success("Audio successfully generated!")
|
233 |
st.audio(audio_filename)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
234 |
except Exception as e:
|
235 |
st.error(f"Error while generating audio: {e}")
|
236 |
|
@@ -240,9 +282,9 @@ if st.button("βΆ Generate Audio with MusicGen"):
|
|
240 |
st.markdown("---")
|
241 |
st.markdown(
|
242 |
"<div class='footer-note'>"
|
243 |
-
"β
Built with Llama
|
244 |
-
"
|
245 |
-
"
|
246 |
"</div>",
|
247 |
unsafe_allow_html=True
|
248 |
)
|
|
|
15 |
st.set_page_config(
|
16 |
page_icon="π§",
|
17 |
layout="wide",
|
18 |
+
page_title="Radio Imaging Audio Generator - Llama 3",
|
19 |
initial_sidebar_state="expanded",
|
20 |
)
|
21 |
|
22 |
# ---------------------------------------------------------------------
|
23 |
+
# Custom CSS for a Catchy UI
|
24 |
# ---------------------------------------------------------------------
|
25 |
CUSTOM_CSS = """
|
26 |
<style>
|
27 |
body {
|
28 |
+
background-color: #FAFCFF;
|
29 |
color: #1F2937;
|
30 |
font-family: 'Segoe UI', Tahoma, sans-serif;
|
31 |
}
|
32 |
h1, h2, h3, h4, h5, h6 {
|
33 |
color: #3B82F6;
|
34 |
+
margin-bottom: 0.5em;
|
35 |
}
|
36 |
.stButton>button {
|
37 |
background-color: #3B82F6 !important;
|
38 |
color: #FFFFFF !important;
|
39 |
border-radius: 8px !important;
|
40 |
font-size: 16px !important;
|
41 |
+
margin: 0.5em 0;
|
42 |
}
|
43 |
.sidebar .sidebar-content {
|
44 |
background: #E0F2FE;
|
|
|
65 |
# ---------------------------------------------------------------------
|
66 |
st.markdown(
|
67 |
"""
|
68 |
+
<h1>π Radio Imaging Audio Generator <span style="font-size: 24px; color: #F59E0B;">(Beta with Llama 3)</span></h1>
|
69 |
<p style='font-size:18px;'>
|
70 |
+
Generate custom radio ads, station promos, and jingles in multiple languages
|
71 |
+
using the **hypothetical Llama 3.3** Instruct model & MusicGen!
|
72 |
</p>
|
73 |
""",
|
74 |
unsafe_allow_html=True
|
|
|
76 |
st.markdown("---")
|
77 |
|
78 |
# ---------------------------------------------------------------------
|
79 |
+
# Instructions Section
|
80 |
# ---------------------------------------------------------------------
|
81 |
with st.expander("π How to Use This Web App"):
|
82 |
st.markdown(
|
83 |
"""
|
84 |
+
1. **Enter a concept** in any language: Describe the style, mood, length, etc.
|
85 |
+
2. **Choose Language**: If you want a Spanish script, select Spanish below (multi-language).
|
86 |
+
3. **Refine with Llama 3**: Let the model transform your brief into a catchy script.
|
87 |
+
4. **Set Audio Options**: Choose a style (Rock, Pop, Classical...) and max tokens for MusicGen output.
|
88 |
+
5. **Generate Audio**: Listen & optionally download or upload the WAV file.
|
89 |
|
90 |
+
**Future Enhancements**:
|
91 |
+
- **User Authentication**: Restrict access or track usage with logins.
|
92 |
+
- **Advanced Fine-tuning**: Adjust Llama or MusicGen for specialized station branding.
|
93 |
+
- **Cloud Storage**: Upload final WAVs to a server or cloud bucket for easy sharing.
|
94 |
"""
|
95 |
)
|
96 |
|
|
|
98 |
# Sidebar: Model Selection & Options
|
99 |
# ---------------------------------------------------------------------
|
100 |
with st.sidebar:
|
101 |
+
st.header("π§ Model & Audio Config")
|
102 |
+
|
103 |
+
# Llama 3 model ID on Hugging Face (hypothetical)
|
104 |
llama_model_id = st.text_input(
|
105 |
+
"Llama 3 Instruct Model ID",
|
106 |
+
value="meta-llama/Llama-3.3-70B-Instruct",
|
107 |
+
help="Requires license acceptance on Hugging Face, if/when available."
|
108 |
)
|
109 |
+
|
110 |
device_option = st.selectbox(
|
111 |
"Hardware Device",
|
112 |
["auto", "cpu"],
|
113 |
+
help="If running locally with a GPU, choose 'auto'. CPU-only might be slow for large models."
|
114 |
+
)
|
115 |
+
|
116 |
+
st.markdown("---")
|
117 |
+
|
118 |
+
# Multi-language prompt
|
119 |
+
language = st.selectbox(
|
120 |
+
"Choose Output Language",
|
121 |
+
["English", "Spanish", "French", "German", "Other (explain in your prompt)"]
|
122 |
+
)
|
123 |
+
|
124 |
+
st.markdown("---")
|
125 |
+
|
126 |
+
# Audio style and tokens
|
127 |
+
music_style = st.selectbox(
|
128 |
+
"Preferred Music Style",
|
129 |
+
["Pop", "Rock", "Electronic", "Classical", "Hip-Hop", "Reggae", "Ambient", "Other"]
|
130 |
+
)
|
131 |
+
audio_tokens = st.slider(
|
132 |
+
"MusicGen Max Tokens (Approx. Track Length)",
|
133 |
+
min_value=128, max_value=1024, value=512, step=64
|
134 |
)
|
135 |
|
136 |
# ---------------------------------------------------------------------
|
137 |
# Prompt Input
|
138 |
# ---------------------------------------------------------------------
|
139 |
+
st.markdown("## βπ» Write Your Concept Brief")
|
140 |
prompt = st.text_area(
|
141 |
+
"Describe the radio imaging or jingle you want to create.",
|
142 |
+
placeholder="e.g. 'An energetic 15-second pop jingle in Spanish for a morning radio show...'"
|
143 |
)
|
144 |
|
145 |
# ---------------------------------------------------------------------
|
146 |
+
# Text Generation with Llama 3
|
147 |
# ---------------------------------------------------------------------
|
148 |
@st.cache_resource
|
149 |
def load_llama_pipeline(model_id: str, device: str):
|
150 |
"""
|
151 |
Load the Llama or other open-source model as a text-generation pipeline.
|
152 |
+
This is hypothetical for Llama 3.3.
|
153 |
+
Must accept license on HF if the model is restricted.
|
154 |
"""
|
155 |
tokenizer = AutoTokenizer.from_pretrained(model_id)
|
156 |
model = AutoModelForCausalLM.from_pretrained(
|
|
|
166 |
)
|
167 |
return gen_pipeline
|
168 |
|
169 |
+
def generate_description(user_prompt: str, pipeline_gen, language_choice: str):
|
170 |
"""
|
171 |
+
Use the pipeline to create a refined description for MusicGen,
|
172 |
+
with multi-language capabilities.
|
173 |
"""
|
174 |
+
# Instruction for Llama (system prompt):
|
|
|
175 |
system_prompt = (
|
176 |
+
"You are a creative ad copywriter specialized in radio imaging. "
|
177 |
+
"Refine the user's concept into a concise script. "
|
178 |
+
"Incorporate the language choice and creative elements for a promotional audio spot."
|
179 |
)
|
180 |
+
|
181 |
+
# Combine user prompt + language + the system instructions
|
182 |
+
combined_prompt = (
|
183 |
+
f"{system_prompt}\n"
|
184 |
+
f"Language to use: {language_choice}\n"
|
185 |
+
f"User Concept: {user_prompt}\n"
|
186 |
+
f"Your refined ad script:"
|
187 |
+
)
|
188 |
+
|
189 |
result = pipeline_gen(
|
190 |
combined_prompt,
|
191 |
+
max_new_tokens=300,
|
192 |
do_sample=True,
|
193 |
+
temperature=0.8
|
194 |
)
|
|
|
195 |
generated_text = result[0]["generated_text"]
|
196 |
+
|
197 |
+
# Attempt to isolate the script portion
|
|
|
198 |
if "script:" in generated_text.lower():
|
199 |
+
generated_text = generated_text.split("script:", 1)[-1].strip()
|
200 |
|
201 |
+
# Add a sign-off or brand line
|
202 |
+
generated_text += "\n\n(Generated by Radio Imaging Audio Generator - Powered by Llama 3)"
|
203 |
return generated_text
|
204 |
|
205 |
# Button: Generate Description
|
206 |
+
if st.button("π Refine Description with Llama 3"):
|
207 |
if not prompt.strip():
|
208 |
+
st.error("Please provide a concept before generating a description.")
|
209 |
else:
|
210 |
with st.spinner("Generating a refined description..."):
|
211 |
try:
|
212 |
pipeline_llama = load_llama_pipeline(llama_model_id, device_option)
|
213 |
+
refined_text = generate_description(prompt, pipeline_llama, language)
|
214 |
st.session_state['refined_prompt'] = refined_text
|
215 |
st.success("Description successfully refined!")
|
216 |
st.write(refined_text)
|
|
|
220 |
file_name="refined_description.txt"
|
221 |
)
|
222 |
except Exception as e:
|
223 |
+
st.error(f"Error while generating with Llama 3: {e}")
|
224 |
|
225 |
st.markdown("---")
|
226 |
|
|
|
236 |
|
237 |
if st.button("βΆ Generate Audio with MusicGen"):
|
238 |
if 'refined_prompt' not in st.session_state or not st.session_state['refined_prompt']:
|
239 |
+
st.error("Please generate or have a refined script before creating audio.")
|
240 |
else:
|
241 |
descriptive_text = st.session_state['refined_prompt']
|
242 |
+
with st.spinner("Generating your audio..."):
|
243 |
try:
|
244 |
musicgen_model, processor = load_musicgen_model()
|
245 |
+
|
246 |
+
# Incorporate the style preference into the final text
|
247 |
+
final_text_for_music = f"{descriptive_text}\nStyle preference: {music_style}"
|
248 |
+
|
249 |
+
# Use the refined prompt + style as input
|
250 |
inputs = processor(
|
251 |
+
text=[final_text_for_music],
|
252 |
padding=True,
|
253 |
return_tensors="pt"
|
254 |
)
|
255 |
+
# Adjust max_new_tokens for track length
|
256 |
+
audio_values = musicgen_model.generate(**inputs, max_new_tokens=audio_tokens)
|
257 |
sampling_rate = musicgen_model.config.audio_encoder.sampling_rate
|
258 |
|
259 |
# Save & display the audio
|
260 |
+
audio_filename = f"radio_imaging_output_{music_style.lower()}.wav"
|
261 |
scipy.io.wavfile.write(
|
262 |
audio_filename,
|
263 |
rate=sampling_rate,
|
264 |
data=audio_values[0, 0].numpy()
|
265 |
)
|
266 |
+
|
267 |
st.success("Audio successfully generated!")
|
268 |
st.audio(audio_filename)
|
269 |
+
|
270 |
+
# Optionally, prompt to "Upload to Cloud" or "Save to Directory"
|
271 |
+
if st.checkbox("Upload this WAV to cloud storage? (Demo)"):
|
272 |
+
with st.spinner("Uploading... (This is a placeholder)"):
|
273 |
+
# Pseudocode for your custom logic, e.g.:
|
274 |
+
# upload_to_s3(audio_filename, bucket_name="radio-imaging-bucket")
|
275 |
+
st.success("File uploaded to your cloud storage (placeholder).")
|
276 |
except Exception as e:
|
277 |
st.error(f"Error while generating audio: {e}")
|
278 |
|
|
|
282 |
st.markdown("---")
|
283 |
st.markdown(
|
284 |
"<div class='footer-note'>"
|
285 |
+
"β
Built with a hypothetical Llama 3.3 & MusicGen Β· "
|
286 |
+
"Multi-language, advanced styles, and a hint of future expansions Β· "
|
287 |
+
"Happy producing!"
|
288 |
"</div>",
|
289 |
unsafe_allow_html=True
|
290 |
)
|