Spaces:
Sleeping
Sleeping
| import torch | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| import streamlit as st | |
| from clarifai_grpc.channel.clarifai_channel import ClarifaiChannel | |
| from clarifai_grpc.grpc.api import resources_pb2, service_pb2, service_pb2_grpc | |
| from clarifai_grpc.grpc.api.status import status_code_pb2 | |
| # GPT-4 credentials | |
| PAT_GPT4 = "3ca5bd8b0f2244eb8d0e4b2838fc3cf1" | |
| USER_ID_GPT4 = "openai" | |
| APP_ID_GPT4 = "chat-completion" | |
| MODEL_ID_GPT4 = "openai-gpt-4-vision" | |
| MODEL_VERSION_ID_GPT4 = "266df29bc09843e0aee9b7bf723c03c2" | |
| # DALL-E credentials | |
| PAT_DALLE = "bfdeb4029ef54d23a2e608b0aa4c00e4" | |
| USER_ID_DALLE = "openai" | |
| APP_ID_DALLE = "dall-e" | |
| MODEL_ID_DALLE = "dall-e-3" | |
| MODEL_VERSION_ID_DALLE = "dc9dcb6ee67543cebc0b9a025861b868" | |
| # TTS credentials | |
| PAT_TTS = "bfdeb4029ef54d23a2e608b0aa4c00e4" | |
| USER_ID_TTS = "openai" | |
| APP_ID_TTS = "tts" | |
| MODEL_ID_TTS = "openai-tts-1" | |
| MODEL_VERSION_ID_TTS = "fff6ce1fd487457da95b79241ac6f02d" | |
| # NewsGuardian model credentials | |
| PAT_NEWSGUARDIAN = "your_news_guardian_pat" | |
| USER_ID_NEWSGUARDIAN = "your_user_id" | |
| APP_ID_NEWSGUARDIAN = "your_app_id" | |
| MODEL_ID_NEWSGUARDIAN = "your_model_id" | |
| MODEL_VERSION_ID_NEWSGUARDIAN = "your_model_version_id" | |
| # Set up gRPC channel for NewsGuardian model | |
| channel_tts = ClarifaiChannel.get_grpc_channel() | |
| stub_tts = service_pb2_grpc.V2Stub(channel_tts) | |
| metadata_tts = (('authorization', 'Key ' + PAT_TTS),) | |
| userDataObject_tts = resources_pb2.UserAppIDSet(user_id=USER_ID_TTS, app_id=APP_ID_TTS) | |
| # Streamlit app | |
| st.title("NewsGuardian") | |
| # Inserting logo | |
| st.image("https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcTdA-MJ_SUCRgLs1prqudpMdaX4x-x10Zqlwp7cpzXWCMM9xjBAJYWdJsDlLoHBqNpj8qs&usqp=CAU") | |
| # Function to generate text using the "microsoft/phi-2" model | |
| def generate_phi2_text(input_text): | |
| inputs = tokenizer(input_text, return_tensors="pt", return_attention_mask=False) | |
| outputs = model.generate(**inputs, max_length=200) | |
| generated_text = tokenizer.batch_decode(outputs)[0] | |
| return generated_text | |
| # User input | |
| raw_text_phi2 = st.text_area("Enter text for phi-2 model") | |
| # Button to generate result using "microsoft/phi-2" model | |
| if st.button("NewsGuardian model Generated fake news with phi-2"): | |
| if raw_text_phi2: | |
| generated_text_phi2 = generate_phi2_text(raw_text_phi2) | |
| st.text("NewsGuardian model Generated fake news with phi-2") | |
| st.text(generated_text_phi2) | |
| else: | |
| st.warning("Please enter news phi-2 model") | |
| # User input | |
| model_type = st.selectbox("Select Model", ["NewsGuardian model", "DALL-E"]) | |
| raw_text_news_guardian = st.text_area("This news is real or fake?") | |
| image_upload_news_guardian = st.file_uploader("Upload Image", type=["jpg", "jpeg", "png"]) | |
| # Button to generate result for NewsGuardian model | |
| if st.button("NewsGuardian News Result"): | |
| if model_type == "NewsGuardian model": | |
| # Set up gRPC channel for NewsGuardian model | |
| channel_news_guardian = ClarifaiChannel.get_grpc_channel() | |
| stub_news_guardian = service_pb2_grpc.V2Stub(channel_news_guardian) | |
| metadata_news_guardian = (('authorization', 'Key ' + PAT_NEWSGUARDIAN),) | |
| userDataObject_news_guardian = resources_pb2.UserAppIDSet(user_id=USER_ID_NEWSGUARDIAN, app_id=APP_ID_NEWSGUARDIAN) | |
| # Prepare the request for NewsGuardian model | |
| input_data_news_guardian = resources_pb2.Data() | |
| if raw_text_news_guardian: | |
| input_data_news_guardian.text.raw = raw_text_news_guardian | |
| if image_upload_news_guardian is not None: | |
| image_bytes_news_guardian = image_upload_news_guardian.read() | |
| input_data_news_guardian.image.base64 = image_bytes_news_guardian | |
| post_model_outputs_response_news_guardian = stub_news_guardian.PostModelOutputs( | |
| service_pb2.PostModelOutputsRequest( | |
| user_app_id=userDataObject_news_guardian, | |
| model_id=MODEL_ID_NEWSGUARDIAN, | |
| version_id=MODEL_VERSION_ID_NEWSGUARDIAN, | |
| inputs=[resources_pb2.Input(data=input_data_news_guardian)] | |
| ), | |
| metadata=metadata_news_guardian # Use metadata directly in the gRPC request | |
| ) | |
| # Check if the request was successful for NewsGuardian model | |
| if post_model_outputs_response_news_guardian.status.code != status_code_pb2.SUCCESS: | |
| st.error(f"NewsGuardian model API request failed: {post_model_outputs_response_news_guardian.status.description}") | |
| else: | |
| # Get the output for NewsGuardian model | |
| output_news_guardian = post_model_outputs_response_news_guardian.outputs[0].data | |
| # Display the result for NewsGuardian model | |
| if output_news_guardian.HasField("image"): | |
| st.image(output_news_guardian.image.base64, caption='Generated Image (NewsGuardian model)', use_column_width=True) | |
| elif output_news_guardian.HasField("text"): | |
| # Display the text result | |
| st.text(output_news_guardian.text.raw) | |
| # Convert text to speech and play the audio | |
| tts_input_data = resources_pb2.Data() | |
| tts_input_data.text.raw = output_news_guardian.text.raw | |
| tts_response = stub_tts.PostModelOutputs( | |
| service_pb2.PostModelOutputsRequest( | |
| user_app_id=userDataObject_tts, | |
| model_id=MODEL_ID_TTS, | |
| version_id=MODEL_VERSION_ID_TTS, | |
| inputs=[resources_pb2.Input(data=tts_input_data)] | |
| ), | |
| metadata=metadata_tts # Use the same metadata for TTS | |
| ) | |
| # Check if the TTS request was successful | |
| if tts_response.status.code == status_code_pb2.SUCCESS: | |
| tts_output = tts_response.outputs[0].data | |
| st.audio(tts_output.audio.base64, format='audio/wav') | |
| else: | |
| st.error(f"TTS API request failed: {tts_response.status.description}") | |
| elif model_type == "DALL-E": | |
| # Set up gRPC channel for DALL-E | |
| channel_dalle = ClarifaiChannel.get_grpc_channel() | |
| stub_dalle = service_pb2_grpc.V2Stub(channel_dalle) | |
| metadata_dalle = (('authorization', 'Key ' + PAT_DALLE),) | |
| userDataObject_dalle = resources_pb2.UserAppIDSet(user_id=USER_ID_DALLE, app_id=APP_ID_DALLE) | |
| # Prepare the request for DALL-E | |
| input_data_dalle = resources_pb2.Data() | |
| if raw_text_news_guardian: | |
| input_data_dalle.text.raw = raw_text_news_guardian | |
| post_model_outputs_response_dalle = stub_dalle.PostModelOutputs( | |
| service_pb2.PostModelOutputsRequest( | |
| user_app_id=userDataObject_dalle, | |
| model_id=MODEL_ID_DALLE, | |
| version_id=MODEL_VERSION_ID_DALLE, | |
| inputs=[resources_pb2.Input(data=input_data_dalle)] | |
| ), | |
| metadata=metadata_dalle | |
| ) | |
| # Check if the request was successful for DALL-E | |
| if post_model_outputs_response_dalle.status.code != status_code_pb2.SUCCESS: | |
| st.error(f"DALL-E API request failed: {post_model_outputs_response_dalle.status.description}") | |
| else: | |
| # Get the output for DALL-E | |
| output_dalle = post_model_outputs_response_dalle.outputs[0].data | |
| # Display the result for DALL-E | |
| if output_dalle.HasField("image"): | |
| st.image(output_dalle.image.base64, caption='Generated Image (DALL-E)', use_column_width=True) | |
| elif output_dalle.HasField("text"): | |
| st.text(output_dalle.text.raw) | |
| # Add the beautiful social media icon section | |
| st.markdown(""" | |
| <div align="center"> | |
| <a href="https://github.com/pyresearch/pyresearch" style="text-decoration:none;"> | |
| <img src="https://user-images.githubusercontent.com/34125851/226594737-c21e2dda-9cc6-42ef-b4e7-a685fea4a21d.png" width="2%" alt="" /></a> | |
| <img src="https://user-images.githubusercontent.com/34125851/226595799-160b0da3-c9e0-4562-8544-5f20460f7cc9.png" width="2%" alt="" /> | |
| <a href="https://www.linkedin.com/company/pyresearch/" style="text-decoration:none;"> | |
| <img src="https://user-images.githubusercontent.com/34125851/226596446-746ffdd0-a47e-4452-84e3-bf11ec2aa26a.png" width="2%" alt="" /></a> | |
| <img src="https://user-images.githubusercontent.com/34125851/226595799-160b0da3-c9e0-4562-8544-5f20460f7cc9.png" width="2%" alt="" /> | |
| <a href="https://twitter.com/Noorkhokhar10" style="text-decoration:none;"> | |
| <img src="https://user-images.githubusercontent.com/34125851/226599162-9b11194e-4998-440a-ba94-c8a5e1cdc676.png" width="2%" alt="" /></a> | |
| <img src="https://user-images.githubusercontent.com/34125851/226595799-160b0da3-c9e0-4562-8544-5f20460f7cc9.png" width="2%" alt="" /> | |
| <a href="https://www.youtube.com/@Pyresearch" style="text-decoration:none;"> | |
| <img src="https://user-images.githubusercontent.com/34125851/226599904-7d5cc5c0-89d2-4d1e-891e-19bee1951744.png" width="2%" alt="" /></a> | |
| <img src="https://user-images.githubusercontent.com/34125851/226595799-160b0da3-c9e0-4562-8544-5f20460f7cc9.png" width="2%" alt="" /> | |
| <a href="https://www.facebook.com/Pyresearch" style="text-decoration:none;"> | |
| <img src="https://user-images.githubusercontent.com/34125851/226600380-a87a9142-e8e0-4ec9-bf2c-dd6e9da2f05a.png" width="2%" alt="" /></a> | |
| <img src="https://user-images.githubusercontent.com/34125851/226595799-160b0da3-c9e0-4562-8544-5f20460f7cc9.png" width="2%" alt="" /> | |
| <a href="https://www.instagram.com/pyresearch/" style="text-decoration:none;"> | |
| <img src="https://user-images.githubusercontent.com/34125851/226601355-ffe0b597-9840-4e10-bbef-43d6c74b5a9e.png" width="2%" alt="" /></a> | |
| </div> | |
| <hr> | |
| """, unsafe_allow_html=True) | |