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Update app.py
Browse files
app.py
CHANGED
@@ -39,7 +39,6 @@ title = "🚲BikeAI🏆 Claude and GPT Multi-Agent Research AI"
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helpURL = 'https://huggingface.co/awacke1'
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bugURL = 'https://huggingface.co/spaces/awacke1'
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icons = '🚲🏆'
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-
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st.set_page_config(
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page_title=title,
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page_icon=icons,
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@@ -51,27 +50,29 @@ st.set_page_config(
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'About': title
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}
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)
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-
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# 2. 🚲BikeAI🏆 Load environment variables and initialize clients
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load_dotenv()
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-
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# OpenAI setup
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openai.api_key = os.getenv('OPENAI_API_KEY')
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if openai.api_key == None:
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openai.api_key = st.secrets['OPENAI_API_KEY']
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-
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openai_client = OpenAI(
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api_key=os.getenv('OPENAI_API_KEY'),
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organization=os.getenv('OPENAI_ORG_ID')
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)
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-
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# 3.🚲BikeAI🏆 Claude setup
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anthropic_key = os.getenv("ANTHROPIC_API_KEY_3")
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if anthropic_key == None:
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anthropic_key = st.secrets["ANTHROPIC_API_KEY"]
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claude_client = anthropic.Anthropic(api_key=anthropic_key)
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-
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if 'transcript_history' not in st.session_state:
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st.session_state.transcript_history = []
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if "chat_history" not in st.session_state:
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@@ -83,17 +84,8 @@ if "messages" not in st.session_state:
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if 'last_voice_input' not in st.session_state:
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st.session_state.last_voice_input = ""
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# 5. 🚲BikeAI🏆 HuggingFace AI setup
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API_URL = os.getenv('API_URL')
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HF_KEY = os.getenv('HF_KEY')
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MODEL1 = "meta-llama/Llama-2-7b-chat-hf"
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MODEL2 = "openai/whisper-small.en"
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headers = {
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"Authorization": f"Bearer {HF_KEY}",
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"Content-Type": "application/json"
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}
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#
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st.markdown("""
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<style>
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.main {
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@@ -134,7 +126,8 @@ st.markdown("""
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""", unsafe_allow_html=True)
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def generate_filename(prompt, file_type):
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"""Generate a safe filename using the prompt and file type."""
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central = pytz.timezone('US/Central')
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@@ -142,11 +135,6 @@ def generate_filename(prompt, file_type):
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replaced_prompt = re.sub(r'[<>:"/\\|?*\n]', ' ', prompt)
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safe_prompt = re.sub(r'\s+', ' ', replaced_prompt).strip()[:230]
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return f"{safe_date_time}_{safe_prompt}.{file_type}"
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# 8. Function to create and save a file (and avoid the black hole of lost data 🕳)
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def create_file(filename, prompt, response, should_save=True):
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if not should_save:
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return
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@@ -163,8 +151,8 @@ def create_and_save_file(content, file_type="md", prompt=None, is_image=False, s
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else:
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f.write(prompt + "\n\n" + content if prompt else content)
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return filename
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def get_download_link(file_path):
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"""Create download link for file."""
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with open(file_path, "rb") as file:
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@@ -172,6 +160,7 @@ def get_download_link(file_path):
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b64 = base64.b64encode(contents).decode()
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return f'<a href="data:file/txt;base64,{b64}" download="{os.path.basename(file_path)}">Download {os.path.basename(file_path)}📂</a>'
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@st.cache_resource
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def SpeechSynthesis(result):
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"""HTML5 Speech Synthesis."""
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@@ -204,9 +193,7 @@ def process_image(image_input, user_prompt):
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if isinstance(image_input, str):
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with open(image_input, "rb") as image_file:
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image_input = image_file.read()
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base64_image = base64.b64encode(image_input).decode("utf-8")
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response = openai_client.chat.completions.create(
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model=st.session_state["openai_model"],
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messages=[
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@@ -220,7 +207,6 @@ def process_image(image_input, user_prompt):
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],
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temperature=0.0,
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)
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return response.choices[0].message.content
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def process_audio(audio_input, text_input=''):
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@@ -228,18 +214,14 @@ def process_audio(audio_input, text_input=''):
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if isinstance(audio_input, str):
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with open(audio_input, "rb") as file:
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audio_input = file.read()
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transcription = openai_client.audio.transcriptions.create(
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model="whisper-1",
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file=audio_input,
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)
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st.session_state.messages.append({"role": "user", "content": transcription.text})
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with st.chat_message("assistant"):
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st.markdown(transcription.text)
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SpeechSynthesis(transcription.text)
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filename = generate_filename(transcription.text, "wav")
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create_and_save_file(audio_input, "wav", transcription.text, True)
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@@ -259,14 +241,12 @@ def process_video(video_path, seconds_per_frame=1):
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break
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_, buffer = cv2.imencode(".jpg", frame)
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base64Frames.append(base64.b64encode(buffer).decode("utf-8"))
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video.release()
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return base64Frames, None
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def process_video_with_gpt(video_input, user_prompt):
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"""Process video with GPT-4 vision."""
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base64Frames, _ = process_video(video_input)
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response = openai_client.chat.completions.create(
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model=st.session_state["openai_model"],
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messages=[
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@@ -291,7 +271,6 @@ def extract_urls(text):
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abs_link_matches = abs_link_pattern.findall(text)
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pdf_link_matches = pdf_link_pattern.findall(text)
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title_matches = title_pattern.findall(text)
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-
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# markdown with the extracted fields
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markdown_text = ""
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for i in range(len(date_matches)):
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markdown_text += f"**PDF Link:** [{pdf_link}]({pdf_link})\n\n"
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markdown_text += "---\n\n"
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return markdown_text
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except:
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st.write('.')
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return ''
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def search_arxiv(query):
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st.write("Performing AI Lookup...")
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client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
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result1 = client.predict(
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prompt=query,
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llm_model_picked="mistralai/Mixtral-8x7B-Instruct-v0.1",
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@@ -324,7 +300,6 @@ def search_arxiv(query):
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)
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st.markdown("### Mixtral-8x7B-Instruct-v0.1 Result")
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st.markdown(result1)
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result2 = client.predict(
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prompt=query,
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llm_model_picked="mistralai/Mistral-7B-Instruct-v0.2",
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st.markdown(result2)
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combined_result = f"{result1}\n\n{result2}"
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return combined_result
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#return responseall
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@@ -365,7 +339,6 @@ def perform_ai_lookup(query):
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Question = '### 🔎 ' + query + '\r\n' # Format for markdown display with links
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References = response1[0]
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ReferenceLinks = extract_urls(References)
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RunSecondQuery = True
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results=''
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if RunSecondQuery:
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@@ -382,7 +355,6 @@ def perform_ai_lookup(query):
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# Restructure results to follow format of Question, Answer, References, ReferenceLinks
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results = Question + '\r\n' + Answer + '\r\n' + References + '\r\n' + ReferenceLinks
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st.markdown(results)
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st.write('🔍Run of Multi-Agent System Paper Summary Spec is Complete')
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end_time = time.strftime("%Y-%m-%d %H:%M:%S")
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start_timestamp = time.mktime(time.strptime(start_time, "%Y-%m-%d %H:%M:%S"))
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st.write(f"Start time: {start_time}")
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st.write(f"Finish time: {end_time}")
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st.write(f"Elapsed time: {elapsed_seconds:.2f} seconds")
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filename = generate_filename(query, "md")
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create_file(filename, query, results)
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return results
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@@ -402,10 +372,8 @@ def process_with_gpt(text_input):
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"""Process text with GPT-4o."""
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if text_input:
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st.session_state.messages.append({"role": "user", "content": text_input})
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with st.chat_message("user"):
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st.markdown(text_input)
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with st.chat_message("assistant"):
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completion = openai_client.chat.completions.create(
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model=st.session_state["openai_model"],
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)
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return_text = completion.choices[0].message.content
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st.write("GPT-4o: " + return_text)
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#filename = generate_filename(text_input, "md")
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filename = generate_filename("GPT-4o: " + return_text, "md")
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create_file(filename, text_input, return_text)
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@@ -427,10 +394,8 @@ def process_with_gpt(text_input):
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def process_with_claude(text_input):
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"""Process text with Claude."""
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if text_input:
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with st.chat_message("user"):
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st.markdown(text_input)
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with st.chat_message("assistant"):
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response = claude_client.messages.create(
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model="claude-3-sonnet-20240229",
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)
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response_text = response.content[0].text
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st.write("Claude: " + response_text)
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#filename = generate_filename(text_input, "md")
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filename = generate_filename("Claude: " + response_text, "md")
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create_file(filename, text_input, response_text)
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st.session_state.chat_history.append({
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"user": text_input,
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"claude": response_text
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zipf.write(file)
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return zip_name
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def get_media_html(media_path, media_type="video", width="100%"):
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"""Generate HTML for media player."""
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media_data = base64.b64encode(open(media_path, 'rb').read()).decode()
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def create_media_gallery():
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"""Create the media gallery interface."""
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st.header("🎬 Media Gallery")
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tabs = st.tabs(["🖼️ Images", "🎵 Audio", "🎥 Video"])
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with tabs[0]:
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image_files = glob.glob("*.png") + glob.glob("*.jpg")
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if image_files:
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with cols[idx % num_cols]:
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img = Image.open(image_file)
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st.image(img, use_container_width=True)
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# Add GPT vision analysis option
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if st.button(f"Analyze {os.path.basename(image_file)}"):
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analysis = process_image(image_file,
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"Describe this image in detail and identify key elements.")
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st.markdown(analysis)
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with tabs[1]:
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audio_files = glob.glob("*.mp3") + glob.glob("*.wav")
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for audio_file in audio_files:
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with open(audio_file, "rb") as f:
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transcription = process_audio(f)
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st.write(transcription)
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with tabs[2]:
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video_files = glob.glob("*.mp4")
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for video_file in video_files:
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st.markdown(analysis)
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-
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def display_file_manager():
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"""Display file management sidebar with guaranteed unique button keys."""
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st.sidebar.title("📁 File Management")
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all_files = glob.glob("*.md")
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all_files.sort(reverse=True)
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if st.sidebar.button("🗑 Delete All", key="delete_all_files_button"):
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for file in all_files:
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os.remove(file)
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st.rerun()
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if st.sidebar.button("⬇️ Download All", key="download_all_files_button"):
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zip_file = create_zip_of_files(all_files)
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st.sidebar.markdown(get_download_link(zip_file), unsafe_allow_html=True)
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# Create unique keys using file attributes
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for idx, file in enumerate(all_files):
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# Get file stats for unique identification
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file_stat = os.stat(file)
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unique_id = f"{idx}_{file_stat.st_size}_{file_stat.st_mtime}"
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col1, col2, col3, col4 = st.sidebar.columns([1,3,1,1])
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with col1:
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if st.button("🌐", key=f"view_{unique_id}"):
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st.rerun()
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# Speech Recognition HTML Component
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speech_recognition_html = """
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<!DOCTYPE html>
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helpURL = 'https://huggingface.co/awacke1'
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bugURL = 'https://huggingface.co/spaces/awacke1'
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icons = '🚲🏆'
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st.set_page_config(
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page_title=title,
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page_icon=icons,
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'About': title
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}
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)
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load_dotenv()
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openai.api_key = os.getenv('OPENAI_API_KEY')
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if openai.api_key == None:
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openai.api_key = st.secrets['OPENAI_API_KEY']
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openai_client = OpenAI(
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api_key=os.getenv('OPENAI_API_KEY'),
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organization=os.getenv('OPENAI_ORG_ID')
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)
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anthropic_key = os.getenv("ANTHROPIC_API_KEY_3")
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if anthropic_key == None:
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anthropic_key = st.secrets["ANTHROPIC_API_KEY"]
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claude_client = anthropic.Anthropic(api_key=anthropic_key)
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API_URL = os.getenv('API_URL')
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HF_KEY = os.getenv('HF_KEY')
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MODEL1 = "meta-llama/Llama-2-7b-chat-hf"
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MODEL2 = "openai/whisper-small.en"
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headers = {
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"Authorization": f"Bearer {HF_KEY}",
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"Content-Type": "application/json"
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}
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# 2.🚲BikeAI🏆 Initialize session states
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if 'transcript_history' not in st.session_state:
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st.session_state.transcript_history = []
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if "chat_history" not in st.session_state:
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if 'last_voice_input' not in st.session_state:
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st.session_state.last_voice_input = ""
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# 3. 🚲BikeAI🏆 Custom CSS
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st.markdown("""
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<style>
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.main {
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""", unsafe_allow_html=True)
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+
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# create and save a file (and avoid the black hole of lost data 🕳)
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def generate_filename(prompt, file_type):
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"""Generate a safe filename using the prompt and file type."""
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central = pytz.timezone('US/Central')
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replaced_prompt = re.sub(r'[<>:"/\\|?*\n]', ' ', prompt)
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safe_prompt = re.sub(r'\s+', ' ', replaced_prompt).strip()[:230]
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return f"{safe_date_time}_{safe_prompt}.{file_type}"
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def create_file(filename, prompt, response, should_save=True):
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if not should_save:
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return
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else:
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f.write(prompt + "\n\n" + content if prompt else content)
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return filename
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# Load a file, base64 it, return as link
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def get_download_link(file_path):
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"""Create download link for file."""
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with open(file_path, "rb") as file:
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b64 = base64.b64encode(contents).decode()
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return f'<a href="data:file/txt;base64,{b64}" download="{os.path.basename(file_path)}">Download {os.path.basename(file_path)}📂</a>'
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+
# Speech Synth Browser Style
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@st.cache_resource
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def SpeechSynthesis(result):
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"""HTML5 Speech Synthesis."""
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if isinstance(image_input, str):
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with open(image_input, "rb") as image_file:
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image_input = image_file.read()
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base64_image = base64.b64encode(image_input).decode("utf-8")
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response = openai_client.chat.completions.create(
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model=st.session_state["openai_model"],
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messages=[
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],
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208 |
temperature=0.0,
|
209 |
)
|
|
|
210 |
return response.choices[0].message.content
|
211 |
|
212 |
def process_audio(audio_input, text_input=''):
|
|
|
214 |
if isinstance(audio_input, str):
|
215 |
with open(audio_input, "rb") as file:
|
216 |
audio_input = file.read()
|
|
|
217 |
transcription = openai_client.audio.transcriptions.create(
|
218 |
model="whisper-1",
|
219 |
file=audio_input,
|
220 |
)
|
|
|
221 |
st.session_state.messages.append({"role": "user", "content": transcription.text})
|
|
|
222 |
with st.chat_message("assistant"):
|
223 |
st.markdown(transcription.text)
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224 |
SpeechSynthesis(transcription.text)
|
|
|
225 |
filename = generate_filename(transcription.text, "wav")
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226 |
create_and_save_file(audio_input, "wav", transcription.text, True)
|
227 |
|
|
|
241 |
break
|
242 |
_, buffer = cv2.imencode(".jpg", frame)
|
243 |
base64Frames.append(base64.b64encode(buffer).decode("utf-8"))
|
|
|
244 |
video.release()
|
245 |
return base64Frames, None
|
246 |
|
247 |
def process_video_with_gpt(video_input, user_prompt):
|
248 |
"""Process video with GPT-4 vision."""
|
249 |
base64Frames, _ = process_video(video_input)
|
|
|
250 |
response = openai_client.chat.completions.create(
|
251 |
model=st.session_state["openai_model"],
|
252 |
messages=[
|
|
|
271 |
abs_link_matches = abs_link_pattern.findall(text)
|
272 |
pdf_link_matches = pdf_link_pattern.findall(text)
|
273 |
title_matches = title_pattern.findall(text)
|
|
|
274 |
# markdown with the extracted fields
|
275 |
markdown_text = ""
|
276 |
for i in range(len(date_matches)):
|
|
|
284 |
markdown_text += f"**PDF Link:** [{pdf_link}]({pdf_link})\n\n"
|
285 |
markdown_text += "---\n\n"
|
286 |
return markdown_text
|
|
|
287 |
except:
|
288 |
st.write('.')
|
289 |
return ''
|
290 |
|
291 |
|
292 |
def search_arxiv(query):
|
|
|
293 |
st.write("Performing AI Lookup...")
|
294 |
client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
|
|
|
295 |
result1 = client.predict(
|
296 |
prompt=query,
|
297 |
llm_model_picked="mistralai/Mixtral-8x7B-Instruct-v0.1",
|
|
|
300 |
)
|
301 |
st.markdown("### Mixtral-8x7B-Instruct-v0.1 Result")
|
302 |
st.markdown(result1)
|
|
|
303 |
result2 = client.predict(
|
304 |
prompt=query,
|
305 |
llm_model_picked="mistralai/Mistral-7B-Instruct-v0.2",
|
|
|
310 |
st.markdown(result2)
|
311 |
combined_result = f"{result1}\n\n{result2}"
|
312 |
return combined_result
|
|
|
313 |
#return responseall
|
314 |
|
315 |
|
|
|
339 |
Question = '### 🔎 ' + query + '\r\n' # Format for markdown display with links
|
340 |
References = response1[0]
|
341 |
ReferenceLinks = extract_urls(References)
|
|
|
342 |
RunSecondQuery = True
|
343 |
results=''
|
344 |
if RunSecondQuery:
|
|
|
355 |
# Restructure results to follow format of Question, Answer, References, ReferenceLinks
|
356 |
results = Question + '\r\n' + Answer + '\r\n' + References + '\r\n' + ReferenceLinks
|
357 |
st.markdown(results)
|
|
|
358 |
st.write('🔍Run of Multi-Agent System Paper Summary Spec is Complete')
|
359 |
end_time = time.strftime("%Y-%m-%d %H:%M:%S")
|
360 |
start_timestamp = time.mktime(time.strptime(start_time, "%Y-%m-%d %H:%M:%S"))
|
|
|
363 |
st.write(f"Start time: {start_time}")
|
364 |
st.write(f"Finish time: {end_time}")
|
365 |
st.write(f"Elapsed time: {elapsed_seconds:.2f} seconds")
|
|
|
|
|
366 |
filename = generate_filename(query, "md")
|
367 |
create_file(filename, query, results)
|
368 |
return results
|
|
|
372 |
"""Process text with GPT-4o."""
|
373 |
if text_input:
|
374 |
st.session_state.messages.append({"role": "user", "content": text_input})
|
|
|
375 |
with st.chat_message("user"):
|
376 |
st.markdown(text_input)
|
|
|
377 |
with st.chat_message("assistant"):
|
378 |
completion = openai_client.chat.completions.create(
|
379 |
model=st.session_state["openai_model"],
|
|
|
385 |
)
|
386 |
return_text = completion.choices[0].message.content
|
387 |
st.write("GPT-4o: " + return_text)
|
|
|
388 |
#filename = generate_filename(text_input, "md")
|
389 |
filename = generate_filename("GPT-4o: " + return_text, "md")
|
390 |
create_file(filename, text_input, return_text)
|
|
|
394 |
def process_with_claude(text_input):
|
395 |
"""Process text with Claude."""
|
396 |
if text_input:
|
|
|
397 |
with st.chat_message("user"):
|
398 |
st.markdown(text_input)
|
|
|
399 |
with st.chat_message("assistant"):
|
400 |
response = claude_client.messages.create(
|
401 |
model="claude-3-sonnet-20240229",
|
|
|
406 |
)
|
407 |
response_text = response.content[0].text
|
408 |
st.write("Claude: " + response_text)
|
|
|
409 |
#filename = generate_filename(text_input, "md")
|
410 |
filename = generate_filename("Claude: " + response_text, "md")
|
411 |
create_file(filename, text_input, response_text)
|
|
|
412 |
st.session_state.chat_history.append({
|
413 |
"user": text_input,
|
414 |
"claude": response_text
|
|
|
430 |
zipf.write(file)
|
431 |
return zip_name
|
432 |
|
|
|
|
|
433 |
def get_media_html(media_path, media_type="video", width="100%"):
|
434 |
"""Generate HTML for media player."""
|
435 |
media_data = base64.b64encode(open(media_path, 'rb').read()).decode()
|
|
|
451 |
def create_media_gallery():
|
452 |
"""Create the media gallery interface."""
|
453 |
st.header("🎬 Media Gallery")
|
|
|
454 |
tabs = st.tabs(["🖼️ Images", "🎵 Audio", "🎥 Video"])
|
|
|
455 |
with tabs[0]:
|
456 |
image_files = glob.glob("*.png") + glob.glob("*.jpg")
|
457 |
if image_files:
|
|
|
461 |
with cols[idx % num_cols]:
|
462 |
img = Image.open(image_file)
|
463 |
st.image(img, use_container_width=True)
|
|
|
464 |
# Add GPT vision analysis option
|
465 |
if st.button(f"Analyze {os.path.basename(image_file)}"):
|
466 |
analysis = process_image(image_file,
|
467 |
"Describe this image in detail and identify key elements.")
|
468 |
st.markdown(analysis)
|
|
|
469 |
with tabs[1]:
|
470 |
audio_files = glob.glob("*.mp3") + glob.glob("*.wav")
|
471 |
for audio_file in audio_files:
|
|
|
475 |
with open(audio_file, "rb") as f:
|
476 |
transcription = process_audio(f)
|
477 |
st.write(transcription)
|
|
|
478 |
with tabs[2]:
|
479 |
video_files = glob.glob("*.mp4")
|
480 |
for video_file in video_files:
|
|
|
486 |
st.markdown(analysis)
|
487 |
|
488 |
|
|
|
489 |
def display_file_manager():
|
490 |
"""Display file management sidebar with guaranteed unique button keys."""
|
491 |
st.sidebar.title("📁 File Management")
|
|
|
492 |
all_files = glob.glob("*.md")
|
493 |
all_files.sort(reverse=True)
|
|
|
494 |
if st.sidebar.button("🗑 Delete All", key="delete_all_files_button"):
|
495 |
for file in all_files:
|
496 |
os.remove(file)
|
497 |
st.rerun()
|
|
|
498 |
if st.sidebar.button("⬇️ Download All", key="download_all_files_button"):
|
499 |
zip_file = create_zip_of_files(all_files)
|
500 |
st.sidebar.markdown(get_download_link(zip_file), unsafe_allow_html=True)
|
|
|
501 |
# Create unique keys using file attributes
|
502 |
for idx, file in enumerate(all_files):
|
503 |
# Get file stats for unique identification
|
504 |
file_stat = os.stat(file)
|
505 |
unique_id = f"{idx}_{file_stat.st_size}_{file_stat.st_mtime}"
|
|
|
506 |
col1, col2, col3, col4 = st.sidebar.columns([1,3,1,1])
|
507 |
with col1:
|
508 |
if st.button("🌐", key=f"view_{unique_id}"):
|
|
|
520 |
st.rerun()
|
521 |
|
522 |
|
|
|
|
|
523 |
# Speech Recognition HTML Component
|
524 |
speech_recognition_html = """
|
525 |
<!DOCTYPE html>
|