import streamlit as st
import anthropic, openai, base64, cv2, glob, json, math, os, pytz, random, re, requests, textract, time, zipfile
import plotly.graph_objects as go
import streamlit.components.v1 as components
from datetime import datetime
from audio_recorder_streamlit import audio_recorder
from bs4 import BeautifulSoup
from collections import defaultdict, deque
from dotenv import load_dotenv
from gradio_client import Client
from huggingface_hub import InferenceClient
from io import BytesIO
from PIL import Image
from PyPDF2 import PdfReader
from urllib.parse import quote
from xml.etree import ElementTree as ET
from openai import OpenAI
import extra_streamlit_components as stx
from streamlit.runtime.scriptrunner import get_script_run_ctx
import asyncio
import edge_tts

# 🔧 Config & Setup
st.set_page_config(
    page_title="🚲BikeAI🏆 Claude/GPT Research",
    page_icon="🚲🏆",
    layout="wide",
    initial_sidebar_state="auto",
    menu_items={
        'Get Help': 'https://huggingface.co/awacke1',
        'Report a bug': 'https://huggingface.co/spaces/awacke1',
        'About': "🚲BikeAI🏆 Claude/GPT Research AI"
    }
)
load_dotenv()

openai_api_key = os.getenv('OPENAI_API_KEY', "")
anthropic_key = os.getenv('ANTHROPIC_API_KEY_3', "")
if 'OPENAI_API_KEY' in st.secrets:
    openai_api_key = st.secrets['OPENAI_API_KEY']
if 'ANTHROPIC_API_KEY' in st.secrets:
    anthropic_key = st.secrets["ANTHROPIC_API_KEY"]

openai.api_key = openai_api_key
claude_client = anthropic.Anthropic(api_key=anthropic_key)
openai_client = OpenAI(api_key=openai.api_key, organization=os.getenv('OPENAI_ORG_ID'))
HF_KEY = os.getenv('HF_KEY')
API_URL = os.getenv('API_URL')

if 'transcript_history' not in st.session_state:
    st.session_state['transcript_history'] = []
if 'chat_history' not in st.session_state:
    st.session_state['chat_history'] = []
if 'openai_model' not in st.session_state:
    st.session_state['openai_model'] = "gpt-4o-2024-05-13"
if 'messages' not in st.session_state:
    st.session_state['messages'] = []
if 'last_voice_input' not in st.session_state:
    st.session_state['last_voice_input'] = ""
if 'editing_file' not in st.session_state:
    st.session_state['editing_file'] = None
if 'edit_new_name' not in st.session_state:
    st.session_state['edit_new_name'] = ""
if 'edit_new_content' not in st.session_state:
    st.session_state['edit_new_content'] = ""
if 'viewing_prefix' not in st.session_state:
    st.session_state['viewing_prefix'] = None
if 'should_rerun' not in st.session_state:
    st.session_state['should_rerun'] = False
# CHANGED LINE: Track old input from mycomponent to avoid recreating files on rerun
if 'old_val' not in st.session_state:
    st.session_state['old_val'] = None

# 🎨 Minimal Custom CSS
st.markdown("""
<style>
    .main { background: linear-gradient(to right, #1a1a1a, #2d2d2d); color: #fff; }
    .stMarkdown { font-family: 'Helvetica Neue', sans-serif; }
    .stButton>button {
        margin-right: 0.5rem;
    }
</style>
""", unsafe_allow_html=True)

FILE_EMOJIS = {
    "md": "📝",
    "mp3": "🎵",
}

def clean_for_speech(text: str) -> str:
    text = text.replace("\n", " ")
    text = text.replace("</s>", " ")
    text = text.replace("#", "")
    # Remove links like (https://...)
    text = re.sub(r"\(https?:\/\/[^\)]+\)", "", text)
    text = re.sub(r"\s+", " ", text).strip()
    return text

def generate_filename(content, file_type="md"):
    prefix = datetime.now().strftime("%y%m_%H%M") + "_"
    words = re.findall(r"\w+", content)
    name_text = '_'.join(words[:3]) if words else 'file'
    filename = f"{prefix}{name_text}.{file_type}"
    return filename

def create_file(prompt, response, file_type="md"):
    filename = generate_filename(response.strip() if response.strip() else prompt.strip(), file_type)
    with open(filename, 'w', encoding='utf-8') as f:
        f.write(prompt + "\n\n" + response)
    return filename

def get_download_link(file):
    with open(file, "rb") as f:
        b64 = base64.b64encode(f.read()).decode()
    return f'<a href="data:file/zip;base64,{b64}" download="{os.path.basename(file)}">📂 Download {os.path.basename(file)}</a>'

@st.cache_resource
def speech_synthesis_html(result):
    html_code = f"""
    <html><body>
    <script>
    var msg = new SpeechSynthesisUtterance("{result.replace('"', '')}");
    window.speechSynthesis.speak(msg);
    </script>
    </body></html>
    """
    components.html(html_code, height=0)

async def edge_tts_generate_audio(text, voice="en-US-AriaNeural", rate=0, pitch=0):
    text = clean_for_speech(text)
    if not text.strip():
        return None
    rate_str = f"{rate:+d}%"
    pitch_str = f"{pitch:+d}Hz"
    communicate = edge_tts.Communicate(text, voice, rate=rate_str, pitch=pitch_str)
    out_fn = generate_filename(text,"mp3")
    await communicate.save(out_fn)
    return out_fn

def speak_with_edge_tts(text, voice="en-US-AriaNeural", rate=0, pitch=0):
    return asyncio.run(edge_tts_generate_audio(text, voice, rate, pitch))

def play_and_download_audio(file_path):
    if file_path and os.path.exists(file_path):
        st.audio(file_path)
        dl_link = f'<a href="data:audio/mpeg;base64,{base64.b64encode(open(file_path,"rb").read()).decode()}" download="{os.path.basename(file_path)}">Download {os.path.basename(file_path)}</a>'
        st.markdown(dl_link, unsafe_allow_html=True)

def process_image(image_path, user_prompt):
    with open(image_path, "rb") as imgf:
        image_data = imgf.read()
    b64img = base64.b64encode(image_data).decode("utf-8")
    resp = openai_client.chat.completions.create(
        model=st.session_state["openai_model"],
        messages=[
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": [
                {"type": "text", "text": user_prompt},
                {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{b64img}"}}
            ]}
        ],
        temperature=0.0,
    )
    return resp.choices[0].message.content

def process_audio(audio_path):
    with open(audio_path, "rb") as f:
        transcription = openai_client.audio.transcriptions.create(model="whisper-1", file=f)
    st.session_state.messages.append({"role": "user", "content": transcription.text})
    return transcription.text

def process_video(video_path, seconds_per_frame=1):
    vid = cv2.VideoCapture(video_path)
    total = int(vid.get(cv2.CAP_PROP_FRAME_COUNT))
    fps = vid.get(cv2.CAP_PROP_FPS)
    skip = int(fps*seconds_per_frame)
    frames_b64 = []
    for i in range(0, total, skip):
        vid.set(cv2.CAP_PROP_POS_FRAMES, i)
        ret, frame = vid.read()
        if not ret: break
        _, buf = cv2.imencode(".jpg", frame)
        frames_b64.append(base64.b64encode(buf).decode("utf-8"))
    vid.release()
    return frames_b64

def process_video_with_gpt(video_path, prompt):
    frames = process_video(video_path)
    resp = openai_client.chat.completions.create(
        model=st.session_state["openai_model"],
        messages=[
            {"role":"system","content":"Analyze video frames."},
            {"role":"user","content":[
                {"type":"text","text":prompt},
                *[{"type":"image_url","image_url":{"url":f"data:image/jpeg;base64,{fr}"}} for fr in frames]
            ]}
        ]
    )
    return resp.choices[0].message.content

def search_arxiv(query):
    st.write("🔍 Searching ArXiv...")
    client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
    r1 = client.predict(prompt=query, llm_model_picked="mistralai/Mixtral-8x7B-Instruct-v0.1", stream_outputs=True, api_name="/ask_llm")
    st.markdown("### Mistral-8x7B-Instruct-v0.1 Result")
    st.markdown(r1)
    r2 = client.predict(prompt=query, llm_model_picked="mistralai/Mistral-7B-Instruct-v0.2", stream_outputs=True, api_name="/ask_llm")
    st.markdown("### Mistral-7B-Instruct-v0.2 Result")
    st.markdown(r2)
    return f"{r1}\n\n{r2}"

def perform_ai_lookup(q, vocal_summary=True, extended_refs=False, titles_summary=True):
    start = time.time()
    client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
    r = client.predict(q,20,"Semantic Search","mistralai/Mixtral-8x7B-Instruct-v0.1",api_name="/update_with_rag_md")
    refs = r[0]
    r2 = client.predict(q,"mistralai/Mixtral-8x7B-Instruct-v0.1",True,api_name="/ask_llm")
    result = f"### 🔎 {q}\n\n{r2}\n\n{refs}"

    st.markdown(result)

    # Clean for speech before TTS
    if vocal_summary:
        main_text = clean_for_speech(r2)
        audio_file_main = speak_with_edge_tts(main_text)
        st.write("### 🎙️ Vocal Summary (Short Answer)")
        play_and_download_audio(audio_file_main)

    if extended_refs:
        summaries_text = "Here are the summaries from the references: " + refs.replace('"','')
        summaries_text = clean_for_speech(summaries_text)
        audio_file_refs = speak_with_edge_tts(summaries_text)
        st.write("### 📜 Extended References & Summaries")
        play_and_download_audio(audio_file_refs)

    if titles_summary:
        titles = []
        for line in refs.split('\n'):
            m = re.search(r"\[([^\]]+)\]", line)
            if m:
                titles.append(m.group(1))
        if titles:
            titles_text = "Here are the titles of the papers: " + ", ".join(titles)
            titles_text = clean_for_speech(titles_text)
            audio_file_titles = speak_with_edge_tts(titles_text)
            st.write("### 🔖 Paper Titles")
            play_and_download_audio(audio_file_titles)

    elapsed = time.time()-start
    st.write(f"**Total Elapsed:** {elapsed:.2f} s")
    # CHANGED LINE: Only create a file after explicit user action is taken (already covered by button triggers)
    create_file(q, result, "md")
    return result

def process_with_gpt(text):
    if not text: return
    st.session_state.messages.append({"role":"user","content":text})
    with st.chat_message("user"):
        st.markdown(text)
    with st.chat_message("assistant"):
        c = openai_client.chat.completions.create(
            model=st.session_state["openai_model"],
            messages=st.session_state.messages,
            stream=False
        )
        ans = c.choices[0].message.content
        st.write("GPT-4o: " + ans)
        # CHANGED LINE: create_file is safe here since it's triggered by a user action button
        create_file(text, ans, "md")
        st.session_state.messages.append({"role":"assistant","content":ans})
    return ans

def process_with_claude(text):
    if not text: return
    with st.chat_message("user"):
        st.markdown(text)
    with st.chat_message("assistant"):
        r = claude_client.messages.create(
            model="claude-3-sonnet-20240229",
            max_tokens=1000,
            messages=[{"role":"user","content":text}]
        )
        ans = r.content[0].text
        st.write("Claude: " + ans)
        # CHANGED LINE: create_file only after button press/user action
        create_file(text, ans, "md")
        st.session_state.chat_history.append({"user":text,"claude":ans})
    return ans

def create_zip_of_files(md_files, mp3_files):
    # Exclude README.md
    md_files = [f for f in md_files if os.path.basename(f).lower() != 'readme.md']
    all_files = md_files + mp3_files
    if not all_files:
        return None
    stems = [os.path.splitext(os.path.basename(f))[0] for f in all_files]
    joined = "_".join(stems)
    if len(joined) > 50:
        joined = joined[:50] + "_etc"
    zip_name = f"{joined}.zip"
    with zipfile.ZipFile(zip_name,'w') as z:
        for f in all_files:
            z.write(f)
    return zip_name

def load_files_for_sidebar():
    md_files = glob.glob("*.md")
    mp3_files = glob.glob("*.mp3")

    # Exclude README.md
    md_files = [f for f in md_files if os.path.basename(f).lower() != 'readme.md']

    all_files = md_files + mp3_files

    groups = defaultdict(list)
    for f in all_files:
        fname = os.path.basename(f)
        prefix = fname[:10]  # first 10 chars as group prefix
        groups[prefix].append(f)

    for prefix in groups:
        groups[prefix].sort(key=lambda x: os.path.getmtime(x), reverse=True)

    sorted_prefixes = sorted(groups.keys(), key=lambda pre: max(os.path.getmtime(x) for x in groups[pre]), reverse=True)

    return groups, sorted_prefixes

def extract_keywords_from_md(files):
    text = ""
    for f in files:
        if f.endswith(".md"):
            c = open(f,'r',encoding='utf-8').read()
            text += " " + c
    words = re.findall(r"\w+", text.lower())
    unique_words = []
    for w in words:
        if w not in unique_words:
            unique_words.append(w)
        if len(unique_words) == 5:
            break
    return unique_words

def display_file_manager_sidebar(groups, sorted_prefixes):
    st.sidebar.title("🎵 Audio & Document Manager")

    all_md = []
    all_mp3 = []
    for prefix in groups:
        for f in groups[prefix]:
            if f.endswith(".md"):
                all_md.append(f)
            elif f.endswith(".mp3"):
                all_mp3.append(f)

    top_bar = st.sidebar.columns(3)
    with top_bar[0]:
        if st.button("🗑 Del All MD"):
            for f in all_md:
                os.remove(f)
            st.session_state.should_rerun = True
    with top_bar[1]:
        if st.button("🗑 Del All MP3"):
            for f in all_mp3:
                os.remove(f)
            st.session_state.should_rerun = True
    with top_bar[2]:
        if st.button("⬇️ Zip All"):
            z = create_zip_of_files(all_md, all_mp3)
            if z:
                st.sidebar.markdown(get_download_link(z),unsafe_allow_html=True)

    for prefix in sorted_prefixes:
        files = groups[prefix]
        kw = extract_keywords_from_md(files)
        keywords_str = " ".join(kw) if kw else "No Keywords"
        with st.sidebar.expander(f"{prefix} Files ({len(files)}) - Keywords: {keywords_str}", expanded=True):
            c1,c2 = st.columns(2)
            with c1:
                if st.button("👀View Group", key="view_group_"+prefix):
                    st.session_state.viewing_prefix = prefix
            with c2:
                if st.button("🗑Del Group", key="del_group_"+prefix):
                    for f in files:
                        os.remove(f)
                    # CHANGED LINE: Show success message after deletion
                    st.success(f"Deleted all files in group {prefix} successfully!")
                    st.session_state.should_rerun = True

            for f in files:
                fname = os.path.basename(f)
                ctime = datetime.fromtimestamp(os.path.getmtime(f)).strftime("%Y-%m-%d %H:%M:%S")
                st.write(f"**{fname}** - {ctime}")

def main():
    st.sidebar.markdown("### 🚲BikeAI🏆 Multi-Agent Research AI")
    tab_main = st.radio("Action:",["🎤 Voice Input","📸 Media Gallery","🔍 Search ArXiv","📝 File Editor"],horizontal=True)

    model_choice = st.sidebar.radio("AI Model:", ["Arxiv","GPT-4o","Claude-3","GPT+Claude+Arxiv"], index=0)

    mycomponent = components.declare_component("mycomponent", path="mycomponent")
    val = mycomponent(my_input_value="Hello")

    # CHANGED BLOCK: Wrap processing val in a button to avoid re-creation on rerun
    if val:
        st.write("**Input Detected:**", val)
        if st.button("Process Input"):
            # Only process if val is new
            if val != st.session_state.old_val:
                st.session_state.old_val = val
                if model_choice == "GPT-4o":
                    process_with_gpt(val)
                elif model_choice == "Claude-3":
                    process_with_claude(val)
                elif model_choice == "Arxiv":
                    st.subheader("Arxiv Only Results:")
                    perform_ai_lookup(val, vocal_summary=True, extended_refs=False, titles_summary=True)
                else:
                    col1,col2,col3=st.columns(3)
                    with col1:
                        st.subheader("GPT-4o Omni:")
                        try:
                            process_with_gpt(val)
                        except:
                            st.write('GPT 4o error')
                    with col2:
                        st.subheader("Claude-3 Sonnet:")
                        try:
                            process_with_claude(val)
                        except:
                            st.write('Claude error')
                    with col3:
                        st.subheader("Arxiv + Mistral:")
                        try:
                            perform_ai_lookup(val, vocal_summary=True, extended_refs=False, titles_summary=True)
                        except:
                            st.write("Arxiv error")

    if tab_main == "🔍 Search ArXiv":
        st.subheader("🔍 Search ArXiv")
        q=st.text_input("Research query:")

        st.markdown("### 🎛️ Audio Generation Options")
        vocal_summary = st.checkbox("🎙️ Vocal Summary (Short Answer)", value=True)
        extended_refs = st.checkbox("📜 Extended References & Summaries (Long)", value=False)
        titles_summary = st.checkbox("🔖 Paper Titles Only", value=True)

        if q and st.button("Run ArXiv Query"):
            perform_ai_lookup(q, vocal_summary=vocal_summary, extended_refs=extended_refs, titles_summary=titles_summary)

    elif tab_main == "🎤 Voice Input":
        st.subheader("🎤 Voice Recognition")
        user_text = st.text_area("Message:", height=100)
        user_text = user_text.strip()
        if st.button("Send 📨"):
            if user_text:
                if model_choice == "GPT-4o":
                    process_with_gpt(user_text)
                elif model_choice == "Claude-3":
                    process_with_claude(user_text)
                elif model_choice == "Arxiv":
                    st.subheader("Arxiv Only Results:")
                    perform_ai_lookup(user_text, vocal_summary=True, extended_refs=False, titles_summary=True)
                else:
                    col1,col2,col3=st.columns(3)
                    with col1:
                        st.subheader("GPT-4o Omni:")
                        process_with_gpt(user_text)
                    with col2:
                        st.subheader("Claude-3 Sonnet:")
                        process_with_claude(user_text)
                    with col3:
                        st.subheader("Arxiv & Mistral:")
                        res = perform_ai_lookup(user_text, vocal_summary=True, extended_refs=False, titles_summary=True)
                        st.markdown(res)
        st.subheader("📜 Chat History")
        t1,t2=st.tabs(["Claude History","GPT-4o History"])
        with t1:
            for c in st.session_state.chat_history:
                st.write("**You:**", c["user"])
                st.write("**Claude:**", c["claude"])
        with t2:
            for m in st.session_state.messages:
                with st.chat_message(m["role"]):
                    st.markdown(m["content"])

    elif tab_main == "📸 Media Gallery":
        st.header("🎬 Media Gallery - Images and Videos")
        tabs = st.tabs(["🖼️ Images", "🎥 Video"])
        with tabs[0]:
            imgs = glob.glob("*.png")+glob.glob("*.jpg")
            if imgs:
                c = st.slider("Cols",1,5,3)
                cols = st.columns(c)
                for i,f in enumerate(imgs):
                    with cols[i%c]:
                        st.image(Image.open(f),use_container_width=True)
                        if st.button(f"👀 Analyze {os.path.basename(f)}", key=f"analyze_{f}"):
                            a = process_image(f,"Describe this image.")
                            st.markdown(a)
            else:
                st.write("No images found.")
        with tabs[1]:
            vids = glob.glob("*.mp4")
            if vids:
                for v in vids:
                    with st.expander(f"🎥 {os.path.basename(v)}"):
                        st.video(v)
                        if st.button(f"Analyze {os.path.basename(v)}", key=f"analyze_{v}"):
                            a = process_video_with_gpt(v,"Describe video.")
                            st.markdown(a)
            else:
                st.write("No videos found.")

    elif tab_main == "📝 File Editor":
        if getattr(st.session_state,'current_file',None):
            st.subheader(f"Editing: {st.session_state.current_file}")
            new_text = st.text_area("Content:", st.session_state.file_content, height=300)
            if st.button("Save"):
                with open(st.session_state.current_file,'w',encoding='utf-8') as f:
                    f.write(new_text)
                st.success("Updated!")
                st.session_state.should_rerun = True
        else:
            st.write("Select a file from the sidebar to edit.")

    groups, sorted_prefixes = load_files_for_sidebar()
    display_file_manager_sidebar(groups, sorted_prefixes)

    if st.session_state.viewing_prefix and st.session_state.viewing_prefix in groups:
        st.write("---")
        st.write(f"**Viewing Group:** {st.session_state.viewing_prefix}")
        for f in groups[st.session_state.viewing_prefix]:
            fname = os.path.basename(f)
            ext = os.path.splitext(fname)[1].lower().strip('.')
            st.write(f"### {fname}")
            if ext == "md":
                content = open(f,'r',encoding='utf-8').read()
                st.markdown(content)
            elif ext == "mp3":
                st.audio(f)
            else:
                st.markdown(get_download_link(f), unsafe_allow_html=True)
        if st.button("Close Group View"):
            st.session_state.viewing_prefix = None

    if st.session_state.should_rerun:
        st.session_state.should_rerun = False
        st.rerun()

if __name__=="__main__":
    main()