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Create app.py
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‎app.py‎

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import streamlit as st
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from openai import OpenAI
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import httpx
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import requests
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import re
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import json
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import os
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import pyperclip
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# --- Helper to fetch model list ---
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def fetch_models(base_url: str, api_key: str):
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try:
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if base_url.startswith("http://localhost:11434") or re.match(r"^http://[a-zA-Z0-9.-]+:11434$", base_url):
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res = requests.get(base_url.rstrip("/") + "/api/tags")
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res.raise_for_status()
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data = res.json()
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return sorted([m["name"] for m in data.get("models", [])])
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else:
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endpoint = base_url.rstrip("/") + "/models"
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headers = {"Authorization": f"Bearer {api_key}"} if api_key else {}
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r = httpx.get(endpoint, headers=headers, timeout=10)
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r.raise_for_status()
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data = r.json()
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models = [m["id"] for m in data.get("data", []) if m.get("id")]
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return sorted(models)
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except Exception as e:
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st.error(f"Could not fetch models: {e}")
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return []
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# --- Save chat history to JSON ---
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def save_chat_history(messages, filename="chat_history.json"):
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try:
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with open(filename, "w", encoding="utf-8") as f:
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json.dump(messages, f, indent=2, ensure_ascii=False)
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except Exception as e:
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st.error(f"Error saving chat history: {e}")
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# --- Load from JSON ---
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def load_chat_history(filename="chat_history.json"):
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try:
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if os.path.exists(filename):
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with open(filename, "r", encoding="utf-8") as f:
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return json.load(f)
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except Exception as e:
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st.error(f"Error loading chat history: {e}")
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return []
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# --- Clipboard copy helper ---
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def copy_to_clipboard(text):
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try:
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pyperclip.copy(text)
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st.toast("Copied to clipboard!")
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except Exception as e:
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st.error(f"Could not copy to clipboard: {e}")
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# --- Text truncation helper ---
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def get_truncated_text(text, word_limit=50):
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words = text.split()
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if len(words) > word_limit:
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return ' '.join(words[:word_limit]) + "..."
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return text
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# --- Page config ---
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st.set_page_config(page_title="Custom LLM Chat", page_icon="💬")
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st.title("💬 Chat with Any Model Provider")
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# --- Sidebar: credentials & model list ---
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with st.sidebar:
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st.header("Connect")
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base_url = st.text_input("Base URL (no trailing slash) & Hit Enter", value=st.session_state.get("base_url", ""))
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api_key_required = not re.match(r"^http://[a-zA-Z0-9.-]+:11434$", base_url)
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api_key = st.text_input("API Key", type="password", value=st.session_state.get("api_key", "")) if api_key_required else ""
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if st.button("List / Refresh Models", use_container_width=True):
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if base_url:
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with st.spinner("Fetching models…"):
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model_list = fetch_models(base_url, api_key)
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st.session_state["model_list"] = model_list
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st.session_state["base_url"] = base_url
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st.session_state["api_key"] = api_key
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else:
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st.error("Please enter Base URL")
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if "model_list" in st.session_state:
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chosen_model = st.selectbox(
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"Select a model:",
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st.session_state["model_list"],
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key="chosen_model",
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)
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else:
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chosen_model = None
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# --- Chat area ---
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if chosen_model and "base_url" in st.session_state:
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if "messages" not in st.session_state:
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st.session_state.messages = load_chat_history()
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base_url = st.session_state["base_url"].rstrip("/")
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if not base_url.endswith("/v1"):
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base_url += "/v1"
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client = OpenAI(
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base_url=base_url,
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api_key=st.session_state.get("api_key", ""),
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)
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st.subheader("Chat History")
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i = 0
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while i < len(st.session_state.messages):
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msg = st.session_state.messages[i]
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if msg["role"] == "user":
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with st.chat_message("user"):
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st.markdown(msg["content"])
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i += 1
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if i < len(st.session_state.messages) and st.session_state.messages[i]["role"] == "assistant":
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assistant_idx = i
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response_text = st.session_state.messages[assistant_idx]["content"]
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toggle_key = f"read_more_{assistant_idx}"
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if toggle_key not in st.session_state:
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st.session_state[toggle_key] = False
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with st.chat_message("assistant"):
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words = response_text.split()
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if len(words) > 50 and not st.session_state[toggle_key]:
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st.markdown(get_truncated_text(response_text, 50))
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else:
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st.markdown(response_text)
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col1, col2, col3 = st.columns(3)
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with col1:
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if len(words) > 50:
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label = "Read More" if not st.session_state[toggle_key] else "Show Less"
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if st.button(label, key=f"toggle_{assistant_idx}"):
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st.session_state[toggle_key] = not st.session_state[toggle_key]
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st.rerun()
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with col2:
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if st.button("Copy Output", key=f"copy_{assistant_idx}"):
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copy_to_clipboard(response_text)
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with col3:
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if st.button("🗑️ Delete Response", key=f"delete_{assistant_idx}"):
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st.session_state.messages.pop(assistant_idx) # assistant
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st.session_state.messages.pop(assistant_idx - 1) # user
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save_chat_history(st.session_state.messages)
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st.rerun()
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i += 1
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else:
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with st.chat_message("assistant"):
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st.markdown(msg["content"])
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i += 1
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# --- Input box for new message ---
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if prompt := st.chat_input("Type your message…"):
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st.session_state.messages.append({"role": "user", "content": prompt})
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with st.chat_message("user"):
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st.markdown(prompt)
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st.session_state.messages.append({"role": "assistant", "content": ""})
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current_assistant_message_idx = len(st.session_state.messages) - 1
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with st.chat_message("assistant"):
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stop_button_placeholder = st.empty()
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response_placeholder = st.empty()
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collected_text = ""
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stop_flag_key = f"stop_flag_{current_assistant_message_idx}"
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st.session_state[stop_flag_key] = False
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st.session_state["is_streaming"] = True
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def stop_stream_callback():
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st.session_state[stop_flag_key] = True
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st.session_state["is_streaming"] = False
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stop_button_placeholder.button("Stop Response", on_click=stop_stream_callback, key=f"stop_button_{current_assistant_message_idx}")
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try:
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stream = client.chat.completions.create(
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model=chosen_model,
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messages=[
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{"role": m["role"], "content": m["content"]}
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for m in st.session_state.messages[:-1]
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] + [{"role": "user", "content": prompt}],
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max_tokens=20000,
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stream=True,
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)
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for chunk in stream:
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if st.session_state[stop_flag_key]:
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break
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delta = chunk.choices[0].delta.content or ""
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collected_text += delta
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response_placeholder.markdown(collected_text + "▌")
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st.session_state.messages[current_assistant_message_idx]["content"] = collected_text
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except Exception as e:
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st.error(f"Request failed: {e}")
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collected_text = st.session_state.messages[current_assistant_message_idx]["content"] + f"\n\n<Request failed: {e}>"
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st.session_state.messages[current_assistant_message_idx]["content"] = collected_text
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finally:
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response_placeholder.markdown(collected_text)
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stop_button_placeholder.empty()
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st.session_state["is_streaming"] = False
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st.session_state.messages[current_assistant_message_idx]["content"] = collected_text
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save_chat_history(st.session_state.messages)
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# Read More block immediately for new response
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toggle_key = f"read_more_{current_assistant_message_idx}"
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if toggle_key not in st.session_state:
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st.session_state[toggle_key] = False
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words = collected_text.split()
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if len(words) > 50 and not st.session_state[toggle_key]:
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st.markdown(get_truncated_text(collected_text, 50))
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else:
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st.markdown(collected_text)
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col1, col2, col3 = st.columns(3)
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with col1:
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if len(words) > 50:
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label = "Read More" if not st.session_state[toggle_key] else "Show Less"
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if st.button(label, key=f"toggle_{current_assistant_message_idx}"):
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st.session_state[toggle_key] = not st.session_state[toggle_key]
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st.rerun()
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with col2:
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if st.button("Copy Output", key=f"copy_{current_assistant_message_idx}_final"):
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copy_to_clipboard(collected_text)
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with col3:
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if st.button("🗑️ Delete Response", key=f"delete_{current_assistant_message_idx}_final"):
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st.session_state.messages.pop(current_assistant_message_idx)
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st.session_state.messages.pop(current_assistant_message_idx - 1)
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save_chat_history(st.session_state.messages)
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st.rerun()
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elif "model_list" not in st.session_state:
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st.info("👈 Use the sidebar to enter your credentials and load available models.")
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else:
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st.info("Please pick a model from the sidebar.")

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