Create app_t.py

app_t.py

@@ -0,0 +1,252 @@
+import os
+import textwrap
+import traceback
+import gradio as gr
+from transformers import pipeline
+
+# ---------------------------
+# Configuration
+# ---------------------------
+MODEL_ID = "openai/gpt-oss-20b"  # Hugging Face Transformers model
+
+# ---------------------------
+# Load pipeline
+# ---------------------------
+# device_map="auto" will use GPU if available, otherwise CPU
+pipe = pipeline("text-generation", model=MODEL_ID, device_map="auto")
+
+# ---------------------------
+# Research loader (project root)
+# ---------------------------
+ROOT_DIR = "."
+ALLOWED_EXT = (".txt", ".md")
+
+def load_research_from_root(max_total_chars: int = 12000):
+    files = []
+    for name in sorted(os.listdir(ROOT_DIR)):
+        if name.lower().endswith(ALLOWED_EXT) and name != "requirements.txt":
+            if name == os.path.basename(__file__):
+                continue
+            files.append(name)
+
+    if not files:
+        return "No research files (.txt/.md) found in project root."
+
+    combined_parts, total_len = [], 0
+    for fname in files:
+        try:
+            with open(os.path.join(ROOT_DIR, fname), "r", encoding="utf-8", errors="ignore") as f:
+                txt = f.read()
+        except Exception as e:
+            txt = f"[Error reading {fname}: {e}]"
+
+        if len(txt) > 8000:
+            sample = txt[:8000] + "\n\n[TRUNCATED]\n"
+        else:
+            sample = txt
+
+        part = f"--- {fname} ---\n{sample.strip()}\n"
+        combined_parts.append(part)
+        total_len += len(part)
+        if total_len >= max_total_chars:
+            break
+
+    combined = "\n\n".join(combined_parts)
+    if len(combined) > max_total_chars:
+        combined = combined[:max_total_chars] + "\n\n[TRUNCATED]"
+    return combined
+
+# ---------------------------
+# System prompt templates
+# ---------------------------
+research_context = load_research_from_root(max_total_chars=12000)
+
+def get_system_prompt(mode="chat"):
+    if mode == "chat":
+        return textwrap.dedent(f"""
+        OhamLab A Quantum Intelligence AI.
+        Mode: Conversational.
+        Guidelines:
+        - Answer clearly in natural paragraphs (3–6 sentences).
+        - Do NOT use tables, spreadsheets, or rigid formatting unless explicitly asked.
+        - Always address the user’s question directly before expanding.
+        - Be insightful, empathetic, and concise.
+
+        --- BEGIN RESEARCH CONTEXT (TRIMMED) ---
+        {research_context}
+        --- END RESEARCH CONTEXT ---
+        """).strip()
+    else:
+        return textwrap.dedent(f"""
+        You are OhamLab, a Quantum Dialectical Agentic Crosssphere Intelligence AI.
+        Mode: Research / Analytical.
+        Guidelines:
+        - Write structured, multi-sphere reasoning (science, philosophy, psychology, etc).
+        - Use sections, subpoints, and dialectical chains.
+        - Provide deep analysis, even if it looks like a research paper.
+        - Always reference the research context if relevant.
+
+        --- BEGIN RESEARCH CONTEXT (TRIMMED) ---
+        {research_context}
+        --- END RESEARCH CONTEXT ---
+        """).strip()
+
+# ---------------------------
+# State
+# ---------------------------
+conversation_mode = "chat"  # default
+history_messages = [{"role": "system", "content": get_system_prompt("chat")}]
+chat_history_for_ui = []
+
+# ---------------------------
+# Model call helper
+# ---------------------------
+def call_model_get_response(model_id: str, messages: list, max_tokens: int = 700):
+    # Convert structured messages into plain text
+    conversation_text = ""
+    for m in messages:
+        if m["role"] == "system":
+            conversation_text += f"[SYSTEM]: {m['content']}\n"
+        elif m["role"] == "user":
+            conversation_text += f"[USER]: {m['content']}\n"
+        elif m["role"] == "assistant":
+            conversation_text += f"[ASSISTANT]: {m['content']}\n"
+
+    conversation_text += "[ASSISTANT]:"
+
+    try:
+        output = pipe(
+            conversation_text,
+            max_new_tokens=max_tokens,
+            do_sample=True,
+            temperature=0.7,
+            return_full_text=False,
+        )
+        return output[0]["generated_text"].strip()
+    except Exception as e:
+        tb = traceback.format_exc()
+        return f"⚠️ **Error**: {str(e)}\n\nTraceback:\n{tb.splitlines()[-6:]}"
+
+# ---------------------------
+# Chat logic
+# ---------------------------
+def chat_with_model(user_message, chat_history):
+    global history_messages, chat_history_for_ui, conversation_mode
+
+    if not user_message or str(user_message).strip() == "":
+        return "", chat_history
+
+    # Mode switching commands
+    if "switch to research mode" in user_message.lower():
+        conversation_mode = "research"
+        history_messages = [{"role": "system", "content": get_system_prompt("research")}]
+        return "", chat_history + [("🟢 Mode switched", "🔬 Research Mode activated.")]
+    elif "switch to chat mode" in user_message.lower():
+        conversation_mode = "chat"
+        history_messages = [{"role": "system", "content": get_system_prompt("chat")}]
+        return "", chat_history + [("🟢 Mode switched", "💬 Chat Mode activated.")]
+
+    # Append user message
+    history_messages.append({"role": "user", "content": user_message})
+
+    try:
+        bot_text = call_model_get_response(MODEL_ID, history_messages, max_tokens=700)
+    except Exception as e:
+        tb = traceback.format_exc()
+        bot_text = f"⚠️ **Error**: {str(e)}\n\nTraceback:\n{tb.splitlines()[-6:]}"
+
+    # Append response
+    history_messages.append({"role": "assistant", "content": bot_text})
+    chat_history_for_ui.append((user_message, bot_text))
+
+    return "", chat_history_for_ui
+
+def reset_chat():
+    global history_messages, chat_history_for_ui
+    history_messages = [{"role": "system", "content": get_system_prompt(conversation_mode)}]
+    chat_history_for_ui = []
+    return []
+
+# ---------------------------
+# Gradio UI
+# ---------------------------
+def build_ui():
+    with gr.Blocks(
+        theme=gr.themes.Soft(),
+        css="""
+        #chatbot {
+            background-color: #f9f9fb;
+            border-radius: 12px;
+            padding: 10px;
+            overflow-y: auto;
+        }
+        .user-bubble {
+            background: #4a90e2;
+            color: white;
+            border-radius: 14px;
+            padding: 8px 12px;
+            margin: 6px;
+            max-width: 75%;
+            align-self: flex-end;
+            font-size: 14px;
+        }
+        .bot-bubble {
+            background: #e6e6e6;
+            color: #333;
+            border-radius: 14px;
+            padding: 8px 12px;
+            margin: 6px;
+            max-width: 75%;
+            align-self: flex-start;
+            font-size: 14px;
+        }
+        #controls {
+            display: flex;
+            gap: 8px;
+            align-items: center;
+            margin-top: 6px;
+        }
+        #topbar {
+            display: flex;
+            justify-content: flex-end;
+            gap: 8px;
+            margin-bottom: 6px;
+        }
+        """
+    ) as demo:
+        # Top bar with close + clear
+        with gr.Row(elem_id="topbar"):
+            close_btn = gr.Button("❌", size="sm")
+            clear_btn = gr.Button("🧹 Clear", size="sm")
+
+        chatbot = gr.Chatbot(
+            label="",
+            height=350,   # reduced height so input is visible
+            elem_id="chatbot",
+            type="tuples",
+            bubble_full_width=False,
+            avatar_images=("👤", "🤖"),
+        )
+
+        with gr.Row(elem_id="controls"):
+            msg = gr.Textbox(
+                placeholder="Type your message here...",
+                lines=2,
+                scale=8,
+            )
+            submit_btn = gr.Button("🚀 Send", variant="primary", scale=2)
+
+        # Wire buttons
+        submit_btn.click(chat_with_model, inputs=[msg, chatbot], outputs=[msg, chatbot])
+        msg.submit(chat_with_model, inputs=[msg, chatbot], outputs=[msg, chatbot])
+        clear_btn.click(reset_chat, inputs=None, outputs=chatbot)
+
+        demo.launch(server_name="0.0.0.0", server_port=7860, share=False)
+    return demo
+
+# ---------------------------
+# Entrypoint
+# ---------------------------
+if __name__ == "__main__":
+    print(f"✅ Starting Aerelyth with Transformers model: {MODEL_ID}")
+    build_ui()