Upload folder using huggingface_hub

.gitattributes

@@ -1,35 +1,35 @@
-*.7z filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
-*.bin filter=lfs diff=lfs merge=lfs -text
-*.bz2 filter=lfs diff=lfs merge=lfs -text
-*.ckpt filter=lfs diff=lfs merge=lfs -text
-*.ftz filter=lfs diff=lfs merge=lfs -text
-*.gz filter=lfs diff=lfs merge=lfs -text
-*.h5 filter=lfs diff=lfs merge=lfs -text
-*.joblib filter=lfs diff=lfs merge=lfs -text
-*.lfs.* filter=lfs diff=lfs merge=lfs -text
-*.mlmodel filter=lfs diff=lfs merge=lfs -text
-*.model filter=lfs diff=lfs merge=lfs -text
-*.msgpack filter=lfs diff=lfs merge=lfs -text
-*.npy filter=lfs diff=lfs merge=lfs -text
-*.npz filter=lfs diff=lfs merge=lfs -text
-*.onnx filter=lfs diff=lfs merge=lfs -text
-*.ot filter=lfs diff=lfs merge=lfs -text
-*.parquet filter=lfs diff=lfs merge=lfs -text
-*.pb filter=lfs diff=lfs merge=lfs -text
-*.pickle filter=lfs diff=lfs merge=lfs -text
-*.pkl filter=lfs diff=lfs merge=lfs -text
-*.pt filter=lfs diff=lfs merge=lfs -text
-*.pth filter=lfs diff=lfs merge=lfs -text
-*.rar filter=lfs diff=lfs merge=lfs -text
-*.safetensors filter=lfs diff=lfs merge=lfs -text
-saved_model/**/* filter=lfs diff=lfs merge=lfs -text
-*.tar.* filter=lfs diff=lfs merge=lfs -text
-*.tar filter=lfs diff=lfs merge=lfs -text
-*.tflite filter=lfs diff=lfs merge=lfs -text
-*.tgz filter=lfs diff=lfs merge=lfs -text
-*.wasm filter=lfs diff=lfs merge=lfs -text
-*.xz filter=lfs diff=lfs merge=lfs -text
-*.zip filter=lfs diff=lfs merge=lfs -text
-*.zst filter=lfs diff=lfs merge=lfs -text
-*tfevents* filter=lfs diff=lfs merge=lfs -text
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -0,0 +1,42 @@
+# Virtual environments
+venv/
+.venv/
+env/
+
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+*.egg
+*.egg-info/
+.eggs/
+dist/
+build/
+pip-wheel-metadata/
+
+# Testing / type check / lint caches
+.pytest_cache/
+.mypy_cache/
+.ruff_cache/
+.coverage
+htmlcov/
+
+# Gradio / local runs
+.gradio/
+flagged/
+
+# Environment
+.env
+.env.*
+!.env.example
+
+# IDE / OS
+.idea/
+.vscode/
+*.swp
+.DS_Store
+Thumbs.db
+
+logs/

README.md

@@ -7,7 +7,126 @@ sdk: gradio
 sdk_version: 6.11.0
 app_file: app.py
 pinned: false
-short_description: Sequential Thinking MCP Server
+short_description: Sequential Thinking MCP Server (Gradio + Python)
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Sequential Thinking — Gradio MCP Server
+
+Python [Gradio](https://www.gradio.app/) app that exposes **Sequential Thinking** as an MCP server over SSE, alongside a small UI for manual thought steps. It mirrors the behaviour of the reference [Sequential Thinking MCP server](https://github.com/modelcontextprotocol/servers/tree/main/src/sequentialthinking) (TypeScript) using Gradio’s built-in MCP support (`gradio[mcp]`).
+
+## What’s included
+
+- **MCP over HTTP (SSE)** — connect any MCP client to the Gradio `/gradio_api/mcp/sse` endpoint  
+- **Web UI** — process thoughts, reset session, inspect history, and copy-paste MCP config  
+- **Structured thinking** — revisions, branches, adjustable totals, optional “needs more thoughts”  
+- **Logging** — every thought is appended to `logs/chat_logs.jsonl`; optional periodic uploads to a Hugging Face dataset when `HF_TOKEN` and `HF_DATASET_REPO` are set (see [docs/LOGGING.md](docs/LOGGING.md))
+
+## Requirements
+
+- Python 3.10+ recommended  
+- Dependencies: see [requirements.txt](requirements.txt) (`gradio[mcp]==6.11.0`)
+
+## Run locally
+
+```bash
+python -m venv .venv
+# Windows: .venv\Scripts\activate
+# macOS/Linux: source .venv/bin/activate
+pip install -r requirements.txt
+python app.py
+```
+
+Gradio starts (default [http://localhost:7860](http://localhost:7860)). **MCP SSE URL:**
+
+`http://localhost:7860/gradio_api/mcp/sse`
+
+On Windows, if your default console encoding breaks Gradio’s startup output, use UTF-8, for example:
+
+```bash
+python -X utf8 app.py
+```
+
+**PowerShell helper:** [run.ps1](run.ps1) expects a virtualenv folder named `venv` at the repo root (`venv\Scripts\python.exe`). If you use `.venv` instead, activate it and run `python app.py` as above.
+
+## MCP tools
+
+| Tool                  | Description                                                      |
+| --------------------- | ---------------------------------------------------------------- |
+| `sequential_thinking` | Record one thinking step and return progress metadata            |
+| `reset_session`       | Clear in-memory history and branches; new session id for logging |
+| `get_history`         | Return the full thought list for the current session             |
+
+### `sequential_thinking` parameters
+
+Names follow the Python implementation (snake_case):
+
+| Parameter             | Type    | Required | Description                              |
+| --------------------- | ------- | -------- | ---------------------------------------- |
+| `thought`             | string  | yes      | Current thinking step                    |
+| `thought_number`      | integer | yes      | Step index (starts at 1)                 |
+| `total_thoughts`      | integer | yes      | Estimated total steps (can grow)         |
+| `next_thought_needed` | boolean | yes      | Whether another step is expected         |
+| `is_revision`         | boolean | no       | This step revises earlier thinking       |
+| `revises_thought`     | integer | no       | Which thought number is revised          |
+| `branch_from_thought` | integer | no       | Branch from this thought number          |
+| `branch_id`           | string  | no       | Label for the branch                     |
+| `needs_more_thoughts` | boolean | no       | Extend beyond the current total estimate |
+
+## Configure your MCP client
+
+Point the client at the SSE URL (adjust host/port if you change Gradio’s `server_name` / `server_port`).
+
+### Claude Desktop (`claude_desktop_config.json`)
+
+```json
+{
+  "mcpServers": {
+    "sequential-thinking": {
+      "url": "http://localhost:7860/gradio_api/mcp/sse"
+    }
+  }
+}
+```
+
+### VS Code — user or workspace `mcp.json`
+
+```json
+{
+  "servers": {
+    "sequential-thinking": {
+      "url": "http://localhost:7860/gradio_api/mcp/sse"
+    }
+  }
+}
+```
+
+See [VS Code MCP documentation](https://code.visualstudio.com/docs/copilot/customization/mcp-servers) for file locations.
+
+### Cursor
+
+Add an MCP server entry with the same `url` as above (for example in your Cursor MCP configuration), with the app running locally.
+
+## Environment variables
+
+| Variable                  | Effect                                                                                      |
+| ------------------------- | ------------------------------------------------------------------------------------------- |
+| `DISABLE_THOUGHT_LOGGING` | Set to `true` to suppress **console** banners for each thought (JSONL logging is unchanged) |
+| `HF_TOKEN`                | Optional — Hugging Face token for dataset upload                                            |
+| `HF_DATASET_REPO`         | Optional — dataset id (e.g. `username/my-logs`) used with `HF_TOKEN`                        |
+
+Details: [docs/LOGGING.md](docs/LOGGING.md).
+
+## Hugging Face Spaces
+
+The YAML front matter at the top of this file is for Space deployment. After deploy, use your Space URL for MCP, for example:
+
+`https://<your-space-name>.hf.space/gradio_api/mcp/sse`
+
+## Relation to other packages
+
+The npm package `@modelcontextprotocol/server-sequential-thinking` and the `mcp/sequentialthinking` Docker image are **separate** official distributions. **This repository** is source for the Gradio/Python app only; it does not ship a Dockerfile or Node build in-tree.
+
+## Docs
+
+- [docs/LOGGING.md](docs/LOGGING.md) — log format, Hugging Face upload, troubleshooting  
+- [docs/IMPLEMENTATION_SUMMARY.md](docs/IMPLEMENTATION_SUMMARY.md) — logging implementation notes  

app.py

@@ -0,0 +1,354 @@
+"""
+Sequential Thinking — Gradio MCP App
+
+Ports the Sequential Thinking MCP Server (TypeScript) to a Python Gradio app
+that exposes the same tool via Gradio's built-in MCP server support.
+
+Launch:  python app.py
+MCP SSE endpoint:  http://localhost:7860/gradio_api/mcp/sse
+"""
+
+import json
+import os
+import sys
+from typing import Optional
+from uuid import uuid4
+
+# On Windows the default console encoding (cp1252) cannot represent the emoji
+# characters that Gradio prints on startup.  Reconfigure stdout/stderr to
+# UTF-8 early so those prints succeed.  When running via `run.ps1` (or with
+# `python -X utf8 app.py`) the streams are already UTF-8 and this is a no-op.
+if sys.platform == "win32":
+    for _stream in (sys.stdout, sys.stderr):
+        try:
+            if hasattr(_stream, "reconfigure") and _stream.encoding.lower() != "utf-8":
+                _stream.reconfigure(encoding="utf-8", errors="replace")
+        except Exception:
+            pass
+
+import gradio as gr
+from theme import soft_professional_theme
+from chat_logger import log_chat, shutdown_logger
+
+# ---------------------------------------------------------------------------
+# Core state (mirrors SequentialThinkingServer in lib.ts)
+# ---------------------------------------------------------------------------
+
+_thought_history: list[dict] = []
+_branches: dict[str, list[dict]] = {}
+_session_id: str = uuid4().hex  # Session identifier for logging
+
+
+# ---------------------------------------------------------------------------
+# Tool logic
+# ---------------------------------------------------------------------------
+
+def sequential_thinking(
+    thought: str,
+    thought_number: int,
+    total_thoughts: int,
+    next_thought_needed: bool,
+    is_revision: bool = False,
+    revises_thought: Optional[int] = None,
+    branch_from_thought: Optional[int] = None,
+    branch_id: Optional[str] = None,
+    needs_more_thoughts: bool = False,
+) -> dict:
+    """
+    A detailed tool for dynamic and reflective problem-solving through thoughts.
+    This tool helps analyze problems through a flexible thinking process that
+    can adapt and evolve. Each thought can build on, question, or revise
+    previous insights as understanding deepens.
+
+    Use this tool when:
+    - Breaking down complex problems into steps
+    - Planning and design with room for revision
+    - Analysis that might need course correction
+    - Problems where the full scope is not clear initially
+    - Tasks that need context maintained over multiple steps
+
+    Args:
+        thought: Your current thinking step (analytical step, revision, question, hypothesis, etc.)
+        thought_number: Current thought number in sequence (starts at 1)
+        total_thoughts: Estimated total thoughts needed — can be adjusted up or down
+        next_thought_needed: True if more thinking is required, even if at what seemed like the end
+        is_revision: True if this thought revises or corrects a previous thought
+        revises_thought: Which thought number is being reconsidered (required when is_revision=True)
+        branch_from_thought: Thought number this branch splits off from (for alternative paths)
+        branch_id: Unique identifier for this branch (e.g. "alternative-approach")
+        needs_more_thoughts: True if you realise more thoughts are needed beyond totalThoughts
+
+    Returns:
+        dict with thoughtNumber, totalThoughts, nextThoughtNeeded, branches, thoughtHistoryLength
+    """
+    global _thought_history, _branches
+
+    # Sanitise optional int inputs that arrive as 0 from Gradio Number widgets
+    if revises_thought == 0:
+        revises_thought = None
+    if branch_from_thought == 0:
+        branch_from_thought = None
+
+    # Mirror TypeScript behaviour: expand totalThoughts if thoughtNumber exceeds it
+    if thought_number > total_thoughts:
+        total_thoughts = thought_number
+
+    thought_data: dict = {
+        "thought": thought,
+        "thoughtNumber": thought_number,
+        "totalThoughts": total_thoughts,
+        "isRevision": is_revision,
+        "revisesThought": revises_thought,
+        "branchFromThought": branch_from_thought,
+        "branchId": branch_id if branch_id and branch_id.strip() else None,
+        "needsMoreThoughts": needs_more_thoughts,
+        "nextThoughtNeeded": next_thought_needed,
+    }
+
+    _thought_history.append(thought_data)
+
+    if branch_from_thought and branch_id and branch_id.strip():
+        _branches.setdefault(branch_id, []).append(thought_data)
+
+    _log_thought(thought_data)
+
+    # Log to local storage
+    log_chat(
+        session_id=_session_id,
+        model_name="sequential-thinking",
+        thought=thought,
+        thought_number=thought_number,
+        total_thoughts=total_thoughts,
+        metadata={
+            "is_revision": is_revision,
+            "revises_thought": revises_thought,
+            "branch_from_thought": branch_from_thought,
+            "branch_id": branch_id,
+            "needs_more_thoughts": needs_more_thoughts,
+            "next_thought_needed": next_thought_needed,
+        }
+    )
+
+    return {
+        "thoughtNumber": thought_number,
+        "totalThoughts": total_thoughts,
+        "nextThoughtNeeded": next_thought_needed,
+        "branches": list(_branches.keys()),
+        "thoughtHistoryLength": len(_thought_history),
+    }
+
+
+def reset_session() -> str:
+    """
+    Reset the thought history and all branches, starting a fresh problem-solving session.
+
+    Returns:
+        Confirmation message string.
+    """
+    global _thought_history, _branches, _session_id
+    _thought_history = []
+    _branches = {}
+    _session_id = uuid4().hex  # Generate new session ID
+    return "Session reset. Ready for a new problem-solving session."
+
+
+def get_history() -> list:
+    """
+    Return the full thought history for the current session.
+
+    Returns:
+        List of all recorded thought objects.
+    """
+    return _thought_history
+
+
+# ---------------------------------------------------------------------------
+# Logging helper (mirrors lib.ts formatThought, without chalk colours)
+# ---------------------------------------------------------------------------
+
+def _log_thought(data: dict) -> None:
+    if os.environ.get("DISABLE_THOUGHT_LOGGING", "").lower() == "true":
+        return
+
+    t_num = data["thoughtNumber"]
+    t_total = data["totalThoughts"]
+    thought = data["thought"]
+
+    if data.get("isRevision"):
+        label = f"[Revision] {t_num}/{t_total} (revising thought {data.get('revisesThought')})"
+    elif data.get("branchFromThought"):
+        label = (
+            f"[Branch] {t_num}/{t_total} "
+            f"(from thought {data['branchFromThought']}, ID: {data.get('branchId')})"
+        )
+    else:
+        label = f"[Thought] {t_num}/{t_total}"
+
+    width = max(len(label), len(thought)) + 4
+    border = "-" * width
+    try:
+        print(f"\n+{border}+")
+        print(f"| {label.ljust(width - 2)} |")
+        print(f"+{border}+")
+        print(f"| {thought.ljust(width - 2)} |")
+        print(f"+{border}+")
+    except UnicodeEncodeError:
+        print(f"\n{label}\n  {thought}")
+
+
+# ---------------------------------------------------------------------------
+# Gradio UI
+# ---------------------------------------------------------------------------
+
+DESCRIPTION = """
+# 🧠 Sequential Thinking MCP Server
+
+Dynamic, reflective problem-solving through structured thoughts.  
+This Gradio app exposes the **Sequential Thinking** tool as an MCP server.
+
+**MCP endpoint (SSE):** `http://localhost:7860/gradio_api/mcp/sse`
+"""
+
+# Load custom CSS
+with open('styles.css', 'r') as f:
+    custom_css = f.read()
+
+with gr.Blocks(title="Sequential Thinking MCP", theme=soft_professional_theme, css=custom_css) as demo:
+    gr.Markdown(DESCRIPTION)
+
+    with gr.Tabs():
+
+        # ------------------------------------------------------------------
+        # Tab 1 — process a thought
+        # ------------------------------------------------------------------
+        with gr.Tab("Process Thought"):
+            with gr.Row(equal_height=False):
+                with gr.Column(scale=1):
+                    thought_input = gr.Textbox(
+                        label="Thought",
+                        placeholder="Enter your current thinking step…",
+                        lines=5,
+                    )
+                    with gr.Row():
+                        thought_number_input = gr.Number(
+                            label="Thought Number", value=1, minimum=1, precision=0
+                        )
+                        total_thoughts_input = gr.Number(
+                            label="Total Thoughts (estimate)", value=5, minimum=1, precision=0
+                        )
+                    next_thought_needed_input = gr.Checkbox(
+                        label="Next Thought Needed", value=True
+                    )
+
+                    with gr.Accordion("Advanced options", open=False):
+                        is_revision_input = gr.Checkbox(label="Is Revision", value=False)
+                        revises_thought_input = gr.Number(
+                            label="Revises Thought #",
+                            minimum=0,
+                            precision=0,
+                            value=0,
+                            info="0 = not applicable",
+                        )
+                        branch_from_thought_input = gr.Number(
+                            label="Branch From Thought #",
+                            minimum=0,
+                            precision=0,
+                            value=0,
+                            info="0 = not applicable",
+                        )
+                        branch_id_input = gr.Textbox(
+                            label="Branch ID",
+                            placeholder="e.g. alternative-approach",
+                        )
+                        needs_more_thoughts_input = gr.Checkbox(
+                            label="Needs More Thoughts", value=False
+                        )
+
+                    with gr.Row():
+                        submit_btn = gr.Button("Process Thought", variant="primary")
+                        reset_btn = gr.Button("Reset Session", variant="secondary")
+
+                with gr.Column(scale=1):
+                    output_json = gr.JSON(label="Result")
+                    status_box = gr.Textbox(label="Status", interactive=False, visible=True)
+
+            submit_btn.click(
+                fn=sequential_thinking,
+                inputs=[
+                    thought_input,
+                    thought_number_input,
+                    total_thoughts_input,
+                    next_thought_needed_input,
+                    is_revision_input,
+                    revises_thought_input,
+                    branch_from_thought_input,
+                    branch_id_input,
+                    needs_more_thoughts_input,
+                ],
+                outputs=output_json,
+            )
+
+            reset_btn.click(fn=reset_session, inputs=[], outputs=status_box)
+
+        # ------------------------------------------------------------------
+        # Tab 2 — inspect history
+        # ------------------------------------------------------------------
+        with gr.Tab("Thought History"):
+            refresh_btn = gr.Button("Refresh")
+            history_output = gr.JSON(label="All Thoughts")
+            refresh_btn.click(fn=get_history, inputs=[], outputs=history_output)
+
+        # ------------------------------------------------------------------
+        # Tab 3 — quick reference
+        # ------------------------------------------------------------------
+        with gr.Tab("MCP Reference"):
+            gr.Markdown("""
+## Connecting via MCP
+
+Add this to your MCP client configuration:
+
+```json
+{
+  "mcpServers": {
+    "sequential-thinking": {
+      "url": "http://localhost:7860/gradio_api/mcp/sse"
+    }
+  }
+}
+```
+
+## Exposed MCP Tools
+
+| Tool | Description |
+|------|-------------|
+| `sequential_thinking` | Process a single thought step |
+| `reset_session` | Clear history and branches |
+| `get_history` | Return the full thought history |
+
+## Parameters for `sequential_thinking`
+
+| Parameter | Type | Required | Description |
+|-----------|------|----------|-------------|
+| `thought` | string | ✅ | Current thinking step |
+| `thought_number` | int | ✅ | Step index (starts at 1) |
+| `total_thoughts` | int | ✅ | Estimated total steps |
+| `next_thought_needed` | bool | ✅ | More steps required? |
+| `is_revision` | bool | | Revises an earlier thought |
+| `revises_thought` | int | | Which thought is revised |
+| `branch_from_thought` | int | | Branch origin thought |
+| `branch_id` | string | | Branch label |
+| `needs_more_thoughts` | bool | | Extend beyond estimate |
+
+## Environment Variables
+
+| Variable | Default | Description |
+|----------|---------|-------------|
+| `DISABLE_THOUGHT_LOGGING` | `false` | Set to `true` to suppress console output |
+""")
+
+
+if __name__ == "__main__":
+    try:
+        demo.launch(mcp_server=True)
+    finally:
+        shutdown_logger()

chat_logger.py

@@ -0,0 +1,143 @@
+"""Chat logging module with local JSONL storage and optional HuggingFace upload."""
+
+import os
+import json
+import threading
+import atexit
+from queue import Queue
+from datetime import datetime
+from pathlib import Path
+from typing import Any, Optional
+
+try:
+    from huggingface_hub import HfApi
+    HF_AVAILABLE = True
+except ImportError:
+    HF_AVAILABLE = False
+
+# Configuration
+HF_TOKEN = os.environ.get("HF_TOKEN")
+DATASET_REPO_ID = os.environ.get("HF_DATASET_REPO")
+LOCAL_LOG_DIR = Path("logs")
+LOCAL_LOG_FILE = LOCAL_LOG_DIR / "chat_logs.jsonl"
+UPLOAD_INTERVAL_SECONDS = 300  # 5 minutes
+
+# Ensure log directory exists
+LOCAL_LOG_DIR.mkdir(exist_ok=True)
+
+# Thread-safe queue for async logging
+_log_queue: Queue = Queue()
+_shutdown_event = threading.Event()
+_upload_lock = threading.Lock()
+_worker_thread_started = False
+
+
+def log_chat(
+    session_id: str,
+    model_name: str,
+    thought: str,
+    thought_number: int,
+    total_thoughts: int,
+    metadata: Optional[dict] = None
+) -> None:
+    """Queue a thought log entry for async processing."""
+    _log_queue.put({
+        "session_id": session_id,
+        "model_name": model_name,
+        "thought": thought,
+        "thought_number": thought_number,
+        "total_thoughts": total_thoughts,
+        "metadata": metadata or {},
+        "timestamp": datetime.now().isoformat()
+    })
+
+
+def _write_to_jsonl(entry: dict) -> None:
+    """Append a log entry to the local JSONL file."""
+    try:
+        with open(LOCAL_LOG_FILE, "a", encoding="utf-8") as f:
+            f.write(json.dumps(entry, ensure_ascii=False) + "\n")
+    except Exception as e:
+        print(f"Error writing to JSONL: {e}")
+
+
+def _worker_thread():
+    """Background worker that processes the log queue."""
+    while not _shutdown_event.is_set():
+        try:
+            entry = _log_queue.get(timeout=1.0)
+            _write_to_jsonl(entry)
+            _log_queue.task_done()
+        except Exception:
+            continue
+
+
+def _upload_to_huggingface() -> bool:
+    """Upload local JSONL to HuggingFace dataset (if configured)."""
+    if not HF_AVAILABLE or not HF_TOKEN or not DATASET_REPO_ID:
+        return False
+
+    with _upload_lock:
+        if not LOCAL_LOG_FILE.exists():
+            return False
+
+        try:
+            api = HfApi(token=HF_TOKEN)
+
+            # Ensure repo exists
+            try:
+                api.repo_info(repo_id=DATASET_REPO_ID, repo_type="dataset")
+            except Exception:
+                api.create_repo(
+                    repo_id=DATASET_REPO_ID,
+                    repo_type="dataset",
+                    private=True
+                )
+
+            # Upload with timestamp
+            timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+            api.upload_file(
+                path_or_fileobj=str(LOCAL_LOG_FILE),
+                path_in_repo=f"logs/chat_logs_{timestamp}.jsonl",
+                repo_id=DATASET_REPO_ID,
+                repo_type="dataset",
+                commit_message=f"Chat logs upload {timestamp}"
+            )
+
+            # Clear local file after successful upload
+            LOCAL_LOG_FILE.unlink()
+            LOCAL_LOG_FILE.touch()
+            return True
+        except Exception as e:
+            print(f"HuggingFace upload failed: {e}")
+            return False
+
+
+def _upload_timer_thread():
+    """Periodic upload thread."""
+    while not _shutdown_event.is_set():
+        _shutdown_event.wait(timeout=UPLOAD_INTERVAL_SECONDS)
+        if not _shutdown_event.is_set():
+            _upload_to_huggingface()
+
+
+def shutdown_logger():
+    """Gracefully shutdown logger and upload remaining logs."""
+    _shutdown_event.set()
+    _log_queue.join()  # Wait for queue to empty
+    _upload_to_huggingface()  # Final upload
+
+
+def _ensure_threads_started():
+    """Start background threads if not already started."""
+    global _worker_thread_started
+    if not _worker_thread_started:
+        _worker_thread_started = True
+        threading.Thread(target=_worker_thread, daemon=True).start()
+        if HF_AVAILABLE and HF_TOKEN and DATASET_REPO_ID:
+            threading.Thread(target=_upload_timer_thread, daemon=True).start()
+        atexit.register(shutdown_logger)
+
+
+# Ensure threads start when module is imported
+_ensure_threads_started()

docs/IMPLEMENTATION_SUMMARY.md

@@ -0,0 +1,89 @@
+# Chat Logging Implementation Summary
+
+## Changes Made
+
+### 1. **New File: `chat_logger.py`**
+   - Implements local JSONL chat logging with thread-safe async processing
+   - **Local logging**: Always enabled, writes to `logs/chat_logs.jsonl`
+   - **Optional HuggingFace upload**: Only if `HF_TOKEN` and `HF_DATASET_REPO` environment variables are set
+   - **Features**:
+     - Queue-based async processing (non-blocking)
+     - Automatic background worker thread
+     - Periodic HuggingFace uploads (every 5 minutes)
+     - Graceful shutdown with final flush
+     - Automatic dataset creation if needed
+
+### 2. **Updated `app.py`**
+   - Added imports: `uuid4`, `log_chat`, `shutdown_logger`
+   - Added `_session_id` state variable (unique per session)
+   - Updated `sequential_thinking()`: Logs each thought with metadata
+   - Updated `reset_session()`: Generates new session ID when resetting
+   - Updated `__main__`: Calls `shutdown_logger()` on app exit for graceful cleanup
+
+### 3. **New File: `LOGGING.md`**
+   - Complete documentation of logging features
+   - Configuration instructions
+   - Environment variables reference
+   - Data format examples
+   - Troubleshooting guide
+
+## Usage
+
+### No Configuration (Local Logging Only)
+```bash
+python app.py
+```
+- Logs all thoughts to `logs/chat_logs.jsonl`
+- No external dependencies required
+
+### With HuggingFace Upload
+```bash
+export HF_TOKEN=hf_xxxxxxxxxxxxx
+export HF_DATASET_REPO=username/my-logs
+python app.py
+```
+- Logs locally AND uploads to HuggingFace every 5 minutes
+- Automatic dataset creation
+
+## What Gets Logged
+
+Each thought entry includes:
+- **session_id**: Unique session identifier
+- **model_name**: `"sequential-thinking"`
+- **thought**: The actual thought text
+- **thought_number**: Step number in sequence
+- **total_thoughts**: Estimated total steps
+- **metadata**: Revision/branch information
+- **timestamp**: ISO 8601 timestamp
+
+Example:
+```json
+{
+  "session_id": "abc123xyz...",
+  "model_name": "sequential-thinking",
+  "thought": "First, let me understand the problem...",
+  "thought_number": 1,
+  "total_thoughts": 5,
+  "metadata": {
+    "is_revision": false,
+    "branch_id": null,
+    "next_thought_needed": true
+  },
+  "timestamp": "2024-01-15T10:30:00.123456"
+}
+```
+
+## Key Features
+
+✅ **Always on** - Local logging works without any configuration  
+✅ **Optional upload** - HuggingFace integration only if credentials set  
+✅ **Async processing** - Non-blocking, runs in background threads  
+✅ **Graceful shutdown** - Flushes all pending logs before exit  
+✅ **Session tracking** - Groups related thoughts by session ID  
+✅ **Error handling** - Continues working even if upload fails  
+
+## Files Modified/Created
+
+- ✅ Created: `chat_logger.py` (140 lines)
+- ✅ Created: `LOGGING.md` (documentation)
+- ✅ Updated: `app.py` (added logging integration)

docs/LOGGING.md

@@ -0,0 +1,153 @@
+# Sequential Thinking with Chat Logging
+
+This Gradio application now includes automatic chat logging for all thoughts and thinking processes.
+
+## Chat Logging Features
+
+### Local Logging (Always Enabled)
+
+All thought records are automatically logged to a local JSONL file at `logs/chat_logs.jsonl`:
+
+```json
+{
+  "session_id": "abc123xyz789...",
+  "model_name": "sequential-thinking",
+  "thought": "Let me break down this problem step by step...",
+  "thought_number": 1,
+  "total_thoughts": 5,
+  "metadata": {
+    "is_revision": false,
+    "revises_thought": null,
+    "branch_from_thought": null,
+    "branch_id": null,
+    "needs_more_thoughts": false,
+    "next_thought_needed": true
+  },
+  "timestamp": "2024-01-15T10:30:00.123456"
+}
+```
+
+#### Accessing Local Logs
+
+Local logs are written asynchronously to `logs/chat_logs.jsonl`. Each line is a complete JSON object representing one thought entry.
+
+### HuggingFace Dataset Upload (Optional)
+
+If you have HuggingFace Hub credentials configured, logs are automatically uploaded periodically:
+
+#### Configuration
+
+Set these environment variables:
+
+```bash
+export HF_TOKEN=hf_xxxxxxxxxxxxx
+export HF_DATASET_REPO=username/my-sequential-thinking-logs
+```
+
+#### Upload Behavior
+
+- **Interval**: Every 5 minutes (configurable in `chat_logger.py`)
+- **Format**: Timestamped files named `logs/chat_logs_YYYYMMDD_HHMMSS.jsonl`
+- **Cleanup**: Local file is cleared after successful upload
+- **Fallback**: If upload fails, logs remain locally and retry on next interval
+
+#### Creating a HuggingFace Dataset
+
+If the dataset doesn't exist, the logger creates it automatically on first upload (must be private).
+
+## Running the App
+
+### Standard Launch
+
+```bash
+python app.py
+```
+
+The app will:
+1. Start the Gradio interface at `http://localhost:7860`
+2. Begin logging all thoughts to `logs/chat_logs.jsonl`
+3. Upload to HuggingFace (if configured) every 5 minutes
+4. Flush remaining logs on shutdown
+
+### Environment Variables
+
+| Variable | Default | Description |
+|----------|---------|-------------|
+| `HF_TOKEN` | - | HuggingFace API token (optional) |
+| `HF_DATASET_REPO` | - | HuggingFace dataset repo ID (optional) |
+| `DISABLE_THOUGHT_LOGGING` | `false` | Suppress console output of thoughts |
+
+### Disabling Console Output
+
+```bash
+DISABLE_THOUGHT_LOGGING=true python app.py
+```
+
+Logs will still be saved locally; only console printing is suppressed.
+
+## MCP Server
+
+The app also exposes an MCP (Model Context Protocol) endpoint:
+
+**SSE Endpoint**: `http://localhost:7860/gradio_api/mcp/sse`
+
+Configure in your MCP client:
+
+```json
+{
+  "mcpServers": {
+    "sequential-thinking": {
+      "url": "http://localhost:7860/gradio_api/mcp/sse"
+    }
+  }
+}
+```
+
+## Log Data Structure
+
+Each logged thought contains:
+
+- **session_id**: Unique identifier for the current thinking session
+- **model_name**: Always `"sequential-thinking"` for this app
+- **thought**: The actual thought text
+- **thought_number**: Current step number
+- **total_thoughts**: Estimated total steps
+- **metadata**: Additional context including revision/branch info
+- **timestamp**: ISO 8601 timestamp
+
+## Sessions
+
+A new session ID is generated:
+- When the app starts
+- When "Reset Session" is clicked in the UI
+
+All thoughts in a session share the same `session_id`, making it easy to group related thinking processes.
+
+## Data Privacy
+
+- Local logs are stored in `logs/chat_logs.jsonl` on your machine
+- Only uploaded to HuggingFace if credentials are configured
+- Uploaded datasets are set to private by default
+- Logs are cleared from local storage after successful HuggingFace upload
+
+## Troubleshooting
+
+### Logs Not Appearing
+
+1. Check that `logs/` directory exists: `ls logs/`
+2. Verify JSONL file: `tail -f logs/chat_logs.jsonl`
+3. Check console for any error messages
+
+### HuggingFace Upload Issues
+
+1. Verify `HF_TOKEN` is valid: `huggingface-cli whoami`
+2. Ensure `HF_DATASET_REPO` follows format: `username/repo-name`
+3. Check internet connection
+4. Logs will retry on next interval; check for error messages in console
+
+### Performance
+
+Logging runs in background threads and has minimal impact on performance:
+- Queue-based async processing
+- Non-blocking JSONL writes
+- Periodic batch uploads to HuggingFace

requirements.txt

@@ -0,0 +1 @@
+gradio[mcp]==6.11.0

run.ps1

@@ -0,0 +1,6 @@
+# Activate the virtual environment and launch the Gradio MCP app.
+# The -X utf8 flag forces UTF-8 I/O so Gradio's emoji startup messages
+# render correctly on Windows terminals.
+
+$scriptDir = Split-Path -Parent $MyInvocation.MyCommand.Path
+& "$scriptDir\venv\Scripts\python.exe" -X utf8 -u "$scriptDir\app.py" @args

styles.css

@@ -0,0 +1,179 @@
+:root {
+    --color-grey-50: #f9fafb;
+    --banner-background: var(--secondary-400);
+    --banner-text-color: var(--primary-200);
+    --banner-background-dark: var(--secondary-800);
+    --banner-text-color-dark: var(--primary-100);
+    --banner-text-a-color: var(--primary-100);
+    --banner-text-a-color-dark: var(--secondary-100);
+    --banner-chrome-height: calc(16px + 43px);
+
+    /* Chrome height with no banner */
+    --chat-chrome-height-wide-no-banner: 320px;
+    --chat-chrome-height-narrow-no-banner: 450px;
+
+    /* Use these when we are not using a banner */
+    /*--chat-chrome-height-wide: var(--chat-chrome-height-wide-no-banner);*/
+    /*--chat-chrome-height-narrow: var(--chat-chrome-height-narrow-no-banner);*/
+
+    /* When we are using a banner, add the banner height to the chat chrome height */
+    --chat-chrome-height-wide: calc(var(--chat-chrome-height-wide-no-banner) + var(--banner-chrome-height));
+    --chat-chrome-height-narrow: calc(var(--chat-chrome-height-narrow-no-banner) + var(--banner-chrome-height));
+}
+
+.banner-message {
+    background-color: var(--banner-background);
+    padding: 5px;
+    margin: 0;
+    border-radius: 5px;
+    border: none;
+}
+
+.banner-message-text {
+    font-size: 14px;
+    font-weight: bolder;
+    color: var(--banner-text-color) !important;
+}
+
+.banner-message-emoji {
+    margin-right: 3px;
+    font-size: 16px;
+}
+
+.banner-message-text a {
+    color: var(--banner-text-a-color) !important;
+}
+
+body.dark .banner-message {
+    background-color: var(--banner-background-dark) !important;
+}
+body.dark .gradio-container .contain .banner-message .banner-message-text {
+    color: var(--banner-text-color-dark) !important;
+}
+
+body.dark .gradio-container .contain .banner-message .banner-message-text a {
+    color: var(--banner-text-a-color-dark) !important;
+}
+
+.toast-body {
+    background-color: var(--color-grey-50);
+}
+
+.html-container:has(.css-styles) {
+    padding: 0;
+    margin: 0;
+}
+
+.css-styles {
+    height: 0;
+}
+
+.model-message {
+    text-align: end;
+}
+
+.model-dropdown-container {
+    display: flex;
+    align-items: center;
+    gap: 10px;
+    padding: 0;
+}
+
+.user-input-container .multimodal-textbox{
+    border: none !important;
+}
+
+/* Match the height of the modified multimodal input box on the same row */
+.control-button {
+    height: 51px;
+}
+
+button.cancel {
+    border: var(--button-border-width) solid var(--button-cancel-border-color);
+    background: var(--button-cancel-background-fill);
+    color: var(--button-cancel-text-color);
+    box-shadow: var(--button-cancel-shadow);
+}
+
+button.cancel:hover, .cancel[disabled] {
+    background: var(--button-cancel-background-fill-hover);
+    color: var(--button-cancel-text-color-hover);
+}
+
+.opt-out-message {
+    top: 8px;
+}
+
+.opt-out-message .html-container, .opt-out-checkbox label {
+    font-size: 14px !important;
+    padding: 0 !important;
+    margin: 0 !important;
+    color: var(--neutral-400) !important;
+}
+
+div.block.chatbot {
+    height: calc(100svh - var(--chat-chrome-height-wide)) !important;
+    max-height: 900px !important;
+}
+
+div.no-padding {
+    padding: 0 !important;
+}
+
+@media (max-width: 1280px) {
+    div.block.chatbot {
+        height: calc(100svh - var(--chat-chrome-height-wide)) !important;
+    }
+}
+
+@media (max-width: 1024px) {
+    .responsive-row {
+        flex-direction: column;
+    }
+
+    .model-message {
+        text-align: start;
+        font-size: 10px !important;
+    }
+
+    .model-dropdown-container {
+        flex-direction: column;
+        align-items: flex-start;
+    }
+
+    div.block.chatbot {
+        height: calc(100svh - var(--chat-chrome-height-narrow)) !important;
+    }
+}
+
+@media (max-width: 400px) {
+    .responsive-row {
+        flex-direction: column;
+    }
+
+    .model-message {
+        text-align: start;
+        font-size: 10px !important;
+    }
+
+    .model-dropdown-container {
+        flex-direction: column;
+        align-items: flex-start;
+    }
+
+    div.block.chatbot {
+        max-height: 360px !important;
+    }
+}
+
+@media (max-height: 932px) {
+    .chatbot {
+        max-height: 500px !important;
+    }
+}
+
+@media (max-height: 1280px) {
+    div.block.chatbot {
+        max-height: 800px !important;
+    }
+}

theme.py

@@ -0,0 +1,136 @@
+"""
+Soft Professional Tech Theme for Sequential Thinking MCP App
+Clean, modern aesthetic with teal-gray accents, soft gradients, and professional typography.
+"""
+
+from typing import Iterable
+from gradio.themes import Soft
+from gradio.themes.utils import colors, fonts, sizes
+
+# Primary accent color - Teal Gray
+# A sophisticated blue-teal that works well in both light and dark modes
+colors.teal_gray = colors.Color(
+    name="teal_gray",
+    c50="#e8f1f4",   # Lightest - backgrounds
+    c100="#cddde3",  # Light accents
+    c200="#a8c3cf",  # Subtle highlights
+    c300="#7da6b8",  # Secondary text
+    c400="#588aa2",  # Primary buttons
+    c500="#3d6e87",  # Base accent color
+    c600="#335b70",  # Hover states
+    c700="#2b495a",  # Dark mode accents
+    c800="#2c5364",  # Dark backgrounds
+    c900="#233f4b",  # Darker backgrounds
+    c950="#1b323c",  # Darkest
+)
+
+# Cancel/destructive action color - Muted Red Gray
+# Less aggressive than pure red, better for professional UIs
+colors.red_gray = colors.Color(
+    name="red_gray",
+    c50="#f7eded",
+    c100="#f5dcdc",
+    c200="#efb4b4",
+    c300="#e78f8f",
+    c400="#d96a6a",  # Cancel button background
+    c500="#c65353",  # Cancel button hover
+    c600="#b24444",
+    c700="#8f3434",  # Dark mode cancel
+    c800="#732d2d",
+    c900="#5f2626",
+    c950="#4d2020",
+)
+
+
+class SoftProfessionalTheme(Soft):
+    """
+    Soft Professional Tech Theme
+    
+    A clean, modern theme with teal-gray accents, soft gradients,
+    and professional typography. Suitable for chat apps, dashboards,
+    and any professional-grade Gradio application.
+    """
+    def __init__(
+            self,
+            *,
+            primary_hue: colors.Color | str = colors.gray,
+            secondary_hue: colors.Color | str = colors.teal_gray,
+            neutral_hue: colors.Color | str = colors.slate,
+            text_size: sizes.Size | str = sizes.text_md,
+            font: fonts.Font | str | Iterable[fonts.Font | str] = (
+                fonts.GoogleFont("Inconsolata"),
+                "Arial",
+                "sans-serif",
+            ),
+            font_mono: fonts.Font | str | Iterable[fonts.Font | str] = (
+                fonts.GoogleFont("IBM Plex Mono"),
+                "ui-monospace",
+                "monospace",
+            ),
+    ):
+        super().__init__(
+            primary_hue=primary_hue,
+            secondary_hue=secondary_hue,
+            neutral_hue=neutral_hue,
+            text_size=text_size,
+            font=font,
+            font_mono=font_mono,
+        )
+        super().set(
+            # === BACKGROUNDS ===
+            # Soft diagonal gradient for body - creates depth without distraction
+            body_background_fill="linear-gradient(135deg, *primary_200, *primary_100)",
+            body_background_fill_dark="linear-gradient(135deg, *primary_900, *primary_800)",
+            background_fill_primary="*primary_50",
+            background_fill_primary_dark="*primary_900",
+
+            # === PRIMARY BUTTONS ===
+            # Teal-gray gradient buttons with proper hover states
+            button_primary_text_color="white",
+            button_primary_text_color_hover="black",
+            button_primary_background_fill="linear-gradient(90deg, *secondary_400, *secondary_400)",
+            button_primary_background_fill_hover="linear-gradient(90deg, *secondary_300, *secondary_300)",
+            button_primary_background_fill_dark="linear-gradient(90deg, *secondary_600, *secondary_800)",
+            button_primary_background_fill_hover_dark="linear-gradient(90deg, *secondary_500, *secondary_500)",
+            button_primary_shadow="*shadow_drop_lg",
+
+            # === SECONDARY BUTTONS ===
+            # Subtle gray gradient for secondary actions
+            button_secondary_text_color="black",
+            button_secondary_text_color_hover="white",
+            button_secondary_background_fill="linear-gradient(90deg, *primary_300, *primary_300)",
+            button_secondary_background_fill_hover="linear-gradient(90deg, *primary_400, *primary_400)",
+            button_secondary_background_fill_dark="linear-gradient(90deg, *primary_500, *primary_600)",
+            button_secondary_background_fill_hover_dark="linear-gradient(90deg, *primary_500, *primary_500)",
+
+            # === CANCEL/STOP BUTTONS ===
+            # Muted red-gray for less aggressive cancel actions
+            button_cancel_background_fill=f"linear-gradient(90deg, {colors.red_gray.c400}, {colors.red_gray.c500})",
+            button_cancel_background_fill_dark=f"linear-gradient(90deg, {colors.red_gray.c700}, {colors.red_gray.c800})",
+            button_cancel_background_fill_hover=f"linear-gradient(90deg, {colors.red_gray.c500}, {colors.red_gray.c600})",
+            button_cancel_background_fill_hover_dark=f"linear-gradient(90deg, {colors.red_gray.c800}, {colors.red_gray.c900})",
+            button_cancel_text_color="white",
+            button_cancel_text_color_dark="white",
+            button_cancel_text_color_hover="white",
+            button_cancel_text_color_hover_dark="white",
+
+            # === SLIDERS ===
+            slider_color="*secondary_300",
+            slider_color_dark="*secondary_600",
+
+            # === BLOCKS & CONTAINERS ===
+            block_title_text_weight="600",
+            block_border_width="3px",
+            block_shadow="*shadow_drop_lg",
+            block_label_background_fill="*primary_200",
+
+            # === BUTTONS GENERAL ===
+            button_large_padding="11px",
+
+            # === ACCENTS ===
+            color_accent_soft="*primary_100",
+        )
+
+
+# Export theme instance for easy import
+soft_professional_theme = SoftProfessionalTheme()