Spaces:
Sleeping
Sleeping
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#!/usr/bin/env python3
"""
Docs Navigator MCP - Modern Gradio UI
An elegant, AI-powered documentation assistant with advanced features.
"""
import os
import gradio as gr
from pathlib import Path
from typing import List, Dict, Optional
from anthropic import Anthropic
from dotenv import load_dotenv
from document_intelligence import DocumentIntelligence
import time
# Load environment variables
load_dotenv()
# Configuration
DOCS_DIR = Path(__file__).parent / "docs"
ANTHROPIC_API_KEY = os.getenv("ANTHROPIC_API_KEY")
# Initialize services
client = Anthropic(api_key=ANTHROPIC_API_KEY)
doc_intelligence = DocumentIntelligence(DOCS_DIR)
# Supported file extensions
SUPPORTED_EXTENSIONS = {'.md', '.txt', '.rst', '.pdf'}
def load_documentation() -> str:
"""Load all documentation files into a single context."""
all_docs = []
if not DOCS_DIR.exists():
return "Documentation directory not found."
for file_path in DOCS_DIR.rglob('*'):
if file_path.is_file() and file_path.suffix in SUPPORTED_EXTENSIONS:
try:
if file_path.suffix == '.pdf':
content = extract_pdf_content(file_path)
else:
content = file_path.read_text(encoding='utf-8', errors='ignore')
relative_path = file_path.relative_to(DOCS_DIR)
all_docs.append(f"=== {relative_path} ===\n{content}\n")
except Exception as e:
all_docs.append(f"=== {file_path.name} ===\nError reading file: {str(e)}\n")
return "\n\n".join(all_docs) if all_docs else "No documentation files found."
def extract_pdf_content(pdf_path: Path) -> str:
"""Extract text content from PDF files."""
try:
from PyPDF2 import PdfReader
reader = PdfReader(pdf_path)
content = []
for i, page in enumerate(reader.pages, 1):
try:
text = page.extract_text()
content.append(f"--- Page {i} ---\n{text}")
except Exception as e:
content.append(f"--- Page {i} (Error reading: {str(e)}) ---")
return "\n\n".join(content)
except Exception as e:
return f"Error extracting PDF: {str(e)}"
def get_available_files() -> List[str]:
"""Get list of available documentation files."""
files = []
if DOCS_DIR.exists():
for file_path in DOCS_DIR.rglob('*'):
if file_path.is_file() and file_path.suffix in SUPPORTED_EXTENSIONS:
files.append(str(file_path.relative_to(DOCS_DIR)))
return sorted(files)
def chat_with_docs(message: str, history: List, system_prompt: str = None) -> str:
"""Process user message and generate AI response."""
if not ANTHROPIC_API_KEY:
return "β οΈ Please set your ANTHROPIC_API_KEY in the .env file."
# Load documentation context
docs_context = load_documentation()
# Build conversation history - support both tuple and dict formats
messages = []
for item in history:
if isinstance(item, dict):
# Messages format (Gradio 6.x)
if item.get("role") in ["user", "assistant"]:
messages.append({"role": item["role"], "content": item["content"]})
elif isinstance(item, (list, tuple)) and len(item) == 2:
# Tuple format (Gradio 4.x)
user_msg, assistant_msg = item
if user_msg:
messages.append({"role": "user", "content": user_msg})
if assistant_msg:
messages.append({"role": "assistant", "content": assistant_msg})
messages.append({"role": "user", "content": message})
# Default system prompt
default_system = f"""You are an expert documentation assistant. You have access to the following documentation:
{docs_context}
Your role is to:
- Answer questions accurately based on the documentation
- Provide clear, concise, and helpful responses
- Reference specific sections when relevant
- Admit when information is not in the documentation
- Use markdown formatting for better readability
- Be friendly and professional
Always base your answers on the provided documentation."""
system = system_prompt if system_prompt else default_system
try:
# Call Claude API with streaming
response_text = ""
with client.messages.stream(
model="claude-3-haiku-20240307",
max_tokens=4096,
system=system,
messages=messages
) as stream:
for text in stream.text_stream:
response_text += text
return response_text
except Exception as e:
return f"β Error: {str(e)}"
def get_document_stats() -> str:
"""Get statistics about the documentation."""
if not DOCS_DIR.exists():
return "π No documentation directory found"
files = list(DOCS_DIR.rglob('*'))
doc_files = [f for f in files if f.is_file() and f.suffix in SUPPORTED_EXTENSIONS]
total_size = sum(f.stat().st_size for f in doc_files) / 1024 # KB
stats = f"""
π **Documentation Statistics**
- π Total Files: {len(doc_files)}
- πΎ Total Size: {total_size:.1f} KB
- π Directory: `{DOCS_DIR.name}/`
**File Types:**
"""
by_type = {}
for f in doc_files:
ext = f.suffix
by_type[ext] = by_type.get(ext, 0) + 1
for ext, count in sorted(by_type.items()):
stats += f"\n- {ext}: {count} files"
return stats
def analyze_document(file_name: str, analysis_type: str) -> str:
"""Analyze a specific document."""
if not file_name:
return "β οΈ Please select a file to analyze"
file_path = DOCS_DIR / file_name
if not file_path.exists():
return f"β File not found: {file_name}"
try:
if file_path.suffix == '.pdf':
content = extract_pdf_content(file_path)
else:
content = file_path.read_text(encoding='utf-8', errors='ignore')
if analysis_type == "Summary":
summary = doc_intelligence.generate_smart_summary(content, "medium")
return f"π **Summary of {file_name}**\n\n{summary}"
elif analysis_type == "Key Concepts":
concepts = doc_intelligence.extract_key_concepts(content)
result = f"π **Key Concepts in {file_name}**\n\n"
for i, concept in enumerate(concepts[:10], 1):
result += f"{i}. **{concept['concept']}** ({concept['type']}) - appears {concept['frequency']} times\n"
return result
elif analysis_type == "Readability":
analysis = doc_intelligence.analyze_readability(content)
return f"""
π **Readability Analysis of {file_name}**
- **Flesch Reading Ease**: {analysis['flesch_score']} ({analysis['complexity']})
- **Grade Level**: {analysis['grade_level']}
- **Avg Sentence Length**: {analysis['avg_sentence_length']} words
- **Total Words**: {analysis['total_words']}
- **Total Sentences**: {analysis['total_sentences']}
"""
elif analysis_type == "Q&A Extraction":
qa_pairs = doc_intelligence.extract_questions_and_answers(content)
if not qa_pairs:
return f"β No Q&A pairs found in {file_name}"
result = f"β **Questions & Answers from {file_name}**\n\n"
for i, qa in enumerate(qa_pairs[:5], 1):
result += f"**Q{i}:** {qa['question']}\n**A:** {qa['answer']}\n\n"
return result
except Exception as e:
return f"β Error analyzing file: {str(e)}"
# Custom CSS for sleek indigo/dark mode design with messenger-style chat
custom_css = """
/* Indigo dark mode color scheme */
:root {
--bg-primary: #0a0e27;
--bg-secondary: #0f1629;
--bg-tertiary: #1a1f3a;
--accent-primary: #6366f1;
--accent-secondary: #818cf8;
--accent-tertiary: #4f46e5;
--accent-glow: rgba(99, 102, 241, 0.4);
--text-primary: #e0e7ff;
--text-secondary: #a5b4fc;
--border-color: #312e81;
--message-user: linear-gradient(135deg, #6366f1 0%, #8b5cf6 100%);
--message-bot: #1e1b4b;
--hover-glow: rgba(129, 140, 248, 0.2);
}
/* Main container - full dark mode */
.gradio-container {
font-family: 'Inter', -apple-system, BlinkMacSystemFont, 'Segoe UI', sans-serif !important;
background: var(--bg-primary) !important;
}
body, .gradio-container, .main, .contain {
background: var(--bg-primary) !important;
}
/* Header styling - indigo gradient */
.header-container {
background: linear-gradient(135deg, #4f46e5 0%, #6366f1 50%, #818cf8 100%);
padding: 3rem 2rem;
border-radius: 20px;
margin-bottom: 2rem;
box-shadow: 0 25px 70px rgba(99, 102, 241, 0.5), 0 0 100px rgba(99, 102, 241, 0.2);
border: 1px solid rgba(99, 102, 241, 0.3);
position: relative;
overflow: hidden;
}
.header-container::before {
content: '';
position: absolute;
top: 0;
left: 0;
right: 0;
bottom: 0;
background: radial-gradient(circle at 30% 50%, rgba(129, 140, 248, 0.3) 0%, transparent 50%);
pointer-events: none;
}
.header-title {
color: white;
font-size: 3rem;
font-weight: 900;
margin: 0;
text-align: center;
text-shadow: 0 0 30px rgba(129, 140, 248, 0.8), 0 4px 20px rgba(0, 0, 0, 0.4);
letter-spacing: -0.02em;
position: relative;
z-index: 1;
background: linear-gradient(to bottom, #ffffff 0%, #e0e7ff 100%);
-webkit-background-clip: text;
-webkit-text-fill-color: transparent;
background-clip: text;
}
.header-subtitle {
color: rgba(224, 231, 255, 0.95);
font-size: 1.2rem;
text-align: center;
margin-top: 1rem;
font-weight: 500;
letter-spacing: 0.02em;
position: relative;
z-index: 1;
text-shadow: 0 2px 10px rgba(0, 0, 0, 0.3);
}
/* Messenger-style chat window with indigo accents */
.chatbot, [class*="chatbot"] {
background: linear-gradient(135deg, var(--bg-secondary) 0%, var(--bg-tertiary) 100%) !important;
border: 2px solid var(--border-color) !important;
border-radius: 20px !important;
box-shadow: 0 12px 48px rgba(0, 0, 0, 0.5), 0 0 60px rgba(99, 102, 241, 0.15), inset 0 1px 0 rgba(99, 102, 241, 0.1) !important;
position: relative;
overflow: hidden;
}
.chatbot::before, [class*="chatbot"]::before {
content: '';
position: absolute;
top: 0;
left: 0;
right: 0;
height: 3px;
background: linear-gradient(90deg, transparent, var(--accent-primary), transparent);
animation: shimmer 3s infinite;
}
@keyframes shimmer {
0%, 100% { transform: translateX(-100%); }
50% { transform: translateX(100%); }
}
/* Chat messages - indigo messenger style with glow */
.message-wrap {
padding: 0.5rem 1rem !important;
}
.user.message, .message.user {
background: linear-gradient(135deg, #6366f1 0%, #8b5cf6 100%) !important;
color: white !important;
border-radius: 20px 20px 4px 20px !important;
padding: 1rem 1.5rem !important;
margin: 0.75rem 0 !important;
max-width: 75% !important;
margin-left: auto !important;
box-shadow: 0 6px 20px rgba(99, 102, 241, 0.4), 0 0 20px rgba(99, 102, 241, 0.2) !important;
font-size: 0.98rem !important;
line-height: 1.6 !important;
border: 1px solid rgba(99, 102, 241, 0.4) !important;
position: relative;
}
.bot.message, .message.bot {
background: var(--message-bot) !important;
color: var(--text-primary) !important;
border-radius: 20px 20px 20px 4px !important;
padding: 1rem 1.5rem !important;
margin: 0.75rem 0 !important;
max-width: 85% !important;
border: 1px solid var(--border-color) !important;
box-shadow: 0 4px 16px rgba(0, 0, 0, 0.3), inset 0 1px 0 rgba(99, 102, 241, 0.1) !important;
font-size: 0.98rem !important;
line-height: 1.7 !important;
backdrop-filter: blur(10px);
}
/* Enhance all message containers */
.message {
animation: messageSlide 0.3s ease-out;
}
@keyframes messageSlide {
from {
opacity: 0;
transform: translateY(10px);
}
to {
opacity: 1;
transform: translateY(0);
}
}
/* Button styling - indigo gradient with glow */
button, .primary-button {
background: linear-gradient(135deg, #6366f1 0%, #4f46e5 100%) !important;
border: none !important;
border-radius: 14px !important;
font-weight: 700 !important;
transition: all 0.3s cubic-bezier(0.4, 0, 0.2, 1) !important;
box-shadow: 0 4px 20px var(--accent-glow), 0 0 20px rgba(99, 102, 241, 0.3) !important;
color: white !important;
padding: 0.875rem 1.75rem !important;
text-transform: uppercase;
letter-spacing: 0.05em;
font-size: 0.85rem !important;
position: relative;
overflow: hidden;
}
button::before, .primary-button::before {
content: '';
position: absolute;
top: 0;
left: -100%;
width: 100%;
height: 100%;
background: linear-gradient(90deg, transparent, rgba(255, 255, 255, 0.2), transparent);
transition: left 0.5s;
}
button:hover::before, .primary-button:hover::before {
left: 100%;
}
button:hover, .primary-button:hover {
transform: translateY(-3px) scale(1.02) !important;
box-shadow: 0 12px 32px rgba(99, 102, 241, 0.6), 0 0 40px rgba(99, 102, 241, 0.4) !important;
background: linear-gradient(135deg, #818cf8 0%, #6366f1 100%) !important;
}
/* Tabs - indigo dark mode with glow */
.tabs {
background: var(--bg-secondary) !important;
border-radius: 20px !important;
border: 1px solid var(--border-color) !important;
box-shadow: 0 8px 32px rgba(0, 0, 0, 0.4) !important;
}
.tab-nav {
background: linear-gradient(180deg, var(--bg-tertiary) 0%, var(--bg-secondary) 100%) !important;
border-radius: 20px 20px 0 0 !important;
border-bottom: 2px solid var(--border-color) !important;
padding: 0.75rem !important;
box-shadow: inset 0 -1px 0 rgba(99, 102, 241, 0.1) !important;
}
.tab-nav button {
font-weight: 700 !important;
border-radius: 12px !important;
color: var(--text-secondary) !important;
border: 1px solid transparent !important;
transition: all 0.3s cubic-bezier(0.4, 0, 0.2, 1) !important;
padding: 0.875rem 1.75rem !important;
margin: 0 0.25rem !important;
text-transform: uppercase;
letter-spacing: 0.05em;
font-size: 0.85rem !important;
position: relative;
}
.tab-nav button:hover {
background: rgba(99, 102, 241, 0.15) !important;
color: var(--accent-secondary) !important;
border-color: rgba(99, 102, 241, 0.3) !important;
transform: translateY(-2px);
box-shadow: 0 4px 12px var(--hover-glow) !important;
}
.tab-nav button.selected {
background: linear-gradient(135deg, #6366f1 0%, #4f46e5 100%) !important;
color: white !important;
box-shadow: 0 6px 20px var(--accent-glow), 0 0 30px rgba(99, 102, 241, 0.3) !important;
border-color: rgba(99, 102, 241, 0.5) !important;
transform: translateY(-2px);
}
/* Input fields - indigo dark mode with glow effect */
textarea, input, .input-box {
background: var(--bg-tertiary) !important;
border: 2px solid var(--border-color) !important;
border-radius: 16px !important;
color: var(--text-primary) !important;
transition: all 0.3s cubic-bezier(0.4, 0, 0.2, 1) !important;
padding: 1rem 1.25rem !important;
box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.3) !important;
}
textarea:focus, input:focus, .input-box:focus {
border-color: var(--accent-primary) !important;
box-shadow: 0 0 0 4px var(--accent-glow), 0 0 30px rgba(99, 102, 241, 0.3), inset 0 2px 8px rgba(0, 0, 0, 0.2) !important;
background: var(--bg-secondary) !important;
outline: none !important;
transform: translateY(-1px);
}
textarea::placeholder, input::placeholder {
color: var(--text-secondary) !important;
opacity: 0.8 !important;
}
/* Dropdown styling */
.dropdown, select {
background: var(--bg-tertiary) !important;
border: 2px solid var(--border-color) !important;
border-radius: 12px !important;
color: var(--text-primary) !important;
padding: 0.75rem 1rem !important;
}
/* Stats and info cards - indigo dark mode with depth */
.stats-box, .info-card {
background: linear-gradient(135deg, var(--bg-secondary) 0%, var(--bg-tertiary) 100%) !important;
padding: 2rem !important;
border-radius: 20px !important;
border: 1px solid var(--border-color) !important;
box-shadow: 0 8px 32px rgba(0, 0, 0, 0.4), inset 0 1px 0 rgba(99, 102, 241, 0.1) !important;
color: var(--text-primary) !important;
transition: all 0.4s cubic-bezier(0.4, 0, 0.2, 1) !important;
position: relative;
overflow: hidden;
}
.stats-box::before, .info-card::before {
content: '';
position: absolute;
top: 0;
left: 0;
right: 0;
bottom: 0;
background: radial-gradient(circle at 80% 20%, rgba(99, 102, 241, 0.15) 0%, transparent 50%);
opacity: 0;
transition: opacity 0.4s ease;
pointer-events: none;
}
.info-card:hover, .stats-box:hover {
transform: translateY(-6px) scale(1.01) !important;
box-shadow: 0 16px 48px rgba(99, 102, 241, 0.3), 0 0 60px rgba(99, 102, 241, 0.2) !important;
border-color: var(--accent-primary) !important;
}
.info-card:hover::before, .stats-box:hover::before {
opacity: 1;
}
/* Markdown content styling - indigo dark mode */
.markdown-text, .prose {
color: var(--text-primary) !important;
line-height: 1.8 !important;
}
.markdown-text h1, .markdown-text h2, .markdown-text h3,
.prose h1, .prose h2, .prose h3 {
color: var(--accent-secondary) !important;
font-weight: 800 !important;
text-shadow: 0 0 20px rgba(99, 102, 241, 0.3);
margin-top: 1.5em !important;
margin-bottom: 0.75em !important;
}
.markdown-text strong, .prose strong {
color: var(--accent-secondary) !important;
font-weight: 700 !important;
}
.markdown-text code, .prose code {
background: var(--bg-tertiary) !important;
color: var(--accent-secondary) !important;
padding: 0.3rem 0.6rem !important;
border-radius: 8px !important;
font-size: 0.9em !important;
border: 1px solid rgba(99, 102, 241, 0.3) !important;
box-shadow: 0 0 10px rgba(99, 102, 241, 0.2) !important;
font-family: 'Fira Code', 'Courier New', monospace !important;
}
.markdown-text pre, .prose pre {
background: linear-gradient(135deg, #0a0e27 0%, #1a1b26 100%) !important;
color: #a9b1d6 !important;
padding: 1.5rem !important;
border-radius: 16px !important;
overflow-x: auto !important;
border: 1px solid var(--border-color) !important;
box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.4), 0 4px 16px rgba(0, 0, 0, 0.3) !important;
}
.markdown-text a, .prose a {
color: var(--accent-secondary) !important;
text-decoration: none !important;
border-bottom: 2px solid var(--accent-primary) !important;
transition: all 0.3s ease !important;
}
.markdown-text a:hover, .prose a:hover {
color: var(--accent-primary) !important;
text-shadow: 0 0 10px rgba(99, 102, 241, 0.5) !important;
}
/* Labels and text */
label, .label {
color: var(--text-primary) !important;
font-weight: 600 !important;
font-size: 0.95rem !important;
margin-bottom: 0.5rem !important;
}
.secondary-text {
color: var(--text-secondary) !important;
}
/* Remove white backgrounds globally */
.block, .form, .panel {
background: var(--bg-secondary) !important;
border: 1px solid var(--border-color) !important;
border-radius: 12px !important;
}
/* Scrollbar styling - indigo themed */
::-webkit-scrollbar {
width: 12px;
height: 12px;
}
::-webkit-scrollbar-track {
background: var(--bg-secondary);
border-radius: 10px;
border: 1px solid var(--border-color);
}
::-webkit-scrollbar-thumb {
background: linear-gradient(180deg, var(--accent-primary) 0%, var(--accent-tertiary) 100%);
border-radius: 10px;
border: 2px solid var(--bg-secondary);
box-shadow: 0 0 10px rgba(99, 102, 241, 0.3);
}
::-webkit-scrollbar-thumb:hover {
background: linear-gradient(180deg, var(--accent-secondary) 0%, var(--accent-primary) 100%);
box-shadow: 0 0 20px rgba(99, 102, 241, 0.5);
}
/* Loading animation */
.pending {
background: linear-gradient(90deg, var(--bg-tertiary) 25%, var(--border-color) 50%, var(--bg-tertiary) 75%);
background-size: 200% 100%;
animation: loading 1.5s ease-in-out infinite;
}
@keyframes loading {
0% { background-position: 200% 0; }
100% { background-position: -200% 0; }
}
/* Examples section */
.examples {
background: var(--bg-tertiary) !important;
border-radius: 12px !important;
border: 1px solid var(--border-color) !important;
padding: 1rem !important;
}
.example-item {
background: var(--bg-secondary) !important;
border: 1px solid var(--border-color) !important;
border-radius: 8px !important;
color: var(--text-primary) !important;
transition: all 0.2s ease !important;
}
.example-item:hover {
background: var(--bg-tertiary) !important;
border-color: var(--accent-primary) !important;
transform: translateX(4px) !important;
}
/* Radio buttons */
.radio-group {
background: var(--bg-tertiary) !important;
border-radius: 12px !important;
padding: 0.5rem !important;
}
"""
# Create the Gradio interface with dark theme - backward compatible
try:
# Try Gradio 4.x+ with css parameter
demo = gr.Blocks(
css=custom_css,
title="Docs Navigator MCP - AI Documentation Assistant"
)
except TypeError:
# Fallback for older Gradio versions
demo = gr.Blocks(title="Docs Navigator MCP - AI Documentation Assistant")
# CSS will be injected via HTML if needed
with demo:
# Inject CSS and Header with indigo gradient
gr.HTML(f"""
<style>
{custom_css}
</style>
<div class="header-container">
<h1 class="header-title">π Docs Navigator MCP</h1>
<p class="header-subtitle">β¨ AI-Powered Documentation Intelligence with Claude β¨</p>
</div>
""")
with gr.Tabs() as tabs:
# Chat Tab - Messenger Style
with gr.Tab("π¬ Chat", id=0):
gr.HTML("""
<div style='padding: 1rem 0 0.5rem 0; color: var(--text-secondary); font-size: 0.95rem;'>
<strong style='color: var(--accent-secondary);'>π¬ AI Chat Assistant</strong><br>
Ask anything about your documentation - I have full context of all your files.
</div>
""")
try:
chatbot = gr.Chatbot(
height=550,
show_label=False,
type="messages"
)
except TypeError:
# Fallback for older Gradio versions
chatbot = gr.Chatbot(
height=550,
show_label=False
)
with gr.Row():
msg = gr.Textbox(
placeholder="π Message the docs assistant...",
show_label=False,
scale=5,
container=False,
lines=1,
max_lines=3
)
submit_btn = gr.Button("Send", scale=1, variant="primary", elem_classes="primary-button", size="lg")
with gr.Row():
clear_btn = gr.Button("ποΈ Clear", size="sm", variant="secondary")
gr.HTML("<div style='flex-grow: 1;'></div>")
with gr.Accordion("π‘ Example Questions", open=False):
gr.Examples(
examples=[
"What is this documentation about?",
"How do I get started with setup?",
"What are the main features?",
"Show me troubleshooting steps",
"What configuration options are available?",
"Explain the architecture"
],
inputs=msg,
label=None
)
# Document Analysis Tab
with gr.Tab("π Analysis", id=1):
gr.HTML("""
<div style='padding: 1rem 0 0.5rem 0; color: var(--text-secondary); font-size: 0.95rem;'>
<strong style='color: var(--accent-secondary);'>π Document Intelligence</strong><br>
Deep analysis of individual documentation files with AI-powered insights.
</div>
""")
with gr.Row():
with gr.Column(scale=1):
file_dropdown = gr.Dropdown(
choices=get_available_files(),
label="π Select Document",
interactive=True,
container=True
)
analysis_type = gr.Radio(
choices=["Summary", "Key Concepts", "Readability", "Q&A Extraction"],
value="Summary",
label="π― Analysis Type",
container=True
)
analyze_btn = gr.Button("π Analyze Document", variant="primary", elem_classes="primary-button", size="lg")
refresh_btn = gr.Button("π Refresh Files", size="sm", variant="secondary")
with gr.Column(scale=2):
analysis_output = gr.Markdown(
value="<div style='text-align: center; padding: 3rem; color: #8b949e;'><div style='font-size: 2.5rem; margin-bottom: 1rem;'>π</div><div style='font-size: 1.1rem;'>Select a document and analysis type to begin</div></div>",
elem_classes="info-card"
)
# Statistics Tab
with gr.Tab("π Stats", id=2):
gr.HTML("""
<div style='padding: 1rem 0 0.5rem 0; color: var(--text-secondary); font-size: 0.95rem;'>
<strong style='color: var(--accent-secondary);'>π Documentation Overview</strong><br>
Real-time statistics and insights about your documentation collection.
</div>
""")
stats_display = gr.Markdown(
value=get_document_stats(),
elem_classes="stats-box"
)
refresh_stats_btn = gr.Button("π Refresh Statistics", variant="secondary", size="sm")
# Settings Tab
with gr.Tab("βοΈ Settings", id=3):
gr.HTML("""
<div style='padding: 1rem 0 0.5rem 0; color: var(--text-secondary); font-size: 0.95rem;'>
<strong style='color: var(--accent-secondary);'>βοΈ Configuration</strong><br>
Customize the AI assistant behavior and view system information.
</div>
""")
with gr.Group():
custom_system_prompt = gr.Textbox(
label="π¨ Custom System Prompt (Optional)",
placeholder="Enter a custom system prompt to modify the AI's personality and behavior...",
lines=6,
info="π‘ Leave empty to use the default documentation assistant prompt",
container=True
)
gr.HTML("""
<div style='margin-top: 2rem; padding: 2rem; background: linear-gradient(135deg, rgba(139, 92, 246, 0.1) 0%, rgba(99, 102, 241, 0.1) 100%); border-radius: 16px; border: 1px solid var(--border-color);'>
<h3 style='color: var(--accent-secondary); margin: 0 0 1rem 0; font-size: 1.5rem;'>π About Docs Navigator MCP</h3>
<p style='color: var(--text-primary); line-height: 1.8; margin-bottom: 1.5rem;'>
An intelligent documentation assistant combining <strong>Claude AI</strong> with
<strong>Model Context Protocol (MCP)</strong> for powerful document analysis and Q&A.
</p>
<div style='display: grid; grid-template-columns: repeat(auto-fit, minmax(200px, 1fr)); gap: 1rem; margin-top: 1.5rem;'>
<div style='padding: 1rem; background: rgba(139, 92, 246, 0.1); border-radius: 12px; border: 1px solid rgba(139, 92, 246, 0.2);'>
<div style='font-size: 1.5rem; margin-bottom: 0.5rem;'>π€</div>
<div style='color: var(--text-primary); font-weight: 600;'>Claude 3 Haiku</div>
<div style='color: var(--text-secondary); font-size: 0.85rem;'>Latest AI Model</div>
</div>
<div style='padding: 1rem; background: rgba(139, 92, 246, 0.1); border-radius: 12px; border: 1px solid rgba(139, 92, 246, 0.2);'>
<div style='font-size: 1.5rem; margin-bottom: 0.5rem;'>π</div>
<div style='color: var(--text-primary); font-weight: 600;'>Smart Analysis</div>
<div style='color: var(--text-secondary); font-size: 0.85rem;'>Document Intelligence</div>
</div>
<div style='padding: 1rem; background: rgba(139, 92, 246, 0.1); border-radius: 12px; border: 1px solid rgba(139, 92, 246, 0.2);'>
<div style='font-size: 1.5rem; margin-bottom: 0.5rem;'>π</div>
<div style='color: var(--text-primary); font-weight: 600;'>Multi-Format</div>
<div style='color: var(--text-secondary); font-size: 0.85rem;'>MD, TXT, RST, PDF</div>
</div>
<div style='padding: 1rem; background: rgba(139, 92, 246, 0.1); border-radius: 12px; border: 1px solid rgba(139, 92, 246, 0.2);'>
<div style='font-size: 1.5rem; margin-bottom: 0.5rem;'>β‘</div>
<div style='color: var(--text-primary); font-weight: 600;'>Fast & Responsive</div>
<div style='color: var(--text-secondary); font-size: 0.85rem;'>Streaming Responses</div>
</div>
</div>
</div>
""")
gr.HTML("<div style='margin: 2rem 0 1rem 0; padding-top: 1.5rem; border-top: 1px solid var(--border-color);'></div>")
api_status = gr.Markdown(
value=f"""
### π API Status
{"β
**Anthropic API Key Configured** - Ready to use!" if ANTHROPIC_API_KEY else "β οΈ **API Key Missing** - Set `ANTHROPIC_API_KEY` in your `.env` file"}
""",
elem_classes="info-card"
)
# Event handlers
def respond(message, chat_history, system_prompt):
if not message.strip():
return "", chat_history
response = chat_with_docs(message, chat_history, system_prompt if system_prompt.strip() else None)
# Detect format and append accordingly
if chat_history and isinstance(chat_history[0], dict):
# Messages format
chat_history.append({"role": "user", "content": message})
chat_history.append({"role": "assistant", "content": response})
else:
# Tuple format
chat_history.append((message, response))
return "", chat_history
msg.submit(respond, [msg, chatbot, custom_system_prompt], [msg, chatbot])
submit_btn.click(respond, [msg, chatbot, custom_system_prompt], [msg, chatbot])
clear_btn.click(lambda: [], None, chatbot)
analyze_btn.click(
analyze_document,
[file_dropdown, analysis_type],
analysis_output
)
refresh_btn.click(
lambda: gr.update(choices=get_available_files()),
None,
file_dropdown
)
refresh_stats_btn.click(
get_document_stats,
None,
stats_display
)
if __name__ == "__main__":
print("π Starting Docs Navigator MCP...")
print("π AI-Powered Documentation Assistant")
print("π‘ Ask questions about your documentation!")
print("-" * 50)
# Detect if running on Hugging Face Spaces
is_spaces = os.getenv("SPACE_ID") is not None
demo.launch(
server_name="0.0.0.0" if is_spaces else "127.0.0.1",
server_port=7860,
show_error=True,
share=False
) |