doc-mcp / app.py
mdabidhussain's picture
added tools for github file listing and retrieval
3fcc667
raw
history blame
65.6 kB
import asyncio
import os
import time
import traceback
from typing import Dict, List
import gradio as gr
from dotenv import load_dotenv
from llama_index.core import Settings
from llama_index.core.text_splitter import SentenceSplitter
from rag.config import (delete_repository_data, embed_model,
get_available_repos, get_repo_details,
get_repository_stats, llm)
from rag.github_file_loader import \
fetch_markdown_files as fetch_files_with_loader
from rag.github_file_loader import fetch_repository_files, load_github_files
from rag.ingest import ingest_documents_async
from rag.query import QueryRetriever
load_dotenv()
Settings.llm = llm
Settings.embed_model = embed_model
Settings.node_parser = SentenceSplitter(chunk_size=3072)
def get_available_repositories():
return get_available_repos()
def start_file_loading(
repo_url: str, selected_files: List[str], current_progress: Dict
):
"""Step 1: Load files from GitHub"""
print("\nπŸ”„ STARTING FILE LOADING STEP")
print(f"πŸ“ Repository: {repo_url}")
print(f"πŸ“‹ Selected files: {selected_files}")
if not selected_files:
return {
"status": "error",
"message": "❌ No files selected for loading",
"progress": 0,
"details": "",
"step": "file_loading",
}
total_files = len(selected_files)
start_time = time.time()
# Parse repo name from URL
if "github.com" in repo_url:
repo_name = (
repo_url.replace("https://github.com/", "")
.replace("http://github.com/", "")
.strip("/")
)
if "/" not in repo_name:
return {
"status": "error",
"message": "❌ Invalid repository URL format",
"progress": 0,
"details": "",
"step": "file_loading",
}
else:
repo_name = repo_url.strip()
try:
batch_size = 25
all_documents = []
all_failed = []
current_progress.update(
{
"status": "loading",
"message": f"πŸš€ Loading files from {repo_name}",
"progress": 0,
"total_files": total_files,
"processed_files": 0,
"phase": "File Loading",
"details": f"Processing {total_files} files in batches...",
"step": "file_loading",
}
)
for i in range(0, len(selected_files), batch_size):
batch = selected_files[i : i + batch_size]
print(f"\nπŸ“¦ PROCESSING BATCH {i // batch_size + 1}")
print(f" Files: {batch}")
# Update progress for current batch
progress_percentage = (i / total_files) * 100
current_progress.update(
{
"progress": progress_percentage,
"processed_files": i,
"current_batch": i // batch_size + 1,
"details": f"Loading batch {i // batch_size + 1}: {', '.join([f.split('/')[-1] for f in batch])}",
}
)
try:
documents, failed = load_github_files(
repo_name=repo_name,
file_paths=batch,
branch="main",
concurrent_requests=10,
github_token=os.getenv("GITHUB_API_KEY"),
)
print("βœ… Load results:")
print(f" - Documents: {len(documents)}")
print(f" - Failed: {len(failed)}")
if documents:
for j, doc in enumerate(documents):
print(f" πŸ“„ Doc {j + 1}: {doc.doc_id}")
print(f" Size: {len(doc.text)} chars")
# Ensure repo metadata is set
if "repo" not in doc.metadata:
doc.metadata["repo"] = repo_name
print(f" βœ… Added repo metadata: {repo_name}")
all_documents.extend(documents)
all_failed.extend(failed)
except Exception as batch_error:
print(f"❌ Batch processing error: {batch_error}")
all_failed.extend(batch)
loading_time = time.time() - start_time
# Store loaded documents in progress state for next step
current_progress.update(
{
"status": "loaded",
"message": f"βœ… File Loading Complete! Loaded {len(all_documents)} documents",
"progress": 100,
"phase": "Files Loaded",
"details": f"Successfully loaded {len(all_documents)} documents in {loading_time:.1f}s",
"step": "file_loading_complete",
"loaded_documents": all_documents, # Store documents for next step
"failed_files": all_failed,
"loading_time": loading_time,
"repo_name": repo_name,
}
)
return current_progress
except Exception as e:
total_time = time.time() - start_time
error_msg = f"❌ File loading error after {total_time:.1f}s: {str(e)}"
print(error_msg)
current_progress.update(
{
"status": "error",
"message": error_msg,
"progress": 0,
"phase": "Failed",
"details": str(e),
"error": str(e),
"step": "file_loading",
}
)
return current_progress
def start_vector_ingestion(current_progress: Dict):
"""Step 2: Ingest loaded documents into vector store"""
print("\nπŸ”„ STARTING VECTOR INGESTION STEP")
# Check if we have loaded documents from previous step
if current_progress.get("step") != "file_loading_complete":
return {
"status": "error",
"message": "❌ No loaded documents found. Please load files first.",
"progress": 0,
"details": "",
"step": "vector_ingestion",
}
all_documents = current_progress.get("loaded_documents", [])
repo_name = current_progress.get("repo_name", "")
if not all_documents:
return {
"status": "error",
"message": "❌ No documents available for vector ingestion",
"progress": 0,
"details": "",
"step": "vector_ingestion",
}
vector_start_time = time.time()
# Update state for vector store phase
current_progress.update(
{
"status": "vectorizing",
"message": "πŸ”„ Generating embeddings and storing in vector database",
"progress": 0,
"phase": "Vector Store Ingestion",
"details": f"Processing {len(all_documents)} documents for embedding...",
"step": "vector_ingestion",
}
)
try:
print("πŸ”„ STARTING VECTOR STORE INGESTION")
print(f" Repository: {repo_name}")
print(f" Documents to process: {len(all_documents)}")
# Call the async ingestion function with repo name
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
try:
loop.run_until_complete(ingest_documents_async(all_documents, repo_name))
finally:
loop.close()
vector_time = time.time() - vector_start_time
loading_time = current_progress.get("loading_time", 0)
total_time = loading_time + vector_time
print(f"βœ… Vector ingestion completed in {vector_time:.2f} seconds")
failed_files_data = current_progress.get("failed_files", [])
if isinstance(failed_files_data, list):
failed_files_count = len(failed_files_data)
else:
failed_files_count = failed_files_data if isinstance(failed_files_data, int) else 0
# Update final success state with repository update flag
current_progress.update(
{
"status": "complete",
"message": "βœ… Complete Ingestion Pipeline Finished!",
"progress": 100,
"phase": "Complete",
"details": f"Successfully processed {len(all_documents)} documents for {repo_name}",
"step": "complete",
"total_time": total_time,
"documents_processed": len(all_documents),
"failed_files_count": failed_files_count, # Use count instead of trying len()
"failed_files": failed_files_data, # Keep original data
"vector_time": vector_time,
"loading_time": loading_time,
"repo_name": repo_name,
"repository_updated": True, # Flag to trigger repo list refresh
}
)
return current_progress
except Exception as ingest_error:
vector_time = time.time() - vector_start_time
print(f"❌ Vector ingestion failed after {vector_time:.2f} seconds")
print(f"❌ Error: {ingest_error}")
# Get failed files data safely
failed_files_data = current_progress.get("failed_files", [])
if isinstance(failed_files_data, list):
failed_files_count = len(failed_files_data)
else:
failed_files_count = failed_files_data if isinstance(failed_files_data, int) else 0
current_progress.update(
{
"status": "error",
"message": "❌ Vector Store Ingestion Failed",
"progress": 0,
"phase": "Failed",
"details": f"Error: {str(ingest_error)}",
"error": str(ingest_error),
"step": "vector_ingestion",
"failed_files_count": failed_files_count,
"failed_files": failed_files_data,
}
)
return current_progress
def start_file_loading_generator(
repo_url: str, selected_files: List[str], current_progress: Dict
):
"""Step 1: Load files from GitHub with yield-based real-time updates"""
print("\nπŸ”„ STARTING FILE LOADING STEP")
print(f"πŸ“ Repository: {repo_url}")
print(f"πŸ“‹ Selected files: {len(selected_files)} files")
if not selected_files:
error_progress = {
"status": "error",
"message": "❌ No files selected for loading",
"progress": 0,
"details": "Please select at least one file to proceed.",
"step": "file_loading",
}
yield error_progress
return error_progress
total_files = len(selected_files)
start_time = time.time()
# Parse repo name from URL
if "github.com" in repo_url:
repo_name = (
repo_url.replace("https://github.com/", "")
.replace("http://github.com/", "")
.strip("/")
)
if "/" not in repo_name:
error_progress = {
"status": "error",
"message": "❌ Invalid repository URL format",
"progress": 0,
"details": "Expected format: owner/repo or https://github.com/owner/repo",
"step": "file_loading",
}
yield error_progress
return error_progress
else:
repo_name = repo_url.strip()
try:
batch_size = 10
all_documents = []
all_failed = []
# Initial progress update
initial_progress = {
"status": "loading",
"message": f"πŸš€ Starting file loading from {repo_name}",
"progress": 0,
"total_files": total_files,
"processed_files": 0,
"successful_files": 0,
"failed_files": 0,
"phase": "File Loading",
"details": f"Preparing to load {total_files} files in batches of {batch_size}...",
"step": "file_loading",
"current_batch": 0,
"total_batches": (len(selected_files) + batch_size - 1) // batch_size,
"repo_name": repo_name,
}
yield initial_progress
time.sleep(0.5)
for i in range(0, len(selected_files), batch_size):
batch = selected_files[i : i + batch_size]
current_batch_num = i // batch_size + 1
total_batches = (len(selected_files) + batch_size - 1) // batch_size
# Update progress at batch start
batch_start_progress = {
"status": "loading",
"message": f"πŸ”„ Loading batch {current_batch_num}/{total_batches}",
"progress": (i / total_files) * 90,
"processed_files": i,
"successful_files": len(all_documents),
"failed_files": len(all_failed),
"current_batch": current_batch_num,
"total_batches": total_batches,
"phase": "File Loading",
"details": f"Processing batch {current_batch_num}: {', '.join([f.split('/')[-1] for f in batch[:3]])}{'...' if len(batch) > 3 else ''}",
"step": "file_loading",
"repo_name": repo_name,
}
yield batch_start_progress
try:
print(f"\nπŸ“¦ PROCESSING BATCH {current_batch_num}/{total_batches}")
print(f" Files: {[f.split('/')[-1] for f in batch]}")
documents, failed = load_github_files(
repo_name=repo_name,
file_paths=batch,
branch="main",
concurrent_requests=10,
github_token=os.getenv("GITHUB_API_KEY"),
)
print("βœ… Load results:")
print(f" - Documents: {len(documents)}")
print(f" - Failed: {len(failed)}")
# Process documents
for j, doc in enumerate(documents):
print(f" πŸ“„ Doc {j + 1}: {doc.doc_id}")
print(f" Size: {len(doc.text)} chars")
if "repo" not in doc.metadata:
doc.metadata["repo"] = repo_name
print(f" βœ… Added repo metadata: {repo_name}")
all_documents.extend(documents)
all_failed.extend(failed)
# Update progress after batch completion
batch_complete_progress = {
"status": "loading",
"message": f"βœ… Completed batch {current_batch_num}/{total_batches}",
"progress": ((i + len(batch)) / total_files) * 90,
"processed_files": i + len(batch),
"successful_files": len(all_documents),
"failed_files": len(all_failed),
"current_batch": current_batch_num,
"total_batches": total_batches,
"phase": "File Loading",
"details": f"βœ… Batch {current_batch_num} complete: {len(documents)} loaded, {len(failed)} failed. Total progress: {len(all_documents)} documents loaded.",
"step": "file_loading",
"repo_name": repo_name,
}
yield batch_complete_progress
time.sleep(0.3)
except Exception as batch_error:
print(f"❌ Batch processing error: {batch_error}")
all_failed.extend(batch)
error_progress = {
"status": "loading",
"message": f"⚠️ Error in batch {current_batch_num}",
"progress": ((i + len(batch)) / total_files) * 90,
"processed_files": i + len(batch),
"successful_files": len(all_documents),
"failed_files": len(all_failed),
"current_batch": current_batch_num,
"phase": "File Loading",
"details": f"❌ Batch {current_batch_num} error: {str(batch_error)[:100]}... Continuing with next batch.",
"step": "file_loading",
"repo_name": repo_name,
}
yield error_progress
loading_time = time.time() - start_time
# Final completion update
completion_progress = {
"status": "loaded",
"message": f"βœ… File Loading Complete! Loaded {len(all_documents)} documents",
"progress": 100,
"phase": "Files Loaded Successfully",
"details": f"🎯 Final Results:\nβœ… Successfully loaded: {len(all_documents)} documents\n❌ Failed files: {len(all_failed)}\n⏱️ Total time: {loading_time:.1f}s\nπŸ“Š Success rate: {(len(all_documents)/(len(all_documents)+len(all_failed))*100):.1f}%",
"step": "file_loading_complete",
"loaded_documents": all_documents,
"failed_files": all_failed,
"loading_time": loading_time,
"repo_name": repo_name,
"total_files": total_files,
"processed_files": total_files,
"successful_files": len(all_documents),
}
yield completion_progress
return completion_progress
except Exception as e:
total_time = time.time() - start_time
error_msg = f"❌ File loading error after {total_time:.1f}s: {str(e)}"
print(error_msg)
error_progress = {
"status": "error",
"message": error_msg,
"progress": 0,
"phase": "Loading Failed",
"details": f"Critical error during file loading:\n{str(e)}",
"error": str(e),
"step": "file_loading",
}
yield error_progress
return error_progress
# Progress display component
def format_progress_display(progress_state: Dict) -> str:
"""Format progress state into readable display with enhanced details"""
if not progress_state:
return "πŸš€ Ready to start ingestion...\n\nπŸ“‹ **Two-Step Process:**\n1️⃣ Load files from GitHub repository\n2️⃣ Generate embeddings and store in vector database"
status = progress_state.get("status", "unknown")
message = progress_state.get("message", "")
progress = progress_state.get("progress", 0)
phase = progress_state.get("phase", "")
details = progress_state.get("details", "")
# Enhanced progress bar
filled = int(progress / 2.5) # 40 chars total
progress_bar = "β–ˆ" * filled + "β–‘" * (40 - filled)
# Status emoji mapping
status_emoji = {
"loading": "⏳",
"loaded": "βœ…",
"vectorizing": "🧠",
"complete": "πŸŽ‰",
"error": "❌"
}
emoji = status_emoji.get(status, "πŸ”„")
output = f"{emoji} **{message}**\n\n"
# Phase and progress section
output += f"πŸ“Š **Current Phase:** {phase}\n"
output += f"πŸ“ˆ **Progress:** {progress:.1f}%\n"
output += f"[{progress_bar}] {progress:.1f}%\n\n"
# Step-specific details for file loading
if progress_state.get("step") == "file_loading":
processed = progress_state.get("processed_files", 0)
total = progress_state.get("total_files", 0)
successful = progress_state.get("successful_files", 0)
failed = progress_state.get("failed_files", 0)
if total > 0:
output += "πŸ“ **File Processing Status:**\n"
output += f" β€’ Total files: {total}\n"
output += f" β€’ Processed: {processed}/{total}\n"
output += f" β€’ βœ… Successful: {successful}\n"
output += f" β€’ ❌ Failed: {failed}\n"
if "current_batch" in progress_state and "total_batches" in progress_state:
output += f" β€’ πŸ“¦ Current batch: {progress_state['current_batch']}/{progress_state['total_batches']}\n"
output += "\n"
# Step-specific details for vector ingestion
elif progress_state.get("step") == "vector_ingestion":
docs_count = progress_state.get("documents_count", 0)
repo_name = progress_state.get("repo_name", "Unknown")
if docs_count > 0:
output += "🧠 **Vector Processing Status:**\n"
output += f" β€’ Repository: {repo_name}\n"
output += f" β€’ Documents: {docs_count:,}\n"
output += f" β€’ Stage: {phase}\n\n"
# Detailed information
output += f"πŸ“ **Details:**\n{details}\n"
# Final summary for completion
if status == "complete":
total_time = progress_state.get("total_time", 0)
docs_processed = progress_state.get("documents_processed", 0)
failed_files = progress_state.get("failed_files", 0)
vector_time = progress_state.get("vector_time", 0)
loading_time = progress_state.get("loading_time", 0)
repo_name = progress_state.get("repo_name", "Unknown")
output += "\n🎊 **INGESTION COMPLETED SUCCESSFULLY!**\n"
output += "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n"
output += f"🎯 **Repository:** {repo_name}\n"
output += f"πŸ“„ **Documents processed:** {docs_processed:,}\n"
output += f"❌ **Failed files:** {len(failed_files) if isinstance(failed_files, list) else failed_files}\n"
output += f"⏱️ **Total time:** {total_time:.1f} seconds\n"
output += f" β”œβ”€ File loading: {loading_time:.1f}s\n"
output += f" └─ Vector processing: {vector_time:.1f}s\n"
output += f"πŸ“Š **Processing rate:** {docs_processed/total_time:.1f} docs/second\n\n"
output += "πŸš€ **Next Step:** Go to the 'Query Interface' tab to start asking questions!"
elif status == "error":
error = progress_state.get("error", "Unknown error")
output += "\nπŸ’₯ **ERROR OCCURRED**\n"
output += "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\n"
output += f"❌ **Error Details:** {error[:300]}{'...' if len(error) > 300 else ''}\n"
output += "\nπŸ”§ **Troubleshooting Tips:**\n"
output += " β€’ Check your GitHub token permissions\n"
output += " β€’ Verify repository URL format\n"
output += " β€’ Ensure selected files exist\n"
output += " β€’ Check network connectivity\n"
return output
# Create the main Gradio interface
with gr.Blocks(title="Doc-MCP") as demo:
gr.Markdown("# πŸ“šDoc-MCP: Documentation RAG System")
gr.Markdown(
"Transform GitHub documentation repositories into accessible MCP (Model Context Protocol) servers for AI agents. Upload documentation, generate vector embeddings, and query with intelligent context retrieval."
)
# State variables
files_state = gr.State([])
progress_state = gr.State({})
with gr.Tabs():
with gr.TabItem("πŸ“₯ Documentation Ingestion"):
gr.Markdown("### πŸš€ Two-Step Documentation Processing Pipeline")
gr.Markdown(
"**Step 1:** Fetch markdown files from GitHub repository β†’ **Step 2:** Generate vector embeddings and store in MongoDB Atlas"
)
with gr.Row():
with gr.Column(scale=2):
repo_input = gr.Textbox(
label="πŸ“‚ GitHub Repository URL",
placeholder="Enter: owner/repo or https://github.com/owner/repo (e.g., gradio-app/gradio)",
value="",
info="Enter any GitHub repository containing markdown documentation"
)
load_btn = gr.Button("πŸ” Discover Documentation Files", variant="secondary")
with gr.Column(scale=1):
status_output = gr.Textbox(
label="Repository Discovery Status", interactive=False, lines=4,
placeholder="Repository scanning results will appear here..."
)
with gr.Row():
select_all_btn = gr.Button("πŸ“‹ Select All Documents", variant="secondary")
clear_all_btn = gr.Button("πŸ—‘οΈ Clear Selection", variant="secondary")
# File selection
with gr.Accordion(label="Available Documentation Files"):
file_selector = gr.CheckboxGroup(
choices=[], label="Select Markdown Files for RAG Processing", visible=False
)
# Two-step ingestion controls
gr.Markdown("### πŸ”„ RAG Pipeline Execution")
gr.Markdown("Process your documentation through our advanced RAG pipeline using Nebius AI embeddings and MongoDB Atlas vector storage.")
with gr.Row():
with gr.Column():
step1_btn = gr.Button(
"πŸ“₯ Step 1: Load Files from GitHub",
variant="primary",
size="lg",
interactive=False,
)
with gr.Column():
step2_btn = gr.Button(
"πŸ”„ Step 2: Start Ingestion",
variant="primary",
size="lg",
interactive=False,
)
with gr.Row():
refresh_btn = gr.Button("πŸ”„ Refresh Progress", variant="secondary")
reset_btn = gr.Button("πŸ—‘οΈ Reset Progress", variant="secondary")
# Progress display
progress_display = gr.Textbox(
label="πŸ“Š Real-time Ingestion Progress",
interactive=False,
lines=25,
value="πŸš€ Ready to start two-step ingestion process...\n\nπŸ“‹ Steps:\n1️⃣ Load files from GitHub repository\n2️⃣ Generate embeddings and store in vector database",
max_lines=30,
show_copy_button=True,
)
# Event handlers
def load_files_handler(repo_url: str):
if not repo_url.strip():
return (
gr.CheckboxGroup(choices=[], visible=False),
"Please enter a repository URL",
[],
gr.Button(interactive=False),
gr.Button(interactive=False),
)
files, message = fetch_files_with_loader(repo_url)
if files:
return (
gr.CheckboxGroup(
choices=files,
value=[],
label=f"Select Files from {repo_url} ({len(files)} files)",
visible=True,
),
message,
files,
gr.Button(interactive=True), # Enable step 1 button
gr.Button(interactive=False), # Keep step 2 disabled
)
else:
return (
gr.CheckboxGroup(choices=[], visible=False),
message,
[],
gr.Button(interactive=False),
gr.Button(interactive=False),
)
def start_step1_generator(repo_url: str, selected_files: List[str], current_progress: Dict):
"""Start Step 1 with generator-based real-time progress updates"""
for progress_update in start_file_loading_generator(repo_url, selected_files, current_progress.copy()):
progress_text = format_progress_display(progress_update)
step2_enabled = progress_update.get("step") == "file_loading_complete"
yield (
progress_update,
progress_text,
gr.Button(interactive=step2_enabled),
)
def start_step2(current_progress: Dict):
"""Start Step 2: Vector Ingestion"""
new_progress = start_vector_ingestion(current_progress.copy())
progress_text = format_progress_display(new_progress)
return new_progress, progress_text
def refresh_progress(current_progress: Dict):
"""Refresh the progress display"""
progress_text = format_progress_display(current_progress)
return progress_text
def reset_progress():
"""Reset all progress"""
return (
{},
"Ready to start two-step ingestion process...",
gr.Button(interactive=False),
)
def select_all_handler(available_files):
if available_files:
return gr.CheckboxGroup(value=available_files)
return gr.CheckboxGroup(value=[])
def clear_all_handler():
return gr.CheckboxGroup(value=[])
# Wire up events
load_btn.click(
fn=load_files_handler,
inputs=[repo_input],
outputs=[
file_selector,
status_output,
files_state,
step1_btn,
step2_btn,
],
show_api=False,
)
select_all_btn.click(
fn=select_all_handler,
inputs=[files_state],
outputs=[file_selector],
show_api=False,
)
clear_all_btn.click(
fn=clear_all_handler, outputs=[file_selector], show_api=False
)
step1_btn.click(
fn=start_step1_generator,
inputs=[repo_input, file_selector, progress_state],
outputs=[progress_state, progress_display, step2_btn],
show_api=False,
)
step2_btn.click(
fn=start_step2,
inputs=[progress_state],
outputs=[progress_state, progress_display],
show_api=False,
)
refresh_btn.click(
fn=refresh_progress,
inputs=[progress_state],
outputs=[progress_display],
show_api=False,
)
reset_btn.click(
fn=reset_progress,
outputs=[progress_state, progress_display, step2_btn],
show_api=False,
)
# ================================
# Tab 2: Query Interface
# ================================
with gr.TabItem("πŸ€– AI Documentation Assistant"):
gr.Markdown("### πŸ’¬ Intelligent Documentation Q&A")
gr.Markdown(
"Query your processed documentation using advanced semantic search. Get contextual answers with source citations powered by Nebius LLM and vector similarity search."
)
with gr.Row():
with gr.Column(scale=2):
# Repository selection - Dropdown that becomes textbox when selected
with gr.Row():
repo_dropdown = gr.Dropdown(
choices=get_available_repositories() or ["No repositories available"],
label="πŸ“š Select Documentation Repository",
value=None,
interactive=True,
allow_custom_value=True,
info="Choose from available repositories"
)
# Hidden textbox that will become visible when repo is selected
selected_repo_textbox = gr.Textbox(
label="🎯 Selected Repository",
value="",
interactive=False,
visible=False,
info="Currently selected repository for querying"
)
refresh_repos_btn = gr.Button(
"πŸ”„ Refresh Repository List", variant="secondary", size="sm"
)
# Query mode selection
query_mode = gr.Radio(
choices=["default", "text_search", "hybrid"],
label="πŸ” Search Strategy",
value="default",
info="β€’ default: Semantic similarity (AI understanding)\nβ€’ text_search: Keyword matching\nβ€’ hybrid: Combined approach for best results",
)
# Query input
query_input = gr.Textbox(
label="πŸ’­ Ask About Your Documentation",
placeholder="How do I implement a custom component? What are the available API endpoints? How to configure the system?",
lines=3,
info="Ask natural language questions about your documentation"
)
query_btn = gr.Button("πŸš€ Search Documentation", variant="primary", size="lg")
# Response display as text area
response_output = gr.Textbox(
label="πŸ€– AI Assistant Response",
value="Your AI-powered documentation response will appear here with contextual information and source citations...",
lines=10,
interactive=False,
info="Generated using Nebius LLM with retrieved documentation context"
)
with gr.Column(scale=2):
gr.Markdown("### πŸ“– Source References")
gr.Markdown("View the exact documentation sources used to generate the response, with relevance scores and GitHub links.")
# Source nodes display as JSON
sources_output = gr.JSON(
label="πŸ“Ž Source Citations & Metadata",
value={
"message": "Source documentation excerpts with relevance scores will appear here after your query...",
"info": "Each source includes file path, relevance score, and content snippet"
},
)
# Event handlers
def handle_repo_selection(selected_repo):
"""Handle repository selection from dropdown"""
if not selected_repo or selected_repo in ["No repositories available", ""]:
return (
gr.Dropdown(visible=True), # Keep dropdown visible
gr.Textbox(visible=False, value=""), # Hide textbox
gr.Button(interactive=False) # Disable query button
)
else:
return (
gr.Dropdown(visible=False), # Hide dropdown
gr.Textbox(visible=True, value=selected_repo), # Show textbox with selected repo
gr.Button(interactive=True) # Enable query button
)
def reset_repo_selection():
"""Reset to show dropdown again"""
try:
repos = get_available_repositories() or ["No repositories available"]
return (
gr.Dropdown(choices=repos, value=None, visible=True), # Show dropdown with refreshed choices
gr.Textbox(visible=False, value=""), # Hide textbox
gr.Button(interactive=False) # Disable query button
)
except Exception as e:
print(f"Error refreshing repository list: {e}")
return (
gr.Dropdown(choices=["Error loading repositories"], value=None, visible=True),
gr.Textbox(visible=False, value=""),
gr.Button(interactive=False)
)
def get_available_docs_repo():
"""
List the available docs of repositories - should be called first to list out all the available repo docs to chat with
Returns:
Updated dropdown with available repositories
"""
try:
repos = get_available_repositories()
if not repos:
repos = ["No repositories available - Please ingest documentation first"]
return gr.Dropdown(choices=repos, value=None)
except Exception as e:
print(f"Error refreshing repository list: {e}")
return gr.Dropdown(choices=["Error loading repositories"], value=None)
# Simple query handler
def handle_query(repo: str, mode: str, query: str):
"""
Handle query request - returns raw data from retriever
Args:
repo: Selected repository from textbox
mode: Query mode (default, text_search, hybrid)
query: User's query
Returns:
Raw result dict from QueryRetriever.make_query()
"""
if not query.strip():
return {"error": "Please enter a query."}
if not repo or repo in ["No repositories available", "Error loading repositories", ""]:
return {"error": "Please select a valid repository."}
try:
# Create query retriever for the selected repo
retriever = QueryRetriever(repo)
# Make the query and return raw result
result = retriever.make_query(query, mode)
return result
except Exception as e:
print(f"Query error: {e}")
traceback.print_exc()
return {"error": f"Query failed: {str(e)}"}
def make_query(repo: str, mode: str, query: str):
"""
Retrieve relevant documentation context for a given query using specified retrieval mode.
This function is designed to support Retrieval-Augmented Generation (RAG) by extracting
the most relevant context chunks from indexed documentation sources.
Args:
repo: Selected repository from the textbox input
mode: Query mode (default, text_search, hybrid)
query: User's query
Returns:
Tuple of (response_text, source_nodes_json)
"""
# Get raw result
result = handle_query(repo, mode, query)
# Extract response text
if "error" in result:
response_text = f"Error: {result['error']}"
source_nodes = {"error": result["error"]}
else:
response_text = result.get("response", "No response available")
source_nodes = result.get("source_nodes", [])
return response_text, source_nodes
# Wire up events
# Handle repository selection from dropdown
repo_dropdown.change(
fn=handle_repo_selection,
inputs=[repo_dropdown],
outputs=[repo_dropdown, selected_repo_textbox, query_btn],
show_api=False
)
# Handle refresh button - resets to dropdown view
refresh_repos_btn.click(
fn=reset_repo_selection,
outputs=[repo_dropdown, selected_repo_textbox, query_btn],
show_api=False
)
# Also provide API endpoint for listing repositories
refresh_repos_btn.click(
fn=get_available_docs_repo,
outputs=[repo_dropdown],
api_name="list_available_docs",
)
# Query button uses the textbox value (not dropdown)
query_btn.click(
fn=make_query,
inputs=[selected_repo_textbox, query_mode, query_input], # Use textbox, not dropdown
outputs=[response_output, sources_output],
api_name="query_documentation",
)
# Also allow Enter key to trigger query
query_input.submit(
fn=make_query,
inputs=[selected_repo_textbox, query_mode, query_input], # Use textbox, not dropdown
outputs=[response_output, sources_output],
show_api=False,
)
# ================================
# Tab 3: Repository Management
# ================================
with gr.TabItem("πŸ—‚οΈ Repository Management"):
gr.Markdown("Manage your ingested repositories - view details and delete repositories when needed.")
with gr.Row():
with gr.Column(scale=1):
gr.Markdown("### πŸ“Š Repository Statistics")
stats_display = gr.JSON(
label="Database Statistics",
value={"message": "Click refresh to load statistics..."}
)
refresh_stats_btn = gr.Button("πŸ”„ Refresh Statistics", variant="secondary")
with gr.Column(scale=2):
gr.Markdown("### πŸ“‹ Repository Details")
repos_table = gr.Dataframe(
headers=["Repository", "Files", "Last Updated"],
datatype=["str", "number", "str"],
label="Ingested Repositories",
interactive=False,
wrap=True
)
refresh_repos_btn = gr.Button("πŸ”„ Refresh Repository List", variant="secondary")
gr.Markdown("### πŸ—‘οΈ Delete Repository")
gr.Markdown("**⚠️ Warning:** This will permanently delete all documents and metadata for the selected repository.")
with gr.Row():
with gr.Column(scale=2):
delete_repo_dropdown = gr.Dropdown(
choices=[],
label="Select Repository to Delete",
value=None,
interactive=True,
allow_custom_value=False,
)
# Confirmation checkbox
confirm_delete = gr.Checkbox(
label="I understand this action cannot be undone",
value=False
)
delete_btn = gr.Button(
"πŸ—‘οΈ Delete Repository",
variant="stop",
size="lg",
interactive=False
)
with gr.Column(scale=1):
deletion_status = gr.Textbox(
label="Deletion Status",
value="Select a repository and confirm to enable deletion.",
interactive=False,
lines=6
)
# Management functions
def load_repository_stats():
"""Load overall repository statistics"""
try:
stats = get_repository_stats()
return stats
except Exception as e:
return {"error": f"Failed to load statistics: {str(e)}"}
def load_repository_details():
"""Load detailed repository information as a table"""
try:
details = get_repo_details()
if not details:
return [["No repositories found", 0, "N/A"]]
# Format for dataframe
table_data = []
for repo in details:
last_updated = repo.get("last_updated", "Unknown")
if hasattr(last_updated, 'strftime'):
last_updated = last_updated.strftime("%Y-%m-%d %H:%M")
elif last_updated != "Unknown":
last_updated = str(last_updated)
table_data.append([
repo.get("repo_name", "Unknown"),
repo.get("file_count", 0),
last_updated
])
return table_data
except Exception as e:
return [["Error loading repositories", 0, str(e)]]
def update_delete_dropdown():
"""Update the dropdown with available repositories"""
try:
repos = get_available_repositories()
return gr.Dropdown(choices=repos, value=None)
except Exception as e:
print(f"Error updating delete dropdown: {e}")
return gr.Dropdown(choices=[], value=None)
def check_delete_button_state(repo_selected, confirmation_checked):
"""Enable/disable delete button based on selection and confirmation"""
if repo_selected and confirmation_checked:
return gr.Button(interactive=True)
else:
return gr.Button(interactive=False)
def delete_repository(repo_name: str, confirmed: bool):
"""Delete the selected repository"""
if not repo_name:
return "❌ No repository selected.", gr.Dropdown(choices=[]), gr.Checkbox(value=False)
if not confirmed:
return "❌ Please confirm deletion by checking the checkbox.", gr.Dropdown(choices=[]), gr.Checkbox(value=False)
try:
# Perform deletion
result = delete_repository_data(repo_name)
# Prepare status message
status_msg = result["message"]
if result["success"]:
status_msg += "\n\nπŸ“Š Deletion Summary:"
status_msg += f"\n- Vector documents removed: {result['vector_docs_deleted']}"
status_msg += f"\n- Repository record deleted: {'Yes' if result['repo_record_deleted'] else 'No'}"
status_msg += f"\n\nβœ… Repository '{repo_name}' has been completely removed."
# Update dropdown (remove deleted repo)
updated_dropdown = update_delete_dropdown()
# Reset confirmation checkbox
reset_checkbox = gr.Checkbox(value=False)
return status_msg, updated_dropdown, reset_checkbox
except Exception as e:
error_msg = f"❌ Error deleting repository: {str(e)}"
return error_msg, gr.Dropdown(choices=[]), gr.Checkbox(value=False)
# Wire up management events
refresh_stats_btn.click(
fn=load_repository_stats,
outputs=[stats_display],
show_api=False
)
refresh_repos_btn.click(
fn=load_repository_details,
outputs=[repos_table],
show_api=False
)
# Update delete dropdown when refreshing repos
refresh_repos_btn.click(
fn=update_delete_dropdown,
outputs=[delete_repo_dropdown],
show_api=False
)
# Enable/disable delete button based on selection and confirmation
delete_repo_dropdown.change(
fn=check_delete_button_state,
inputs=[delete_repo_dropdown, confirm_delete],
outputs=[delete_btn],
show_api=False
)
confirm_delete.change(
fn=check_delete_button_state,
inputs=[delete_repo_dropdown, confirm_delete],
outputs=[delete_btn],
show_api=False
)
# Delete repository
delete_btn.click(
fn=delete_repository,
inputs=[delete_repo_dropdown, confirm_delete],
outputs=[deletion_status, delete_repo_dropdown, confirm_delete],
show_api=False
)
# Load data on tab load
demo.load(
fn=load_repository_stats,
outputs=[stats_display],
show_api=False
)
demo.load(
fn=load_repository_details,
outputs=[repos_table],
show_api=False
)
demo.load(
fn=update_delete_dropdown,
outputs=[delete_repo_dropdown],
show_api=False
)
# ================================
# Tab 4: GitHub File Search (Hidden API)
# ================================
with gr.TabItem("πŸ” GitHub File Search", visible=False):
gr.Markdown("### πŸ”§ GitHub Repository File Search API")
gr.Markdown("Pure API endpoints for GitHub file operations - all responses in JSON format")
with gr.Row():
with gr.Column():
gr.Markdown("#### πŸ“‹ List Repository Files")
# Repository input for file operations
api_repo_input = gr.Textbox(
label="Repository URL",
placeholder="owner/repo or https://github.com/owner/repo",
value="",
info="GitHub repository to scan"
)
# Branch selection
api_branch_input = gr.Textbox(
label="Branch",
value="main",
placeholder="main",
info="Branch to search (default: main)"
)
# File extensions
api_extensions_input = gr.Textbox(
label="File Extensions (comma-separated)",
value=".md,.mdx",
placeholder=".md,.mdx,.txt",
info="File extensions to include"
)
# List files button
list_files_btn = gr.Button("πŸ“‹ List Files", variant="primary")
with gr.Column():
gr.Markdown("#### πŸ“„ Get Single File")
# Single file inputs
single_repo_input = gr.Textbox(
label="Repository URL",
placeholder="owner/repo or https://github.com/owner/repo",
value="",
info="GitHub repository"
)
single_file_input = gr.Textbox(
label="File Path",
placeholder="docs/README.md",
value="",
info="Path to specific file in repository"
)
single_branch_input = gr.Textbox(
label="Branch",
value="main",
placeholder="main",
info="Branch name (default: main)"
)
# Get single file button
get_single_btn = gr.Button("πŸ“„ Get Single File", variant="secondary")
with gr.Row():
with gr.Column():
gr.Markdown("#### πŸ“š Get Multiple Files")
# Multiple files inputs
multiple_repo_input = gr.Textbox(
label="Repository URL",
placeholder="owner/repo or https://github.com/owner/repo",
value="",
info="GitHub repository"
)
multiple_files_input = gr.Textbox(
label="File Paths (comma-separated)",
placeholder="README.md,docs/guide.md,api/overview.md",
value="",
lines=3,
info="Comma-separated list of file paths"
)
multiple_branch_input = gr.Textbox(
label="Branch",
value="main",
placeholder="main",
info="Branch name (default: main)"
)
# Get multiple files button
get_multiple_btn = gr.Button("πŸ“š Get Multiple Files", variant="secondary")
# Single JSON output for all operations
gr.Markdown("### πŸ“Š API Response")
api_response_output = gr.JSON(
label="JSON Response",
value={
"message": "API responses will appear here",
"info": "Use the buttons above to interact with GitHub repositories"
}
)
# Pure API Functions (JSON only responses)
def list_repository_files(repo_url: str, branch: str = "main", extensions: str = ".md,.mdx"):
"""
List all files in a GitHub repository with specified extensions
Args:
repo_url: GitHub repository URL or owner/repo format
branch: Branch name to search (default: main)
extensions: Comma-separated file extensions (default: .md,.mdx)
Returns:
JSON response with file list and metadata
"""
try:
if not repo_url.strip():
return {"success": False, "error": "Repository URL is required"}
# Parse extensions list
ext_list = [ext.strip() for ext in extensions.split(",") if ext.strip()]
if not ext_list:
ext_list = [".md", ".mdx"]
# Get files list
files, status_message = fetch_repository_files(
repo_url=repo_url,
file_extensions=ext_list,
github_token=os.getenv("GITHUB_API_KEY"),
branch=branch
)
if files:
return {
"success": True,
"repository": repo_url,
"branch": branch,
"extensions": ext_list,
"total_files": len(files),
"files": files,
"status": status_message
}
else:
return {
"success": False,
"repository": repo_url,
"branch": branch,
"extensions": ext_list,
"total_files": 0,
"files": [],
"error": status_message or "No files found"
}
except Exception as e:
return {
"success": False,
"error": f"Failed to list files: {str(e)}",
"repository": repo_url,
"branch": branch
}
def get_single_file(repo_url: str, file_path: str, branch: str = "main"):
"""
Retrieve a single file from GitHub repository
Args:
repo_url: GitHub repository URL or owner/repo format
file_path: Path to the file in the repository
branch: Branch name (default: main)
Returns:
JSON response with file content and metadata
"""
try:
if not repo_url.strip():
return {"success": False, "error": "Repository URL is required"}
if not file_path.strip():
return {"success": False, "error": "File path is required"}
# Parse repo name
if "github.com" in repo_url:
repo_name = (
repo_url.replace("https://github.com/", "")
.replace("http://github.com/", "")
.strip("/")
)
else:
repo_name = repo_url.strip()
# Load single file
documents, failed = load_github_files(
repo_name=repo_name,
file_paths=[file_path.strip()],
branch=branch,
github_token=os.getenv("GITHUB_API_KEY")
)
if documents and len(documents) > 0:
doc = documents[0]
return {
"success": True,
"repository": repo_name,
"branch": branch,
"file_path": file_path,
"file_name": doc.metadata.get("file_name", ""),
"file_size": len(doc.text),
"content": doc.text,
"metadata": doc.metadata,
"url": doc.metadata.get("url", ""),
"raw_url": doc.metadata.get("raw_url", "")
}
else:
error_msg = f"Failed to retrieve file: {failed[0] if failed else 'File not found or access denied'}"
return {
"success": False,
"repository": repo_name,
"branch": branch,
"file_path": file_path,
"error": error_msg
}
except Exception as e:
return {
"success": False,
"error": f"Failed to get single file: {str(e)}",
"repository": repo_url,
"file_path": file_path,
"branch": branch
}
def get_multiple_files(repo_url: str, file_paths_str: str, branch: str = "main"):
"""
Retrieve multiple files from GitHub repository
Args:
repo_url: GitHub repository URL or owner/repo format
file_paths_str: Comma-separated string of file paths
branch: Branch name (default: main)
Returns:
JSON response with multiple file contents and metadata
"""
try:
if not repo_url.strip():
return {"success": False, "error": "Repository URL is required"}
if not file_paths_str.strip():
return {"success": False, "error": "File paths are required"}
# Parse file paths from comma-separated string
file_paths = [path.strip() for path in file_paths_str.split(",") if path.strip()]
if not file_paths:
return {"success": False, "error": "No valid file paths provided"}
# Parse repo name
if "github.com" in repo_url:
repo_name = (
repo_url.replace("https://github.com/", "")
.replace("http://github.com/", "")
.strip("/")
)
else:
repo_name = repo_url.strip()
# Load multiple files
documents, failed = load_github_files(
repo_name=repo_name,
file_paths=file_paths,
branch=branch,
github_token=os.getenv("GITHUB_API_KEY")
)
# Process successful documents
successful_files = []
for doc in documents:
file_data = {
"file_path": doc.metadata.get("file_path", ""),
"file_name": doc.metadata.get("file_name", ""),
"file_size": len(doc.text),
"content": doc.text,
"metadata": doc.metadata,
"url": doc.metadata.get("url", ""),
"raw_url": doc.metadata.get("raw_url", "")
}
successful_files.append(file_data)
return {
"success": True,
"repository": repo_name,
"branch": branch,
"requested_files": len(file_paths),
"successful_files": len(successful_files),
"failed_files": len(failed),
"files": successful_files,
"failed_file_paths": failed,
"total_content_size": sum(len(doc.text) for doc in documents),
"requested_file_paths": file_paths
}
except Exception as e:
return {
"success": False,
"error": f"Failed to get multiple files: {str(e)}",
"repository": repo_url,
"file_paths": file_paths_str,
"branch": branch
}
# Wire up the GitHub file search events - all output to single JSON component
list_files_btn.click(
fn=list_repository_files,
inputs=[api_repo_input, api_branch_input, api_extensions_input],
outputs=[api_response_output],
api_name="list_repository_files"
)
get_single_btn.click(
fn=get_single_file,
inputs=[single_repo_input, single_file_input, single_branch_input],
outputs=[api_response_output],
api_name="get_single_file"
)
get_multiple_btn.click(
fn=get_multiple_files,
inputs=[multiple_repo_input, multiple_files_input, multiple_branch_input],
outputs=[api_response_output],
api_name="get_multiple_files"
)
if __name__ == "__main__":
demo.launch(mcp_server=True)