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import json
import os
import traceback
import uuid
from datetime import datetime
from typing import Dict
import pandas as pd
import streamlit as st
from datasets import load_dataset
from dotenv import load_dotenv
# Only import if file exists
try:
from langgraph_agent import DataAnalystAgent
AGENT_AVAILABLE = True
except ImportError as e:
AGENT_AVAILABLE = False
IMPORT_ERROR = str(e)
# Load environment variables
load_dotenv()
# Set up page config
st.set_page_config(
page_title="🤖 LangGraph Data Analyst Agent (Debug)",
layout="wide",
page_icon="🤖",
initial_sidebar_state="expanded",
)
def check_environment():
"""Check the deployment environment and dependencies."""
st.markdown("## 🔍 Environment Debug Info")
# Check Python version
import sys
st.write(f"**Python Version:** {sys.version}")
# Check if running on Hugging Face
is_hf_space = os.environ.get("SPACE_ID") is not None
st.write(f"**Running on Hugging Face Spaces:** {is_hf_space}")
if is_hf_space:
st.write(f"**Space ID:** {os.environ.get('SPACE_ID', 'Unknown')}")
# Check API key availability
nebius_key = os.environ.get("NEBIUS_API_KEY")
openai_key = os.environ.get("OPENAI_API_KEY")
st.write(f"**Nebius API Key Available:** {'Yes' if nebius_key else 'No'}")
st.write(f"**OpenAI API Key Available:** {'Yes' if openai_key else 'No'}")
if nebius_key:
st.write(f"**Nebius Key Length:** {len(nebius_key)} characters")
if openai_key:
st.write(f"**OpenAI Key Length:** {len(openai_key)} characters")
# Check agent import
st.write(
f"**LangGraph Agent Import:** {'✅ Success' if AGENT_AVAILABLE else '❌ Failed'}"
)
if not AGENT_AVAILABLE:
st.error(f"Import Error: {IMPORT_ERROR}")
# Check required packages
required_packages = [
"langchain",
"langchain_core",
"langchain_openai",
"langgraph",
"datasets",
"pandas",
]
st.markdown("### 📦 Package Availability")
for package in required_packages:
try:
__import__(package)
st.write(f"✅ {package}")
except ImportError as e:
st.write(f"❌ {package} - {str(e)}")
def test_simple_agent():
"""Test basic agent functionality."""
if not AGENT_AVAILABLE:
st.error("Cannot test agent - import failed")
return
st.markdown("## 🧪 Agent Test")
# Get API key
api_key = os.environ.get("NEBIUS_API_KEY") or os.environ.get("OPENAI_API_KEY")
if not api_key:
st.error("No API key found!")
return
st.write("**API Key:** ✅ Available")
# Test agent creation
try:
st.write("**Creating Agent...**")
agent = DataAnalystAgent(api_key=api_key)
st.write("✅ Agent created successfully")
# Test simple query
if st.button("🧪 Test Simple Query"):
with st.spinner("Testing agent with simple query..."):
try:
result = agent.invoke("Hello, are you working?", "debug_test")
st.success("✅ Agent responded successfully!")
st.markdown("**Response Messages:**")
for i, msg in enumerate(result.get("messages", [])):
st.write(
f"{i+1}. {type(msg).__name__}: {getattr(msg, 'content', 'No content')[:100]}..."
)
except Exception as e:
st.error(f"❌ Agent test failed: {str(e)}")
st.code(traceback.format_exc())
except Exception as e:
st.error(f"❌ Agent creation failed: {str(e)}")
st.code(traceback.format_exc())
def test_dataset_loading():
"""Test dataset loading."""
st.markdown("## 📊 Dataset Test")
try:
with st.spinner("Loading dataset..."):
dataset = load_dataset(
"bitext/Bitext-customer-support-llm-chatbot-training-dataset"
)
df = pd.DataFrame(dataset["train"])
st.success(f"✅ Dataset loaded: {len(df):,} records")
st.dataframe(df.head(3))
except Exception as e:
st.error(f"❌ Dataset loading failed: {str(e)}")
st.code(traceback.format_exc())
def main():
st.title("🔧 LangGraph Agent Debug Tool")
st.markdown("This tool helps diagnose issues with the LangGraph agent deployment.")
# Environment check
check_environment()
st.markdown("---")
# Dataset test
test_dataset_loading()
st.markdown("---")
# Agent test
test_simple_agent()
st.markdown("---")
st.markdown("## 💡 Common Solutions")
st.markdown(
"""
**If agent creation fails:**
- Check API key is correctly set as Space secret
- Verify all dependencies are in requirements.txt
- Check for import errors above
**If agent hangs on 'thinking':**
- API key might be invalid/expired
- Network connectivity issues to API endpoint
- Unhandled exceptions in LangGraph workflow
**If dataset loading fails:**
- Network connectivity issues
- Hugging Face datasets library not properly installed
"""
)
if __name__ == "__main__":
main()
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