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# interface.py
import streamlit as st
import logging
from typing import Dict
from langchain_core.messages import HumanMessage
from workflow import ResearchWorkflow
from config import ResearchConfig
from langchain_core.messages import AIMessage
logger = logging.getLogger(__name__)
class ResearchInterface:
"""
Provides the Streamlit-based interface for executing the research workflow.
"""
def __init__(self) -> None:
self.workflow = ResearchWorkflow()
self._initialize_interface()
def _initialize_interface(self) -> None:
st.set_page_config(
page_title="NeuroResearch AI",
layout="wide",
initial_sidebar_state="expanded"
)
self._inject_styles()
self._build_sidebar()
self._build_main_interface()
def _inject_styles(self) -> None:
st.markdown(
"""
<style>
:root {
--primary: #2ecc71;
--secondary: #3498db;
--background: #0a0a0a;
--text: #ecf0f1;
}
.stApp {
background: var(--background);
color: var(--text);
font-family: 'Roboto', sans-serif;
}
.stTextArea textarea {
background: #1a1a1a !important;
color: var(--text) !important;
border: 2px solid var(--secondary);
border-radius: 8px;
padding: 1rem;
}
.stButton>button {
background: linear-gradient(135deg, var(--primary), var(--secondary));
border: none;
border-radius: 8px;
padding: 1rem 2rem;
transition: all 0.3s;
}
.stButton>button:hover {
transform: translateY(-2px);
box-shadow: 0 4px 12px rgba(46, 204, 113, 0.3);
}
.stExpander {
background: #1a1a1a;
border: 1px solid #2a2a2a;
border-radius: 8px;
margin: 1rem 0;
}
</style>
""",
unsafe_allow_html=True
)
def _build_sidebar(self) -> None:
with st.sidebar:
st.title("🔍 Research Database")
st.subheader("Technical Papers")
for title, short in ResearchConfig.DOCUMENT_MAP.items():
with st.expander(short):
st.markdown(f"```\n{title}\n```")
st.subheader("Analysis Metrics")
st.metric("Vector Collections", 2)
st.metric("Embedding Dimensions", ResearchConfig.EMBEDDING_DIMENSIONS)
with st.sidebar.expander("Collaboration Hub"):
st.subheader("Live Research Team")
st.write("👩💻 Researcher A")
st.write("👨🔬 Researcher B")
st.write("🤖 AI Assistant")
st.subheader("Knowledge Graph")
if st.button("🕸 View Current Graph"):
self._display_knowledge_graph()
def _build_main_interface(self) -> None:
st.title("🧠 NeuroResearch AI")
query = st.text_area("Research Query:", height=200, placeholder="Enter technical research question...")
domain = st.selectbox(
"Select Research Domain:",
options=[
"Biomedical Research",
"Legal Research",
"Environmental and Energy Studies",
"Competitive Programming and Theoretical Computer Science",
"Social Sciences"
],
index=0
)
if st.button("Execute Analysis", type="primary"):
self._execute_analysis(query, domain)
def _execute_analysis(self, query: str, domain: str) -> None:
try:
with st.spinner("Initializing Quantum Analysis..."):
results = self.workflow.app.stream(
{
"messages": [HumanMessage(content=query)],
"context": {"domain": domain},
"metadata": {}
},
{"recursion_limit": 100}
)
for event in results:
self._render_event(event)
st.success("✅ Analysis Completed Successfully")
except Exception as e:
st.error(
f"""**Analysis Failed**
{str(e)}
Potential issues:
- Complex query structure
- Document correlation failure
- Temporal processing constraints"""
)
def _render_event(self, event: Dict) -> None:
if 'ingest' in event:
with st.container():
st.success("✅ Query Ingested")
elif 'retrieve' in event:
with st.container():
docs = event['retrieve']['context'].get('documents', [])
st.info(f"📚 Retrieved {len(docs)} documents")
with st.expander("View Retrieved Documents", expanded=False):
for idx, doc in enumerate(docs, start=1):
st.markdown(f"**Document {idx}**")
st.code(doc.page_content, language='text')
elif 'analyze' in event:
with st.container():
content = event['analyze']['messages'][0].content
with st.expander("Technical Analysis Report", expanded=True):
st.markdown(content)
elif 'validate' in event:
with st.container():
content = event['validate']['messages'][0].content
if "VALID" in content:
st.success("✅ Validation Passed")
with st.expander("View Validated Analysis", expanded=True):
st.markdown(content.split("Validation:")[0])
else:
st.warning("⚠️ Validation Issues Detected")
with st.expander("View Validation Details", expanded=True):
st.markdown(content)
elif 'enhance' in event:
with st.container():
content = event['enhance']['messages'][0].content
with st.expander("Enhanced Multi-Modal Analysis Report", expanded=True):
st.markdown(content)
def _display_knowledge_graph(self) -> None:
st.write("Knowledge Graph visualization is not implemented yet.")
class ResearchInterfaceExtended(ResearchInterface):
"""
Extended interface that includes domain adaptability, collaboration features, and graph visualization.
"""
def _build_main_interface(self) -> None:
super()._build_main_interface()
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