app.py

import streamlit as st
import requests
import networkx as nx
import matplotlib.pyplot as plt

# Replace with your actual HF Inference Endpoint URL
INFERENCE_API_URL = "https://your-inference-endpoint-url"

# Replace with your actual Hugging Face Access Token
HF_TOKEN = "Bearer YOUR-HUGGINGFACE-TOKEN"

headers = {
    "Authorization": HF_TOKEN,
    "Content-Type": "application/json"
}

st.set_page_config(page_title="Causal Loop Diagram Generator", page_icon="♻️")
st.title("♻️ Causal Loop Diagram (CLD) Generator (Simple Version)")
st.markdown("Enter a system description (even a paragraph). The app will extract causal links and draw the CLD diagram.")

user_input = st.text_area("Enter System Description:", height=200)

if st.button("Generate CLD Diagram"):
    if user_input.strip() == "":
        st.error("Please enter a valid system description.")
    else:
        try:
            prompt_text = f"Extract causal relationships from the paragraph and format them like [Cause] → [Effect] (+/-):\n\n{user_input}"
            response = requests.post(
                INFERENCE_API_URL,
                headers=headers,
                json={"inputs": prompt_text}
            )

            if response.status_code == 200:
                generated_text = response.json()[0]['generated_text']
                causal_links = []

                lines = generated_text.split("\n")
                for line in lines:
                    line = line.strip()
                    if "→" in line and ("(+)" in line or "(-)" in line):
                        if line.endswith("(+)") or line.endswith("(-)"):
                            causal_links.append(line)

                if causal_links:
                    st.success("✅ Extracted Causal Relationships:")
                    st.text("\n".join(causal_links))

                    G = nx.DiGraph()

                    for line in causal_links:
                        parts = line.split("→")
                        if len(parts) == 2:
                            cause = parts[0].strip()
                            rest = parts[1].strip()

                            if rest.endswith("(+)"):
                                effect = rest[:-3].strip()
                                polarity = "+"
                            elif rest.endswith("(-)"):
                                effect = rest[:-3].strip()
                                polarity = "-"
                            else:
                                continue

                            G.add_edge(cause, effect, polarity=polarity)

                    pos = nx.spring_layout(G, seed=42)
                    plt.figure(figsize=(10, 8))
                    nx.draw(G, pos, with_labels=True, arrows=True, node_color="skyblue", edge_color="black", node_size=2000, font_size=12, font_weight='bold')

                    edge_labels = {(u, v): G.edges[u, v]['polarity'] for u, v in G.edges()}
                    nx.draw_networkx_edge_labels(G, pos, edge_labels=edge_labels, font_color="red", font_size=14)

                    st.pyplot(plt)

                else:
                    st.warning("⚠️ No causal relationships detected.")
            else:
                st.error(f"❌ API Error: {response.status_code} - {response.text}")

        except Exception as e:
            st.error(f"❌ Connection Error: {e}")