Update app.py

app.py

@@ -2,6 +2,7 @@ import os
 import streamlit as st
 import requests
 import datetime
+import time
 from dotenv import load_dotenv
 from tavily import TavilyClient
 import feedparser
@@ -29,13 +30,23 @@ def call_llm(messages, model="deepseek/deepseek-chat-v3-0324:free", max_tokens=3
         "model": model,
         "messages": messages,
         "max_tokens": max_tokens,
-        "temperature": temperature
+        "temperature": temperature,
+        "stream": True
     }
-    response = requests.post(url, headers=headers, json=data)
-    result = response.json()
-    if response.status_code != 200:
-        raise RuntimeError(result.get("error", {}).get("message", "LLM API error"))
-    return result["choices"][0]["message"]["content"]
+    with requests.post(url, headers=headers, json=data, stream=True) as response:
+        content = ""
+        for line in response.iter_lines():
+            if line:
+                decoded = line.decode("utf-8")
+                if decoded.startswith("data: "):
+                    piece = decoded.replace("data: ", "").strip()
+                    if piece != "[DONE]":
+                        try:
+                            content += eval(piece)['choices'][0]['delta'].get('content', '')
+                            yield content
+                        except:
+                            continue
+
 
 def get_sources(topic, domains=None):
     query = topic
@@ -47,6 +58,7 @@ def get_sources(topic, domains=None):
         "title": r["title"],
         "url": r["url"],
         "snippet": r.get("content", ""),
+        "image_url": r.get("image_url"),
         "source": "web"
     } for r in response.get("results", [])]
 
@@ -125,7 +137,6 @@ def generate_download_button(file, label, mime_type):
         </a>
     """
 
-# --- Streamlit UI ---
 st.set_page_config("Deep Research Bot", layout="centered")
 st.markdown("""
     <style>
@@ -148,17 +159,35 @@ st.title("📘 Research Output")
 
 if research_button and topic:
     try:
-        with st.spinner("Gathering sources and analyzing deeply..."):
-            all_sources = []
-            if source_type in ["Web Only", "Hybrid"]:
-                all_sources += get_sources(topic, custom_domains)
-            if source_type in ["Academic Only", "Hybrid"]:
-                all_sources += get_arxiv_papers(topic)
-                all_sources += get_semantic_papers(topic)
+        with st.status("🔍 Gathering and analyzing sources...") as status:
+            def fetch_all_sources():
+                sources = []
+                if source_type in ["Web Only", "Hybrid"]:
+                    sources += get_sources(topic, custom_domains)
+                if source_type in ["Academic Only", "Hybrid"]:
+                    status.update(label="📚 Fetching academic sources...")
+                    sources += get_arxiv_papers(topic) or []
+                    sources += get_semantic_papers(topic) or []
+                return sources
+
+            all_sources, retries = [], 0
+            while retries < 3:
+                all_sources = fetch_all_sources()
+                if all_sources:
+                    break
+                retries += 1
+                status.update(label=f"🔁 Retrying... ({retries}) Deeper research underway...")
+                time.sleep(2)
+
+            if not all_sources:
+                raise ValueError("Unable to fetch any sources. Please try again later.")
 
             merged = merge_duplicates(all_sources)
             citations = [generate_apa_citation(m['title'], m['url'], m['source']) for m in merged]
-            combined_text = "\n\n".join([f"- [{m['title']}]({m['url']})\n> {m.get('snippet', m.get('summary', ''))[:300]}..." for m in merged])
+            combined_text = "\n\n".join(
+                [f"- [{m['title']}]({m['url']})\n> {m.get('snippet', m.get('summary', ''))[:300]}..." for m in merged]
+            )
+            status.update(label="🧠 Synthesizing final report...")
 
         prompt = f"""
 You are an expert assistant. Based on the following sources, write a {report_type.lower()} in a {tone.lower()} tone on the topic: {topic}.
@@ -171,16 +200,19 @@ APA Citations:
         """
 
         st.subheader(f"📝 {report_type} on '{topic}'")
-        final_output = call_llm([{"role": "user", "content": prompt}])
-        st.markdown(final_output, unsafe_allow_html=True)
+        output_placeholder = st.empty()
+        full_output = ""
+        for chunk in call_llm([{"role": "user", "content": prompt}]):
+            full_output = chunk
+            output_placeholder.markdown(full_output, unsafe_allow_html=True)
 
         if report_type == "Thorough Academic Research":
             st.markdown("---")
             st.subheader("📄 Downloads")
-            st.markdown(generate_download_button(generate_pdf(final_output), "Research_Report.pdf", "application/pdf"), unsafe_allow_html=True)
-            st.markdown(generate_download_button(generate_latex(final_output), "Research_Report.tex", "application/x-latex"), unsafe_allow_html=True)
+            st.markdown(generate_download_button(generate_pdf(full_output), "Research_Report.pdf", "application/pdf"), unsafe_allow_html=True)
+            st.markdown(generate_download_button(generate_latex(full_output), "Research_Report.tex", "application/x-latex"), unsafe_allow_html=True)
 
-        overlaps = check_plagiarism(final_output, topic)
+        overlaps = check_plagiarism(full_output, topic)
         st.markdown("---")
         st.subheader("🔎 Plagiarism Check")
         if overlaps:
@@ -191,4 +223,4 @@ APA Citations:
             st.success("✅ No major overlaps found.")
 
     except Exception as e:
-        st.error(f"❌ Error occurred: {e}")
+        st.error(f"❌ Error occurred: {e}")