Update app.py

app.py

@@ -1,3 +1,6 @@
+# app.py ────────────────────────────────────────────────────────────────
+# Pin Gradio ≤ 3.31.0 in requirements.txt so <a target="_blank"> is kept
+# and place architecture.png beside this file.
 import os, re, faiss, zipfile, warnings, gradio as gr
 from pathlib import Path
 from typing import List
@@ -6,13 +9,12 @@ from PyPDF2 import PdfReader
 from docx import Document
 from docx.opc.exceptions import PackageNotFoundError
 from openai import OpenAI
-from openai import OpenAIError
 
 # ───────── 0. résumé → plain-text ──────────────────────────────────────
-FILE = Path(__file__).parent / "my_resume.pdf"
+FILE = Path("my_resume.pdf")
 
 def read_pdf(p: Path) -> str:
-    return " ".join((pg.extract_text() or "") for pg in PdfReader(p).pages)
+    return " ".join(pg.extract_text() or "" for pg in PdfReader(p).pages)
 
 def read_docx(p: Path) -> str:
     return " ".join(par.text for par in Document(p).paragraphs if par.text.strip())
@@ -26,12 +28,18 @@ except (PackageNotFoundError, KeyError, zipfile.BadZipFile):
 text = re.sub(r"\s+", " ", raw).strip()
 
 # ───────── 0-bis. extra searchable metadata ───────────────────────────
-LINK_MD = '<a href="https://www.linkedin.com/in/sriharideep/" target="_blank">LinkedIn Profile</a>'
-BLOG_MD = '<a href="https://sfdcbrewery.github.io/" target="_blank">Technical Blog</a>'
-ARCH_NOTE = (
-    '<b>ARCHITECTURE NOTE</b> – The bot follows a Retrieval-Augmented Generation (RAG) design: PDF → 180-token chunks → MiniLM-L6 embeddings → FAISS similarity search → GPT-3.5-turbo answer constrained to context.'
+LINK_MD = '<a href="https://www.linkedin.com/in/sriharideep/" target="_blank">' \
+          'LinkedIn Profile</a>'
+BLOG_MD = '<a href="https://sfdcbrewery.github.io/" target="_blank">' \
+          'Technical Blog</a>'
+ARCH_MD = (
+    "ARCHITECTURE NOTE – The bot follows a Retrieval-Augmented Generation "
+    "(RAG) design: PDF → 180-token chunks → MiniLM-L6 embeddings → FAISS "
+    "similarity search → GPT-3.5-turbo answer constrained to context."
 )
-text += f" LinkedIn: {LINK_MD} Blog: {BLOG_MD} {ARCH_NOTE}"
+
+# make them retrievable by the RAG index (even though we’ll short-circuit)
+text += f" LinkedIn: {LINK_MD} Blog: {BLOG_MD} {ARCH_MD}"
 
 # ───────── 1. text → embeddings → FAISS ───────────────────────────────
 def chunkify(t: str, max_tok: int = 180) -> List[str]:
@@ -46,13 +54,12 @@ def chunkify(t: str, max_tok: int = 180) -> List[str]:
     return out
 
 CHUNKS = chunkify(text)
+
 embedder = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
-try:
-    vecs = embedder.encode(CHUNKS, convert_to_numpy=True)
-except Exception as e:
-    raise RuntimeError("Embedding model failed to encode résumé.") from e
+vecs = embedder.encode(CHUNKS, convert_to_numpy=True)
 faiss.normalize_L2(vecs)
 index = faiss.IndexFlatIP(vecs.shape[1]); index.add(vecs)
+
 def retrieve(q: str, k: int = 4):
     qv = embedder.encode([q], convert_to_numpy=True); faiss.normalize_L2(qv)
     sims, idx = index.search(qv, k)
@@ -65,8 +72,10 @@ SYSTEM = ("You are a helpful assistant. Answer ONLY with facts in the context. "
           "If missing, reply exactly: \"I don't know based on the resume.\"")
 
 def overlap(a: str, b: str) -> bool:
-    return bool(set(re.findall(r"\w+", a.lower())) & set(re.findall(r"\w+", b.lower())))
+    return bool(set(re.findall(r"\w+", a.lower())) &
+                set(re.findall(r"\w+", b.lower())))
 
+# ───────── 2-bis. guard words & static answers ─────────────────────────
 SAFE = {"experience","project","certification","certifications","education",
         "skill","skills","summary","company","companies","role","linkedin",
         "website","blog","portfolio","architecture"}
@@ -75,34 +84,41 @@ STATIC_ANSWERS = {
     "linkedin": LINK_MD,
     "linked-in": LINK_MD,
     "blog": BLOG_MD,
-    "architecture": ARCH_NOTE
+    "architecture": ARCH_MD
 }
 
+# ───────── 2-ter. generator ───────────────────────────────────────────
 def generate(msg: str) -> str:
     lower_msg = msg.lower().strip()
+
+    # A. serve static responses verbatim
     for key, val in STATIC_ANSWERS.items():
         if key in lower_msg:
             return val
+
+    # B. resume-related check
     if not (SAFE & set(re.findall(r"\w+", lower_msg))):
         return "Please ask something related to my résumé."
+
+    # C. retrieve
     sims, ctxs = retrieve(msg)
     min_sim = 0.10 if len(msg.split()) < 3 else 0.25
     if max(sims) < min_sim:
         return "I don't know based on the resume."
+
+    # D. GPT-3.5-turbo
     ctx = "\n".join(ctxs)
-    try:
-        ans = client.chat.completions.create(
-            model=MODEL,
-            messages=[
-                {"role": "system", "content": SYSTEM},
-                {"role": "user",   "content": f"Context:\n{ctx}"},
-                {"role": "user",   "content": f"Question: {msg}"}
-            ],
-            max_tokens=256,
-            temperature=0.2
-        ).choices[0].message.content.strip()
-    except OpenAIError:
-        return "OpenAI API error. Please try again."
+    ans = client.chat.completions.create(
+        model=MODEL,
+        messages=[
+            {"role": "system", "content": SYSTEM},
+            {"role": "user",   "content": f"Context:\n{ctx}"},
+            {"role": "user",   "content": f"Question: {msg}"}
+        ],
+        max_tokens=256,
+        temperature=0.2
+    ).choices[0].message.content.strip()
+
     return ans if overlap(ans, ctx) else "I don't know based on the resume."
 
 # ───────── 3. Gradio UI ────────────────────────────────────────────────
@@ -118,10 +134,11 @@ with gr.Blocks(theme="soft") as demo:
             btns = [gr.Button(q) for q in quick]
 
         with gr.Column(scale=4):
-            chat  = gr.Chatbot(type="messages", label="Résumé Bot", height=520, render_markdown=True)
+            chat  = gr.Chatbot(type="messages", label="Résumé Bot", height=520)
             inp   = gr.Textbox(placeholder="Ask about my résumé…", show_label=False)
             state = gr.State([])
 
+    # ENTER
     def user_submit(msg, hist):
         ans  = generate(msg)
         hist = hist + [{"role":"user","content":msg},
@@ -130,6 +147,7 @@ with gr.Blocks(theme="soft") as demo:
 
     inp.submit(user_submit, [inp, state], [inp, chat, state])
 
+    # QUICK buttons
     def quick_send(hist, q):
         ans = generate(q)
         hist = hist + [{"role":"user","content":q},
@@ -140,4 +158,5 @@ with gr.Blocks(theme="soft") as demo:
         b.click(quick_send, [state, q], [chat, state])
 
 if __name__ == "__main__":
+    # When running in HF Spaces, share=True is ignored; safe to leave as-is.
     demo.launch(share=True)