Update chatbot_rag.py

chatbot_rag.py

@@ -6,8 +6,9 @@ from langchain.prompts import PromptTemplate
 from langchain_core.runnables import RunnablePassthrough
 from langchain_core.output_parsers import StrOutputParser
 import traceback
-
+import re
 import os
+
 from huggingface_hub import login
 token = os.getenv("HF_TOKEN")
 print("🔑 HF_TOKEN available?", token is not None)
@@ -48,14 +49,18 @@ def build_qa():
     )
     
     pipe = pipeline(
-        "text-generation",
-        model=model,
-        tokenizer=tokenizer,
-        max_new_tokens=256,
-        temperature=0.2,
-        do_sample=True,
-        return_full_text=False   # 🚀 only return new text, avoids messy context echoes
+    "text-generation",
+    model=model,
+    tokenizer=tokenizer,
+    max_new_tokens=128,
+    temperature=0.2,      # keeps answers deterministic but less rigid than 0
+    do_sample=True,       # allow some randomness
+    top_p=0.9,            # nucleus sampling to avoid loops
+    repetition_penalty=1.2,  # 🚀 penalize repeats
+    eos_token_id=tokenizer.eos_token_id,  # stop at EOS
+    return_full_text=False
     )
+
     
     llm = HuggingFacePipeline(pipeline=pipe)
 
@@ -81,11 +86,28 @@ def build_qa():
     def format_docs(docs):
         return "\n".join(doc.page_content for doc in docs)
 
+
     def hf_to_str(x):
-        """Convert Hugging Face pipeline output to plain string"""
+        """Convert Hugging Face pipeline output to plain string (clean + generalized)."""
         if isinstance(x, list) and "generated_text" in x[0]:
-            return x[0]["generated_text"]
-        return str(x)
+            text = x[0]["generated_text"]
+        else:
+            text = str(x)
+    
+        # 1. Remove markdown/code artifacts
+        text = text.replace("```", "").replace("#", "").strip()
+    
+        # 2. Normalize whitespace & line breaks
+        text = re.sub(r"\s+", " ", text)
+    
+        # 3. Remove duplicated consecutive phrases (up to ~5 words repeated)
+        text = re.sub(r"\b(\w+\s+){1,5}(\1){2,}", r"\1", text)
+    
+        # 4. Trim leading/trailing junk
+        text = text.strip(" .,-\n\t")
+    
+        return text
+
 
     # 7. RAG chain
     rag_chain = (