Update chatbot.py

chatbot.py

@@ -1,6 +1,7 @@
 import streamlit as st
-from openai import OpenAI
+from langchain_openai import ChatOpenAI
 from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.output_parsers import StrOutputParser
 from html import escape
 import edge_tts
 import asyncio
@@ -9,12 +10,13 @@ import uuid
 
 OPENROUTER_API_KEY = os.getenv("OPENROUTER_API_KEY")
 
-
 class CodeAssistantBot:
     def __init__(self):
-        self.client = OpenAI(
+        self.model = ChatOpenAI(
+            model="meta-llama/llama-3-70b-instruct",
             base_url="https://openrouter.ai/api/v1",
-            api_key=OPENROUTER_API_KEY
+            api_key=OPENROUTER_API_KEY,
+            temperature=0.6
         )
 
         self.analysis_prompt = ChatPromptTemplate.from_messages([
@@ -26,12 +28,10 @@ class CodeAssistantBot:
              "Code: {code}\nInput: {input}\nOutput: {output}\nError: {error}\n"
              "Summary: {summary}\nRecent: {recent}\nQuestion: {question}")
         ])
-
         self.summary_prompt = ChatPromptTemplate.from_messages([
             ("system", "Summarize key technical points from the conversation so far."),
             ("user", "Conversation: {conversation}")
         ])
-
         self.voice_prompt = ChatPromptTemplate.from_messages([
             ("system",
              "You are a friendly narrator voice bot. Given a technical answer and its context,"
@@ -43,8 +43,10 @@ class CodeAssistantBot:
         ])
 
     def analyze_code(self, code, input, output, error, question, summary="", history=None):
+        parser = StrOutputParser()
         recent = "\n".join([f"User: {q}\nBot: {a}" for q, a in (history or [])[-4:]])
-        prompt = self.analysis_prompt.format_messages({
+        chain = self.analysis_prompt | self.model | parser
+        return chain.invoke({
             'code': code,
             'input': input,
             'output': output,
@@ -53,14 +55,11 @@ class CodeAssistantBot:
             'recent': recent,
             'question': question
         })
-        completion = self.client.chat.completions.create(
-            model="qwen/qwen3-coder:free",
-            messages=[m.dict() for m in prompt]
-        )
-        return completion.choices[0].message.content.strip()
 
     def narrate_response(self, code, input, output, error, answer, summary=""):
-        prompt = self.voice_prompt.format_messages({
+        parser = StrOutputParser()
+        narration_chain = self.voice_prompt | self.model | parser
+        return narration_chain.invoke({
             'code': code,
             'input': input,
             'output': output,
@@ -68,29 +67,12 @@ class CodeAssistantBot:
             'summary': summary,
             'answer': answer
         })
-        completion = self.client.chat.completions.create(
-            model="qwen/qwen3-coder:free",
-            messages=[m.dict() for m in prompt]
-        )
-        return completion.choices[0].message.content.strip()
-
-    def summarize_conversation(self, conversation):
-        prompt = self.summary_prompt.format_messages({
-            'conversation': conversation
-        })
-        completion = self.client.chat.completions.create(
-            model="qwen/qwen3-coder:free",
-            messages=[m.dict() for m in prompt]
-        )
-        return completion.choices[0].message.content.strip()
-
 
 async def text_to_speech(text, filename):
     voice = "fr-FR-VivienneMultilingualNeural"
     communicate = edge_tts.Communicate(text, voice)
     await communicate.save(filename)
 
-
 def render_chatbot(code, input, output, error):
     st.markdown("""
     <style>
@@ -139,11 +121,11 @@ def render_chatbot(code, input, output, error):
         response = bot.analyze_code(code, input, output, error, question, summary, history)
         st.session_state.conversation.append((question, response))
         st.session_state.chat_display_count = 5
-
         if len(st.session_state.conversation) >= 3:
             try:
                 full_chat = "\n".join([f"User: {q}\nBot: {a}" for q, a in st.session_state.conversation[-10:]])
-                st.session_state.chat_summary = bot.summarize_conversation(full_chat)
+                summarizer = bot.summary_prompt | bot.model | StrOutputParser()
+                st.session_state.chat_summary = summarizer.invoke({'conversation': full_chat})
             except:
                 pass
 
@@ -172,7 +154,6 @@ def render_chatbot(code, input, output, error):
         st.markdown(f'<div class="chat-message bot-message">{formatted}</div>', unsafe_allow_html=True)
 
         audio_file = st.session_state.narrated_audio.get((q, a))
-
         if not audio_file:
             if st.button("🔊 Narrate", key=f"narrate_{idx}"):
                 status_placeholder = st.empty()