Replacing groq with open roter

chatbot.py

@@ -1,20 +1,22 @@
 import streamlit as st
-from groq import Groq
-from langchain_groq import ChatGroq
+from openai import OpenAI
 from langchain_core.prompts import ChatPromptTemplate
-from langchain_core.output_parsers import StrOutputParser
 from html import escape
 import edge_tts
 import asyncio
 import os
 import uuid
 
-GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+OPENROUTER_API_KEY = os.getenv("OPENROUTER_API_KEY")
+
 
 class CodeAssistantBot:
     def __init__(self):
-        self.client = Groq(api_key=GROQ_API_KEY)
-        self.model = ChatGroq(model="llama-3.3-70b-versatile", temperature=0.6)
+        self.client = OpenAI(
+            base_url="https://openrouter.ai/api/v1",
+            api_key=OPENROUTER_API_KEY
+        )
+
         self.analysis_prompt = ChatPromptTemplate.from_messages([
             ("system",
              "You are a skilled coding assistant. Use the following context and user input to help."
@@ -24,10 +26,12 @@ 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,"
@@ -39,10 +43,8 @@ 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:]])
-        chain = self.analysis_prompt | self.model | parser
-        return chain.invoke({
+        prompt = self.analysis_prompt.format_messages({
             'code': code,
             'input': input,
             'output': output,
@@ -51,11 +53,14 @@ 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=""):
-        parser = StrOutputParser()
-        narration_chain = self.voice_prompt | self.model | parser
-        return narration_chain.invoke({
+        prompt = self.voice_prompt.format_messages({
             'code': code,
             'input': input,
             'output': output,
@@ -63,12 +68,29 @@ 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>
@@ -117,11 +139,11 @@ 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:]])
-                summarizer = bot.summary_prompt | bot.model | StrOutputParser()
-                st.session_state.chat_summary = summarizer.invoke({'conversation': full_chat})
+                st.session_state.chat_summary = bot.summarize_conversation(full_chat)
             except:
                 pass
 
@@ -149,7 +171,6 @@ def render_chatbot(code, input, output, error):
         formatted = format_response(a)
         st.markdown(f'<div class="chat-message bot-message">{formatted}</div>', unsafe_allow_html=True)
 
-        # Check if already narrated
         audio_file = st.session_state.narrated_audio.get((q, a))
 
         if not audio_file: