Update app.py

app.py

@@ -18,6 +18,7 @@ _dash_renderer._set_react_version("18.2.0")
 import plotly.io as pio
 from langchain_community.llms import HuggingFaceEndpoint
 from langchain_core.prompts import ChatPromptTemplate, PromptTemplate
+from langchain_openai import ChatOpenAI
 from langchain.schema.output_parser import StrOutputParser
 from pinecone import Pinecone
 from bs4 import BeautifulSoup
@@ -1461,12 +1462,13 @@ def run_chatbot(n_clicks, n_submit, user_input, chat_history, array_value):
     
     os.environ['HUGGINGFACEHUB_API_TOKEN'] = os.environ['HUGGINGFACEHUB_API_TOKEN']
     #repo_id = "mistralai/Mistral-7B-Instruct-v0.3"
-    repo_id = "mistralai/Mistral-7B-Instruct-v0.2"
+    #repo_id = "mistralai/Mistral-7B-Instruct-v0.2"
     #repo_id = "microsoft/Phi-3.5-mini-instruct"
     #mistral_url = "https://api-inference.huggingface.co/models/mistralai/Mixtral-8x22B-Instruct-v0.1"
-    llm = HuggingFaceEndpoint(
-        repo_id=repo_id, task="text2text-generation", max_new_tokens=8000, temperature=0.7, streaming=True
-    )
+    #llm = HuggingFaceEndpoint(
+    #    repo_id=repo_id, task="text2text-generation", max_new_tokens=8000, temperature=0.7, streaming=True
+    #)
+    llm = ChatOpenAI(model_name="mistralai/Mistral-Small-3.1-24B-Instruct-2503", base_url=os.environ['BASEURL_RENNES_API_KEY'], api_key=os.environ['ENDPOINT_RENNES_API_KEY'])
     model_output = ""
     chain = prompt | llm | StrOutputParser()
     for s in chain.stream({"question":"D'après le contexte, " + user_input,"context":context_p}):