Update app.py

app.py

@@ -9,7 +9,7 @@ from langchain_groq.chat_models import ChatGroq
 
 load_dotenv("Groq.txt")
 Groq_Token = os.environ["GROQ_API_KEY"]
-models = {"mixtral": "mixtral-8x7b-32768", "llama": "llama2-70b-4096", "gemma": "gemma-7b-it"}
+models = {"llama3":"llama3-70b-8192","mixtral": "mixtral-8x7b-32768", "llama2": "llama2-70b-4096", "gemma": "gemma-7b-it"}
 
 self_path = os.path.dirname(os.path.abspath(__file__))
 
@@ -39,7 +39,7 @@ st.markdown("<h2 class='title'>VayuBuddy</h2>", unsafe_allow_html=True)
 # inference_server = "https://api-inference.huggingface.co/models/codellama/CodeLlama-13b-hf"
 # inference_server = "https://api-inference.huggingface.co/models/pandasai/bamboo-llm"
 
-model_name = st.sidebar.selectbox("Select LLM:", ["mixtral", "llama", "gemma"])
+model_name = st.sidebar.selectbox("Select LLM:", ["llama3","mixtral", "llama2", "gemma"])
 
 questions = ('Custom Prompt',
              'Plot the monthly average PM2.5 for the year 2023.',
@@ -132,6 +132,7 @@ df["Timestamp"] = pd.to_datetime(df["Timestamp"])
                 query = f"""I have a pandas dataframe data of PM2.5 and PM10.
                 * Frequency of data is daily. 
                 * `pollution` generally means `PM2.5`.
+                * You already have df, so don't read the csv file 
                 * DOn't print, but save result in a variable `answer` and make it global.
                 * If result is a plot make it in tight layout, save it and save path in `answer`. Example: `answer='plot.png'`
                 * If result is not a plot, save it as a string in `answer`. Example: `answer='The city is Mumbai'`