update to the latest ft model

.gitattributes

@@ -32,5 +32,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.xz filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
+*.json filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 data/**/* filter=lfs diff=lfs merge=lfs -text

LLaMA-TOMMI-1.0/.gitattributes

@@ -0,0 +1,36 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

llm_files/llama-tommi-v0.35-weights/adapter_model.safetensors → LLaMA-TOMMI-1.0/adapter_config.json

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7b75475f5803beba2c32986066ae0167a5a3428879039a0084b0fc23fd9dc154
-size 111486576
+oid sha256:d8492657726200a0c539327a5050494d42a13da218beed20fbca268cf56622b0
+size 774

app.py

@@ -1,12 +1,9 @@
 import os
-import json
-import re
-import numpy as np
-import streamlit as st
 
-# from openai import OpenAI
-import random
+# Set the cache directory to persistent storage
+os.environ["HF_HOME"] = "/data/.cache/huggingface"
 
+import streamlit as st
 from utils.help import get_disclaimer
 from utils.format import sec_to_time, fix_latex, get_youtube_embed
 from utils.rag_utils import load_youtube_data, load_book_data, load_summary, fixed_knn_retrieval, get_random_question
@@ -33,24 +30,18 @@ st.markdown("""
     </style>
     """, unsafe_allow_html=True)
 
-
-# Set the cache directory to persistent storage
-os.environ["HF_HOME"] = "/data/.cache/huggingface"
-
-# # client = OpenAI(api_key=st.secrets["general"]["OpenAI_API"])
-# client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
-
+# ---------------------------------------
+# paths
 # ---------------------------------------
 base_path = "data/"
-
 base_model_path = "meta-llama/Llama-3.2-11B-Vision-Instruct"
-adapter_path = "./llm_files/llama-tommi-v0.35-weights/"
+adapter_path = "./LLaMA-TOMMI-1.0/"
 
+st.title(":red[AI University] / Finite Element Method")
+# st.markdown("### Finite Element Method")
+st.markdown(" Welcome to :red[AI University] — an AI-powered system for customized scientific course delivery, adapting to both instructors' teaching styles and students' learning needs. In this demo, we leverage the AI University system to provide expert answers to queries related to the :red[Finite Element Method (FEM)].")
 
-st.title(":red[AI University]")
-st.markdown("### Finite Element Methods")
-# st.markdown("### Based on Introduction to Finite Element Methods (FEM) by Prof. Krishna Garikipati")
-# st.markdown("##### [YouTube playlist of the FEM lectures](https://www.youtube.com/playlist?list=PLJhG_d-Sp_JHKVRhfTgDqbic_4MHpltXZ)")
+# st.markdown(":gray[Welcome to] :red[AI University]:gray[, developed at the] :red[University of Southern California]:gray[. This app leverages AI to provide expert answers to queries related to] :red[Finite Element Method (FEM)]:gray[.]")
 
 st.markdown(":gray[Welcome to] :red[AI University]:gray[, developed at the] :red[University of Southern California]:gray[. This app leverages AI to provide expert answers to queries related to] :red[Finite Element Methods (FEM)]:gray[.]")
 
@@ -108,11 +99,11 @@ with st.sidebar:
                 "Choose the LLM model",
                 ["gpt-4o-mini",
                  "gpt-3.5-turbo",
-                 "llama-tommi-0.35"],
+                 "LLaMA-TOMMI-1.0"],
                 key='a1model'
             )
 
-            if st.session_state.expert_model == "llama-tommi-0.35":
+            if st.session_state.expert_model == "LLaMA-TOMMI-1.0":
                 tommi_do_sample = st.toggle("Enable Sampling", value=False, key='tommi_sample')
 
                 if tommi_do_sample:
@@ -226,7 +217,7 @@ if submit_button_placeholder.button("AI Answer", type="primary"):
                     context += context_item['text'] + '\n\n'
             
             if use_expert_answer:
-                if st.session_state.expert_model  == "llama-tommi-0.35":
+                if st.session_state.expert_model  == "LLaMA-TOMMI-1.0":
                     if 'tommi_model' not in st.session_state:
                         tommi_model, tommi_tokenizer = load_fine_tuned_model(adapter_path, base_model_path)
                         st.session_state.tommi_model = tommi_model

llm_files/llama-tommi-v0.35-weights/adapter_config.json

@@ -1,37 +0,0 @@
-{
-  "alpha_pattern": {},
-  "auto_mapping": null,
-  "base_model_name_or_path": "",
-  "bias": "none",
-  "eva_config": null,
-  "exclude_modules": null,
-  "fan_in_fan_out": false,
-  "inference_mode": true,
-  "init_lora_weights": true,
-  "layer_replication": null,
-  "layers_pattern": null,
-  "layers_to_transform": null,
-  "loftq_config": {},
-  "lora_alpha": 60,
-  "lora_bias": false,
-  "lora_dropout": 0.1,
-  "megatron_config": null,
-  "megatron_core": "megatron.core",
-  "modules_to_save": null,
-  "peft_type": "LORA",
-  "r": 17,
-  "rank_pattern": {},
-  "revision": null,
-  "target_modules": [
-    "down_proj",
-    "q_proj",
-    "gate_proj",
-    "v_proj",
-    "o_proj",
-    "k_proj",
-    "up_proj"
-  ],
-  "task_type": "CAUSAL_LM",
-  "use_dora": false,
-  "use_rslora": false
-}

special_tokens_map.json

@@ -1,23 +1,3 @@
-{
-  "bos_token": {
-    "content": "<|begin_of_text|>",
-    "lstrip": false,
-    "normalized": false,
-    "rstrip": false,
-    "single_word": false
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-  "eos_token": {
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-    "lstrip": false,
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-    "single_word": false
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-  "pad_token": {
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-    "lstrip": false,
-    "normalized": false,
-    "rstrip": false,
-    "single_word": false
-  }
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:b39edb3c7f3f4c45d30b3a98822e470e4d15c3767c28040c44949763404a148d
+size 343

tokenizer_config.json

@@ -1,2071 +1,3 @@
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-  "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n    {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n    {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n    {%- if strftime_now is defined %}\n        {%- set date_string = strftime_now(\"%d %b %Y\") %}\n    {%- else %}\n        {%- set date_string = \"26 Jul 2024\" %}\n    {%- endif %}\n{%- endif %}\n{%- if not tools is defined %}\n    {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n    {%- set system_message = messages[0]['content']|trim %}\n    {%- set messages = messages[1:] %}\n    {%- set user_supplied_system_message = true %}\n{%- else %}\n    {%- set system_message = \"\" %}\n    {%- set user_supplied_system_message = false %}\n{%- endif %}\n\n{#- Find out if there are any images #}\n{% set image_ns = namespace(has_images=false) %}      \n{%- for message in messages %}\n    {%- for content in message['content'] %}\n        {%- if content['type'] == 'image' %}\n            {%- set image_ns.has_images = true %}\n        {%- endif %}\n    {%- endfor %}\n{%- endfor %}\n\n{#- System message if there are no images, or if the user supplied one #}\n{%- if user_supplied_system_message or not image_ns.has_images %}\n    {{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n    {%- if tools is not none %}\n        {{- \"Environment: ipython\\n\" }}\n    {%- endif %}\n    {{- \"Cutting Knowledge Date: December 2023\\n\" }}\n    {{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n    {%- if tools is not none and not tools_in_user_message %}\n        {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n        {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n        {{- \"Do not use variables.\\n\\n\" }}\n        {%- for t in tools %}\n            {{- t | tojson(indent=4) }}\n            {{- \"\\n\\n\" }}\n        {%- endfor %}\n    {%- endif %}\n    {{- system_message }}\n    {{- \"<|eot_id|>\" }}\n{%- endif %}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n    {#- Extract the first user message so we can plug it in here #}\n    {%- if messages | length != 0 %}\n        {%- set first_user_message = messages[0]['content']|trim %}\n        {%- set messages = messages[1:] %}\n    {%- else %}\n        {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n    {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n    {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n    {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n    {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n    {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n' }}\n        {%- if message['content'] is string %}\n            {{- message['content'] }}\n        {%- else %}\n            {%- for content in message['content'] %}\n                {%- if content['type'] == 'image' %}\n                    {{- '<|image|>' }}\n                {%- elif content['type'] == 'text' %}\n                    {{- content['text'] }}\n                {%- endif %}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|eot_id|>' }}\n    {%- elif 'tool_calls' in message %}\n        {%- if not message.tool_calls|length == 1 %}\n            {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n        {%- endif %}\n        {%- set tool_call = message.tool_calls[0].function %}\n        {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n        {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n        {{- '\"parameters\": ' }}\n        {{- tool_call.arguments | tojson }}\n        {{- \"}\" }}\n        {{- \"<|eot_id|>\" }}\n    {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n        {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n        {%- if message.content is mapping or message.content is iterable %}\n            {{- message.content | tojson }}\n        {%- else %}\n            {{- message.content }}\n        {%- endif %}\n        {{- \"<|eot_id|>\" }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n",
-  "clean_up_tokenization_spaces": true,
-  "eos_token": "<|eot_id|>",
-  "model_input_names": [
-    "input_ids",
-    "attention_mask"
-  ],
-  "model_max_length": 131072,
-  "pad_token": "<|finetune_right_pad_id|>",
-  "tokenizer_class": "PreTrainedTokenizerFast"
-}
+version https://git-lfs.github.com/spec/v1
+oid sha256:368d355841b584df5e764e446852d4755116b3e596f748c50b6e02729e1a67fb
+size 55837

utils/llama_utils.py

@@ -1,7 +1,11 @@
+import os
 import torch
 from transformers import BitsAndBytesConfig, AutoModelForCausalLM, PreTrainedTokenizerFast
 from peft import PeftModel
 
+# Set the cache directory to persistent storage
+os.environ["HF_HOME"] = "/data/.cache/huggingface"
+
 #-----------------------------------------
 # Quantization Config
 #-----------------------------------------