diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
new file mode 100644
index 0000000..b55caee
--- /dev/null
+++ b/.pre-commit-config.yaml
@@ -0,0 +1,21 @@
+repos:
+  - repo: https://github.com/psf/black
+    rev: 23.3.0
+    hooks:
+      - id: black
+        language_version: python3.11
+  - repo: https://github.com/pycqa/isort
+    rev: 5.12.0  # Use the ref you want to point at
+    hooks:
+      - id: isort
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v4.0.1
+    hooks:
+      - id: trailing-whitespace
+      - id: end-of-file-fixer
+      - id: check-yaml
+      - id: check-added-large-files
+  - repo: https://github.com/hadialqattan/pycln
+    rev: v2.1.5
+    hooks:
+      - id: pycln
diff --git a/Pipfile b/Pipfile
new file mode 100644
index 0000000..668a63b
--- /dev/null
+++ b/Pipfile
@@ -0,0 +1,34 @@
+[[source]]
+url = "https://pypi.org/simple"
+verify_ssl = true
+name = "pypi"
+
+[packages]
+streamlit = ">=1.3.0"
+pypdf2 = ">=1.26.0"
+pypdf = ">=0.0.1"
+langchain = ">=0.0.188"
+openai = ">=0.27.0"
+faiss-cpu = ">=1.7.1.post2"
+pinecone-client = ">=0.0.8"
+pandas = ">=1.3.4"
+tiktoken = ">=0.0.1"
+gsheetsdb = ">=0.1.13.1"
+shillelagh = ">=1.2.4"
+gradio-tools = ">=0.0.9"
+gspread = ">=5.7.2"
+config = ">=0.5.1"
+google-api-python-client = ">=2.86.0"
+pymupdf = ">=1.22.3"
+python-dotenv = ">=1.0.0"
+colorama = ">=0.4.6"
+bs4 = ">=0.0.1"
+black = "*"
+isort = "*"
+pycln = "*"
+pre-commit = "*"
+
+[dev-packages]
+
+[requires]
+python_version = "3.11"
diff --git a/Pipfile.lock b/Pipfile.lock
new file mode 100644
index 0000000..3edf585
--- /dev/null
+++ b/Pipfile.lock
@@ -0,0 +1,2184 @@
+{
+    "_meta": {
+        "hash": {
+            "sha256": "329a9ff8748a237a5420561577803bc91ee6ac70b4cc926f303621dd656c5f37"
+        },
+        "pipfile-spec": 6,
+        "requires": {
+            "python_version": "3.11"
+        },
+        "sources": [
+            {
+                "name": "pypi",
+                "url": "https://pypi.org/simple",
+                "verify_ssl": true
+            }
+        ]
+    },
+    "default": {
+        "aiohttp": {
+            "hashes": [
+                "sha256:03543dcf98a6619254b409be2d22b51f21ec66272be4ebda7b04e6412e4b2e14",
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+                "sha256:0a63f03189a6fa7c900226e3ef5ba4d3bd047e18f445e69adbd65af433add5a2",
+                "sha256:10c8cefcff98fd9168cdd86c4da8b84baaa90bf2da2269c6161984e6737bf23e",
+                "sha256:147ae376f14b55f4f3c2b118b95be50a369b89b38a971e80a17c3fd623f280c9",
+                "sha256:176a64b24c0935869d5bbc4c96e82f89f643bcdf08ec947701b9dbb3c956b7dd",
+                "sha256:17b79c2963db82086229012cff93ea55196ed31f6493bb1ccd2c62f1724324e4",
+                "sha256:1a45865451439eb320784918617ba54b7a377e3501fb70402ab84d38c2cd891b",
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+            "version": "==3.8.4"
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+        "aiosignal": {
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+                "sha256:6a5883464143ab3ae9ba68daae8e7c5c95b969462bbe42e2464d60e7e2698368",
+                "sha256:6e7221580dc1db478464cfeef9b03b95c5852cc22894e418562997df0d074ccc",
+                "sha256:75df5ef94c3fdc393c6b19d80e6ef1ecc9ae2f4263c09cacb178d871c02a5ba9",
+                "sha256:783185c75c12a017cc345015ea359cc801c3b29a2966c2655cd12b233bf5a2be",
+                "sha256:822b30a0f22e588b32d3120f6d41e4ed021806418b4c9f0bc3048b8c8cb3f92a",
+                "sha256:8288d7cd28f8119b07dd49b7230d6b4562f9b61ee9a4ab02221060d21136be80",
+                "sha256:82aa6264b36c50acfb2424ad5ca537a2060ab6de158a5bd2a72a032cc75b9eb8",
+                "sha256:832b7e711027c114d79dffb92576acd1bd2decc467dec60e1cac96912602d0e6",
+                "sha256:838162460b3a08987546e881a2bfa573960bb559dfa739e7800ceeec92e64417",
+                "sha256:83fcc480d7549ccebe9415d96d9263e2d4226798c37ebd18c930fce43dfb9574",
+                "sha256:84e0b1599334b1e1478db01b756e55937d4614f8654311eb26012091be109d59",
+                "sha256:891c0e3ec5ec881541f6c5113d8df0315ce5440e244a716b95f2525b7b9f3608",
+                "sha256:8c2ad583743d16ddbdf6bb14b5cd76bf43b0d0006e918809d5d4ddf7bde8dd82",
+                "sha256:8c56986609b057b4839968ba901944af91b8e92f1725d1a2d77cbac6972b9ed1",
+                "sha256:8ea48e0a2f931064469bdabca50c2f578b565fc446f302a79ba6cc0ee7f384d3",
+                "sha256:8ec53a0ea2a80c5cd1ab397925f94bff59222aa3cf9c6da938ce05c9ec20428d",
+                "sha256:95d2ecefbcf4e744ea952d073c6922e72ee650ffc79028eb1e320e732898d7e8",
+                "sha256:9b3152f2f5677b997ae6c804b73da05a39daa6a9e85a512e0e6823d81cdad7cc",
+                "sha256:9bf345c3a4f5ba7f766430f97f9cc1320786f19584acc7086491f45524a551ac",
+                "sha256:a60347f234c2212a9f0361955007fcf4033a75bf600a33c88a0a8e91af77c0e8",
+                "sha256:a74dcbfe780e62f4b5a062714576f16c2f3493a0394e555ab141bf0d746bb955",
+                "sha256:a83503934c6273806aed765035716216cc9ab4e0364f7f066227e1aaea90b8d0",
+                "sha256:ac9bb4c5ce3975aeac288cfcb5061ce60e0d14d92209e780c93954076c7c4367",
+                "sha256:aff634b15beff8902d1f918012fc2a42e0dbae6f469fce134c8a0dc51ca423bb",
+                "sha256:b03917871bf859a81ccb180c9a2e6c1e04d2f6a51d953e6a5cdd70c93d4e5a2a",
+                "sha256:b124e2a6d223b65ba8768d5706d103280914d61f5cae3afbc50fc3dfcc016623",
+                "sha256:b25322201585c69abc7b0e89e72790469f7dad90d26754717f3310bfe30331c2",
+                "sha256:b7232f8dfbd225d57340e441d8caf8652a6acd06b389ea2d3222b8bc89cbfca6",
+                "sha256:b8cc1863402472f16c600e3e93d542b7e7542a540f95c30afd472e8e549fc3f7",
+                "sha256:b9a4e67ad7b646cd6f0938c7ebfd60e481b7410f574c560e455e938d2da8e0f4",
+                "sha256:be6b3fdec5c62f2a67cb3f8c6dbf56bbf3f61c0f046f84645cd1ca73532ea051",
+                "sha256:bf74d08542c3a9ea97bb8f343d4fcbd4d8f91bba5ec9d5d7f792dbe727f88938",
+                "sha256:c027a6e96ef77d401d8d5a5c8d6bc478e8042f1e448272e8d9752cb0aff8b5c8",
+                "sha256:c0c77533b5ed4bcc38e943178ccae29b9bcf48ffd1063f5821192f23a1bd27b9",
+                "sha256:c1012fa63eb6c032f3ce5d2171c267992ae0c00b9e164efe4d73db818465fac3",
+                "sha256:c3a53ba34a636a256d767c086ceb111358876e1fb6b50dfc4d3f4951d40133d5",
+                "sha256:d4e2c6d555e77b37288eaf45b8f60f0737c9efa3452c6c44626a5455aeb250b9",
+                "sha256:de119f56f3c5f0e2fb4dee508531a32b069a5f2c6e827b272d1e0ff5ac040333",
+                "sha256:e65610c5792870d45d7b68c677681376fcf9cc1c289f23e8e8b39c1485384185",
+                "sha256:e9fdc7ac0d42bc3ea78818557fab03af6181e076a2944f43c38684b4b6bed8e3",
+                "sha256:ee4afac41415d52d53a9833ebae7e32b344be72835bbb589018c9e938045a560",
+                "sha256:f364d3480bffd3aa566e886587eaca7c8c04d74f6e8933f3f2c996b7f09bee1b",
+                "sha256:f3b078dbe227f79be488ffcfc7a9edb3409d018e0952cf13f15fd6512847f3f7",
+                "sha256:f4e2d08f07a3d7d3e12549052eb5ad3eab1c349c53ac51c209a0e5991bbada78",
+                "sha256:f7a3d8146575e08c29ed1cd287068e6d02f1c7bdff8970db96683b9591b86ee7"
+            ],
+            "markers": "python_version >= '3.7'",
+            "version": "==1.9.2"
+        },
+        "zipp": {
+            "hashes": [
+                "sha256:112929ad649da941c23de50f356a2b5570c954b65150642bccdd66bf194d224b",
+                "sha256:48904fc76a60e542af151aded95726c1a5c34ed43ab4134b597665c86d7ad556"
+            ],
+            "markers": "python_version >= '3.7'",
+            "version": "==3.15.0"
+        }
+    },
+    "develop": {}
+}
diff --git a/docs/contribution_guidelines.md b/docs/contribution_guidelines.md
index b52993e..ac02999 100644
--- a/docs/contribution_guidelines.md
+++ b/docs/contribution_guidelines.md
@@ -25,9 +25,10 @@ Follow these steps to contribute code through a pull request:
 3. Create a new branch for your changes: `git checkout -b my-branch`.
 4. Make your desired changes or additions to the codebase.
 5. Test your changes to ensure they work as intended.
-6. Commit your changes: `git commit -m "Add feature or fix"`.
-7. Push your changes to your forked repository: `git push origin my-branch`.
-8. Open a pull request from your forked repository to the main Nuggt repository.
+6. Run the pre-commit hook to ensure your code adheres to the project's coding conventions: `pre-commit run --all-files`.
+7. Commit your changes: `git commit -m "Add feature or fix"`.
+8. Push your changes to your forked repository: `git push origin my-branch`.
+9. Open a pull request from your forked repository to the main Nuggt repository.
 
 Please ensure that your code adheres to the project's coding conventions. It's also helpful to include a clear and concise description of your changes in the pull request.
 
diff --git a/nuggt-release/browse.py b/nuggt-release/browse.py
index 5c33cd4..1b909d7 100644
--- a/nuggt-release/browse.py
+++ b/nuggt-release/browse.py
@@ -1,25 +1,37 @@
-#This file is taken from https://github.com/Significant-Gravitas/Auto-GPT
+# This file is taken from https://github.com/Significant-Gravitas/Auto-GPT
 
 import requests
 from bs4 import BeautifulSoup
 
+
 # Define and check for local file address prefixes
 def check_local_file_access(url):
-    local_prefixes = ['file:///', 'file://localhost', 'http://localhost', 'https://localhost']
+    local_prefixes = [
+        "file:///",
+        "file://localhost",
+        "http://localhost",
+        "https://localhost",
+    ]
     return any(url.startswith(prefix) for prefix in local_prefixes)
 
+
 def scrape_text(url):
     """Scrape text from a webpage"""
     # Most basic check if the URL is valid:
-    if not url.startswith('http'):
+    if not url.startswith("http"):
         return "Error: Invalid URL"
 
     # Restrict access to local files
     if check_local_file_access(url):
         return "Error: Access to local files is restricted"
-    
+
     try:
-        response = requests.get(url, headers={"User-Agent":"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.4103.97 Safari/537.36"})
+        response = requests.get(
+            url,
+            headers={
+                "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.4103.97 Safari/537.36"
+            },
+        )
     except requests.exceptions.RequestException as e:
         return "Error: " + str(e)
 
@@ -35,7 +47,6 @@ def scrape_text(url):
     text = soup.get_text()
     lines = (line.strip() for line in text.splitlines())
     chunks = (phrase.strip() for line in lines for phrase in line.split("  "))
-    text = '\n'.join(chunk for chunk in chunks if chunk)
+    text = "\n".join(chunk for chunk in chunks if chunk)
 
     return text
-
diff --git a/nuggt-release/nuggt.py b/nuggt-release/nuggt.py
index 5fd539d..231592d 100644
--- a/nuggt-release/nuggt.py
+++ b/nuggt-release/nuggt.py
@@ -1,16 +1,16 @@
-import streamlit as st
-import openai
-import re
-import os
 import glob
-import requests
-from colorama import Fore
+import os
+import re
 import tempfile
-from helper.sidebar_functions import sidebar_logo
-from dotenv import load_dotenv
+
+import openai
+import requests
+import streamlit as st
 import toml
 import tool
-import openai
+from colorama import Fore
+from dotenv import load_dotenv
+from helper.sidebar_functions import sidebar_logo
 
 load_dotenv()
 config = toml.load("./.streamlit/config.toml")
@@ -37,47 +37,118 @@
 count = 0
 global tmp_path
 
+
 def save_to_sheets(userInput, outputFormat, feedback, logs):
     url = "https://docs.google.com/forms/d/1PveqD5klH2geQvI3nlkI6l-chBctNz6O-jmpwSO2FYk/formResponse"
 
     data = {
-        'entry.2013000889': userInput,
-        'entry.586411750': outputFormat,
-        'entry.1340987871': feedback,
-        'entry.697215161': logs
+        "entry.2013000889": userInput,
+        "entry.586411750": outputFormat,
+        "entry.1340987871": feedback,
+        "entry.697215161": logs,
     }
     try:
-        requests.post(url, data = data)
+        requests.post(url, data=data)
     except:
         print("Error!")
 
+
 def is_file(filename):
     return os.path.isfile(filename)
 
+
 def extract_variables(input_string):
-    pattern = r'\{(.*?)\}'
+    pattern = r"\{(.*?)\}"
     variables = re.findall(pattern, input_string)
     return variables
 
+
 def get_tool_info(tool_name):
     tools = {
-        "python": {"type": "tool", "name": "python", "use": "Use this to execute python code. Display your results using the print funçction.", "input": "Input should be a valid python code. Ensure proper indentation", "function": tool.python},
-        "search": {"type": "tool", "name": "search", "use": "Use this tool to get information from the internet", "input": "Input should be the query you want to search", "function": tool.search},
-        "video_tool": {"type": "tool", "name": "video_tool", "use": "useful when you want to retrieve information from a video", "input": "The input should be a JSON of the following format:\n{\"video_url\": \"URL of the video\", \"information\": \"the information you want to retrieve from the video\"}", "function": tool.video_tool},
-        "llm": {"type": "tool", "name": "llm", "use": "useful to get answer from an llm model", "input": "The input should be in the following format:\n{\"prompt\": \"The prompt to initialise the LLM\", \"input\": \"The input to the LLM\"}", "function": tool.custom_llm},
-        "stable_diffusion": {"type": "tool", "name": "stable_diffusion", "use": "Use this to generate an image from a prompt. This tool will return the path to the generated image.", "input": "the prompt to generate the image", "function": tool.stable_diffusion},
-        "generate_video": {"type": "tool", "name": "generate_video", "use": "Use this to generate a video from a prompt. This tool will return the path to the generated video.", "input": "the prompt to generate the video", "function": tool.generate_video},
-        "image_caption": {"type": "tool", "name": "image_caption", "use": "Use this to caption an image.", "input": "the path to the image", "function": tool.image_caption},
-        "display" : {"type": "tool", "name": "display", "use": "Use this to display things using streamlit", "input": "The input should be a valid python code using the streamlit library", "function": tool.display},
-        "browse_website": {"type": "tool", "name": "browse_website", "use": "Use this to get information from a website", "input": "The input should be in the following format:\n{\"url\": \"URL of the website\", \"information\": \"the information you want to retrieve from the website\"}", "function": tool.browse_website},
-        "google": {"type": "tool", "name": "google", "use": "use it to get google results", "input": "The input should be a google query", "function": tool.google},
-        "document_tool": {"type": "tool", "name": "document_tool", "use": "useful when you want to retrieve information from a document", "input": "The input should be a JSON of the following format:\n{\"document_name\": \"name of the document you want to retrieve information from\", \"information\": \"the information you want to retrieve from the document\"}", "function": tool.document_tool},
-        }
+        "python": {
+            "type": "tool",
+            "name": "python",
+            "use": "Use this to execute python code. Display your results using the print funçction.",
+            "input": "Input should be a valid python code. Ensure proper indentation",
+            "function": tool.python,
+        },
+        "search": {
+            "type": "tool",
+            "name": "search",
+            "use": "Use this tool to get information from the internet",
+            "input": "Input should be the query you want to search",
+            "function": tool.search,
+        },
+        "video_tool": {
+            "type": "tool",
+            "name": "video_tool",
+            "use": "useful when you want to retrieve information from a video",
+            "input": 'The input should be a JSON of the following format:\n{"video_url": "URL of the video", "information": "the information you want to retrieve from the video"}',
+            "function": tool.video_tool,
+        },
+        "llm": {
+            "type": "tool",
+            "name": "llm",
+            "use": "useful to get answer from an llm model",
+            "input": 'The input should be in the following format:\n{"prompt": "The prompt to initialise the LLM", "input": "The input to the LLM"}',
+            "function": tool.custom_llm,
+        },
+        "stable_diffusion": {
+            "type": "tool",
+            "name": "stable_diffusion",
+            "use": "Use this to generate an image from a prompt. This tool will return the path to the generated image.",
+            "input": "the prompt to generate the image",
+            "function": tool.stable_diffusion,
+        },
+        "generate_video": {
+            "type": "tool",
+            "name": "generate_video",
+            "use": "Use this to generate a video from a prompt. This tool will return the path to the generated video.",
+            "input": "the prompt to generate the video",
+            "function": tool.generate_video,
+        },
+        "image_caption": {
+            "type": "tool",
+            "name": "image_caption",
+            "use": "Use this to caption an image.",
+            "input": "the path to the image",
+            "function": tool.image_caption,
+        },
+        "display": {
+            "type": "tool",
+            "name": "display",
+            "use": "Use this to display things using streamlit",
+            "input": "The input should be a valid python code using the streamlit library",
+            "function": tool.display,
+        },
+        "browse_website": {
+            "type": "tool",
+            "name": "browse_website",
+            "use": "Use this to get information from a website",
+            "input": 'The input should be in the following format:\n{"url": "URL of the website", "information": "the information you want to retrieve from the website"}',
+            "function": tool.browse_website,
+        },
+        "google": {
+            "type": "tool",
+            "name": "google",
+            "use": "use it to get google results",
+            "input": "The input should be a google query",
+            "function": tool.google,
+        },
+        "document_tool": {
+            "type": "tool",
+            "name": "document_tool",
+            "use": "useful when you want to retrieve information from a document",
+            "input": 'The input should be a JSON of the following format:\n{"document_name": "name of the document you want to retrieve information from", "information": "the information you want to retrieve from the document"}',
+            "function": tool.document_tool,
+        },
+    }
     return tools[tool_name]
 
+
 def nuggt(user_input, output_format, variables):
     tools = []
-    tools_description = "\n\nYou can use the following actions:\n\n" 
+    tools_description = "\n\nYou can use the following actions:\n\n"
     value_dict = {}
     uploaded_file = None
     form_user = st.form("user-form")
@@ -88,7 +159,7 @@ def nuggt(user_input, output_format, variables):
             if choice not in value_dict.keys():
                 temp = form_user.text_input(f"Enter value for {choice}: ")
 
-                if (is_file(temp)):
+                if is_file(temp):
                     new_file_path = os.path.join(os.getcwd(), temp)
                     print(new_file_path)
 
@@ -97,51 +168,67 @@ def nuggt(user_input, output_format, variables):
                 value_dict[choice] = temp
             else:
                 replace_string = "{" + variable + "}"
-                user_input = user_input.replace(replace_string, "<" + value_dict[choice] + ">")
+                user_input = user_input.replace(
+                    replace_string, "<" + value_dict[choice] + ">"
+                )
 
         elif type == "upload":
             if choice not in value_dict.keys():
-                uploaded_file = form_user.file_uploader(f"Upload {choice}") 
+                uploaded_file = form_user.file_uploader(f"Upload {choice}")
                 replace_string = "{" + variable + "}"
                 if uploaded_file:
-                    user_input = user_input.replace(replace_string, "<" + uploaded_file.name + ">")
+                    user_input = user_input.replace(
+                        replace_string, "<" + uploaded_file.name + ">"
+                    )
                     value_dict[choice] = uploaded_file.name
                     with tempfile.NamedTemporaryFile(delete=False) as tmp:
                         global tmp_path
                         tmp.write(uploaded_file.getvalue())
                         tmp_path = tmp.name
-                    with open(os.path.join("",uploaded_file.name),"wb") as f:
+                    with open(os.path.join("", uploaded_file.name), "wb") as f:
                         f.write(uploaded_file.getbuffer())
-                        
+
             else:
                 replace_string = "{" + variable + "}"
-                user_input = user_input.replace(replace_string, "<" + value_dict[choice] + ">")
+                user_input = user_input.replace(
+                    replace_string, "<" + value_dict[choice] + ">"
+                )
 
         elif type == "tool":
             replace_string = "{" + variable + "}"
-            user_input = user_input.replace(replace_string, "<" + "action " + choice + ">")
+            user_input = user_input.replace(
+                replace_string, "<" + "action " + choice + ">"
+            )
             if choice not in value_dict.keys():
                 tools.append(choice)
                 tool_info = get_tool_info(choice)
-                tools_description = tools_description + "Action Name: " + tool_info["name"] + "\nWhen To Use: " + tool_info["use"] + "\nInput: " + tool_info["input"]
+                tools_description = (
+                    tools_description
+                    + "Action Name: "
+                    + tool_info["name"]
+                    + "\nWhen To Use: "
+                    + tool_info["use"]
+                    + "\nInput: "
+                    + tool_info["input"]
+                )
                 tools_description = tools_description + "\n\n"
                 value_dict[choice] = tool_info["function"]
-    
+
     agent_instruction = f"""\nUse the following format:
         Step 1: The first step
         Reason: Reason for taking this step
         Action: the action to take, should be one of {tools}.
         Action Input: the input to the action
         Observation: the result of the action
-        
+
         Step 2: The second step
         Reason: Reason for taking this step
         Action: the action to take, should be one of {tools}.
-        Action Input: the input to the action 
+        Action Input: the input to the action
         Observation: the result of the action
 
         ... (this Step/Reason/Action/Action Input/Observation repeats for all steps)
-        
+
         Once you have completed all the steps, your final answer should be in the format:
         Final Answer: {output_format}
         """
@@ -149,43 +236,48 @@ def nuggt(user_input, output_format, variables):
     print(nuggt)
     submit = form_user.form_submit_button("Submit")
     if submit:
-        with st.spinner('I am still working on it....'):
+        with st.spinner("I am still working on it...."):
             try:
                 agent = st.write(initialise_agent(nuggt, value_dict, tools))
             except Exception as e:
                 print(e)
-                st.write("Oops, something went wrong. Please make sure you have entered the correct API keys. If the issue still persists, please reach out to us at https://discord.gg/gzdCDM84")
-        #save_to_sheets("-", "-", "-", agent)
-        feedback = st.text_input("Thank you for experimenting with Nuggt! We would appreciate some feedback to help improve the product :smiley:")
+                st.write(
+                    "Oops, something went wrong. Please make sure you have entered the correct API keys. If the issue still persists, please reach out to us at https://discord.gg/gzdCDM84"
+                )
+        # save_to_sheets("-", "-", "-", agent)
+        feedback = st.text_input(
+            "Thank you for experimenting with Nuggt! We would appreciate some feedback to help improve the product :smiley:"
+        )
         save_to_sheets("-", "-", feedback, "-")
         if uploaded_file:
             os.remove(uploaded_file.name)
-        #st.write("All uploaded files have been deleted")
-      
-def initialise_agent(nuggt, value_dict, tools):   
+        # st.write("All uploaded files have been deleted")
+
+
+def initialise_agent(nuggt, value_dict, tools):
     messages = [{"role": "user", "content": nuggt}]
     output = ""
     count = 0
-    log_expander = st.expander('Logs')  # create expander
-    while(True):
+    log_expander = st.expander("Logs")  # create expander
+    while True:
         count = count + 1
         if count > 10:
             raise ValueError("Too many steps")
-        
+
         response = openai.ChatCompletion.create(
             api_key=os.environ.get("OPENAI_API_KEY"),
             model=os.getenv("MODEL_NAME"),
             messages=messages,
-            temperature=0, 
+            temperature=0,
             top_p=0,
             stop=["\nObservation: "],
         )
-       
+
         output = response.choices[0].message["content"]
         output = output.replace("Observation:", "")
         print(Fore.BLUE + output)
 
-        #with log_expander:  # write to expander
+        # with log_expander:  # write to expander
         #    st.write(output.split("Reason:")[0] + "\n")
 
         regex = r"Action\s*\d*\s*:(.*?)\nAction\s*\d*\s*Input\s*\d*\s*:[\s]*(.*)"
@@ -193,37 +285,51 @@ def initialise_agent(nuggt, value_dict, tools):
 
         if "Final Answer:" in output and not match:
             return output.split("Final Answer:")[1]
-            #return output.replace("Final Answer:", "")
-        
+            # return output.replace("Final Answer:", "")
+
         if "Step" not in output:
             print(Fore.YELLOW + "The model didnt output a step.")
-            output = "Please follow the format Step/Reason/Action/Action Input/Observation"
-            messages = [{"role": "user", "content": messages[0]["content"] + "\n" + output}]
+            output = (
+                "Please follow the format Step/Reason/Action/Action Input/Observation"
+            )
+            messages = [
+                {"role": "user", "content": messages[0]["content"] + "\n" + output}
+            ]
             continue
-        
+
         if "Reason" not in output:
             print(Fore.YELLOW + "The model didnt output a reason.")
-            output = "Please follow the format Step/Reason/Action/Action Input/Observation"
-            messages = [{"role": "user", "content": messages[0]["content"] + "\n" + output}]
+            output = (
+                "Please follow the format Step/Reason/Action/Action Input/Observation"
+            )
+            messages = [
+                {"role": "user", "content": messages[0]["content"] + "\n" + output}
+            ]
             continue
-        
+
         if output.count("Action Input") > 1:
             print(Fore.YELLOW + "The model went crazy.")
             output = "Please go one step at a time."
-            messages = [{"role": "user", "content": messages[0]["content"] + "\n" + output}]
+            messages = [
+                {"role": "user", "content": messages[0]["content"] + "\n" + output}
+            ]
             continue
 
         if not match:
             print(Fore.RED + "The model was sidetracked.")
             output = "You are not following the format. Please follow the given format."
-            messages = [{"role": "user", "content": messages[0]["content"] + "\n" + output}]
+            messages = [
+                {"role": "user", "content": messages[0]["content"] + "\n" + output}
+            ]
             continue
-       
+
         action = match.group(1).strip().lower()
         if action not in tools:
             output = f"Invalid Action. Your action should be one of {tools}."
-            print(Fore.YELLOW + "The agent forgot his tools." + output) 
-            messages = [{"role": "user", "content": messages[0]["content"] + "\n" + output}]
+            print(Fore.YELLOW + "The agent forgot his tools." + output)
+            messages = [
+                {"role": "user", "content": messages[0]["content"] + "\n" + output}
+            ]
             continue
 
         with log_expander:  # write to expander
@@ -232,45 +338,34 @@ def initialise_agent(nuggt, value_dict, tools):
         action_input = match.group(2)
         observation = value_dict[action](action_input)
         print(Fore.GREEN + "\nObservation: " + observation)
-        output = output + "\nObservation: " + observation 
+        output = output + "\nObservation: " + observation
         messages = [{"role": "user", "content": messages[0]["content"] + "\n" + output}]
 
+
 def get_most_recent_file(dir_path):
     # Get a list of all files in directory
     files = glob.glob(dir_path + "/*")
-    
+
     if not files:
         return None
-    
+
     # Find the most recent file
     most_recent_file = max(files, key=os.path.getctime)
 
     return most_recent_file
-    
+
+
 def main():
     st.header("Nuggt Playground")
-    user_input = st.text_area(label='Enter instruction here')
+    user_input = st.text_area(label="Enter instruction here")
 
-    output_format = st.text_input(label='Output format')
+    output_format = st.text_input(label="Output format")
 
     if user_input and output_format:
-        #save_to_sheets(user_input, output_format, "-", "-")
+        # save_to_sheets(user_input, output_format, "-", "-")
         variables = extract_variables(user_input)
         nuggt(user_input, output_format, variables)
-        
-if __name__ == "__main__":
-    main()
-
-
-
-
-
-
-
-
-
-
-
-
 
 
+if __name__ == "__main__":
+    main()
diff --git a/nuggt-release/python_repl.py b/nuggt-release/python_repl.py
index 32202af..46ff92d 100644
--- a/nuggt-release/python_repl.py
+++ b/nuggt-release/python_repl.py
@@ -1,9 +1,11 @@
-from colorama import Fore
-from io import StringIO
+import os
+import sys
 import traceback
+from io import StringIO
+
 import openai
-import sys
-import os
+from colorama import Fore
+
 
 class PythonREPL:
     def __init__(self):
@@ -31,10 +33,17 @@ def run(self, code: str) -> str:
         if "Traceback" not in error:
             error = False
 
-        return output if not error else "Your code has the following error. Please provide the corrected code.\n" + error
+        return (
+            output
+            if not error
+            else "Your code has the following error. Please provide the corrected code.\n"
+            + error
+        )
+
 
 python_repl = PythonREPL()
 
+
 def extract_code_from_block(text):
     if "!pip" in text:
         return "The package is successfully installed."
@@ -42,22 +51,28 @@ def extract_code_from_block(text):
     text = text.replace("python", "")
     return text
 
+
 def fix_error(code, result):
     while "Your code has the following error." in result:
-        error = result.replace("Your code has the following error. Please provide the corrected code.", "")
+        error = result.replace(
+            "Your code has the following error. Please provide the corrected code.", ""
+        )
         user_input = f"Input:\n{code}\nError:\n{error}\nOutput:"
 
         print(f"I am going to correct: {user_input}")
         print(Fore.RED + "Code needs some correction.")
         messages = [
-        {"role": "user", "content": f"""Output the corrected code in the following format:\n```Your code here```\n{user_input}"""},
+            {
+                "role": "user",
+                "content": f"""Output the corrected code in the following format:\n```Your code here```\n{user_input}""",
+            },
         ]
 
         response = openai.ChatCompletion.create(
-                api_key=os.getenv("OPENAI_API_KEY"),
-                model=os.getenv("MODEL_NAME"),
-                messages=messages,
-                temperature=0, 
+            api_key=os.getenv("OPENAI_API_KEY"),
+            model=os.getenv("MODEL_NAME"),
+            messages=messages,
+            temperature=0,
         )
 
         code = response.choices[0].message["content"].strip()
@@ -65,20 +80,20 @@ def fix_error(code, result):
         print(f"\nOutput of the model: {code}")
 
         result = python_repl.run(code)
-        
 
     print(Fore.GREEN + "Code has been corrected.")
     return result
 
+
 def python(code):
     code = extract_code_from_block(code)
     if code == "The package is successfully installed.":
         return code
-    result = python_repl.run(code) 
+    result = python_repl.run(code)
     if "Your code has the following error." in result:
         result = fix_error(code, result)
 
     if result == "":
         result = "Your code was successfully executed."
 
-    return result 
\ No newline at end of file
+    return result
diff --git a/nuggt-release/tool.py b/nuggt-release/tool.py
index a61d3c8..6bcf745 100644
--- a/nuggt-release/tool.py
+++ b/nuggt-release/tool.py
@@ -1,23 +1,26 @@
-from gradio_tools.tools import (StableDiffusionTool, StableDiffusionPromptGeneratorTool, TextToVideoTool)
-from langchain.utilities import GoogleSerperAPIWrapper, GoogleSearchAPIWrapper
-from langchain.text_splitter import RecursiveCharacterTextSplitter
+import json
+import os
+
+import browse
+import openai
+import python_repl
+from gradio_tools.tools import (StableDiffusionPromptGeneratorTool,
+                                StableDiffusionTool, TextToVideoTool)
+from langchain.chains import RetrievalQA
 from langchain.chains.question_answering import load_qa_chain
+from langchain.document_loaders import PyMuPDFLoader, YoutubeLoader
 from langchain.embeddings.openai import OpenAIEmbeddings
-from langchain.document_loaders import PyMuPDFLoader
-from langchain.document_loaders import YoutubeLoader
+from langchain.llms import OpenAI
+from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain.tools import SceneXplainTool
-from langchain.chains import RetrievalQA
+from langchain.utilities import GoogleSearchAPIWrapper, GoogleSerperAPIWrapper
 from langchain.vectorstores import FAISS
-from langchain.llms import OpenAI
-import python_repl
-import openai
-import browse
-import json
-import os 
+
 
 def google(query):
     search = GoogleSearchAPIWrapper()
-    return str(search.results(query.replace('"', ''), 3))
+    return str(search.results(query.replace('"', ""), 3))
+
 
 def browse_website(query):
     data = json.loads(query)
@@ -30,6 +33,7 @@ def browse_website(query):
     chain = load_qa_chain(OpenAI(), chain_type="stuff")
     return chain.run(input_documents=docs, question=data["information"])
 
+
 def load_video(video_url):
     embeddings = OpenAIEmbeddings()
     loader = YoutubeLoader.from_youtube_url(video_url)
@@ -41,6 +45,7 @@ def load_video(video_url):
     db = FAISS.from_documents(docs, embeddings)
     return db
 
+
 def video_tool(query):
     data = json.loads(query)
     transcript = load_video(data["video_url"])
@@ -48,51 +53,61 @@ def video_tool(query):
     chain = load_qa_chain(OpenAI(), chain_type="stuff")
     return chain.run(input_documents=docs, question=query)
 
+
 def document_tool(query):
     data = json.loads(query)
     loader = PyMuPDFLoader(data["document_name"])
     pages = loader.load_and_split()
     faiss_index = FAISS.from_documents(pages, OpenAIEmbeddings())
-    retriever = faiss_index.as_retriever(search_type="similarity", search_kwargs={"k":2})
-    rqa = RetrievalQA.from_chain_type(llm=OpenAI(), 
-                                chain_type="stuff", 
-                                retriever=retriever, 
-                                return_source_documents=True,
-                                )
+    retriever = faiss_index.as_retriever(
+        search_type="similarity", search_kwargs={"k": 2}
+    )
+    rqa = RetrievalQA.from_chain_type(
+        llm=OpenAI(),
+        chain_type="stuff",
+        retriever=retriever,
+        return_source_documents=True,
+    )
     return str(rqa(data["information"]))
-    
+
+
 def python(code):
     return python_repl.python(code)
 
+
 def display(code):
     return python_repl.python(code)
 
+
 def search(query):
     search_api = GoogleSerperAPIWrapper()
     return search_api.run(query)
 
+
 def custom_llm(query):
     data = json.loads(query)
     messages = [
         {"role": "system", "content": data["prompt"]},
-        {"role": "user", "content": data["input"]}
+        {"role": "user", "content": data["input"]},
     ]
     response = openai.ChatCompletion.create(
-            api_key=os.environ.get("OPENAI_API_KEY"),
-            model=os.getenv("MODEL_NAME"),
-            messages=messages,
-            temperature=0, 
+        api_key=os.environ.get("OPENAI_API_KEY"),
+        model=os.getenv("MODEL_NAME"),
+        messages=messages,
+        temperature=0,
     )
 
     return response.choices[0].message["content"].strip()
 
+
 def stable_diffusion(query):
     prompt = StableDiffusionPromptGeneratorTool().langchain.run(query)
     return StableDiffusionTool().run(prompt)
 
+
 def image_caption(path):
     return SceneXplainTool().run(path)
 
+
 def generate_video(query):
     return TextToVideoTool().langchain.run(query)
-
diff --git a/requirements.txt b/requirements.txt
index 2ed8286..b61fc13 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -17,3 +17,7 @@ PyMuPDF>=1.22.3
 python-dotenv>=1.0.0
 colorama>=0.4.6
 bs4>=0.0.1
+black
+isort
+pycln
+pre-commit