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Update app.py
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app.py
CHANGED
@@ -82,6 +82,7 @@ docstatus = ""
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sample_table = ""
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#This is to define the summary of the runtime tool. This summary will be updated in prompt template and description of the new tool
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run_time_tool_summary=""
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# Define global variables for managing the thread and current_event
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executor = concurrent.futures.ThreadPoolExecutor(max_workers=1)
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@@ -845,6 +846,8 @@ def handle_dislike(data: gr.LikeData):
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# greet with user name on successful login
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def update_message(request: gr.Request):
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return f"<h2 style=' font-family: Calibri;'>Welcome, {request.username}</h4>"
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# Function to generate a 50-word summary of the newly uploaded doc using OpenAI
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@@ -1174,8 +1177,8 @@ def handle_large_dataset(df, create_document,isDataFrame):
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current_folder = os.getcwd()
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file_path = os.path.join(current_folder, 'output_data.xlsx')
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df.to_excel(file_path, index=False)
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@@ -1211,14 +1214,23 @@ def handle_large_dataset(df, create_document,isDataFrame):
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def create_file_HF(file_path):
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from huggingface_hub import create_branch, create_tag
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from huggingface_hub import login
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login(token=os.getenv("HF_TOKEN"))
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#create_branch("Redmind/NewageNXTGPT_Repo_trial", repo_type="space", branch="test-branch")
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#create_tag("bigcode/the-stack", repo_type="dataset", revision="v0.1-release", tag="v0.1.1", tag_message="Bump release version.")
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api = HfApi()
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api.upload_file(path_or_fileobj=file_path, repo_id="Redmind/NewageNXTGPT_Repo_trial",revision = "test-branch", repo_type= "space", path_in_repo='output_data.xlsx')
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@@ -1243,7 +1255,17 @@ def create_pdf(cname,ename,account_number):
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api = HfApi()
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#api.upload_file(path_or_fileobj=output_file_name, repo_id=repo_id, repo_type= "space", path_in_repo=file_output)
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return f"{output_file_name} is created successfully."
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css = """
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sample_table = ""
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#This is to define the summary of the runtime tool. This summary will be updated in prompt template and description of the new tool
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run_time_tool_summary=""
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user_name = ""
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# Define global variables for managing the thread and current_event
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executor = concurrent.futures.ThreadPoolExecutor(max_workers=1)
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# greet with user name on successful login
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def update_message(request: gr.Request):
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global user_name
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user_name = request.username
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return f"<h2 style=' font-family: Calibri;'>Welcome, {request.username}</h4>"
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# Function to generate a 50-word summary of the newly uploaded doc using OpenAI
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current_folder = os.getcwd()
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file_path = "output_data.xlsx"
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#file_path = os.path.join(current_folder, 'output_data.xlsx')
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df.to_excel(file_path, index=False)
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def create_file_HF(file_path):
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from huggingface_hub import create_branch, create_tag
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from huggingface_hub import login
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from huggingface_hub import HfApi
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api = HfApi()
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global user_name
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repo_id = "Redmind/NewageNXTGPT_Repo_trial"
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directory = user_name
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token = os.getenv("HF_TOKEN")
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#check if direcotry exists
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dir_exists_flag = directory_exists(repo_id, directory, token)
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if not dir_exists_flag:
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file_path = directory + "/" + file_path
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#if directory does not exist, create the directoty
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login(token=os.getenv("HF_TOKEN"))
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#create_branch("Redmind/NewageNXTGPT_Repo_trial", repo_type="space", branch="test-branch")
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#create_tag("bigcode/the-stack", repo_type="dataset", revision="v0.1-release", tag="v0.1.1", tag_message="Bump release version.")
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api.upload_file(path_or_fileobj=file_path, repo_id="Redmind/NewageNXTGPT_Repo_trial",revision = "test-branch", repo_type= "space", path_in_repo='output_data.xlsx')
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api = HfApi()
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#api.upload_file(path_or_fileobj=output_file_name, repo_id=repo_id, repo_type= "space", path_in_repo=file_output)
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return f"{output_file_name} is created successfully."
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def directory_exists(repo_id, directory, token):
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try:
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# List all files in the repository
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files = api.list_repo_files(repo_id=repo_id, repo_type="space", token=token)
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# Check if any file starts with the directory path
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return any(file.startswith(directory) for file in files)
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except Exception as e:
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print(f"Error checking directory existence: {e}")
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return False
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css = """
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