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Update app.py
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app.py
CHANGED
@@ -6,12 +6,8 @@ import os
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HF_TOKEN = os.getenv("HF_TOKEN") # Replace with your actual token if not using an environment variable
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# Initialize the Gradio Client for the specified API
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client = Client("on1onmangoes/
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#client = Client("on1onmangoes/CNIHUB101524v11", hf_token=HF_TOKEN)
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# Update the conversation history within the function.
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# Return the updated history along with any other required outputs.
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client_name = ['rosariarossi','bianchifiordaliso','lorenzoverdi','lucia', 'quarto4', 'quinto5', 'secondo6', 'sesto6', 'settimo7','ottavo8','nono9']
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@@ -45,7 +41,7 @@ def stream_chat_with_rag(
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# Call the API with the user's message
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question = message
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answer = client.predict(question=question, api_name="/
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# Debugging: Print the raw response
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print("Raw answer from API:")
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@@ -119,17 +115,17 @@ def format_relevant_documents(relevant_docs: list):
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def process_pdf(pdf_file, client_name):
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return client.predict(
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pdf_file=handle_file(pdf_file),
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client_name=client_name, # Hardcoded client name
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api_name="/
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)[1] # Return only the result string
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# Function to handle search API call
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def search_api(query):
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# Function to handle RAG API call
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def rag_api(question):
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return client.predict(question=question, api_name="/
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# CSS for custom styling
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CSS = """
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@@ -139,7 +135,7 @@ CSS = """
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"""
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# Title for the application
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TITLE = "<h1 style='text-align:center;'>CNI RAG
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# Create the Gradio Blocks interface
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with gr.Blocks(css=CSS) as demo:
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HF_TOKEN = os.getenv("HF_TOKEN") # Replace with your actual token if not using an environment variable
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# Initialize the Gradio Client for the specified API
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client = Client("on1onmangoes/cnianswer101724v3", hf_token=HF_TOKEN)
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client_name = ['rosariarossi','bianchifiordaliso','lorenzoverdi','lucia', 'quarto4', 'quinto5', 'secondo6', 'sesto6', 'settimo7','ottavo8','nono9']
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# Call the API with the user's message
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question = message
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answer = client.predict(question=question, api_name="/run_graph")
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# Debugging: Print the raw response
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print("Raw answer from API:")
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def process_pdf(pdf_file, client_name):
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return client.predict(
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pdf_file=handle_file(pdf_file),
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#client_name=client_name, # Hardcoded client name
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api_name="/process_pdf"
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)[1] # Return only the result string
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# # Function to handle search API call
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# def search_api(query):
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# return client.predict(query=query, api_name="/search_with_confidence")
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# Function to handle RAG API call
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def rag_api(question):
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return client.predict(question=question, api_name="/run_graph")
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# CSS for custom styling
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CSS = """
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"""
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# Title for the application
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TITLE = "<h1 style='text-align:center;'>CNI RAG AGENTIC v0.1</h1>"
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# Create the Gradio Blocks interface
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with gr.Blocks(css=CSS) as demo:
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