Update app.py
Browse files
app.py
CHANGED
@@ -101,10 +101,8 @@ def doj_info(q):
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MINISTRY OF LAW AND JUSTICE
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DEPARTMENT OF JUSTICE
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----
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Ministry of Law and Justice is the oldest limb of the Government of
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Department of Legal Affairs, Legislative Department and the
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Department of Justice.
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VISION OF THE DEPARTMENT OF JUSTICE
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Facilitating administration of Justice that ensures easy access and
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timely delivery of Justice to all
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@@ -317,7 +315,7 @@ Peoples’ Prosecution Service of the People’s Republic of China
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relating to promotion of cooperation in Legal/Judicial matters was
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signed on 23rd June, 2003.
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--------
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""".replace('/n','')
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ipc_tool = Tool(
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name="IPC Information Retrieval",
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@@ -351,18 +349,18 @@ llm = ChatOpenAI(
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max_retries=5
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)
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template="""
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agent_tools = [ipc_tool, crpc_tool, doj_tool, faq_tool]
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@@ -378,8 +376,16 @@ agent = initialize_agent(
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def encode_image_to_base64(image_path):
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return pytesseract.image_to_string(Image.open(image_path))
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def chatbot_response(history,query):
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if query.get('files'):
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# Encode image to base64
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image_data=""
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@@ -389,15 +395,14 @@ def chatbot_response(history,query):
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# Create a multimodal message with both text and image data
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message = HumanMessage(
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content=[
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{"type": "text", "text": template.format(query['text'] +" System :Image(s) was added to this prompt by this user. Text Extracted from this image (Some words may be misspelled ,Use your understanding ):"+image_data)}, # Add text input
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]
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)
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#k+=" System :Image(s) was added to this prompt by this user. Text Extracted from this image (Some words may be misspelled ,Use your understanding ):"+image_data
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else:
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# If no image, only pass the text
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message = HumanMessage(content=[{"type": "text", "text": template.format(query)}])
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# Invoke the model with the multimodal message
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result = agent.invoke([message],handle_parsing_errors=True)
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response = result['output']
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MINISTRY OF LAW AND JUSTICE
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DEPARTMENT OF JUSTICE
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----
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Ministry of Law and Justice is the oldest limb of the Government of India. The Ministry functions through three integral departments -
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Department of Legal Affairs, Legislative Department and the Department of Justice.
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VISION OF THE DEPARTMENT OF JUSTICE
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Facilitating administration of Justice that ensures easy access and
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timely delivery of Justice to all
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relating to promotion of cooperation in Legal/Judicial matters was
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signed on 23rd June, 2003.
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--------
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""".replace('/n',' ')
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ipc_tool = Tool(
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name="IPC Information Retrieval",
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max_retries=5
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)
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template="""
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You are a highly specialized legal assistant with deep knowledge of the Indian Penal Code (IPC).
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Your primary task is to retrieve and summarize legal information accurately from the IPC.pdf document provided to you.
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Your responses should be highly specific, fact-based, and free from any speculation or hallucinations.
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Always cite the exact section from the IPC when providing an answer.
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If the information is not available in the document, clearly state that and do not make any assumptions.
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History: {}
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User: {}
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Response:
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"""
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agent_tools = [ipc_tool, crpc_tool, doj_tool, faq_tool]
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def encode_image_to_base64(image_path):
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return pytesseract.image_to_string(Image.open(image_path))
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def parse(history):
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p='\n'
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if history==[]:
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return "No Chat till now"
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for i in history:
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p+=i['role']+': '+i['content']+'\n'
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return p
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def chatbot_response(history,query):
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l=parse(history)
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if query.get('files'):
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# Encode image to base64
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image_data=""
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# Create a multimodal message with both text and image data
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message = HumanMessage(
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content=[
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{"type": "text", "text": template.format(l,query['text'] +" System :Image(s) was added to this prompt by this user. Text Extracted from this image (Some words may be misspelled ,Use your understanding ):"+image_data)}, # Add text input
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]
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)
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#k+=" System :Image(s) was added to this prompt by this user. Text Extracted from this image (Some words may be misspelled ,Use your understanding ):"+image_data
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else:
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# If no image, only pass the text
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message = HumanMessage(content=[{"type": "text", "text": template.format(l,query)}])
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# Invoke the model with the multimodal message
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result = agent.invoke([message],handle_parsing_errors=True)
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response = result['output']
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