Update app.py
Browse files
app.py
CHANGED
@@ -158,7 +158,7 @@ def normalize_text(text):
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return ' '.join(words)
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llm = HuggingFaceEndpoint(
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repo_id="
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task="text-generation",
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max_new_tokens=4096,
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temperature=0.6,
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@@ -194,8 +194,9 @@ def user3(user_message, history, file_path):
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return "", history + [[combined_message, None]], file_path
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messages1 = [
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messages2 = messages1.copy()
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messages3 = messages1.copy()
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messages4 = messages1.copy()
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@@ -213,10 +214,10 @@ def Chat_Message(history):
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messages1 = messages1[-8:]
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history[-1][1] = ""
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def Web_Search(history):
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global messages2
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@@ -235,7 +236,7 @@ def Web_Search(history):
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Query: {message}
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Search Content:
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{source_knowledge}
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#If the query is not related to specific Search Content, engage in general conversation or provide relevant information from other sources.
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"""
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@@ -248,10 +249,10 @@ def Web_Search(history):
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messages2 = messages2[-8:]
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history[-1][1] = ""
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def Chart_Generator(history):
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global messages3
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@@ -292,10 +293,10 @@ def Chart_Generator(history):
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combined_content=response.content
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history[-1][1] = ""
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def Link_Scratch(history):
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global messages4
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@@ -326,7 +327,7 @@ def Link_Scratch(history):
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Query: {user_message}
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Link Content:
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{content_data}
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#If the query is not related to specific Link Content, engage in general conversation or provide relevant information from other sources.
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"""
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message = HumanMessage(content=augmented_prompt)
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@@ -340,10 +341,10 @@ def Link_Scratch(history):
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response_message = response.content
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history[-1][1] = ""
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def insert_line_breaks(text, every=8):
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return '\n'.join(text[i:i+every] for i in range(0, len(text), every))
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@@ -384,7 +385,7 @@ def File_Interact(history,filepath):
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Query: {user_message}
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File Content:
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{content_data}
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#If the query is not related to specific File Content, engage in general conversation or provide relevant information from other sources.
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"""
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message = HumanMessage(content=augmented_prompt)
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@@ -398,10 +399,10 @@ def File_Interact(history,filepath):
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response_message = response.content
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history[-1][1] = ""
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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with gr.Row():
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return ' '.join(words)
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llm = HuggingFaceEndpoint(
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repo_id="HuggingFaceH4/starchat2-15b-v0.1",
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task="text-generation",
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max_new_tokens=4096,
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temperature=0.6,
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return "", history + [[combined_message, None]], file_path
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messages1 = [
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SystemMessage(content="You are a helpful assistant."),
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HumanMessage(content="Hi AI, how are you today?"),
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AIMessage(content="I'm great thank you. How can I help you?")]
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messages2 = messages1.copy()
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messages3 = messages1.copy()
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messages4 = messages1.copy()
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messages1 = messages1[-8:]
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history[-1][1] = ""
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for character in response.content:
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history[-1][1] += character
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time.sleep(0.0025)
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yield history
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def Web_Search(history):
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global messages2
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Query: {message}
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Search Content:
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{source_knowledge}
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#If the query is not related to specific Search Content, engage in general conversation or provide relevant information from other sources.
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"""
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messages2 = messages2[-8:]
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history[-1][1] = ""
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for character in response.content:
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history[-1][1] += character
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time.sleep(0.0025)
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yield history
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def Chart_Generator(history):
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global messages3
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combined_content=response.content
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history[-1][1] = ""
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for character in combined_content:
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history[-1][1] += character
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time.sleep(0.0025)
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yield history
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def Link_Scratch(history):
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global messages4
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Query: {user_message}
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Link Content:
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{content_data}
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#If the query is not related to specific Link Content, engage in general conversation or provide relevant information from other sources.
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"""
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message = HumanMessage(content=augmented_prompt)
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response_message = response.content
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history[-1][1] = ""
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for character in response_message:
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history[-1][1] += character
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time.sleep(0.0025)
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yield history
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def insert_line_breaks(text, every=8):
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return '\n'.join(text[i:i+every] for i in range(0, len(text), every))
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Query: {user_message}
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File Content:
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{content_data}
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#If the query is not related to specific File Content, engage in general conversation or provide relevant information from other sources.
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"""
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message = HumanMessage(content=augmented_prompt)
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response_message = response.content
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history[-1][1] = ""
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for character in response_message:
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history[-1][1] += character
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time.sleep(0.0025)
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yield history
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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with gr.Row():
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