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README.md

@@ -1,12 +1,6 @@
 ---
-title: Test Bot
-emoji: 🌍
-colorFrom: yellow
-colorTo: blue
+title: Test_Bot
+app_file: app2.py
 sdk: gradio
-sdk_version: 5.6.0
-app_file: app.py
-pinned: false
+sdk_version: 4.44.1
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,87 @@
+import openai
+import gradio as gr
+import docx  # For reading Word documents
+
+openai.api_key = "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"
+
+messages = [
+    {"role": "system", "content": "You are a chatbot that is very happy and kind. You will search the website https://www.patch-and-sparks.com/en/"},
+]
+
+
+def read_word_document(file_path):
+    """Read and return all paragraphs from the Word document."""
+    doc = docx.Document(file_path)
+    paragraphs = []
+    for paragraph in doc.paragraphs:
+        paragraphs.append(paragraph.text)
+    return paragraphs
+
+
+def search_in_doc(paragraphs, search_term):
+    """Search for the term in each paragraph of the document and return the matching paragraph."""
+    for paragraph in paragraphs:
+        if search_term.lower() in paragraph.lower():
+            return f"I found this information in the document: '{paragraph}'"
+    return "Sorry, I couldn't find that information in the document."
+
+
+
+def chatbot(input):
+    if input:
+        # Add user input to the chat
+        messages.append({"role": "user", "content": input})
+        
+        # Search for the information in the Word document
+        doc_content = read_word_document("./Info_1.docx")  # Specify the path to your Word document
+        doc_reply = search_in_doc(doc_content, input)
+        
+        ## Get the chatbot response from OpenAI
+        #chat = openai.ChatCompletion.create(
+        #    model="gpt-4", messages=messages
+        #)
+        #ai_reply = chat.choices[0].message.content
+        #messages.append({"role": "assistant", "content": ai_reply})
+        
+        # Combine the response from OpenAI and the document search
+        #combined_reply = f"{ai_reply}\n\n{doc_reply}"
+        combined_reply = f"{doc_reply}"
+        return combined_reply
+
+inputs = gr.Textbox(lines=7, label="Chat with AI")
+outputs = gr.Textbox(label="Reply")
+
+gr.Interface(fn=chatbot, inputs=inputs, outputs=outputs, title="The AI Patch & Sparks Chatbot",
+             description="Ask anything you want about Patch&Sparks \y(((h",
+             theme="compact").launch(share=True)
+
+""" 
+
+import openai
+import gradio as gr
+
+openai.api_key = "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"
+
+messages = [
+    {"role": "system", "content": "You are a chatbot that is very happy and kind. You will search the website https://www.patch-and-sparks.com/en/"},
+]
+
+def chatbot(input):
+    if input:
+        messages.append({"role": "user", "content": input})
+        chat = openai.ChatCompletion.create(
+            #model="gpt-3.5-turbo", messages=messages
+            model="gpt-4o", messages=messages
+        )
+        reply = chat.choices[0].message.content
+        messages.append({"role": "assistant", "content": reply})
+        return reply
+
+inputs = gr.Textbox(lines=7, label="Chat with AI")
+outputs = gr.Textbox(label="Reply")
+
+gr.Interface(fn=chatbot, inputs=inputs, outputs=outputs, title="The AI Patch & Sparks Chatbot",
+             description="Ask anything you want about Patch&Sparks - - - -yeah",
+             theme="compact").launch(share=True)
+
+"""

app2.py

@@ -0,0 +1,87 @@
+import openai
+import gradio as gr
+import docx  # For reading Word documents
+
+openai.api_key = "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"
+
+messages = [
+    {"role": "system", "content": "You are a chatbot that is very happy and kind. You will search the website https://www.patch-and-sparks.com/en/"},
+]
+
+
+def read_word_document(file_path):
+    """Read and return all paragraphs from the Word document."""
+    doc = docx.Document(file_path)
+    paragraphs = []
+    for paragraph in doc.paragraphs:
+        paragraphs.append(paragraph.text)
+    return paragraphs
+
+
+def search_in_doc(paragraphs, search_term):
+    """Search for the term in each paragraph of the document and return the matching paragraph."""
+    for paragraph in paragraphs:
+        if search_term.lower() in paragraph.lower():
+            return f"I found this information in the document: '{paragraph}'"
+    return "Sorry, I couldn't find that information in the document."
+
+
+
+def chatbot(input):
+    if input:
+        # Add user input to the chat
+        messages.append({"role": "user", "content": input})
+        
+        # Search for the information in the Word document
+        doc_content = read_word_document("./Info_1.docx")  # Specify the path to your Word document
+        doc_reply = search_in_doc(doc_content, input)
+        
+        ## Get the chatbot response from OpenAI
+        #chat = openai.ChatCompletion.create(
+        #    model="gpt-4", messages=messages
+        #)
+        #ai_reply = chat.choices[0].message.content
+        #messages.append({"role": "assistant", "content": ai_reply})
+        
+        # Combine the response from OpenAI and the document search
+        #combined_reply = f"{ai_reply}\n\n{doc_reply}"
+        combined_reply = f"{doc_reply}"
+        return combined_reply
+
+inputs = gr.Textbox(lines=7, label="Chat with AI")
+outputs = gr.Textbox(label="Reply")
+
+gr.Interface(fn=chatbot, inputs=inputs, outputs=outputs, title="The AI Patch & Sparks Chatbot",
+             description="Ask anything you want about Patch&Sparks",
+             theme="compact").launch(share=True)
+
+""" 
+
+import openai
+import gradio as gr
+
+openai.api_key = "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"
+
+messages = [
+    {"role": "system", "content": "You are a chatbot that is very happy and kind. You will search the website https://www.patch-and-sparks.com/en/"},
+]
+
+def chatbot(input):
+    if input:
+        messages.append({"role": "user", "content": input})
+        chat = openai.ChatCompletion.create(
+            #model="gpt-3.5-turbo", messages=messages
+            model="gpt-4o", messages=messages
+        )
+        reply = chat.choices[0].message.content
+        messages.append({"role": "assistant", "content": reply})
+        return reply
+
+inputs = gr.Textbox(lines=7, label="Chat with AI")
+outputs = gr.Textbox(label="Reply")
+
+gr.Interface(fn=chatbot, inputs=inputs, outputs=outputs, title="The AI Patch & Sparks Chatbot",
+             description="Ask anything you want about Patch&Sparks - - - -yeah",
+             theme="compact").launch(share=True)
+
+"""

key_words.py

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+import spacy
+from spacy.lang.en.stop_words import STOP_WORDS
+
+# Load spaCy's English language model
+nlp = spacy.load('en_core_web_sm')
+
+def extract_keywords(question):
+    # Process the question using spaCy NLP pipeline
+    doc = nlp(question)
+    
+    # Extract keywords by removing stopwords, punctuation, and selecting nouns/adjectives
+    keywords = [token.text for token in doc if token.is_stop == False and token.is_punct == False and token.pos_ in ['NOUN', 'ADJ', 'VERB']]
+    
+    return keywords
+
+# Example chatbot question
+question = "What is the weather like in New York City today?"
+
+# Extract keywords
+keywords = extract_keywords(question)
+
+print("Keywords:", keywords)

rake_find.py

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+from rake_nltk import Rake
+
+import nltk
+nltk.download('punkt_tab')
+
+def extract_keywords_rake(question):
+    r = Rake()
+    # Extract keywords
+    r.extract_keywords_from_text(question)
+    keywords = r.get_ranked_phrases()
+    
+    return keywords
+
+# Example chatbot question
+question = "What is the weather like in New York City today?"
+
+# Extract keywords using Rake
+keywords_rake = extract_keywords_rake(question)
+
+print("Keywords:", keywords_rake)