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Update app.py
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app.py
CHANGED
@@ -21,11 +21,11 @@ embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-
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vector_store= FAISS.load_local("vector_db/", embeddings)
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repo_id="mistralai/Mixtral-8x7B-Instruct-v0.1"
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llm = HuggingFaceHub(repo_id=repo_id, model_kwargs={"temperature": 0.01, "max_new_tokens":
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retriever = vector_store.as_retriever(
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search_type="similarity",
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search_kwargs={"k":
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)
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df=pd.read_csv('data/Gretel_Data.csv')
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@@ -131,14 +131,12 @@ network_features = {
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]
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}
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def echo(message, history):
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try:
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qa=RetrievalQA.from_chain_type(llm=llm, retriever=retriever, return_source_documents=True)
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message= "You are a senior telecom network engineer having access to troubleshooting tickets data and other technical and product documentation. Stick to the knowledge provided.
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result= qa({"query":message})
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answer= result['result'].split('Helpful Answer:
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for word in target_words:
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if re.search(r'\b' + re.escape(word) + r'\b', answer, flags=re.IGNORECASE):
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columns.extend(network_features.get(word, []))
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@@ -164,11 +162,13 @@ def echo(message, history):
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gr.Dataframe(styled_df)
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return (
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answer + '\n'
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+ '\n' + "Sources: \n"
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+ '\n' + '1. ' + result['source_documents'][0].metadata['source'] + '
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+ '\n' + '2. ' + result['source_documents'][1].metadata['source'] + '
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+ '\n' + "3. " + result['source_documents'][2].metadata['source'] + '
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styled_df
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)
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except Exception as e:
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@@ -218,9 +218,12 @@ with demo_agent:
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gr.Examples([
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"Wi-Fi connected but no internet showing",
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"
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"
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],
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inputs=[message]
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)
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vector_store= FAISS.load_local("vector_db/", embeddings)
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repo_id="mistralai/Mixtral-8x7B-Instruct-v0.1"
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llm = HuggingFaceHub(repo_id=repo_id, model_kwargs={"temperature": 0.01, "max_new_tokens": 4096})
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retriever = vector_store.as_retriever(
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search_type="similarity",
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search_kwargs={"k":10}
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)
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df=pd.read_csv('data/Gretel_Data.csv')
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]
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}
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def echo(message, history):
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try:
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qa=RetrievalQA.from_chain_type(llm=llm, retriever=retriever, return_source_documents=True)
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message= " <s> [INST] You are a senior telecom network engineer having access to troubleshooting tickets data and other technical and product documentation. Stick to the knowledge provided. Search through the product documentation pdfs first before scanning the tickets to generate the answer. Return only the helpful answer. Question:" + message + '[/INST]'
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result= qa({"query":message})
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answer= result['result'].split('Helpful Answer:')[-1]
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for word in target_words:
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if re.search(r'\b' + re.escape(word) + r'\b', answer, flags=re.IGNORECASE):
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columns.extend(network_features.get(word, []))
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gr.Dataframe(styled_df)
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return (
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answer.split('Helpful Answer:')[-1].strip() + '\n'
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+ '\n' + "Sources: \n"
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+ '\n' + '1. ' + result['source_documents'][0].metadata['source'] + '\n' + result['source_documents'][0].page_content + "\n"
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+ '\n' + '2. ' + result['source_documents'][1].metadata['source'] + '\n' + result['source_documents'][1].page_content + "\n"
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+ '\n' + "3. " + result['source_documents'][2].metadata['source'] + '\n' + result['source_documents'][2].page_content + "\n"
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+ '\n' + "4. " + result['source_documents'][3].metadata['source'] + '\n' + result['source_documents'][3].page_content + "\n"
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+ '\n' + "5. " + result['source_documents'][4].metadata['source'] + '\n' + result['source_documents'][4].page_content + "\n",
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styled_df
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)
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except Exception as e:
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gr.Examples([
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"Wi-Fi connected but no internet showing",
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'What are the possible cause of router overheating ?',
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"What are the possible causes of RAN getting disconnected frequently?",
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"For the past week, are there any specific cell towers in Texas experiencing unusually high call failure rates or data latency?",
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"What are the network problems faced by people living in the state of California?",
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"I have an FWA connection and all devices except my iPhone have internet access via this FWA device. Can you suggest steps for resolution?",
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"We're receiving reports of congested cell towers in Cleveland. Can you identify the specific cell towers experiencing overload and suggest any temporary network adjustments to alleviate the congestion?"
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],
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inputs=[message]
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)
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