Update app.py

app.py

@@ -21,30 +21,41 @@ embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-
 vector_store= FAISS.load_local("vector_db/", embeddings)
 
 repo_id="mistralai/Mixtral-8x7B-Instruct-v0.1"
-llm = HuggingFaceHub(repo_id=repo_id, model_kwargs={"temperature": 0.01, "max_new_tokens": 2048})
+llm = HuggingFaceHub(repo_id=repo_id, model_kwargs={"temperature": 0.01, "max_new_tokens": 4096})
 
 retriever = vector_store.as_retriever(
     search_type="similarity",
-    search_kwargs={"k":3, "include_metadata": True})
+    search_kwargs={"k":5, "include_metadata": True})
 
 df=pd.read_csv('data/Gretel_Data.csv')
 averages = df.mean().to_dict()
 agent = Agent([df], config={"llm": llm, 'raw_response':True, 'verbose':True})
 
 global unique_columns
-unique_columns = []
+unique_columns = [
+        'Avg_Connected_UEs',
+        'PRB Util%',
+        'CA Activation Rate',
+        'DLRLCLayerDataVolume MB',
+        'DRB UL Data Volume MB',
+        'UPTP_Mbps',
+        'UPTP Mbps Num',
+        'UPTP Mbps Den',
+        'UL MAC Vol Scell Pct',
+        'DL MAC Vol Scell Pct',
+        'DL MAC Vol Scell MB',
+        'DL Volume',
+        'DL Data Vol MAC in MB',
+        'UL Throughput',
+        'MB_per_connected_UE'
+    ]
 
 global target_words
 target_words = ["Bandwidth", "Interference", "Call Quality", "Network", "Handover"]
 
-global result_dict
-result_dict = {}
-
-global columns
-columns=[]
+columns = []
 
-global column_avgs
-column_avgs={}
+column_avgs = {}
 
 global network_features
 network_features  = {
@@ -98,7 +109,7 @@ network_features  = {
         'SIP Calls with a Leg',
         'SIP_SC_Total_MOU',
         'SIP Dropped Calls',
-        'Volte_MOU',
+        'VoLTE_MOU',
         'QCI 1 Bearer Drops',
         'QCI 1 Bearer Releases',
         'QCI 1 Bearer Drop%',
@@ -120,14 +131,15 @@ network_features  = {
 }
 
 
+
 def echo(message, history):
   try:
     qa=RetrievalQA.from_chain_type(llm=llm, retriever=retriever, return_source_documents=True)
-    message= "Your name is Clara. You are a senior telecom network engineer having access to troubleshooting tickets data and other technical and product documentation.Stick to the knowledge from these tickets. Ask clarification questions if needed.  "+message
-    result=qa({"query":message})
-    bold_answer= "<b>" + result['result'] + "</b>"
+    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. Ask clarification questions if needed.  Return only the helpful answer" + message
+    result= qa({"query":message})
+    answer= result['result'].split('Helpful Answer: ')[1]
     for word in target_words:
-      if re.search(r'\b' + re.escape(word) + r'\b', bold_answer, flags=re.IGNORECASE):
+      if re.search(r'\b' + re.escape(word) + r'\b', answer, flags=re.IGNORECASE):
         columns.extend(network_features.get(word, []))
     unique_columns = list(set(columns))
 
@@ -149,10 +161,18 @@ def echo(message, history):
     for key in column_avgs:
       styled_df = styled_df.applymap(lambda x, k=key: highlight_rows(x, column_avgs[k]), subset=[f'{key}'])
 
-    return "<br></br>"+ bold_answer + "<br></br>" +'1. ' +  "<br>" + str(result["source_documents"][0]) +"<br>" + '2. ' + str(result["source_documents"][1]) +  "<br>" + "3. " + str(result["source_documents"][2]), styled_df
+    gr.Dataframe(styled_df)
+    return (
+       answer + '\n'
+       + '\n' + "Sources: \n" 
+       + '\n' + '1. ' + result['source_documents'][0].metadata['source'] + ' Row: ' +str(result['source_documents'][0].metadata['row']) + '\n' + result['source_documents'][0].page_content + "\n" 
+       + '\n' + '2. ' + result['source_documents'][1].metadata['source'] + ' Row: ' +str(result['source_documents'][1].metadata['row']) + '\n' + result['source_documents'][1].page_content +  "\n" 
+       + '\n' + "3. " + result['source_documents'][2].metadata['source'] + ' Row: ' +str(result['source_documents'][2].metadata['row']) + '\n' + result['source_documents'][2].page_content, 
+       styled_df
+       )
   except Exception as e:
     error_message = f"An error occurred: {e}"+str(e.with_traceback) + str(e.args)
-    return error_message
+    return error_message, error_message
 
 def echo_agent(message, history):
   message="There are 2 df's. If you find a KeyError check for the same in the other df." + "<br>" + message
@@ -160,12 +180,6 @@ def echo_agent(message, history):
     with io.StringIO() as buffer:
       with contextlib.redirect_stdout(buffer):
         result= agent.chat(message)
-      verbose_output = buffer.getvalue()
-      verbose_output = verbose_output.replace("\x1b[36;1m\x1b[1;3m", "")
-      verbose_output = verbose_output.replace("> ", "")
-      verbose_output = verbose_output.replace("", "")
-      verbose_output = verbose_output.replace("", "")
-      result= "<b>" + verbose_output + "<br>" + result + "</b>"
     return result
   except Exception as e:
     error_message = f"An error occurred: {e}"+str(e.with_traceback) + str(e.args)
@@ -190,17 +204,25 @@ with demo_agent:
   with gr.Tab('Clara'):
     with gr.Row():
       message = gr.Text(label="Input Query")
-    
+
     btn = gr.Button("Submit")
 
     with gr.Row():
-      reply = gr.Text(label="RCA and MoP")
-    
+      reply = gr.Text(label="RCA and MoP", autoscroll=False)
+
     with gr.Accordion(label = "Metrics", open=False):
           table = gr.Dataframe()
 
     btn.click(echo, inputs=[message], outputs=[reply, table])
-    gr.Examples(["Wi-Fi connected but no internet showing", "internet stopped working after primary link down", "internet stopped working link not shifted to secondary after primary link down"], inputs=[message])
+
+    gr.Examples([
+        "Wi-Fi connected but no internet showing",
+        "internet stopped working after primary link down",
+        "internet stopped working link not shifted to secondary after primary link down",
+        "What are the network problems faced by people living in the state of California?"
+        ],
+                inputs=[message]
+                )
 
   with gr.Tab('Sam'):
     with gr.Row():
@@ -211,6 +233,5 @@ with demo_agent:
     btn2 = gr.Button("Submit")
     btn2.click(echo_agent, inputs=[message_agent], outputs=[reply_agent])
 
-
 if __name__ == "__main__":
     demo_agent.launch(share=True,debug=True,auth=("admin", "Sam&Clara"))