Update app.py

app.py

@@ -37,6 +37,7 @@ top_p=0.8
 frequency_penalty=0.0
 presence_penalty=0.15
 jezik = "srpski"
+cs = "s0"
 
 system_sr = "Zoveš se U-Chat AI asistent i pomažeš korisniku usluga kompanije United Group. Korisnik postavlja pitanje ili problem, upareno sa dodatnima saznanjima. Na osnovu toga napiši korisniku kratak i ljubazan odgovor koji kompletira njegov zahtev ili mu daje odgovor na pitanje. "
 # " Ako ne znaš odgovor, reci da ne znaš, ne izmišljaj ga."
@@ -75,22 +76,36 @@ Settings.llm = HuggingFaceInferenceAPI(model_name="mistralai/Mistral-Nemo-Instru
 # "BAAI/bge-m3"
 Settings.embed_model = HuggingFaceEmbedding(model_name="sentence-transformers/all-MiniLM-L6-v2")
 #documents = [Document(text="Indian parliament elections happened in April-May 2024. BJP Party won."),
-#             Document(text="Indian parliament elections happened in April-May 2021. XYZ Party won."),
-#             Document(text="Indian parliament elections happened in 2020. ABC Party won."),
 #            ]
 #index = VectorStoreIndex.from_documents(
 #    documents,
 #)
 vector_store = ChromaVectorStore(chroma_collection=collection)
 index = VectorStoreIndex.from_vector_store(vector_store, embed_model=Settings.embed_model)
-query_engine = index.as_query_engine()
+query_engine = index.as_query_engine(
+    similarity_top_k=3,
+    vector_store_query_mode="default",
+#    filters=MetadataFilters(
+#        filters=[
+#            ExactMatchFilter(key="state", value=cs),
+#        ]
+#    ),
+    alpha=None,
+    doc_ids=None,
+))
+chat_engine = index.as_chat_engine(chat_mode="condense_question", verbose=True)
 
 def upload_file(filepath):
     documents = SimpleDirectoryReader(filepath).load_data()
     index = VectorStoreIndex.from_documents(documents)
-    query_engine = index.as_query_engine()
+    #query_engine = index.as_query_engine()
+    chat_engine = index.as_chat_engine(chat_mode="condense_question", verbose=True)
     return filepath
 
+def resetChat():
+    chat_engine.reset()
+    return True
+
 def rag(input_text, jezik, file):
     if (file):
 #        documents = []
@@ -131,16 +146,20 @@ def rag(input_text, jezik, file):
                 Settings.llm.system_prompt = system_sr + "Call centar telefon je 12755 za Crnu Goru, 0800 31111 za BIH, 070 700 700 u Sloveniji, 19900 u Srbiji, 095 1000 444 za hrvatske korisnike."
         if (o_jezik!='N/A'):
             input_text += " - odgovori " + o_jezik + "."
-        query_engine = index.as_query_engine()
-        return query_engine.query(input_text)
+#        return query_engine.query(input_text)
+        return chat_engine.chat(input_text)
 
 iface = gr.Interface(fn=rag, inputs=[gr.Textbox(label="Pitanje:", lines=6),
                                      gr.Dropdown(["slovenski", "hrvatski", "srpski", "makedonski", "Eksperimentalna opcija"], value="srpski", label="Jezik", info="N/A"),
-                                     gr.File()], 
+                                     gr.File(),
+                                     b=gr.Button(label="Resetuj razgovor")
+                                    ], 
                      outputs=[gr.Textbox(label="Odgovor:", lines=6)], 
                      title="Kako Vam mogu pomoći?",
-                     description= "UChat"
+                     description="UChat"
                     )
+b.click(resetChat, b)
+
 
 #with gr.Blocks() as iface:
 #    gr.Markdown("Uchat")