Update app.py

app.py

@@ -44,7 +44,7 @@ CHROMA_PDF = './chroma/kkg/pdf'
 CHROMA_WORD = './chroma/kkg/word'
 CHROMA_EXCEL = './chroma/kkg/excel'
 #HuggingFace Model name--------------------------------
-MODEL_NAME_HF  = "mistralai/Mixtral-8x7B-Instruct-v0.1"
+MODEL_NAME_HF  = "HuggingFaceH4/zephyr-7b-alpha" #"mistralai/Mixtral-8x7B-Instruct-v0.1"
 
 #HuggingFace Reop ID--------------------------------
 #repo_id = "meta-llama/Llama-2-13b-chat-hf"   
@@ -159,8 +159,6 @@ def add_text2(chatbot, prompt):
         chatbot = chatbot + [("", "Prompt fehlt!")]
     else:
         chatbot = chatbot + [(prompt, None)]
-    print("chatbot nach add_text............")
-    print(chatbot)
     return chatbot, prompt, ""
 
     
@@ -214,6 +212,11 @@ def generate_text (prompt, chatbot, history, vektordatenbank, retriever, top_p=0
             top_p=top_p,
             repetition_penalty=repetition_penalty
         )
+        #######################################################
+        #Alternativ, wenn repro_id gegeben:
+        # Verwenden Sie die InferenceApi von huggingface_hub
+        llm = InferenceApi(repo_id, token=hf_token)
+
         
         #Prompt an history anhängen und einen Text daraus machen
         history_text_und_prompt = generate_prompt_with_history(prompt, history) 
@@ -271,7 +274,7 @@ def generate_auswahl(prompt_in, file, file_history, chatbot, history, anzahl_doc
         #summary += " ".join(['Dokument: ' + str(doc['titel']) + '  Seite: ' + str(doc['seite']) + '\nAuschnitt: ' + str(doc["content"]) for doc in results['relevant_docs']])
         summary += " ".join([
             '<b>\nDokument: </b> <span style="color: #BB70FC;">' + str(doc['titel']) + '</span>  '
-            '<span style="color: red;"> (Seite:</span> ' + str(doc['seite']) + ')<br>'
+            ' (<b>Seite:</b></span> <span style="color: red;">' + str(doc['seite']) + ')<br>'
             '<b>Auschnitt:</b> ' + str(doc["content"]) + '\n'
             for doc in results['relevant_docs']
         ])