Update app.py
Browse files
app.py
CHANGED
@@ -209,7 +209,7 @@ def generate_text (prompt, chatbot, history, vektordatenbank, retriever, top_p=0
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endpoint_url=f"https://api-inference.huggingface.co/models/{MODEL_NAME_HF}",
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api_key=hf_token,
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temperature= 0.5,
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max_length =
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top_k=top_k,
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top_p=top_p,
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repetition_penalty=repetition_penalty
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@@ -222,9 +222,6 @@ def generate_text (prompt, chatbot, history, vektordatenbank, retriever, top_p=0
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print("LLM aufrufen mit RAG: ...........")
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#result = rag_chain(history_text_und_prompt, vektordatenbank, ANZAHL_DOCS)
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result = rag_chain(llm, history_text_und_prompt, retriever)
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print("result regchain.....................")
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print(result)
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except Exception as e:
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raise gr.Error(e)
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@@ -254,7 +251,6 @@ def generate_auswahl(prompt_in, file, file_history, chatbot, history, anzahl_doc
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splits = document_loading_splitting()
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if splits:
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vektordatenbank, retriever = document_storage_chroma(splits)
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print("db done............................")
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#kein Bild hochgeladen -> auf Text antworten...
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status = "Antwort der KI ..."
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@@ -275,8 +271,8 @@ def generate_auswahl(prompt_in, file, file_history, chatbot, history, anzahl_doc
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#summary += " ".join(['Dokument: ' + str(doc['titel']) + ' Seite: ' + str(doc['seite']) + '\nAuschnitt: ' + str(doc["content"]) for doc in results['relevant_docs']])
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summary += " ".join([
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'<b>\nDokument: </b> <span style="color: #BB70FC;">' + str(doc['titel']) + '</span> '
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'<span style="color: red;">Seite:</span> ' + str(doc['seite']) + '<br>'
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'<b>Auschnitt:</b> ' + str(doc["content"])
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for doc in results['relevant_docs']
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])
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history = history + [[prompt_in, summary]]
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endpoint_url=f"https://api-inference.huggingface.co/models/{MODEL_NAME_HF}",
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api_key=hf_token,
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temperature= 0.5,
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+
max_length = 2048,
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top_k=top_k,
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top_p=top_p,
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repetition_penalty=repetition_penalty
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print("LLM aufrufen mit RAG: ...........")
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#result = rag_chain(history_text_und_prompt, vektordatenbank, ANZAHL_DOCS)
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result = rag_chain(llm, history_text_und_prompt, retriever)
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except Exception as e:
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raise gr.Error(e)
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splits = document_loading_splitting()
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if splits:
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vektordatenbank, retriever = document_storage_chroma(splits)
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#kein Bild hochgeladen -> auf Text antworten...
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status = "Antwort der KI ..."
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#summary += " ".join(['Dokument: ' + str(doc['titel']) + ' Seite: ' + str(doc['seite']) + '\nAuschnitt: ' + str(doc["content"]) for doc in results['relevant_docs']])
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summary += " ".join([
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'<b>\nDokument: </b> <span style="color: #BB70FC;">' + str(doc['titel']) + '</span> '
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'<span style="color: red;"> (Seite:</span> ' + str(doc['seite']) + ')<br>'
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'<b>Auschnitt:</b> ' + str(doc["content"]) + '\n'
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for doc in results['relevant_docs']
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])
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history = history + [[prompt_in, summary]]
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