Update app.py
Browse files
app.py
CHANGED
@@ -490,9 +490,6 @@ def generate_text (prompt, chatbot, history, rag_option, model_option, openai_ap
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raise gr.Error("Retrieval Augmented Generation ist erforderlich.")
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if (prompt == ""):
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raise gr.Error("Prompt ist erforderlich.")
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-
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#Prompt an history anhängen und einen Text daraus machen
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history_text_und_prompt = generate_prompt_with_history_openai(prompt, history)
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#history für HuggingFace Models formatieren
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#history_text_und_prompt = generate_prompt_with_history_hf(prompt, history)
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@@ -510,6 +507,8 @@ def generate_text (prompt, chatbot, history, rag_option, model_option, openai_ap
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#Anfrage an OpenAI ----------------------------
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print("OpenAI normal.......................")
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llm = ChatOpenAI(model_name = MODEL_NAME, openai_api_key = openai_api_key, temperature=temperature)#, top_p = top_p)
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else:
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#oder an Hugging Face --------------------------
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llm = HuggingFaceHub(repo_id=repo_id, model_kwargs={"temperature": 0.5, "max_length": 128})
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@@ -517,7 +516,9 @@ def generate_text (prompt, chatbot, history, rag_option, model_option, openai_ap
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#llm = HuggingFaceHub(url_??? = "https://wdgsjd6zf201mufn.us-east-1.aws.endpoints.huggingface.cloud", model_kwargs={"temperature": 0.5, "max_length": 64})
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#llm = HuggingFaceTextGenInference( inference_server_url="http://localhost:8010/", max_new_tokens=max_new_tokens,top_k=10,top_p=top_p,typical_p=0.95,temperature=temperature,repetition_penalty=repetition_penalty,)
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print("HF")
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-
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#zusätzliche Dokumenten Splits aus DB zum Prompt hinzufügen (aus VektorDB - Chroma oder Mongo DB)
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if (rag_option == "An"):
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#muss nur einmal ausgeführt werden...
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raise gr.Error("Retrieval Augmented Generation ist erforderlich.")
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if (prompt == ""):
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raise gr.Error("Prompt ist erforderlich.")
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#history für HuggingFace Models formatieren
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#history_text_und_prompt = generate_prompt_with_history_hf(prompt, history)
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#Anfrage an OpenAI ----------------------------
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print("OpenAI normal.......................")
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llm = ChatOpenAI(model_name = MODEL_NAME, openai_api_key = openai_api_key, temperature=temperature)#, top_p = top_p)
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#Prompt an history anhängen und einen Text daraus machen
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history_text_und_prompt = generate_prompt_with_history_openai(prompt, history)
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else:
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#oder an Hugging Face --------------------------
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llm = HuggingFaceHub(repo_id=repo_id, model_kwargs={"temperature": 0.5, "max_length": 128})
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#llm = HuggingFaceHub(url_??? = "https://wdgsjd6zf201mufn.us-east-1.aws.endpoints.huggingface.cloud", model_kwargs={"temperature": 0.5, "max_length": 64})
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#llm = HuggingFaceTextGenInference( inference_server_url="http://localhost:8010/", max_new_tokens=max_new_tokens,top_k=10,top_p=top_p,typical_p=0.95,temperature=temperature,repetition_penalty=repetition_penalty,)
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print("HF")
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#Prompt an history anhängen und einen Text daraus machen
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history_text_und_prompt = generate_prompt_with_history(prompt, history)
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#zusätzliche Dokumenten Splits aus DB zum Prompt hinzufügen (aus VektorDB - Chroma oder Mongo DB)
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if (rag_option == "An"):
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#muss nur einmal ausgeführt werden...
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