oceansweep
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App_Function_Libraries/Summarization/Local_Summarization_Lib.py
CHANGED
@@ -35,6 +35,25 @@ from App_Function_Libraries.Utils.Utils import load_and_log_configs, extract_tex
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logger = logging.getLogger()
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# FIXME - temp is not used
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def summarize_with_local_llm(input_data, custom_prompt_arg, temp, system_message=None):
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try:
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@@ -108,7 +127,7 @@ def summarize_with_local_llm(input_data, custom_prompt_arg, temp, system_message
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return "Local LLM: Error occurred while processing summary"
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-
def summarize_with_llama(input_data, custom_prompt, api_url="http://127.0.0.1:8080/completion",
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try:
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logging.debug("Llama.cpp: Loading and validating configurations")
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loaded_config_data = load_and_log_configs()
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@@ -138,12 +157,12 @@ def summarize_with_llama(input_data, custom_prompt, api_url="http://127.0.0.1:80
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logging.debug("Llama.cpp: Using provided string data for summarization")
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data = input_data
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logging.debug(f"Llama
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logging.debug(f"Llama
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if isinstance(data, dict) and 'summary' in data:
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# If the loaded data is a dictionary and already contains a summary, return it
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logging.debug("Llama
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return data['summary']
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# If the loaded data is a list of segment dictionaries or a string, proceed with summarization
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@@ -153,7 +172,7 @@ def summarize_with_llama(input_data, custom_prompt, api_url="http://127.0.0.1:80
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elif isinstance(data, str):
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text = data
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else:
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raise ValueError("Llama
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headers = {
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'accept': 'application/json',
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@@ -162,13 +181,17 @@ def summarize_with_llama(input_data, custom_prompt, api_url="http://127.0.0.1:80
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if len(api_key) > 5:
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headers['Authorization'] = f'Bearer {api_key}'
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llama_prompt = f"{custom_prompt} \n\n\n\n{text}"
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if system_message is None:
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system_message = "You are a helpful AI assistant."
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logging.debug("
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if system_message is None:
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system_message = "You are a helpful AI assistant."
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data = {
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"messages": [
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{"role": "system", "content": system_message},
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@@ -201,7 +224,7 @@ def summarize_with_llama(input_data, custom_prompt, api_url="http://127.0.0.1:80
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# https://lite.koboldai.net/koboldcpp_api#/api%2Fv1/post_api_v1_generate
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def summarize_with_kobold(input_data, api_key, custom_prompt_input, kobold_api_ip="http://127.0.0.1:5001/api/v1/generate"
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logging.debug("Kobold: Summarization process starting...")
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try:
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logging.debug("Kobold: Loading and validating configurations")
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@@ -253,9 +276,12 @@ def summarize_with_kobold(input_data, api_key, custom_prompt_input, kobold_api_i
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'accept': 'application/json',
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'content-type': 'application/json',
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}
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-
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logging.debug("kobold: Prompt being sent is {kobold_prompt}")
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# FIXME
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# Values literally c/p from the api docs....
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@@ -269,12 +295,12 @@ def summarize_with_kobold(input_data, api_key, custom_prompt_input, kobold_api_i
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#"rep_penalty": 1.0,
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}
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logging.debug("
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print("
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kobold_api_ip = loaded_config_data['local_api_ip']['kobold']
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try:
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response = requests.post(kobold_api_ip, headers=headers, json=data)
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logging.debug("
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if response.status_code == 200:
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try:
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@@ -303,7 +329,7 @@ def summarize_with_kobold(input_data, api_key, custom_prompt_input, kobold_api_i
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# https://github.com/oobabooga/text-generation-webui/wiki/12-%E2%80%90-OpenAI-API
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def summarize_with_oobabooga(input_data, api_key, custom_prompt, api_url="http://127.0.0.1:5000/v1/chat/completions"
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logging.debug("Oobabooga: Summarization process starting...")
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try:
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logging.debug("Oobabooga: Loading and validating configurations")
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@@ -356,9 +382,13 @@ def summarize_with_oobabooga(input_data, api_key, custom_prompt, api_url="http:/
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'content-type': 'application/json',
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}
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-
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-
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-
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ooba_prompt = f"{text}" + f"\n\n\n\n{custom_prompt}"
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logging.debug("ooba: Prompt being sent is {ooba_prompt}")
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@@ -392,8 +422,7 @@ def summarize_with_oobabooga(input_data, api_key, custom_prompt, api_url="http:/
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return f"ooba: Error occurred while processing summary with oobabooga: {str(e)}"
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-
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def summarize_with_tabbyapi(input_data, custom_prompt_input, api_key=None, api_IP="http://127.0.0.1:5000/v1/chat/completions", temp=None, system_message=None):
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logging.debug("TabbyAPI: Summarization process starting...")
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try:
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logging.debug("TabbyAPI: Loading and validating configurations")
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@@ -448,6 +477,11 @@ def summarize_with_tabbyapi(input_data, custom_prompt_input, api_key=None, api_I
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if system_message is None:
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system_message = "You are a helpful AI assistant."
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headers = {
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'Authorization': f'Bearer {api_key}',
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'Content-Type': 'application/json'
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@@ -501,10 +535,10 @@ def summarize_with_vllm(
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input_data: Union[str, dict, list],
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custom_prompt_input: str,
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api_key: str = None,
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vllm_api_url: str = "http://127.0.0.1:8000/v1/chat/completions",
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model: str = None,
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system_prompt: str = None,
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temp: float = 0.7
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) -> str:
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logging.debug("vLLM: Summarization process starting...")
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try:
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@@ -556,6 +590,11 @@ def summarize_with_vllm(
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if system_prompt is None:
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system_prompt = "You are a helpful AI assistant."
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model = model or loaded_config_data['models']['vllm']
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if system_prompt is None:
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system_prompt = "You are a helpful AI assistant."
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@@ -602,7 +641,7 @@ def summarize_with_vllm(
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# FIXME - update to be a summarize request
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def summarize_with_ollama(input_data, custom_prompt, api_url="http://127.0.0.1:11434/api/generate",
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try:
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logging.debug("ollama: Loading and validating configurations")
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loaded_config_data = load_and_log_configs()
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@@ -651,6 +690,11 @@ def summarize_with_ollama(input_data, custom_prompt, api_url="http://127.0.0.1:1
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else:
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raise ValueError("Ollama: Invalid input data format")
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headers = {
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'accept': 'application/json',
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'content-type': 'application/json',
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@@ -761,6 +805,11 @@ def summarize_with_custom_openai(api_key, input_data, custom_prompt_arg, temp=No
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logging.debug(f"Custom OpenAI API: Extracted text (first 500 chars): {text[:500]}...")
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logging.debug(f"v: Custom prompt: {custom_prompt_arg}")
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openai_model = loaded_config_data['models']['openai'] or "gpt-4o"
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logging.debug(f"Custom OpenAI API: Using model: {openai_model}")
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logger = logging.getLogger()
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summarizer_prompt = """
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<s>You are a bulleted notes specialist. [INST]```When creating comprehensive bulleted notes, you should follow these guidelines: Use multiple headings based on the referenced topics, not categories like quotes or terms. Headings should be surrounded by bold formatting and not be listed as bullet points themselves. Leave no space between headings and their corresponding list items underneath. Important terms within the content should be emphasized by setting them in bold font. Any text that ends with a colon should also be bolded. Before submitting your response, review the instructions, and make any corrections necessary to adhered to the specified format. Do not reference these instructions within the notes.``` \nBased on the content between backticks create comprehensive bulleted notes.[/INST]
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**Bulleted Note Creation Guidelines**
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**Headings**:
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- Based on referenced topics, not categories like quotes or terms
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- Surrounded by **bold** formatting
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- Not listed as bullet points
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- No space between headings and list items underneath
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**Emphasis**:
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- **Important terms** set in bold font
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- **Text ending in a colon**: also bolded
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**Review**:
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- Ensure adherence to specified format
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- Do not reference these instructions in your response.</s>[INST] {{ .Prompt }} [/INST]
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"""
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# FIXME - temp is not used
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def summarize_with_local_llm(input_data, custom_prompt_arg, temp, system_message=None):
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try:
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return "Local LLM: Error occurred while processing summary"
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def summarize_with_llama(input_data, custom_prompt, api_key=None, temp=None, system_message=None, api_url="http://127.0.0.1:8080/completion",):
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try:
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logging.debug("Llama.cpp: Loading and validating configurations")
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loaded_config_data = load_and_log_configs()
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logging.debug("Llama.cpp: Using provided string data for summarization")
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data = input_data
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logging.debug(f"Llama Summarize: Loaded data: {data}")
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logging.debug(f"Llama Summarize: Type of data: {type(data)}")
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if isinstance(data, dict) and 'summary' in data:
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# If the loaded data is a dictionary and already contains a summary, return it
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logging.debug("Llama Summarize: Summary already exists in the loaded data")
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return data['summary']
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# If the loaded data is a list of segment dictionaries or a string, proceed with summarization
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elif isinstance(data, str):
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text = data
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else:
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raise ValueError("Llama Summarize: Invalid input data format")
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headers = {
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'accept': 'application/json',
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if len(api_key) > 5:
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headers['Authorization'] = f'Bearer {api_key}'
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if system_message is None:
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system_message = "You are a helpful AI assistant."
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logging.debug(f":Llama Summarize: System Prompt being sent is {system_message}")
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if system_message is None:
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system_message = "You are a helpful AI assistant."
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if custom_prompt is None:
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llama_prompt = f"{summarizer_prompt}\n\n\n\n{text}"
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else:
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llama_prompt = f"{custom_prompt}\n\n\n\n{text}"
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data = {
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"messages": [
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{"role": "system", "content": system_message},
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# https://lite.koboldai.net/koboldcpp_api#/api%2Fv1/post_api_v1_generate
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def summarize_with_kobold(input_data, api_key, custom_prompt_input, system_message=None, temp=None, kobold_api_ip="http://127.0.0.1:5001/api/v1/generate"):
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logging.debug("Kobold: Summarization process starting...")
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try:
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logging.debug("Kobold: Loading and validating configurations")
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'accept': 'application/json',
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'content-type': 'application/json',
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}
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if custom_prompt_input is None:
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kobold_prompt = f"{summarizer_prompt}\n\n\n\n{text}"
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else:
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kobold_prompt = f"{custom_prompt_input}\n\n\n\n{text}"
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logging.debug("Kobold summarization: Prompt being sent is {kobold_prompt}")
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# FIXME
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# Values literally c/p from the api docs....
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#"rep_penalty": 1.0,
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}
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logging.debug("Kobold Summarization: Submitting request to API endpoint")
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print("Kobold Summarization: Submitting request to API endpoint")
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kobold_api_ip = loaded_config_data['local_api_ip']['kobold']
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try:
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response = requests.post(kobold_api_ip, headers=headers, json=data)
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logging.debug("Kobold Summarization: API Response Status Code: %d", response.status_code)
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if response.status_code == 200:
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try:
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# https://github.com/oobabooga/text-generation-webui/wiki/12-%E2%80%90-OpenAI-API
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def summarize_with_oobabooga(input_data, api_key, custom_prompt, system_message=None, temp=None, api_url="http://127.0.0.1:5000/v1/chat/completions"):
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logging.debug("Oobabooga: Summarization process starting...")
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try:
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logging.debug("Oobabooga: Loading and validating configurations")
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'content-type': 'application/json',
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}
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if custom_prompt is None:
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custom_prompt = f"{summarizer_prompt}\n\n\n\n{text}"
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else:
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custom_prompt = f"{custom_prompt}\n\n\n\n{text}"
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logging.debug("Ooba Summarize: Prompt being sent is {kobold_prompt}")
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ooba_prompt = f"{text}" + f"\n\n\n\n{custom_prompt}"
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logging.debug("ooba: Prompt being sent is {ooba_prompt}")
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return f"ooba: Error occurred while processing summary with oobabooga: {str(e)}"
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def summarize_with_tabbyapi(input_data, custom_prompt_input, system_message=None, api_key=None, temp=None, api_IP="http://127.0.0.1:5000/v1/chat/completions"):
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logging.debug("TabbyAPI: Summarization process starting...")
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try:
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logging.debug("TabbyAPI: Loading and validating configurations")
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if system_message is None:
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system_message = "You are a helpful AI assistant."
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if custom_prompt_input is None:
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custom_prompt_input = f"{summarizer_prompt}\n\n\n\n{text}"
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else:
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custom_prompt_input = f"{custom_prompt_input}\n\n\n\n{text}"
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headers = {
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'Authorization': f'Bearer {api_key}',
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'Content-Type': 'application/json'
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input_data: Union[str, dict, list],
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custom_prompt_input: str,
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api_key: str = None,
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model: str = None,
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system_prompt: str = None,
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temp: float = 0.7,
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vllm_api_url: str = "http://127.0.0.1:8000/v1/chat/completions"
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) -> str:
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logging.debug("vLLM: Summarization process starting...")
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try:
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if system_prompt is None:
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system_prompt = "You are a helpful AI assistant."
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if custom_prompt_input is None:
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custom_prompt_input = f"{summarizer_prompt}\n\n\n\n{text}"
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else:
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custom_prompt_input = f"{custom_prompt_input}\n\n\n\n{text}"
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model = model or loaded_config_data['models']['vllm']
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if system_prompt is None:
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system_prompt = "You are a helpful AI assistant."
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# FIXME - update to be a summarize request
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def summarize_with_ollama(input_data, custom_prompt, api_key=None, temp=None, system_message=None, model=None, api_url="http://127.0.0.1:11434/api/generate",):
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try:
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logging.debug("ollama: Loading and validating configurations")
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loaded_config_data = load_and_log_configs()
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else:
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raise ValueError("Ollama: Invalid input data format")
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if custom_prompt is None:
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custom_prompt = f"{summarizer_prompt}\n\n\n\n{text}"
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else:
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custom_prompt = f"{custom_prompt}\n\n\n\n{text}"
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headers = {
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'accept': 'application/json',
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'content-type': 'application/json',
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logging.debug(f"Custom OpenAI API: Extracted text (first 500 chars): {text[:500]}...")
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logging.debug(f"v: Custom prompt: {custom_prompt_arg}")
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if input_data is None:
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input_data = f"{summarizer_prompt}\n\n\n\n{text}"
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else:
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input_data = f"{input_data}\n\n\n\n{text}"
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openai_model = loaded_config_data['models']['openai'] or "gpt-4o"
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logging.debug(f"Custom OpenAI API: Using model: {openai_model}")
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App_Function_Libraries/Summarization/Summarization_General_Lib.py
CHANGED
@@ -30,7 +30,8 @@ from App_Function_Libraries.Chunk_Lib import semantic_chunking, rolling_summariz
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improved_chunking_process
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from App_Function_Libraries.Audio.Diarization_Lib import combine_transcription_and_diarization
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from App_Function_Libraries.Summarization.Local_Summarization_Lib import summarize_with_llama, summarize_with_kobold, \
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-
summarize_with_oobabooga, summarize_with_tabbyapi, summarize_with_vllm, summarize_with_local_llm
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from App_Function_Libraries.DB.DB_Manager import add_media_to_database
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# Import Local
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from App_Function_Libraries.Utils.Utils import load_and_log_configs, load_comprehensive_config, sanitize_filename, \
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@@ -1108,9 +1109,15 @@ def process_video_urls(url_list, num_speakers, whisper_model, custom_prompt_inpu
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def perform_transcription(video_path, offset, whisper_model, vad_filter, diarize=False):
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global segments_json_path
|
1112 |
audio_file_path = convert_to_wav(video_path, offset)
|
|
|
|
|
|
|
1113 |
segments_json_path = audio_file_path.replace('.wav', '.segments.json')
|
|
|
1114 |
|
1115 |
if diarize:
|
1116 |
diarized_json_path = audio_file_path.replace('.wav', '.diarized.json')
|
@@ -1521,16 +1528,22 @@ def process_url(
|
|
1521 |
summary = summarize_with_deepseek(api_key, chunk, custom_prompt_input, temp, system_message)
|
1522 |
elif api_name == "OpenRouter":
|
1523 |
summary = summarize_with_openrouter(api_key, chunk, custom_prompt_input, temp, system_message)
|
|
|
1524 |
elif api_name == "Llama.cpp":
|
1525 |
-
summary = summarize_with_llama(chunk, custom_prompt_input, temp, system_message)
|
1526 |
elif api_name == "Kobold":
|
1527 |
-
summary = summarize_with_kobold(chunk, custom_prompt_input,
|
1528 |
elif api_name == "Ooba":
|
1529 |
-
summary = summarize_with_oobabooga(chunk, custom_prompt_input,
|
1530 |
elif api_name == "Tabbyapi":
|
1531 |
-
summary = summarize_with_tabbyapi(chunk, custom_prompt_input,
|
1532 |
elif api_name == "VLLM":
|
1533 |
-
summary = summarize_with_vllm(chunk, custom_prompt_input,
|
|
|
|
|
|
|
|
|
|
|
1534 |
summarized_chunk_transcriptions.append(summary)
|
1535 |
|
1536 |
# Combine chunked transcriptions into a single file
|
|
|
30 |
improved_chunking_process
|
31 |
from App_Function_Libraries.Audio.Diarization_Lib import combine_transcription_and_diarization
|
32 |
from App_Function_Libraries.Summarization.Local_Summarization_Lib import summarize_with_llama, summarize_with_kobold, \
|
33 |
+
summarize_with_oobabooga, summarize_with_tabbyapi, summarize_with_vllm, summarize_with_local_llm, \
|
34 |
+
summarize_with_ollama, summarize_with_custom_openai
|
35 |
from App_Function_Libraries.DB.DB_Manager import add_media_to_database
|
36 |
# Import Local
|
37 |
from App_Function_Libraries.Utils.Utils import load_and_log_configs, load_comprehensive_config, sanitize_filename, \
|
|
|
1109 |
|
1110 |
|
1111 |
def perform_transcription(video_path, offset, whisper_model, vad_filter, diarize=False):
|
1112 |
+
temp_files = []
|
1113 |
+
logging.info(f"Processing media: {video_path}")
|
1114 |
global segments_json_path
|
1115 |
audio_file_path = convert_to_wav(video_path, offset)
|
1116 |
+
logging.debug(f"Converted audio file: {audio_file_path}")
|
1117 |
+
temp_files.append(audio_file_path)
|
1118 |
+
logging.debug("Replacing audio file with segments.json file")
|
1119 |
segments_json_path = audio_file_path.replace('.wav', '.segments.json')
|
1120 |
+
temp_files.append(segments_json_path)
|
1121 |
|
1122 |
if diarize:
|
1123 |
diarized_json_path = audio_file_path.replace('.wav', '.diarized.json')
|
|
|
1528 |
summary = summarize_with_deepseek(api_key, chunk, custom_prompt_input, temp, system_message)
|
1529 |
elif api_name == "OpenRouter":
|
1530 |
summary = summarize_with_openrouter(api_key, chunk, custom_prompt_input, temp, system_message)
|
1531 |
+
# Local LLM APIs
|
1532 |
elif api_name == "Llama.cpp":
|
1533 |
+
summary = summarize_with_llama(chunk, custom_prompt_input, api_key, temp, system_message)
|
1534 |
elif api_name == "Kobold":
|
1535 |
+
summary = summarize_with_kobold(chunk, None, custom_prompt_input, system_message, temp)
|
1536 |
elif api_name == "Ooba":
|
1537 |
+
summary = summarize_with_oobabooga(chunk, None, custom_prompt_input, system_message, temp)
|
1538 |
elif api_name == "Tabbyapi":
|
1539 |
+
summary = summarize_with_tabbyapi(chunk, custom_prompt_input, system_message, None, temp)
|
1540 |
elif api_name == "VLLM":
|
1541 |
+
summary = summarize_with_vllm(chunk, custom_prompt_input, None, None, system_message)
|
1542 |
+
elif api_name == "Ollama":
|
1543 |
+
summary = summarize_with_ollama(chunk, custom_prompt_input, api_key, temp, system_message, None)
|
1544 |
+
elif api_name == "custom_openai_api":
|
1545 |
+
summary = summarize_with_custom_openai(chunk, custom_prompt_input, api_key, temp=None, system_message=None)
|
1546 |
+
|
1547 |
summarized_chunk_transcriptions.append(summary)
|
1548 |
|
1549 |
# Combine chunked transcriptions into a single file
|