mirror of
https://github.com/BoardWare-Genius/jarvis-models.git
synced 2025-12-13 16:53:24 +00:00
fix: chroma setting url and key
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@ -40,6 +40,9 @@ class Chat(Blackbox):
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user_stop = settings.get("stop")
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user_frequency_penalty = settings.get("frequency_penalty")
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user_presence_penalty = settings.get("presence_penalty")
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user_model_url = settings.get("model_url")
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user_model_key = settings.get("model_key")
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if user_context == None:
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user_context = []
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@ -73,14 +76,19 @@ class Chat(Blackbox):
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if user_presence_penalty is None or user_presence_penalty == "":
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user_presence_penalty = 0.8
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if user_model_url is None or user_model_url.isspace() or user_model_url == "":
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user_model_url = "http://120.196.116.194:48892/v1/chat/completions"
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if user_model_key is None or user_model_key.isspace() or user_model_key == "":
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user_model_key = "YOUR_API_KEY"
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# gpt-4, gpt-3.5-turbo
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if re.search(r"gpt", user_model_name):
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url = 'https://api.openai.com/v1/completions'
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key = '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'
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else:
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url = 'http://120.196.116.194:48892/v1/chat/completions'
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key = 'YOUR_API_KEY'
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url = user_model_url
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key = user_model_key
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prompt_template = [
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{"role": "system", "content": user_template},
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@ -6,7 +6,10 @@ from .blackbox import Blackbox
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from .chat import Chat
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from .chroma_query import ChromaQuery
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from ..log.logging_time import logging_time
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import logging
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logger = logging.getLogger
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DEFAULT_COLLECTION_ID = "123"
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from injector import singleton,inject
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@ -25,18 +28,67 @@ class ChromaChat(Blackbox):
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data = args[0]
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return isinstance(data, list)
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def processing(self, question, context: list) -> str:
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@logging_time(logger=logger)
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def processing(self, question: str, context: list, settings: dict) -> str:
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if settings is None:
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settings = {}
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# # chat setting
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user_model_name = settings.get("model_name")
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user_context = context
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user_question = question
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user_template = settings.get("template")
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user_temperature = settings.get("temperature")
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user_top_p = settings.get("top_p")
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user_n = settings.get("n")
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user_max_tokens = settings.get("max_tokens")
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user_stop = settings.get("stop")
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user_frequency_penalty = settings.get("frequency_penalty")
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user_presence_penalty = settings.get("presence_penalty")
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# # chroma_query settings
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chroma_embedding_model = settings.get("chroma_embedding_model")
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chroma_host = settings.get("chroma_host")
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chroma_port = settings.get("chroma_port")
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chroma_collection_id = settings.get("chroma_collection_id")
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chroma_n_results = settings.get("chroma_n_results")
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if context == None:
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context = []
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# load or create collection
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collection_id = DEFAULT_COLLECTION_ID
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if user_question is None:
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return JSONResponse(content={"error": "question is required"}, status_code=status.HTTP_400_BAD_REQUEST)
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# query it
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chroma_result = self.chroma_query(question, collection_id)
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chroma_settings_json={
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"chroma_embedding_model": chroma_embedding_model,
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"chroma_host": chroma_host,
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"chroma_port": chroma_port,
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"chroma_collection_id": chroma_collection_id,
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"chroma_n_results": chroma_n_results
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}
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fast_question = "问题: "+ question + "。根据问题,总结以下内容和来源:" + chroma_result
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response = self.chat(model_name="Qwen1.5-14B-Chat", prompt=fast_question, template='', context=context, temperature=0.8, top_p=0.8, n=1, max_tokens=1024, stop=100,frequency_penalty=0.5,presence_penalty=0.8)
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# chroma answer
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chroma_result = self.chroma_query(user_question, chroma_settings_json)
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# chat prompt
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fast_question = f"问题: {user_question}。根据问题,总结以下内容和来源:{chroma_result}"
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chat_settings_json = {
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"model_name": user_model_name,
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"context": user_context,
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"template": user_template,
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"temperature": user_temperature,
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"top_p": user_top_p,
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"n": user_n,
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"max_tokens": user_max_tokens,
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"stop": user_stop,
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"frequency_penalty": user_frequency_penalty,
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"presence_penalty": user_presence_penalty
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}
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# chat answer
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response = self.chat(fast_question, chat_settings_json)
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return response
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@ -49,10 +101,8 @@ class ChromaChat(Blackbox):
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user_question = data.get("question")
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user_context = data.get("context")
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if user_question is None:
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return JSONResponse(content={"error": "question is required"}, status_code=status.HTTP_400_BAD_REQUEST)
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setting: dict = data.get("settings")
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return JSONResponse(
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content={"response": self.processing(user_question, user_context)},
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content={"response": self.processing(user_question, user_context, setting)},
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status_code=status.HTTP_200_OK)
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@ -6,8 +6,11 @@ from .blackbox import Blackbox
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import chromadb
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from chromadb.utils import embedding_functions
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from ..utils import chroma_setting
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import logging
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from ..log.logging_time import logging_time
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import re
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logger = logging.getLogger
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DEFAULT_COLLECTION_ID = "123"
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from injector import singleton
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@ -16,10 +19,11 @@ class ChromaQuery(Blackbox):
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def __init__(self, *args, **kwargs) -> None:
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# config = read_yaml(args[0])
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# load embedding model
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self.embedding_model = embedding_functions.SentenceTransformerEmbeddingFunction(model_name="/model/Weight/BAAI/bge-small-en-v1.5", device = "cuda")
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# load chromadb
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self.client = chromadb.HttpClient(host='10.6.82.192', port=8000)
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# load chromadb and embedding model
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self.embedding_model_1 = embedding_functions.SentenceTransformerEmbeddingFunction(model_name="/model/Weight/BAAI/bge-small-en-v1.5", device = "cuda")
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# self.embedding_model_2 = embedding_functions.SentenceTransformerEmbeddingFunction(model_name="/model/Weight/BAAI/bge-small-en-v1.5", device = "cuda")
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self.client_1 = chromadb.HttpClient(host='10.6.82.192', port=8000)
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# self.client_2 = chromadb.HttpClient(host='10.6.82.192', port=8000)
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def __call__(self, *args, **kwargs):
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return self.processing(*args, **kwargs)
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@ -28,14 +32,52 @@ class ChromaQuery(Blackbox):
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data = args[0]
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return isinstance(data, list)
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def processing(self, question: str, collection_id) -> str:
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@logging_time(logger=logger)
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def processing(self, question: str, settings: dict) -> str:
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# load or create collection
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collection = self.client.get_collection(collection_id, embedding_function=self.embedding_model)
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if settings is None:
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settings = {}
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usr_question = question
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# # chroma_query settings
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chroma_embedding_model = settings.get("chroma_embedding_model")
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chroma_host = settings.get("chroma_host")
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chroma_port = settings.get("chroma_port")
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chroma_collection_id = settings.get("chroma_collection_id")
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chroma_n_results = settings.get("chroma_n_results")
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if usr_question is None:
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return JSONResponse(content={"error": "question is required"}, status_code=status.HTTP_400_BAD_REQUEST)
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if chroma_embedding_model is None or chroma_embedding_model.isspace() or chroma_embedding_model == "":
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chroma_embedding_model = "bge-small-en-v1.5"
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if chroma_host is None or chroma_host.isspace() or chroma_host == "":
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chroma_host = "10.6.82.192"
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if chroma_port is None or chroma_port.isspace() or chroma_port == "":
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chroma_port = "8000"
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if chroma_collection_id is None or chroma_collection_id.isspace() or chroma_collection_id == "":
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chroma_collection_id = DEFAULT_COLLECTION_ID
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if chroma_n_results is None or chroma_n_results == "":
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chroma_n_results = 3
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# load client
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if re.search(r"10.6.82.192", chroma_host) and re.search(r"8000", chroma_port):
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client = self.client_1
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if re.search(r"bge-small-en-v1.5", chroma_embedding_model):
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embedding_model = self.embedding_model_1
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# load collection
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collection = client.get_collection(chroma_collection_id, embedding_function=embedding_model)
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# query it
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results = collection.query(
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query_texts=[question],
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query_texts=[usr_question],
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n_results=3,
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)
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@ -50,14 +92,8 @@ class ChromaQuery(Blackbox):
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return JSONResponse(content={"error": "json parse error"}, status_code=status.HTTP_400_BAD_REQUEST)
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user_question = data.get("question")
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user_collection_id = data.get("collection_id")
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if user_question is None:
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return JSONResponse(content={"error": "question is required"}, status_code=status.HTTP_400_BAD_REQUEST)
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if user_collection_id is None:
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user_collection_id = DEFAULT_COLLECTION_ID
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setting = data.get("settings")
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return JSONResponse(
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content={"response": self.processing(user_question, user_collection_id)},
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content={"response": self.processing(user_question, setting)},
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status_code=status.HTTP_200_OK)
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