Spaces:
Sleeping
Sleeping
add keyword list and remove some logs
Browse files- app/api/rag_routes.py +7 -2
app/api/rag_routes.py
CHANGED
@@ -59,6 +59,7 @@ logger = logging.getLogger(__name__)
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# Configure Google Gemini API
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GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
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genai.configure(api_key=GOOGLE_API_KEY)
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# Create router
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router = APIRouter(
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@@ -70,7 +71,7 @@ fix_request = PromptTemplate(
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template = """Goal:
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Your task is to extract important keywords from the user's current request, optionally using chat history if relevant.
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You will receive a conversation history and the user's current message.
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-
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Return Format:
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Only return keywords (comma-separated, no extra explanation).
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@@ -80,6 +81,9 @@ If the current message IS related to the chat history: Return a refined set of k
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Warning:
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Only use chat history if the current message is clearly related to the prior context.
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Conversation History:
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{chat_history}
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@@ -238,6 +242,7 @@ async def chat(request: ChatRequest, background_tasks: BackgroundTasks):
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)
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prompt_request = fix_request.format(
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question=request.question,
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chat_history=chat_history
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)
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@@ -282,7 +287,7 @@ async def chat(request: ChatRequest, background_tasks: BackgroundTasks):
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question=request.question,
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chat_history=chat_history
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)
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-
logger.info(f"
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# Generate response
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response = model.generate_content(prompt_text)
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# Configure Google Gemini API
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GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
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genai.configure(api_key=GOOGLE_API_KEY)
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+
KEYWORD_LIST = os.getenv("KEYWORDS")
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# Create router
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router = APIRouter(
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template = """Goal:
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Your task is to extract important keywords from the user's current request, optionally using chat history if relevant.
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You will receive a conversation history and the user's current message.
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+
Pick 2-3 keywords from "keyword list" that best represent the user's intent.
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Return Format:
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Only return keywords (comma-separated, no extra explanation).
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Warning:
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Only use chat history if the current message is clearly related to the prior context.
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Keyword list:
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{keyword_list}
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Conversation History:
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{chat_history}
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)
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prompt_request = fix_request.format(
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keyword_list=KEYWORD_LIST,
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question=request.question,
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chat_history=chat_history
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)
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question=request.question,
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chat_history=chat_history
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)
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logger.info(f"Context: {context}")
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# Generate response
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response = model.generate_content(prompt_text)
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