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Update app.py
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app.py
CHANGED
@@ -21,10 +21,11 @@ from tqdm.auto import tqdm
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FILE_PATH = "anjibot_chunks.json"
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BATCH_SIZE = 384
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INDEX_NAME = "groq-llama-3-rag"
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PINECONE_API_KEY = os.getenv("PINECONE_API_KEY")
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GROQ_API_KEY = os.getenv("GROQ_API_KEY")
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DIMS = 768
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encoder = SentenceTransformer('dwzhu/e5-base-4k')
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with open(FILE_PATH, 'r') as file:
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data= json.load(file)
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@@ -65,7 +66,7 @@ def get_docs(query: str, top_k: int) -> list[str]:
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res = index.query(vector=xq.tolist(), top_k=top_k, include_metadata=True)
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return [x["metadata"]['content'] for x in res["matches"]]
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def get_response(query: str, docs: list[str]
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system_message = (
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"You are Anjibot, the AI course rep of 400 Level Computer Science department. You are always helpful, jovial, can be sarcastic but still sweet.\n"
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"Provide the answer to class-related queries using\n"
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@@ -90,14 +91,11 @@ def get_response(query: str, docs: list[str], groq_client: any) -> str:
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def handle_query(user_query: str):
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# Initialize Groq client
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groq_client = Groq(api_key=GROQ_API_KEY)
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# Get relevant documents
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docs = get_docs(user_query, top_k=5)
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# Generate and return response
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response = get_response(user_query, docs
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for word in response.split():
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yield word + " "
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FILE_PATH = "anjibot_chunks.json"
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BATCH_SIZE = 384
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INDEX_NAME = "groq-llama-3-rag"
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PINECONE_API_KEY = os.getenv("PINECONE_API_KEY")
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GROQ_API_KEY = os.getenv("GROQ_API_KEY")
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DIMS = 768
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encoder = SentenceTransformer('dwzhu/e5-base-4k')
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groq_client = Groq(api_key=GROQ_API_KEY)
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with open(FILE_PATH, 'r') as file:
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data= json.load(file)
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res = index.query(vector=xq.tolist(), top_k=top_k, include_metadata=True)
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return [x["metadata"]['content'] for x in res["matches"]]
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def get_response(query: str, docs: list[str]) -> str:
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system_message = (
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"You are Anjibot, the AI course rep of 400 Level Computer Science department. You are always helpful, jovial, can be sarcastic but still sweet.\n"
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"Provide the answer to class-related queries using\n"
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def handle_query(user_query: str):
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# Get relevant documents
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docs = get_docs(user_query, top_k=5)
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# Generate and return response
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response = get_response(user_query, docs=docs)
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for word in response.split():
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yield word + " "
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