prasadnu commited on
Commit
426cbe0
·
1 Parent(s): 3c2f6db

model changed to Haiku 3.5 for query re=write

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Files changed (1) hide show
  1. semantic_search/query_rewrite.py +1 -25
semantic_search/query_rewrite.py CHANGED
@@ -32,23 +32,6 @@ import utilities.invoke_models as invoke_models
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- bedrock_params = {
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- "max_tokens_to_sample":2048,
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- "temperature":0.0001,
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- "top_k":250,
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- "top_p":1,
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- "stop_sequences":["\\n\\nHuman:"]
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- }
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- bedrock_region="us-east-1"
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-
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- #boto3_bedrock = boto3.client(service_name="bedrock-runtime", endpoint_url=f"https://bedrock-runtime.{bedrock_region}.amazonaws.com")
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- boto3_bedrock = boto3.client(service_name="bedrock-runtime", config=Config(region_name=bedrock_region))
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-
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- bedrock_titan_llm = Bedrock(model_id="anthropic.claude-instant-v1", client=boto3_bedrock)
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- bedrock_titan_llm.model_kwargs = bedrock_params
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- bedrock_embeddings = BedrockEmbeddings(model_id='amazon.titan-embed-text-v1',client=boto3_bedrock)
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-
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-
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  schema = """{{
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  "content": "Brief summary of a retail product",
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  "attributes": {{
@@ -254,14 +237,9 @@ def get_new_query_res(query):
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  res = invoke_models.invoke_llm_model( prompt_.format(query=query,schema = schema) ,False)
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  inter_query = res[7:-3].replace('\\"',"'").replace("\n","")
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- print("inter_query")
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- print(inter_query)
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  query_struct = StructuredQueryOutputParser.from_components().parse(inter_query)
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- print("query_struct")
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- print(query_struct)
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  opts = OpenSearchTranslator()
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  result_query_llm = opts.visit_structured_query(query_struct)[1]['filter']
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- print(result_query_llm)
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  draft_new_query = {'bool':{'should':[],'must':[]}}
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  if('bool' in result_query_llm and ('must' in result_query_llm['bool'] or 'should' in result_query_llm['bool'])):
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  #draft_new_query['bool']['should'] = []
@@ -331,9 +309,7 @@ def get_new_query_res(query):
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  # return words_stem.strip()
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  #imp_item = stem_(imp_item)
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- print("imp_item---------------")
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- print(imp_item)
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- print(query_)
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  if('must' in query_['bool']):
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  query_['bool']['must'].append({
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  "simple_query_string": {
 
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  schema = """{{
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  "content": "Brief summary of a retail product",
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  "attributes": {{
 
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  res = invoke_models.invoke_llm_model( prompt_.format(query=query,schema = schema) ,False)
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  inter_query = res[7:-3].replace('\\"',"'").replace("\n","")
 
 
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  query_struct = StructuredQueryOutputParser.from_components().parse(inter_query)
 
 
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  opts = OpenSearchTranslator()
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  result_query_llm = opts.visit_structured_query(query_struct)[1]['filter']
 
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  draft_new_query = {'bool':{'should':[],'must':[]}}
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  if('bool' in result_query_llm and ('must' in result_query_llm['bool'] or 'should' in result_query_llm['bool'])):
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  #draft_new_query['bool']['should'] = []
 
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  # return words_stem.strip()
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  #imp_item = stem_(imp_item)
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+
 
 
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  if('must' in query_['bool']):
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  query_['bool']['must'].append({
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  "simple_query_string": {