Here's my function to invoke Claude to answer context relevant question. I have created embeddings and stored in the OpenSearch database with separate functions. After running this code def query_with_context(query_text, top_k=3): """ Query OpenSearch for similar documents and use Claude to generate an answer Args: query_text: The user's question top_k: Number of similar documents to retrieve """ # Get query embedding from Titan query_embedding = get_titan_embeddings(query_text) # Connect to OpenSearch client = OpenSearch( hosts=[{'host': 'domain name', 'port': 443}], http_auth=auth, use_ssl=True, verify_certs=True, connection_class=RequestsHttpConnection ) # Perform vector similarity search search_query = { "size": top_k, "query": { "script_score": { "query": {"match_all": {}}, "script": { "source": "knn_score", "params": { "field": "vector", "query_value": query_embedding, "space_type": "cosinesimil" } } } } } # Get similar documents response = client.search( index="text-embeddings", body=search_query ) # Extract relevant contexts contexts = [] for hit in response['hits']['hits']: contexts.append(hit['_source']['text']) # Combine contexts combined_context = "\n\n".join(contexts) # Initialize Bedrock client for Claude bedrock_runtime = boto3.client('bedrock-runtime', region_name='us-east-1') # Prepare prompt with context prompt = f"""Given the following context: {combined_context} Please answer this question: {query_text} Use only the information from the provided context. If you cannot answer the question based on the context, say so.""" # Query Claude with context claude_response = bedrock_runtime.invoke_model( modelId='anthropic.claude-3-7-sonnet-20250219-v1:0', body=json.dumps({ "anthropic_version": "bedrock-2023-05-31", "max_tokens": 200, "messages": [ { "role": "user", "content": prompt } ] }), accept='application/json', contentType='application/json' ) # Parse Claude's response response_body = json.loads(claude_response.get('body').read()) answer = response_body['content'][0]['text'] return { "answer": answer, "contexts": contexts } I get the following error code opensearchpy.exceptions.RequestError: RequestError(400, 'search_phase_execution_exception', 'compile error') Any suggestions what it might be related to? Incorrect indexing? Some other issue? I am a bit lost here. Continue reading...
