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Update nova_agent.py
Browse files- nova_agent.py +50 -20
nova_agent.py
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@@ -5,9 +5,9 @@ from dotenv import load_dotenv
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load_dotenv()
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class
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def __init__(self):
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print("
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# Get AWS credentials from environment variables
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aws_access_key_id = os.getenv('AWS_ACCESS_KEY_ID')
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@@ -31,17 +31,31 @@ class NovaLiteAgent:
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self.accept = "application/json"
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async def __call__(self, question: str) -> str:
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print(f"
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try:
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#
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Question: {question}
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Answer:"""
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# Prepare the request payload for Nova
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payload = {
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"messages": [
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{
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@@ -52,8 +66,8 @@ Answer:"""
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}
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],
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"inferenceConfig": {
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"max_new_tokens":
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"temperature": 0.0
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}
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}
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@@ -69,30 +83,46 @@ Answer:"""
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response_body = json.loads(response['body'].read())
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answer = response_body['output']['message']['content'][0]['text']
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# Clean up the answer
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answer = answer.strip()
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#
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verbose_starts = [
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"To answer this question",
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"
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"According to",
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"The answer is",
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"Looking at"
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]
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for start in verbose_starts:
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if answer.lower().startswith(start.lower()):
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sentences = answer.split('. ')
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for sentence in sentences[1:]:
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if len(sentence.strip()) >
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answer = sentence.strip()
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break
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#
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sentences = answer.split('. ')
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answer = sentences[0] + '.'
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return answer
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load_dotenv()
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class NovaProAgent:
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def __init__(self):
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print("NovaProAgent initialized.")
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# Get AWS credentials from environment variables
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aws_access_key_id = os.getenv('AWS_ACCESS_KEY_ID')
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self.accept = "application/json"
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async def __call__(self, question: str) -> str:
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print(f"NovaProAgent received question (first 50 chars): {question[:50]}...")
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try:
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# Detect question type and adjust approach
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needs_reasoning = any(keyword in question.lower() for keyword in [
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'calculate', 'how many', 'what is the', 'find', 'determine', 'solve',
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'table', 'given', 'prove', 'counter-example'
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])
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if needs_reasoning:
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prompt = f"""You are an expert problem solver. Think step by step to solve this question accurately.
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Question: {question}
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Think through this step by step, then provide your final answer:"""
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max_tokens = 300
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else:
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prompt = f"""Answer this question directly and concisely. Provide only the essential information requested.
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Question: {question}
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Answer:"""
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max_tokens = 150
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# Prepare the request payload for Nova Pro
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payload = {
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"messages": [
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{
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}
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],
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"inferenceConfig": {
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"max_new_tokens": max_tokens,
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"temperature": 0.1 if needs_reasoning else 0.0
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}
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}
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response_body = json.loads(response['body'].read())
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answer = response_body['output']['message']['content'][0]['text']
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# Clean up the answer
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answer = answer.strip()
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# Handle questions requiring external resources
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if any(phrase in question.lower() for phrase in [
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'attached', 'video', 'image', 'audio', 'file', 'excel', '.mp3', '.jpg', '.png'
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]):
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if 'video' in question.lower() or 'audio' in question.lower():
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return "I cannot access external media files."
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elif 'image' in question.lower():
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return "I cannot view images."
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elif 'excel' in question.lower() or 'file' in question.lower():
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return "I cannot access attached files."
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# Extract final answer if reasoning was used
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if needs_reasoning and 'final answer' in answer.lower():
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lines = answer.split('\n')
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for line in reversed(lines):
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if 'final answer' in line.lower() or 'answer:' in line.lower():
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# Extract the part after the colon
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if ':' in line:
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answer = line.split(':', 1)[1].strip()
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break
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# Remove verbose beginnings
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verbose_starts = [
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"To answer this question", "Based on the information", "According to",
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"The answer is", "Looking at", "Step by step", "Let me think"
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]
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for start in verbose_starts:
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if answer.lower().startswith(start.lower()):
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sentences = answer.split('. ')
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for sentence in sentences[1:]:
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if len(sentence.strip()) > 5:
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answer = sentence.strip()
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break
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# Clean up common patterns
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answer = answer.replace('**', '').replace('*', '')
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return answer
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