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import yaml
from pocketflow import Node
from utils import callLLM, callWebSearch
class Decide(Node):
def setLogger(self,logger):
self.logger = logger
def prep(self,shared):
context = shared.get("context","No previous search")
question = shared["question"]
return question,context
def exec(self,inputs):
question,context = inputs
prompt = f"""
### CONTEXT
You are a research assistant that can search the web
Question: {question}
Previous research: {context}
### ACTION SPACE
[1] search
Description: Look up more information on the web
Parameters:
- query (str): what to search for
[2] answer
Description: Answer the question with current knowledge
Parameters:
- answer (str): final answer to the question
### NEXT ACTION
Decide the next action based on the context and available actions.
Return your response in the following format:
```yaml
thinking: |
<your step-by-step reasoning process>
action: search OR answer
reason: <why you choose this action>
search_query: <specific search query if action is search>
```
IMPORTANT: Make sure to:
1. Use proper indentation (4 spaces) for all multi-line fields
2. Use the | character for multi-line text fields
3. Keep single-line fields without the | character
"""
response = callLLM(prompt)
self.logger.debug(f"=== CALLING LLM\n{prompt}\n=== LLM RESPONSE\n{response}\n\n==========\n\n")
yaml_str = response.replace("|","") #.split("```yaml")[1].split("```")[0].strip()
decision = yaml.safe_load(yaml_str)
return decision
def post(self,shared,prep_res,exec_res):
if exec_res["action"] == "search":
shared["search_query"] = exec_res["search_query"]
return exec_res["action"]
class Search(Node):
def setLogger(self,logger):
self.logger = logger
def prep(self,shared):
return shared["search_query"]
def exec(self,search_query):
results = callWebSearch(search_query)
self.logger.debug(f"*** SEARCHING\n{search_query}\n*** SEARCH RESULTS\n{results}\n\n**********\n\n")
return results
def post(self,shared,prep_res,exec_res):
previous = shared.get("context","")
shared["context"] = f"{previous}\n\nSEARCH: {shared['search_query']}\n\nRESULTS: {exec_res}"
return "decide"
class Answer(Node):
def setLogger(self,logger):
self.logger = logger
def prep(self,shared):
return shared["question"],shared.get("context","")
def exec(self,inputs):
question,context = inputs
prompt = f'''
### CONTEXT
Based on the following information, answer the question.
Question: {question}
Research: {context}
### YOUR ANSWER
Provide a comprehensive answer using research results
'''
response = callLLM(prompt)
self.logger.debug(f"### CALLING LLM\n{prompt}\n### LLM RESPONSE\n{response}\n\n##########\n\n")
return response
def post(self,shared,prep_res,exec_res):
shared["answer"] = exec_res |