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import os
from smolagents import CodeAgent, InferenceClientModel
from a_tools import search_tool, final_answer, image_generation_tool
class StatefulAgent:
def __init__(self, model_id = 'Qwen/Qwen2.5-Coder-32B-Instruct', context_len = 0, structured_code = False):
a_model = InferenceClientModel(
model_id=model_id,
max_tokens=1024,
api_key=os.environ.get("HF_API_KEY"),
)
self.model = a_model
self.tools = [search_tool, final_answer, image_generation_tool]
self.agent = CodeAgent(tools=self.tools,
model=self.model,
stream_outputs=True,
code_block_tags="markdown",
use_structured_outputs_internally=structured_code,
additional_authorized_imports=['requests', 'bs4','pandas','numpy',
'json','datetime','geopandas','shapely'])
self.context = []
self.max_context_len = context_len
self.max_steps = 20
def ask(self, question):
# Refresh context and add it to prompt
self.context.append({"role": "user", "content": question})
if len(self.context) > self.max_context_len:
self.context = self.context[-self.max_context_len:]
# Combine history for prompt (optional)
prompt = ""
for msg in self.context:
if msg["role"] == "user":
prompt += f"User: {msg['content']}\n"
else:
prompt += f"Agent: {msg['content']}\n"
if self.max_steps > 0:
prompt += f"User: {question}\nAgent:"
# Run agent with created prompt
response = self.agent.run(prompt, max_steps=self.max_steps)
# Add answer to history for context
if self.max_steps > 0:
self.context.append({"role": "assistant", "content": response})
if len(self.context) > self.max_context_len:
self.context = self.context[-self.max_context_len:]
return response
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