Update agent.py

agent.py

@@ -1,60 +1,62 @@
-import asyncio
+# import asyncio
+import utils
+# import streamlit as st
 import tools
 from llama_index.core import Settings
 from llama_index.core.agent.workflow import AgentWorkflow
 
-# Silence the torch error
-def init_async():
-    import torch
-    torch.classes.__path__ = [] # add this line to manually set it to empty. 
+# # Silence the torch error
+# def init_async():
+#     import torch
+#     torch.classes.__path__ = [] # add this line to manually set it to empty. 
 
 
-def run_async_task(async_func, *args):
-    """
-    Run an asynchronous function in a new event loop.
+# def run_async_task(async_func, *args):
+#     """
+#     Run an asynchronous function in a new event loop.
 
-    Args:
-    async_func (coroutine): The asynchronous function to execute.
-    *args: Arguments to pass to the asynchronous function.
+#     Args:
+#     async_func (coroutine): The asynchronous function to execute.
+#     *args: Arguments to pass to the asynchronous function.
 
-    Returns:
-    None
-    """
+#     Returns:
+#     None
+#     """
     
-    loop = None
+#     loop = None
 
-    try:
-        loop = asyncio.new_event_loop()
+#     try:
+#         loop = asyncio.new_event_loop()
 
-        loop.run_until_complete(async_func(*args))
-    except:
-        # Close the existing loop if open
-        if loop is not None:
-            loop.close()
+#         loop.run_until_complete(async_func(*args))
+#     except:
+#         # Close the existing loop if open
+#         if loop is not None:
+#             loop.close()
 
-        # Create a new loop for retry
-        loop = asyncio.new_event_loop()
+#         # Create a new loop for retry
+#         loop = asyncio.new_event_loop()
 
-        loop.run_until_complete(async_func(*args))
-    finally:
-        if loop is not None:
-            loop.close()
+#         loop.run_until_complete(async_func(*args))
+#     finally:
+#         if loop is not None:
+#             loop.close()
 
 
 # Initialize model (defaults to llama3.1)
 def init_model(model:str='llama3.1:8b-instruct-q4_0'):
-    # from llama_index.llms.ollama import Ollama
-    from llama_index.llms.huggingface_api import HuggingFaceInferenceAPI
+    from llama_index.llms.ollama import Ollama
+    # from llama_index.llms.huggingface_api import HuggingFaceInferenceAPI
 
-    # llm_model = Ollama(
-    #     model=model,
-    #     request_timeout=360.0
-    #     )
+    llm_model = Ollama(
+        model=model,
+        request_timeout=360.0
+        )
 
-    llm_model = HuggingFaceInferenceAPI(
-        # model='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud/'
-        model_name='Qwen/Qwen2.5-Coder-32B-Instruct'
-    )
+    # llm_model = HuggingFaceInferenceAPI(
+    #     model='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud/'
+    #     # model_name='Qwen/Qwen2.5-Coder-32B-Instruct'
+    # )
 
     return llm_model
 
@@ -96,10 +98,11 @@ def init_agent():
     agent = AgentWorkflow.from_tools_or_functions(
         tools_or_functions=tool_list,
         llm=llm_model,
-        system_prompt = "You are a useful AI assistant. Use all available tools to answer the inquiry. " \
-            "Before giving out the final answer, please verify using available tools." \
-            "When available, use the Wikipedia if it can be verifiable." \
-            "Multiple tools can combine to answer the question as a whole."
+        system_prompt="You are a general AI assistant. I will ask you a question. Report your thoughts, and finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER]. YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string."
+        # system_prompt = "You are a useful AI assistant. Use all available tools to answer the inquiry. " \
+        #     "Before giving out the final answer, please verify using available tools." \
+        #     "When available, use the Wikipedia if it can be verifiable." \
+        #     "Multiple tools can combine to answer the question as a whole."
     )
 
     return agent
@@ -112,4 +115,14 @@ async def run_agent(agent,query:str):
 # Await function for async
 async def await_result(agent,query:str):
     response = await run_agent(agent,query)
-    return response.response.blocks[0].text
+    clean_response = utils.check_value(response.response.blocks[0].text[response.response.blocks[0].text.find(':')+2:])
+
+    # st.write(response.response.blocks[0].text)
+    # st.write(clean_response)
+    # st.write(response.raw)
+    # st.write(response.tool_calls)
+    # st.session_state.messages.append({'role':'assistant','content':response.response.blocks[0].text})
+    # st.session_state.messages.append({'role':'assistant','content':clean_response})
+
+    # return response.response.blocks[0].text
+    return clean_response