errchh
commited on
Commit
·
d0faccd
1
Parent(s):
4a21a58
fix import agent to app
Browse files
agent.py
CHANGED
@@ -135,16 +135,6 @@ with open("system_prompt.txt", "r", encoding="utf-8") as f:
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sys_msg = SystemMessage(content=system_prompt)
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# generate the chat interface and tools
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llm = HuggingFaceEndpoint(
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repo_id = "microsoft/Phi-4-reasoning-plus",
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huggingfacehub_api_token=HUGGINGFACEHUB_API_TOKEN,
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)
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chat = ChatHuggingFace(llm=llm, verbose=False)
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tools = [
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add,
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subtract,
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@@ -157,42 +147,51 @@ tools = [
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]
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class AgentState(TypedDict):
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messages: Annotated[list[AnyMessage], add_messages]
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"messages": [chat_with_tools.invoke(state["messages"])],
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}
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# define nodes
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builder.add_node("assistant", assistant)
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builder.add_node("tools", ToolNode(tools))
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builder.add_edge(START, "assistant")
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builder.add_conditional_edges(
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"assistant",
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# If the latest message requires a tool, route to tools
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# Otherwise, provide a direct response
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tools_condition,
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)
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builder.add_edge("tools", "assistant")
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graph = builder.compile()
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if __name__ == "__main__":
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question = "When was a picture of St. Thomas Aquinas first added to the Wikipedia page on the Principle of double effect?"
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messages = [HumanMessage(content=question)]
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messages = graph.invoke({"messages": messages})
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for m in messages["messages"]:
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sys_msg = SystemMessage(content=system_prompt)
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tools = [
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add,
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subtract,
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]
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# build graph function
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def build_graph():
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# llm
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llm = HuggingFaceEndpoint(
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repo_id = "microsoft/Phi-4-reasoning-plus",
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huggingfacehub_api_token=HUGGINGFACEHUB_API_TOKEN,
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)
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chat = ChatHuggingFace(llm=llm, verbose=False)
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# bind tools to llm
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chat_with_tools = chat.bind_tools(tools)
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# generate AgentState and Agent graph
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class AgentState(TypedDict):
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messages: Annotated[list[AnyMessage], add_messages]
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def assistant(state: AgentState):
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return {
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"messages": [chat_with_tools.invoke(state["messages"])],
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}
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# build graph
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builder = StateGraph(AgentState)
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# define nodes
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builder.add_node("assistant", assistant)
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builder.add_node("tools", ToolNode(tools))
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# define edges
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builder.add_edge(START, "assistant")
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builder.add_conditional_edges(
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"assistant",
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# If the latest message requires a tool, route to tools
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# Otherwise, provide a direct response
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tools_condition,
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)
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builder.add_edge("tools", "assistant")
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return builder.compile()
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if __name__ == "__main__":
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question = "When was a picture of St. Thomas Aquinas first added to the Wikipedia page on the Principle of double effect?"
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graph = build_graph()
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messages = [HumanMessage(content=question)]
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messages = graph.invoke({"messages": messages})
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for m in messages["messages"]:
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app.py
CHANGED
@@ -4,6 +4,9 @@ import requests
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import inspect
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import pandas as pd
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# (Keep Constants as is)
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# --- Constants ---
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DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
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@@ -45,7 +48,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
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print(f"Error instantiating agent: {e}")
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return f"Error initializing agent: {e}", None
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# In the case of an app running as a hugging Face space, this link points toward your codebase ( usefull for others so please keep it public)
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agent_code = f"https://huggingface.co/spaces/
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print(agent_code)
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# 2. Fetch Questions
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@@ -91,7 +94,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
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print("Agent did not produce any answers to submit.")
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return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
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# 4. Prepare Submission
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submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
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status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
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print(status_update)
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@@ -193,4 +196,4 @@ if __name__ == "__main__":
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print("-"*(60 + len(" App Starting ")) + "\n")
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print("Launching Gradio Interface for Basic Agent Evaluation...")
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demo.launch(debug=True, share=False)
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import inspect
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import pandas as pd
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from langchain_core.messages import HumanMessage
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from agent import build_graph
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# (Keep Constants as is)
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# --- Constants ---
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DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
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print(f"Error instantiating agent: {e}")
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return f"Error initializing agent: {e}", None
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# In the case of an app running as a hugging Face space, this link points toward your codebase ( usefull for others so please keep it public)
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agent_code = f"https://huggingface.co/spaces/errchh/hfagentscourse-finalassignment/tree/main"
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print(agent_code)
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# 2. Fetch Questions
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print("Agent did not produce any answers to submit.")
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return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
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# 4. Prepare Submission
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submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
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status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
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print(status_update)
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print("-"*(60 + len(" App Starting ")) + "\n")
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print("Launching Gradio Interface for Basic Agent Evaluation...")
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demo.launch(debug=True, share=False)
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