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Dockerfile

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+FROM python:3.10-slim
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+ENV PYTHONUNBUFFERED=1
+ENV PORT=7860
+
+CMD ["streamlit", "run", "app.py", "--server.port=7860", "--server.address=0.0.0.0"]

app.py

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+import os
+import streamlit as st
+from dotenv import load_dotenv
+from langchain_core.messages import HumanMessage
+from langchain_core.tools import tool
+from langgraph.prebuilt import create_react_agent
+from langchain_openai import ChatOpenAI
+
+load_dotenv()
+api_key = os.getenv("OPENROUTER_API_KEY")
+
+@tool
+def calculator(a: float, b: float) -> str:
+    """Useful for performing basic arithmetic calculations with numbers"""
+    return f"The sum of {a} and {b} is {a + b}"
+
+@tool
+def say_hello(name: str) -> str:
+    """Useful for greeting a user"""
+    return f"Hello {name}, I hope you are well today"
+
+model = ChatOpenAI(
+    model="mistralai/mistral-7b-instruct:free",
+    api_key=api_key,
+    base_url="https://openrouter.ai/api/v1",
+    temperature=0,
+)
+
+tools = [calculator, say_hello]
+agent_executor = create_react_agent(model, tools)
+
+st.title("🧠 Mistral Agent with LangGraph")
+
+user_input = st.text_input("Ask me anything (type 'quit' to exit):")
+
+if user_input and user_input.lower() != "quit":
+    with st.spinner("Thinking..."):
+        chunks = []
+        for chunk in agent_executor.stream({"messages": [HumanMessage(content=user_input)]}):
+            if "agent" in chunk and "messages" in chunk["agent"]:
+                for message in chunk["agent"]["messages"]:
+                    chunks.append(message.content)
+        st.success(" ".join(chunks))

requirements.txt

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+streamlit==1.26.0
+langchain
+langgraph
+langchain-core
+langchain-openai
+langchain-community
+python-dotenv