add chat

cookbook/pocketflow-chat/README.md

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+#  Simple PocketFlow Chat
+
+A basic chat application using PocketFlow with OpenAI's GPT-4o model.
+
+## Features
+
+- Conversational chat interface in the terminal
+- Maintains full conversation history for context
+- Simple implementation demonstrating PocketFlow's node and flow concepts
+
+## Run It
+
+1. Make sure your OpenAI API key is set:
+    ```bash
+    export OPENAI_API_KEY="your-api-key-here"
+    ```
+    Alternatively, you can edit the `utils.py` file to include your API key directly.
+
+2. Install requirements and run the application:
+    ```bash
+    pip install -r requirements.txt
+    python main.py
+    ```
+
+## How It Works
+
+```mermaid
+flowchart LR
+    chat[ChatNode] -->|continue| chat
+```
+
+The chat application uses:
+- A single `ChatNode` with a self-loop that:
+  - Takes user input in the `prep` method
+  - Sends the complete conversation history to GPT-4o
+  - Adds responses to the conversation history
+  - Loops back to continue the chat until the user types 'exit'
+
+
+## Files
+
+- `main.py`: Implementation of the ChatNode and chat flow
+- `utils.py`: Simple wrapper for calling the OpenAI API
+ 

cookbook/pocketflow-chat/main.py

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+from pocketflow import Node, Flow
+from utils import call_llm
+
+class ChatNode(Node):
+    def prep(self, shared):
+        # Initialize messages if this is the first run
+        if "messages" not in shared:
+            shared["messages"] = []
+            print("Welcome to the chat! Type 'exit' to end the conversation.")
+        
+        # Get user input
+        user_input = input("\nYou: ")
+        
+        # Check if user wants to exit
+        if user_input.lower() == 'exit':
+            return None
+        
+        # Add user message to history
+        shared["messages"].append({"role": "user", "content": user_input})
+        
+        # Return all messages for the LLM
+        return shared["messages"]
+
+    def exec(self, messages):
+        if messages is None:
+            return None
+        
+        # Call LLM with the entire conversation history
+        response = call_llm(messages)
+        return response
+
+    def post(self, shared, prep_res, exec_res):
+        if prep_res is None or exec_res is None:
+            print("\nGoodbye!")
+            return None  # End the conversation
+        
+        # Print the assistant's response
+        print(f"\nAssistant: {exec_res}")
+        
+        # Add assistant message to history
+        shared["messages"].append({"role": "assistant", "content": exec_res})
+        
+        # Loop back to continue the conversation
+        return "continue"
+
+# Create the flow with self-loop
+chat_node = ChatNode()
+chat_node - "continue" >> chat_node  # Loop back to continue conversation
+
+flow = Flow(start=chat_node)
+
+# Start the chat
+if __name__ == "__main__":
+    shared = {}
+    flow.run(shared)

cookbook/pocketflow-chat/requirements.txt

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+pocketflow>=0.0.1
+openai>=1.0.0

cookbook/pocketflow-chat/utils.py

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+from openai import OpenAI
+import os
+
+def call_llm(messages):
+    client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY", "your-api-key"))
+    
+    response = client.chat.completions.create(
+        model="gpt-4o",
+        messages=messages,
+        temperature=0.7
+    )
+    
+    return response.choices[0].message.content
+
+if __name__ == "__main__":
+    # Test the LLM call
+    messages = [{"role": "user", "content": "In a few words, what's the meaning of life?"}]
+    response = call_llm(messages)
+    print(f"Prompt: {messages[0]['content']}")
+    print(f"Response: {response}")
+