Upload 5 files

.gitattributes

@@ -0,0 +1,35 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,135 @@
+import gradio as gr
+from langchain_community.chat_models import ChatOpenAI
+from langchain.memory import ConversationBufferMemory, SimpleMemory
+from langchain.agents import initialize_agent, AgentType
+from dotenv import load_dotenv
+import os
+import agent.planning_agent as planning_agent
+import logging
+
+from langchain_community.callbacks import ClearMLCallbackHandler
+from langchain_core.callbacks import StdOutCallbackHandler
+from clearml import Logger, Task
+
+# Global variables
+clearml_callback = None
+def initialize_components():
+
+    OPENAI_API_KEY="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"
+    CLEARML_API_ACCESS_KEY="NYZZ07E2ZEW08V4DUGYY2PA7O6JX5F"
+    CLEARML_API_SECRET_KEY="MkfQrIOuKNFRWHfCz32cN-UVm_19M7_vgxAwRn8twnvHYJ1xeqD9T2GZcIX9RwnD8mw"
+    SERPAPI_API_KEY="619f2302253fbe56448bcf82565caf2a3263d845944682533f10b09a0d1650e6"
+
+
+
+# Setup and use the ClearML Callback
+    clearml_callback = ClearMLCallbackHandler(
+    task_type="inference",
+    project_name="langchain_callback_demo",
+    task_name="llm",
+    tags=["test"],
+    # Change the following parameters based on the amount of detail you want tracked
+    visualize=True,
+    complexity_metrics=True,
+    stream_logs=True,)
+    
+    callbacks = [StdOutCallbackHandler(), clearml_callback]
+
+def main():
+
+        a_task = Task.get_task(project_name='langchain_callback_demo', task_name='llm')
+        loer = a_task.get_logger()
+        report_logs(loer)
+        # report text as debug example
+        report_debug_text(loer)
+        loer.flush()
+
+
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+# Global variables
+llm = None
+chat_memory = None
+query_memory = None
+
+def initialize_components():
+    global llm, chat_memory, query_memory
+    load_dotenv()
+    api_key = os.environ['OA_API']           
+    os.environ['OPENAI_API_KEY'] = api_key
+    
+    llm = ChatOpenAI(
+        model_name="gpt-3.5-turbo",
+        temperature=0,
+        api_key=api_key
+    )
+
+    # Initialize memories
+    chat_memory = ConversationBufferMemory(
+        memory_key="chat_history",
+        return_messages=True
+    )
+    query_memory = SimpleMemory()
+
+    # Initialize planning agent with both memories
+    planning_agent.initialize_planning_agent(llm, chat_memory, query_memory)
+
+    logger.info("Components initialized successfully")
+
+def process_query(query, history):
+    try:
+        # Restore chat history from Gradio's history
+        if history:
+            for human_msg, ai_msg in history:
+                if chat_memory and hasattr(chat_memory, 'chat_memory'):
+                    chat_memory.chat_memory.add_user_message(human_msg)
+                    chat_memory.chat_memory.add_ai_message(ai_msg)
+        
+        # Store original query in query memory
+        query_memory.memories['original_query'] = query
+        
+        # Execute query through planning agent
+        response = planning_agent.execute(query)
+        
+        # Add current interaction to chat memory
+        if chat_memory and hasattr(chat_memory, 'chat_memory'):
+            chat_memory.chat_memory.add_user_message(query)
+            chat_memory.chat_memory.add_ai_message(response)
+        
+        return response
+
+    except Exception as e:
+        error_msg = f"Error processing query: {str(e)}"
+        logger.error(f"Error details: {str(e)}")
+
+        if chat_memory and hasattr(chat_memory, 'chat_memory'):
+            chat_memory.chat_memory.add_user_message(query)
+            chat_memory.chat_memory.add_ai_message(error_msg)
+
+        return error_msg
+
+def clear_context():
+    planning_agent.clear_context()
+    chat_memory.clear()
+    query_memory.memories.clear()
+    return [], []
+
+def create_gradio_app():
+    from interface import create_interface
+    return create_interface(process_query, clear_context)
+
+def main():
+    """Main application entry point"""
+    try:
+        initialize_components()
+        app = create_gradio_app()
+        app.queue()
+        app.launch(server_name="0.0.0.0", server_port=7860, share=True)
+    except Exception as e:
+        logger.error(f"Error in main: {str(e)}")
+        raise
+
+if __name__ == "__main__":
+    main()

documents.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0132d52582d53422098dfaec3a361e369e791db0a137d8b012ad920851f18b3f
+size 2382882

interface.py

@@ -0,0 +1,45 @@
+import gradio as gr
+
+def create_interface(process_query, clear_context):
+    with gr.Blocks(title="AI Assistant") as demo:
+        chatbot = gr.Chatbot(
+            [],
+            elem_id="chatbot",
+            bubble_full_width=False,
+            height=400
+        )
+        
+        with gr.Row():
+            msg = gr.Textbox(
+                label="Your Message",
+                placeholder="Type your message here...",
+                scale=8
+            )
+            submit = gr.Button("Submit", scale=1)
+        
+        clear = gr.Button("Clear")
+
+        def process_message(message, history):
+            response = process_query(message, history)
+            history.append((message, response))
+            return "", history
+
+        msg.submit(
+            process_message,
+            [msg, chatbot],
+            [msg, chatbot]
+        )
+        
+        submit.click(
+            process_message,
+            [msg, chatbot],
+            [msg, chatbot]
+        )
+        
+        clear.click(
+            clear_context,
+            None,
+            [chatbot, msg]
+        )
+
+    return demo

requirements.txt

@@ -0,0 +1,36 @@
+# LangChain Ecosystem
+langchain==0.1.3
+langchain_openai==0.0.5
+langchain-community
+langchain-core
+
+# Vector Databases & Similarity Search
+chromadb==0.5.0
+faiss-cpu
+
+# OpenAI
+openai==1.10
+tiktoken>=0.5.2
+
+# UI Framework
+gradio==4.44.1
+setuptools>=65.5.1
+
+# Data Processing & Utils
+numpy==1.26.2
+pandas==2.1.3
+python-dotenv==1.0.0
+
+# Core Dependencies
+#pydantic==2.5.2
+typing-extensions==4.8.0
+requests==2.31.0
+
+# ClearML 
+clearml
+spacy>=3.0.0,<4.0.0
+en_core_web_sm @ https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.7.1/en_core_web_sm-3.7.1-py3-none-any.whl
+textstat
+serpapi==0.1.5
+google-search-results
+numexpr