Merge branch 'main' into srihari-r-iamreadme-1

Author: AlexanderHodicke

.DS_Store

@@ -2,3 +2,4 @@
 shared-assets/bastion-py-script/.oci/
 shared-assets/bastion-py-script/temp/
 temp/
+app-dev/app-integration-and-automation/oracle-integration-cloud/01-oic-connectivity-agent/README_tmp.html

.gitignore

@@ -0,0 +1,35 @@
+Copyright (c) 2025 Oracle and/or its affiliates.
+
+The Universal Permissive License (UPL), Version 1.0
+
+Subject to the condition set forth below, permission is hereby granted to any
+person obtaining a copy of this software, associated documentation and/or data
+(collectively the "Software"), free of charge and under any and all copyright
+rights in the Software, and any and all patent rights owned or freely
+licensable by each licensor hereunder covering either (i) the unmodified
+Software as contributed to or provided by such licensor, or (ii) the Larger
+Works (as defined below), to deal in both
+
+(a) the Software, and
+(b) any piece of software and/or hardware listed in the lrgrwrks.txt file if
+one is included with the Software (each a "Larger Work" to which the Software
+is contributed by such licensors),
+
+without restriction, including without limitation the rights to copy, create
+derivative works of, display, perform, and distribute the Software and make,
+use, sell, offer for sale, import, export, have made, and have sold the
+Software and the Larger Work(s), and to sublicense the foregoing rights on
+either these or other terms.
+
+This license is subject to the following condition:
+The above copyright notice and either this complete permission notice or at
+a minimum a reference to the UPL must be included in all copies or
+substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

ai/gen-ai-agents/csvpdf_analyzer/LICENSE

@@ -0,0 +1,213 @@
+"""
+File name: assistant_ui.py
+Author: Luigi Saetta & Omar Salem
+Date last modified: 2025-04-18
+Python Version: 3.11
+
+Usage:
+    streamlit run assistant_ui.py
+
+License:
+    This code is released under the MIT License.
+
+Notes:
+    This is part of a series of demos developed using OCI GenAI and LangChain.
+
+Warnings:
+    This module is in development, may change in future versions.
+"""
+
+from typing import List, Union
+import time
+import streamlit as st
+import pandas as pd
+import tempfile
+from langchain_core.messages import HumanMessage, AIMessage
+
+# for APM integration
+# from py_zipkin.zipkin import zipkin_span
+# from py_zipkin import Encoding
+
+from csv_analyzer_agent import State, MultiAgent
+from utils import get_console_logger
+from config import DEBUG
+
+# Constants
+AGENT_NAME = "AI_DATA_ANALYZER"
+
+# User and assistant roles
+USER = "user"
+ASSISTANT = "assistant"
+
+logger = get_console_logger()
+
+# Initialize session state
+if "chat_history" not in st.session_state:
+    st.session_state.chat_history = []
+if "df" not in st.session_state:
+    st.session_state.df = None
+if "pdf_path" not in st.session_state:
+    st.session_state.pdf_path = None
+if "extracted_information" not in st.session_state:
+    st.session_state.extracted_information = None
+if "agent" not in st.session_state:
+    # Initialize the multi-agent system
+    st.session_state.agent = MultiAgent()
+
+def display_msg_on_rerun(chat_hist: List[Union[HumanMessage, AIMessage]]) -> None:
+    """Display all messages on rerun."""
+    for msg in chat_hist:
+        role = USER if isinstance(msg, HumanMessage) else ASSISTANT
+        with st.chat_message(role):
+            st.markdown(msg.content)
+
+def reset_conversation():
+    st.session_state.chat_history = []
+
+def add_to_chat_history(msg):
+    st.session_state.chat_history.append(msg)
+
+def get_chat_history():
+    return st.session_state.chat_history
+
+def display_extracted_data():
+    if st.session_state.extracted_information:
+        st.sidebar.subheader("📄 Extracted PDF Information")
+        extracted = st.session_state.extracted_information.data
+        for key, value in extracted.items():
+            label = f"**{key.replace('_', ' ').title()}:**"
+            if isinstance(value, (dict, list)):
+                st.sidebar.markdown(label)
+                st.sidebar.json(value)
+            else:
+                st.sidebar.markdown(f"{label} {value}")
+
+st.title("AI Data Analyzer")
+
+if st.sidebar.button("Clear Chat History"):
+    reset_conversation()
+
+st.sidebar.header("Options")
+
+model_id = st.sidebar.selectbox("Select the Chat Model", ["meta.llama3.3-70B"])
+
+# Upload CSV
+uploaded_file = st.sidebar.file_uploader("Load a CSV file", type=["csv"])
+
+if uploaded_file:
+    try:
+        df = pd.read_csv(uploaded_file)
+        st.session_state.df = df
+        st.dataframe(df)
+    except Exception as e:
+        st.error(f"Error reading the CSV file: {e}")
+else:
+    st.session_state.df = None
+
+# Upload PDF
+uploaded_pdf = st.sidebar.file_uploader("Upload a PDF file", type=["pdf"])
+
+if uploaded_pdf:
+    try:
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as temp_pdf:
+            temp_pdf.write(uploaded_pdf.getvalue())
+            temp_pdf_path = temp_pdf.name
+
+        st.session_state.pdf_path = temp_pdf_path
+        st.session_state.extracted_information = None
+
+        pdf_state = State(
+            user_request="",
+            pdf_path=temp_pdf_path,
+            extracted_information=None,
+            input_df=st.session_state.df,
+            chat_history=st.session_state.chat_history,
+            previous_error=None,
+            error=None,
+        )
+
+        extracted_info = st.session_state.agent.process_pdf_node(pdf_state)
+
+        if extracted_info["extracted_information"]:
+            st.session_state.extracted_information = extracted_info["extracted_information"]
+            st.toast("✅ PDF Processed Successfully!")
+        else:
+            st.error("⚠️ Failed to extract information from PDF.")
+
+    except Exception as e:
+        st.error(f"Error during PDF processing: {e}")
+else:
+    st.session_state.extracted_information = None
+    st.session_state.pdf_path = None
+
+# DISPLAY PDF INFO in sidebar always if available
+display_extracted_data()
+
+#DISPLAY CHAT HISTORY
+display_msg_on_rerun(get_chat_history())
+
+#
+# Chat Input Handling
+#
+if question := st.chat_input("Hello, how can I help you?"):
+    st.chat_message(USER).markdown(question)
+    add_to_chat_history(HumanMessage(content=question))  # ✅ Store user message
+
+    try:
+        with st.spinner("Calling AI..."):
+            time_start = time.time()
+
+            app = st.session_state.agent.create_workflow()
+
+            state = State(
+                user_request=question,
+                input_df=st.session_state.df,
+                extracted_information=st.session_state.extracted_information or {},
+                pdf_path=st.session_state.pdf_path,
+                chat_history=st.session_state.chat_history.copy(),
+                error=None,
+                previous_error=None,
+            )
+
+            results = []
+            error = None
+            #uncomment to use zipkin however makes it slower.
+            # with zipkin_span(
+            #     service_name=AGENT_NAME,
+            #     span_name="call",
+            #     transport_handler=http_transport,
+            #     encoding=Encoding.V2_JSON,
+            #     sample_rate=100,
+            # ):
+
+            for event in app.stream(state):
+                for key, value in event.items():
+                    logger.info(f"Completed: {key}")
+                    st.toast(f"Completed: {key}")
+                    results.append(value)
+                    error = value.get("error")
+
+                    if key == "CodeGenerator" and error is None:
+                        st.sidebar.header("Generated Code:")
+                        st.sidebar.code(value["code_generated"], language="python")
+
+            if error is None:
+                final_result = results[-1]["final_output"]
+                if isinstance(final_result, pd.DataFrame):
+                    st.dataframe(final_result)
+                    if DEBUG:
+                        logger.info(final_result.head(10))
+                else:
+                    with st.chat_message(ASSISTANT):
+                        st.markdown(final_result)
+                    add_to_chat_history(AIMessage(content=final_result))  # Store AI response
+
+            else:
+                st.error(error)
+
+            elapsed_time = round((time.time() - time_start), 1)
+            logger.info(f"Elapsed time: {elapsed_time} sec.")
+
+    except Exception as e:
+        logger.error(f"Error occurred: {e}")
+        st.error(f"An error occurred: {e}")

ai/gen-ai-agents/csvpdf_analyzer/files/assistant_ui_langgraph.py

@@ -0,0 +1,8 @@
+[DEFAULT]
+user=ocid1.user.oc
+fingerprint=c6:4f:66:e7:
+tenancy=ocid1.tenancy.oc
+region=eu-frankfurt-1
+key_file=~/.oci/
+
+

ai/gen-ai-agents/csvpdf_analyzer/files/config

@@ -0,0 +1,33 @@
+"""
+OCI models configuration and general config
+"""
+
+DEBUG = False
+
+MODEL_ID = "meta.llama-3.3-70b-instruct"
+
+AUTH = "API_KEY"
+SERVICE_ENDPOINT = "https://inference.generativeai.eu-frankfurt-1.oci.oraclecloud.com"
+
+TEMPERATURE = 0.1
+MAX_TOKENS = 1024
+TOP_P = 0.9
+
+# OCI general
+COMPARTMENT_ID = "ocid1.compar"
+
+# history management
+MAX_MSGS_IN_HISTORY = 10
+# low, cause we're generating code
+MAX_ROWS_IN_SAMPLE = 10
+
+RAG_AGENT_ID = "ocid1.genaia"
+RAG_AGENT_ENDPOINT = (
+    "https://agent-runtime.generativeai.uk-london-1.oci.oraclecloud.com"
+)
+
+# integration with APM
+ENABLE_TRACING = True
+APM_BASE_URL = "https://aaa"
+APM_CONTENT_TYPE = "application/json"
+APM_PUBLIC_KEY = "6OXZ45B="