chatbot

app.py

@@ -17,7 +17,7 @@ def main():
 
     pg = st.navigation(
         {
-            "Audit de contenus": [audit_page],
+            "Audit de contenus": [audit_page, kg_page],
             "Equipe d'agents IA": [recommended_agents],
             "Chatbot": [chatbot],
             "Documentation": [documentation]

audit_page/knowledge_graph.py

@@ -1,10 +1,112 @@
 import streamlit as st
+from utils.kg.construct_kg import get_graph
+from utils.audit.rag import get_text_from_content_for_doc,get_text_from_content_for_audio
+from streamlit_agraph import agraph, Node, Edge, Config
+
+def if_node_exists(nodes, node_id):
+    """
+    Check if a node exists in the graph.
+
+    Args:
+        graph (dict): A dictionary representing the graph with keys 'nodes' and 'relationships'.
+        node_id (str): The id of the node to check.
+
+    Returns:
+        return_value: True if the node exists, False otherwise.
+    """
+    for node in nodes:
+        if node.id == node_id:
+            return True
+    return False
+
+def convert_neo4j_to_agraph(neo4j_graph):
+    """
+    Converts a Neo4j graph into an Agraph format.
+
+    Args:
+        neo4j_graph (dict): A dictionary representing the Neo4j graph with keys 'nodes' and 'relationships'.
+                            'nodes' is a list of dicts with each dict having 'id' and 'type' keys.
+                            'relationships' is a list of dicts with 'source', 'target', and 'type' keys.
+
+    Returns:
+        return_value: The Agraph visualization object.
+    """
+    nodes = []
+    edges = []
+
+    # Creating Agraph nodes
+    for node in neo4j_graph.nodes:
+        # Use the node id as the Agraph node id
+        node_id = node.id.replace(" ", "_")  # Replace spaces with underscores for ids
+        label = node.id
+        size = 25  # Default size, can be customized
+        shape = "circle"  # Default shape, can be customized
+        
+        # For example purposes, no images are added, but you can set 'image' if needed.
+        nodes.append(Node(id=node_id, label=label, size=size, shape=shape))
+
+    # Creating Agraph edges
+    for relationship in neo4j_graph.relationships:
+        size = 25  # Default size, can be customized
+        shape = "circle"  # Default shape, can be customized
+
+        source = relationship.source
+        source_id = source.id.replace(" ", "_")
+        label_source = source.id
+        
+        source_node = Node(id=source_id, label=label_source, size=size, shape=shape)
+        if not if_node_exists(nodes, source_node.id):
+            nodes.append(source_node)
+
+        target = relationship.target
+        target_id = target.id.replace(" ", "_")
+        label_target = target.id
+        
+        target_node = Node(id=target_id, label=label_target, size=size, shape=shape)
+        if not if_node_exists(nodes, target_node.id):
+            nodes.append(target_node)
+
+        label = relationship.type
+
+        edges.append(Edge(source=source_id, label=label, target=target_id))
+
+    # Define the configuration for Agraph
+    config = Config(width=750, height=950, directed=True, physics=True, hierarchical=False)
+
+    # Create the Agraph visualization
+    return_value = agraph(nodes=nodes, edges=edges, config=config)
+    st.write(return_value)
+    return return_value
 
 
 def kg_main():
     #st.set_page_config(page_title="Graphe de connaissance", page_icon="", layout="wide")
-
+    if "graph" not in st.session_state:
+        st.session_state.graph = None
     st.title("Graphe de connaissance")
 
+    if "audit" not in st.session_state or st.session_state.audit == {}:
+        st.error("Veuillez d'abord effectuer un audit pour obtenir des recommandations d'agents.")
+        return
+    
+    audit = st.session_state.audit_simplified
+    content = st.session_state.audit["content"]
+
+    if audit["type de fichier"] == "pdf":
+        text = get_text_from_content_for_doc(content)
+    elif audit["type de fichier"] == "audio":
+        text = get_text_from_content_for_audio(content)
+
+    if st.button("Générer le graphe"):
+        graph = get_graph(text)
+        st.session_state.graph = graph
+    else:
+        graph = st.session_state.graph
+    if graph is not None:
+        #st.write(graph)
+        agraph_obj = convert_neo4j_to_agraph(graph[0])
+    
+
+
 
 kg_main()

requirements.txt

@@ -20,3 +20,6 @@ langchain-mistralai
 faiss-cpu
 langchain-community
 python-dotenv
+langchain-experimental 
+neo4j
+streamlit-agraph

utils/audit/audit_audio.py

@@ -1,4 +1,4 @@
-import streamlit as st
+
 import numpy as np
 import scipy.io.wavfile as wavfile
 from pydub import AudioSegment

utils/kg/construct_kg.py

@@ -0,0 +1,17 @@
+from langchain_community.graphs import Neo4jGraph
+from langchain_experimental.graph_transformers import LLMGraphTransformer
+from langchain_openai import ChatOpenAI
+from langchain_core.documents import Document
+
+def get_graph(text):
+    
+    graph = Neo4jGraph()
+    llm = ChatOpenAI(temperature=0, model_name="gpt-4o")
+
+    llm_transformer = LLMGraphTransformer(llm=llm)
+    documents = [Document(page_content=text)]
+
+    graph_documents = llm_transformer.convert_to_graph_documents(documents)
+    return graph_documents
+
+