Edge plotly tools (#8)

* Add edge and plotly tools

* Bump minimal tilores SDK version

* Prepare release

* Bump minimal tilores SDK version

* Add missing dependency

examples/chat/chat.py

@@ -5,6 +5,7 @@
 import os
 
 # LangChain
+import langchain
 from langchain.tools import BaseTool
 from langchain_core.messages import AnyMessage, HumanMessage
 from langchain_openai import ChatOpenAI
@@ -24,6 +25,10 @@
 import chainlit as cl
 from chainlit.sync import run_sync
 
+# Plotly
+import plotly.graph_objects as go
+from plotly.io import from_json
+
 
 class HumanInputChainlit(BaseTool):
     """Tool that adds the capability to ask user for input."""
@@ -72,7 +77,9 @@ def start():
     tools = [
         HumanInputChainlit(),
         tilores_tools.search_tool(),
+        tilores_tools.edge_tool(),
         pdf_tool,
+        plotly_tool,
     ]
     # Use MemorySaver to use the full conversation
     memory = MemorySaver()
@@ -97,6 +104,12 @@ async def main(message: cl.Message):
     ui_message = cl.Message(content="")
     await ui_message.send()
     async for event in runnable.astream_events(state, version="v1", config={'configurable': {'thread_id': 'thread-1'}}):
+        if event["event"] == "on_tool_end":
+            if event["data"].get('output') and event["data"].get('output').artifact:
+                fig = from_json(event["data"].get("output").artifact)
+                chart = cl.Plotly(name="chart", figure=fig, display="inline")
+                ui_message.elements.append(chart)
+
         if event["event"] == "on_chat_model_stream":
             c = event["data"]["chunk"].content
             if c and len(c) > 0 and isinstance(c[0], dict) and c[0]["type"] == "text":
@@ -128,4 +141,17 @@ def load_pdf_from_url(url: str):
     name = "load_pdf",
     func=load_pdf_from_url,
     description="useful for when you need to download and process a PDF file from a given URL"
+)
+
+def render_plotly_graph(figureCode: str):
+    local_vars = {}
+    exec(figureCode, {"go": go}, local_vars)
+    fig = local_vars.get("fig")
+    return "generated a chart from the provided figure", fig.to_json()
+
+plotly_tool = Tool(
+    name = "plotly_tool",
+    func=render_plotly_graph,
+    description="useful for when you need to render a graph using plotly; the figureCode must only import plotly.graph_objects as go and must provide a local variable named fig as a result",
+    response_format='content_and_artifact'
 )

examples/chat/requirements.txt

@@ -1,4 +1,4 @@
-langchain-tilores[all]>=0.1.0
+langchain-tilores[all]>=0.3.0
 langgraph==0.2.22
 langchain_openai
 langchain_aws
@@ -8,3 +8,4 @@ chainlit
 unstructured
 pdfminer.six
 unstructured[pdf]
+plotly==5.24.1

langchain_tilores/tilores_tools.py

@@ -2,6 +2,7 @@
 from tilores.helpers import PydanticFactory
 from functools import cached_property
 from langchain.tools import StructuredTool
+from pydantic import create_model
 
 class TiloresTools:
     """
@@ -21,8 +22,8 @@ def references(self):
 
     def all(self):
         return [
-            # self.record_fields_tool,
-            self.search_tool
+            self.search_tool,
+            self.edge_tool
         ]
 
     def search_tool(self):
@@ -33,6 +34,15 @@ def search_tool(self):
             'return_direct': True,
             'func': self.tilores_api.search
         })
+
+    def edge_tool(self):
+        return StructuredTool.from_function(**{
+            'name': 'tilores_entity_edges',
+            'description': 'useful for when you need to provide details about why certain records of an entity are matching; a single edge contains two record IDs and a rule ID representing the reason why those two records belong to the same entity',
+            'args_schema': create_model("EntityEdgesArgs", entityID=(str, ...)),
+            'return_direct': True,
+            'func': self.tilores_api.entity_edges
+        })
 
 def static_value(val):
     def wrapper():

pyproject.toml

@@ -1,8 +1,9 @@
 [project]
 name = "langchain-tilores"
-version = "0.2.2"
+version = "0.3.0"
 authors = [
   { name="Lukas Rieder", email="lukas@parlant.co" },
+  { name="Stefan Berkner", email="stefan.berkner@tilores.io" },
 ]
 description = "This package contains tools to work with Tilores entity resolution database within Langchain."
 readme = "README.md"
@@ -15,7 +16,7 @@ classifiers = [
     "Operating System :: OS Independent",
 ]
 dependencies = [
-  "tilores-sdk>=0.1.0",
+  "tilores-sdk>=0.3.0",
 ]
 [project.optional-dependencies]
 all = ["langchain-tilores[langchain]"]