localai + wip lecl

lecl.py

@@ -0,0 +1,93 @@
+#!/usr/bin/env python3
+# vim: set expandtab sw=4 ts=4 sts=4 foldmethod=indent filetype=python:
+
+import asyncio
+import os
+from langchain_core.output_parsers import StrOutputParser
+from langchain_core.runnables import RunnablePassthrough
+from langchain_openai import ChatOpenAI
+
+os.environ['OPENAI_API_KEY'] = '2708b7c21129e408899d5a38e6d1af8d'
+os.environ['OPENAI_API_BASE'] = 'http://localai.srvlan:8080' 
+
+
+#|%%--%%| <9871Wi18GN|qMj6mA5jLr>
+r"""°°°
+# Basic invokation
+°°°"""
+
+#|%%--%%| <qMj6mA5jLr|LxJxvWuF27>
+
+llm = ChatOpenAI(model="dolphin-mixtral", temperature=0.2, max_tokens=100)
+
+
+#|%%--%%| <LxJxvWuF27|eTnVsVGPqG>
+
+llm.invoke("how can you help me ?")
+
+#|%%--%%| <eTnVsVGPqG|ChQEPJ4k0e>
+r"""°°°
+# Using prompt templates
+°°°"""
+#|%%--%%| <ChQEPJ4k0e|Tl3tcWLlrF>
+
+from langchain_core.prompts import ChatPromptTemplate
+
+prompt = ChatPromptTemplate.from_messages([
+    ("system", "You are a genius DIY maker assistant."),
+    ("user", "{input}")
+    ])
+
+
+# combine llm and prompt to create a chain
+
+chain = prompt | llm
+
+chain.invoke(dict(input="what are the best adhesives to bind metal to wood ?"))
+
+
+#|%%--%%| <Tl3tcWLlrF|z6Tf8SVZ6W>
+r"""°°°
+# Creating a chain
+
+- Every element in chain implements Runnable interface (invoke, stream, ainvoke, batch ...)
+°°°"""
+#|%%--%%| <z6Tf8SVZ6W|qMHVOmTbk0>
+
+prompt = ChatPromptTemplate.from_template("Tell me a short joke about {topic}")
+output_parser = StrOutputParser()
+llm = ChatOpenAI(model="dolphin-mixtral", temperature=0.6, max_tokens=100)
+chain = (
+        {"topic": RunnablePassthrough()}
+        | prompt
+        | llm
+        | output_parser
+        )
+
+chain.invoke("ice cream")
+
+#|%%--%%| <qMHVOmTbk0|RV24rYEjeh>
+
+
+prompt = ChatPromptTemplate.from_template("Tell me a short joke about {topic}")
+output_parser = StrOutputParser()
+llm = ChatOpenAI(model="dolphin-mixtral", temperature=0.6, max_tokens=100)
+chain = (
+        {"topic": RunnablePassthrough()}
+        | prompt
+        | llm
+        | output_parser
+        )
+
+chain.invoke("ice cream")
+
+#|%%--%%| <RV24rYEjeh|RDvrxXtUVe>
+r"""°°°
+# Streaming the response
+https://python.langchain.com/docs/expression_language/streaming
+°°°"""
+#|%%--%%| <RDvrxXtUVe|arP98HJHVd>
+
+async for chunk in chain.astream(dict(input="how can I bind metal to plastic ?")):
+    print(chunk.content, end="", flush=True)
+

test_localai.ipynb

@@ -0,0 +1,26 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "metadata": {
+        "jukit_cell_id": "NONE"
+      },
+      "source": [
+        "#!/usr/bin/env python3\n",
+        "# vim: set expandtab sw=4 ts=4 sts=4 foldmethod=indent filetype=python:"
+      ],
+      "outputs": [],
+      "execution_count": null
+    }
+  ],
+  "metadata": {
+    "anaconda-cloud": {},
+    "kernelspec": {
+      "display_name": "python",
+      "language": "python",
+      "name": "python3"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 4
+}

test_localai.py

@@ -0,0 +1,26 @@
+#|%%--%%| <v7QcmovzRW|SzAmGcGuz7>
+
+from langchain_core.messages import HumanMessage, SystemMessage
+from langchain_openai import ChatOpenAI
+
+#|%%--%%| <SzAmGcGuz7|5hpjZkupU5>
+
+messages = [
+        SystemMessage(content="You are a helpful assistant."),
+        HumanMessage(content="what is a good company name for colorful socks ?")
+        ]
+
+#|%%--%%| <5hpjZkupU5|qXWlUuUqLc>
+
+chat = ChatOpenAI(temperature=0.2, model="dolphin-mixtral", max_tokens=50)
+
+
+#|%%--%%| <qXWlUuUqLc|00yiGVKIRw>
+
+result = chat.invoke(messages)
+
+
+#|%%--%%| <00yiGVKIRw|ZrwfqMozR5>
+
+print(result.content)
+