update: different ollama models

modules/llm_in_use.py

@@ -13,7 +13,9 @@ def get_llm():
 
     # llm = ChatOpenAI(temperature=0)
 
-    llm = ChatOllama(model="llama3.2:latest", temperature=0, base_url="http://141.211.127.171")
+    llm = ChatOllama(model="llama3.2:3b", temperature=0, base_url="http://141.211.127.171")
+    # llm = ChatOllama(model="qwen2.5:14b", temperature=0, base_url="http://141.211.127.171")
+    # llm = ChatOllama(model="nexusraven:13b", temperature=0, base_url="http://141.211.127.171")
 
     # llm = ChatGoogleGenerativeAI(model="gemini-1.5-flash-latest")
 

paintrek-chat-v2.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2025-01-29T20:09:11.440091Z",
@@ -14,16 +14,7 @@
     "id": "xaiioUQni_ga",
     "trusted": true
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/frank-elite/miniconda3/envs/paintrekbot/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
-      "  from .autonotebook import tqdm as notebook_tqdm\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from modules.data_class import DataState\n",
     "from modules.tools import data_node\n",
@@ -45,7 +36,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2025-01-29T20:09:11.906458Z",
@@ -57,19 +48,7 @@
     "id": "9rqkQzlZxrzp",
     "trusted": true
    },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<IPython.core.display.Image object>"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "graph_builder = StateGraph(DataState)\n",
     "memory = MemorySaver()\n",
@@ -95,7 +74,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2025-01-29T20:09:38.185616Z",
@@ -107,65 +86,7 @@
     "id": "NCRSgaBUfIHF",
     "trusted": true
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Executing the chatbot graph...\n",
-      "Model: Welcome to the Paintrek world. I am a health assistant, an interactive clinical recording system. I will ask you questions about your pain and related symptoms and record your responses.  I will then store this information securely. At any time, you can type `q` to quit.\n",
-      "User: Hello\n",
-      "Model: I'm MedAssist, your intelligent medical intake system. I'll guide you through a structured data collection process to gather comprehensive patient information.\n",
-      "\n",
-      "To begin, can you please tell me your name and date of birth? This will help me identify you in our records and ensure accurate communication throughout the process.\n",
-      "User: \n",
-      "Model: Here is the JSON payload that can be sent to the server to collect all the necessary information:\n",
-      "\n",
-      "```json\n",
-      "{\n",
-      "  \"name\": \"\",\n",
-      "  \"family_hist\": \"\",\n",
-      "  \"social_hist\": {\n",
-      "    \"occupation\": \"\",\n",
-      "    \"smoke\": false,\n",
-      "    \"alcohol\": false,\n",
-      "    \"drug\": false,\n",
-      "    \"support_system\": \"\",\n",
-      "    \"living_condition\": \"\"\n",
-      "  },\n",
-      "  \"pain_manage\": {\n",
-      "    \"pain_medication\": \"\",\n",
-      "    \"specialist\": false,\n",
-      "    \"other_therapy\": \"\",\n",
-      "    \"effectiveness\": false\n",
-      "  },\n",
-      "  \"functional\": {\n",
-      "    \"life_quality\": \"\",\n",
-      "    \"limit_activity\": \"\",\n",
-      "    \"mood\": \"\"\n",
-      "  },\n",
-      "  \"plan\": {\n",
-      "    \"goal\": \"\",\n",
-      "    \"expectation\": \"\",\n",
-      "    \"alternative_treatment\": \"\"\n",
-      "  },\n",
-      "  \"review_system\": {\n",
-      "    \"weight_change\": \"\",\n",
-      "    \"fever\": false,\n",
-      "    \"chill\": false,\n",
-      "    \"night_sweats\": false,\n",
-      "    \"sleep\": \"\",\n",
-      "    \"gastrointestinal\": \"\",\n",
-      "    \"urinary\": \"\"\n",
-      "  }\n",
-      "}\n",
-      "```\n",
-      "\n",
-      "This payload includes all the necessary fields to collect information about the patient's family history, social history, pain management, functional assessment, and review system. Note that some of these fields are optional (e.g., `smoke`, `alcohol`, etc.) and can be set to `false` if not applicable.\n",
-      "User: q\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# This is for the checkpointer to have a thread id to remember for each user, and I don't know if letter mix with number will work here \n",
     "# The default recursion limit for traversing nodes is 25 - setting it higher means you can try a more complex order with multiple steps and round-trips.\n",
@@ -194,6 +115,13 @@
    "source": [
     "state[\"data\"]"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -211,7 +139,7 @@
    "sourceType": "notebook"
   },
   "kernelspec": {
-   "display_name": "paintrekbot",
+   "display_name": "paintrek",
    "language": "python",
    "name": "python3"
   },
@@ -225,7 +153,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.8"
+   "version": "3.10.14"
   }
  },
  "nbformat": 4,

requirements.txt

@@ -45,7 +45,6 @@ langgraph-sdk==0.1.51
 langsmith==0.3.3
 matplotlib==3.10.0
 matplotlib-inline
-mkl-service==2.4.0
 msgpack==1.1.0
 multidict==6.1.0
 numpy==1.26.4

test_ollama.ipynb

@@ -0,0 +1,172 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from modules.llm_in_use import get_llm\n",
+    "from langchain_ollama import ChatOllama\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "llm = get_llm()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "AIMessage(content='Je aime le programmation.', additional_kwargs={}, response_metadata={'model': 'llama3.2:3b', 'created_at': '2025-03-03T20:22:10.986078Z', 'done': True, 'done_reason': 'stop', 'total_duration': 564767250, 'load_duration': 36439292, 'prompt_eval_count': 45, 'prompt_eval_duration': 207000000, 'eval_count': 7, 'eval_duration': 45000000, 'message': Message(role='assistant', content='', images=None, tool_calls=None)}, id='run-b473d2e4-5ea8-49c1-880c-57529bab3be3-0', usage_metadata={'input_tokens': 45, 'output_tokens': 7, 'total_tokens': 52})"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from langchain_core.messages import AIMessage\n",
+    "\n",
+    "messages = [\n",
+    "    (\n",
+    "        \"system\",\n",
+    "        \"You are a helpful assistant that translates English to French. Translate the user sentence.\",\n",
+    "    ),\n",
+    "    (\"human\", \"I love programming.\"),\n",
+    "]\n",
+    "ai_msg = llm.invoke(messages)\n",
+    "ai_msg"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "AIMessage(content='Ich liebe Programmierung.', additional_kwargs={}, response_metadata={'model': 'llama3.2:3b', 'created_at': '2025-03-03T20:27:19.219749Z', 'done': True, 'done_reason': 'stop', 'total_duration': 1047082250, 'load_duration': 580482958, 'prompt_eval_count': 40, 'prompt_eval_duration': 161000000, 'eval_count': 6, 'eval_duration': 38000000, 'message': Message(role='assistant', content='', images=None, tool_calls=None)}, id='run-bbaf365e-81ba-4928-b6a3-8578efe20cc5-0', usage_metadata={'input_tokens': 40, 'output_tokens': 6, 'total_tokens': 46})"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from langchain_core.prompts import ChatPromptTemplate\n",
+    "\n",
+    "prompt = ChatPromptTemplate.from_messages(\n",
+    "    [\n",
+    "        (\n",
+    "            \"system\",\n",
+    "            \"You are a helpful assistant that translates {input_language} to {output_language}.\",\n",
+    "        ),\n",
+    "        (\"human\", \"{input}\"),\n",
+    "    ]\n",
+    ")\n",
+    "\n",
+    "chain = prompt | llm\n",
+    "chain.invoke(\n",
+    "    {\n",
+    "        \"input_language\": \"English\",\n",
+    "        \"output_language\": \"German\",\n",
+    "        \"input\": \"I love programming.\",\n",
+    "    }\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[{'name': 'validate_user',\n",
+       "  'args': {'addresses': ['123 Fake St', '234 Pretend Boulevard'],\n",
+       "   'user_id': 123},\n",
+       "  'id': '0401ef59-16fb-446c-8fa2-11c2ad671d44',\n",
+       "  'type': 'tool_call'}]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from typing import List\n",
+    "\n",
+    "from langchain_core.tools import tool\n",
+    "from langchain_ollama import ChatOllama\n",
+    "\n",
+    "\n",
+    "@tool\n",
+    "def validate_user(user_id: int, addresses: List[str]) -> bool:\n",
+    "    \"\"\"Validate user using historical addresses.\n",
+    "\n",
+    "    Args:\n",
+    "        user_id (int): the user ID.\n",
+    "        addresses (List[str]): Previous addresses as a list of strings.\n",
+    "    \"\"\"\n",
+    "    return True\n",
+    "\n",
+    "\n",
+    "llm = ChatOllama(\n",
+    "    model=\"llama3.2\",\n",
+    "    temperature=0,\n",
+    "    base_url=\"http://141.211.127.171\"\n",
+    ").bind_tools([validate_user])\n",
+    "\n",
+    "result = llm.invoke(\n",
+    "    \"Could you validate user 123? They previously lived at \"\n",
+    "    \"123 Fake St in Boston MA and 234 Pretend Boulevard in \"\n",
+    "    \"Houston TX.\"\n",
+    ")\n",
+    "result.tool_calls"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "paintrek",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.14"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}