Trying Out Ollama Part 4 (Conversations Between LLMs, Gemma3:4B, Python, Node-RED)
管理人Introduction
In this post, I tried using Ollama to facilitate a conversation between two local LLMs.
In a previous article, I used a Python library to enable interactions while maintaining conversation history. By connecting the output of one local LLM to the input of another, I’ve made it possible for them to converse.
▼I am using a gaming laptop purchased for around 100,000 yen, running Windows 11.
Shopping: New Laptop and SSD Expansion (ASUS TUF Gaming A15)
Info This article is translated from Japanese to English. Introduction In this post, I’ll be talking about replacing my PC after my previous one broke down. I …
趣味的ロボット研究所 
ポチップ
▼Previous articles are here:
Searching with Python and Summarizing with a Local LLM (Ollama, Node-RED)
Info This article is translated from Japanese to English. Introduction In this post, I experimented with a Python-based search program to automate information …
Using Ollama Part 2 (Local LLM for Code Generation and Execution, qwen2.5-coder, Node-RED)
Info This article is translated from Japanese to English. Introduction This time, I tried generating code with a local LLM and created a Node-RED flow so that …
Creating the Node-RED Flow
In a previous post, I set up a TCP server using Ollama. This time, I’ll build upon that flow.
▼This is the article:
Trying Out Ollama Part 3 (Usage in Python, Node-RED, Gemma 3:4B)
Info This article is translated from Japanese to English. Introduction In this post, I checked how to use Ollama with Python and set it up so that it can be ex…
I set up TCP servers using Ollama in Python and send messages to those servers using the "tcp request" node.
▼Here is the flow:
I didn't save the JSON file from this specific stage, but it's almost the same as the one in the previous article. I used a "switch" node to filter out the initial messages sent when the server starts.
▼Messages that do not contain "Client connected" or "Listening on" are passed through.
The initial human input is sent via an "inject" node or a "text input" node. The TCP server is set to shut down when "bye" is sent, just like when conversing with Ollama via the command prompt.
Letting Them Converse
I ran the conversation using the flow I created. Both local LLM models are "Gemma3:4B."
I started with a simple "Hello" (Konnichiwa).
▼The small talk progressed even faster than a human conversation.
Even though I only sent "Hello," the AIs started proposing topics and moving the conversation forward. For some reason, they assumed they had just seen a beautiful view.
▼The content of the conversation changes every time you run it. It’s interesting how AIs "watch" YouTube videos or read novels as training data…
I occasionally encountered errors during the process, so some troubleshooting might be necessary.
▼One conversation ended in a way that made it sound like they wanted to stop talking.
I adjusted the settings to keep the answers short and added "Delay" nodes, but I plan to keep refining it as I use it.
▼Sometimes the responses were so short it felt like a conversation that wasn't going anywhere.
▼Perhaps because they are using the same model, they are generally very agreeable with each other.
▼When the conversation flowed well, they engaged in discussions involving technical knowledge.
▼Check the video here. They are discussing robot simulations.
Improving the Flow
I improved the flow using Dashboard 2.0.
▼The scale has grown significantly. Here is the overall flow: (Although not included this time, it further connects to a speech synthesis process.)
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▼The screen looks like this:
By the way, I struggled a bit with displaying the AI's responses in Markdown format. I plan to summarize that in a separate article.
The gauges on the right side of the dashboard were inspired by a teammate's work during last year's Osaka 24-hour AI Hackathon, so I included them.
▼This was the screen during the hackathon:
ちょっと振り返り：いろいろ参加しました（MFK2024、大阪24時間AIハッカソン、IoTLTなど）
はじめに 今回は最近参加していたイベントについてです。以前書いたのは三月頃でしたが、その後もいろいろありました。 まだまだ忙しい日々が続きそうです。 ▼これま…
▼It's also used in this post. Various AI tools are being tested.
I didn't want to put unnecessary load on the process, so I set it to update at 10-second intervals.
▼It uses Windows commands to perform the calculations.
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I operated the dashboard screen to let the AIs converse again.
▼I asked them what they thought of the proverb "Three people together have the wisdom of Monju" (Two heads are better than one). I also provided user input during the process.
▼When I made them take opposing stances, the conversation progressed with a somewhat hostile atmosphere.
Perhaps because the theme was abstract, I got the impression that "Node-2" spent more time critiquing the wording and attitude rather than the actual theme.
Now that I’ve confirmed it works, I plan to experiment with various scenarios.
Finally
By connecting this to speech synthesis and playback, the conversation continued like a radio show. Since the conversation content remains as text, it could be used as an "AI Radio."
The use case depends on the theme, but I think if I have them discuss AI-generated code, they might just start improving it on their own.
