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blog: fix internal links in streamlit post (#605)

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Ben 2026-03-17 15:33:08 -04:00 committed by GitHub
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hindsight-docs/blog/2026-03-17-streamlit-chatbot-memory.md
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@ -24,7 +24,7 @@ Build a web chatbot with persistent memory using Streamlit and Hindsight. ~80 li
## The Problem: Terminal Chatbots Don't Ship ## The Problem: Terminal Chatbots Don't Ship
You built a chatbot with memory using [OpenAI and Hindsight](/blog/give-your-openai-app-a-memory). It works in a terminal: You built a chatbot with memory using [OpenAI and Hindsight](/blog/2026/03/05/add-memory-to-openai-application). It works in a terminal:
```python ```python
user_input = input("You: ") user_input = input("You: ")
@ -63,7 +63,7 @@ st.sidebar → show recalled facts + reflect button
Three layers: Three layers:
- **`st.session_state`** — per-tab, ephemeral conversation history (lost on browser close) - **`st.session_state`** — per-tab, ephemeral conversation history (lost on browser close)
- **[Hindsight](https://hindsight.vectorize.io)** — persistent memory across restarts (facts, entities, [knowledge graph](/blog/spreading-activation-memory-graphs)) - **[Hindsight](https://hindsight.vectorize.io)** — persistent memory across restarts (facts, entities, [knowledge graph](/blog/2026/03/12/spreading-activation-memory-graphs))
- **OpenAI** — generates responses with memory-augmented context - **OpenAI** — generates responses with memory-augmented context
--- ---
@ -140,7 +140,7 @@ export HINDSIGHT_API_LLM_API_KEY=YOUR_OPENAI_KEY
hindsight-api hindsight-api
``` ```
> **Note:** You can also use [Hindsight Cloud](https://ui.hindsight.vectorize.io/signup) instead of self-hosting — just change the `base_url` to `https://api.hindsight.vectorize.io` and add your API key. See the [n8n integration guide](/blog/n8n-memory-persistent-workflows) for details on Cloud vs. self-hosted setup. > **Note:** You can also use [Hindsight Cloud](https://ui.hindsight.vectorize.io/signup) instead of self-hosting — just change the `base_url` to `https://api.hindsight.vectorize.io` and add your API key. See the [n8n integration guide](/blog/2026/03/16/n8n-memory-workflows) for details on Cloud vs. self-hosted setup.
Now wire Hindsight into the chat. The key pattern: use [`@st.cache_resource`](https://docs.streamlit.io/develop/api-reference/caching-and-state/st.cache_resource) to initialize the client once, not on every re-run. Now wire Hindsight into the chat. The key pattern: use [`@st.cache_resource`](https://docs.streamlit.io/develop/api-reference/caching-and-state/st.cache_resource) to initialize the client once, not on every re-run.
@ -411,6 +411,6 @@ Streamlit handles the UI. Hindsight handles the memory. OpenAI handles the gener
- **Show the knowledge graph** — use `include_entities=True` on recall and render entity connections - **Show the knowledge graph** — use `include_entities=True` on recall and render entity connections
- **Deploy with Streamlit Community Cloud** — add `OPENAI_API_KEY` and `HINDSIGHT_API_URL` as secrets - **Deploy with Streamlit Community Cloud** — add `OPENAI_API_KEY` and `HINDSIGHT_API_URL` as secrets
- **Try [Hindsight Cloud](https://ui.hindsight.vectorize.io/signup)** for deployment without self-hosting the memory server - **Try [Hindsight Cloud](https://ui.hindsight.vectorize.io/signup)** for deployment without self-hosting the memory server
- **Customize agent reasoning** — use [disposition traits](/blog/ai-agent-personality-disposition-model) to make your chatbot more empathetic, skeptical, or literal - **Customize agent reasoning** — use [disposition traits](/blog/2026/03/13/disposition-aware-agents) to make your chatbot more empathetic, skeptical, or literal
A chatbot with memory is useful. A chatbot with memory you can inspect is a development tool. A chatbot with memory is useful. A chatbot with memory you can inspect is a development tool.