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docs: update annotation in tutorial (#2293)
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@@ -46,8 +46,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"%pip install -U --quiet langgraph langchain_anthropic\n",
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"%pip install -U --quiet tavily-python"
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"%pip install -U --quiet langgraph langchain_anthropic tavily-python"
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]
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},
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{
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@@ -189,7 +188,7 @@
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" self.runnable = runnable\n",
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" self.validator = validator\n",
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"\n",
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" def respond(self, state: list):\n",
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" def respond(self, state: dict):\n",
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" response = []\n",
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" for attempt in range(3):\n",
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" response = self.runnable.invoke(\n",
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@@ -622,12 +621,6 @@
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"2. The 'reflections' can be paired with additional external feedback (such as validators), to further guide the actor.\n",
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"3. In the paper, 1 environment (AlfWorld) uses external memory. It does this by storing summaries of the reflections to an external store and using them in subsequent trials/invocations."
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]
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},
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{
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"cell_type": "markdown",
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"id": "39e44dd6",
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"metadata": {},
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"source": []
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}
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],
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"metadata": {
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@@ -646,7 +639,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.9"
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"version": "3.12.3"
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}
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},
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"nbformat": 4,
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