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https://github.com/hwchase17/langchain.git
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Adding ability to return_pl_id
to all PromptLayer Models in LangChain (#1699)
PromptLayer now has support for [several different tracking features.](https://magniv.notion.site/Track-4deee1b1f7a34c1680d085f82567dab9) In order to use any of these features you need to have a request id associated with the request. In this PR we add a boolean argument called `return_pl_id` which will add `pl_request_id` to the `generation_info` dictionary associated with a generation. We also updated the relevant documentation.
This commit is contained in:
@@ -25,9 +25,25 @@ from langchain.llms import PromptLayerOpenAI
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llm = PromptLayerOpenAI(pl_tags=["langchain-requests", "chatbot"])
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```
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To get the PromptLayer request id, use the argument `return_pl_id` when instanializing the LLM
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```python
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from langchain.llms import PromptLayerOpenAI
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llm = PromptLayerOpenAI(return_pl_id=True)
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```
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This will add the PromptLayer request ID in the `generation_info` field of the `Generation` returned when using `.generate` or `.agenerate`
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For example:
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```python
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llm_results = llm.generate(["hello world"])
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for res in llm_results.generations:
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print("pl request id: ", res[0].generation_info["pl_request_id"])
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```
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You can use the PromptLayer request ID to add a prompt, score, or other metadata to your request. [Read more about it here](https://magniv.notion.site/Track-4deee1b1f7a34c1680d085f82567dab9).
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This LLM is identical to the [OpenAI LLM](./openai), except that
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- all your requests will be logged to your PromptLayer account
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- you can add `pl_tags` when instantializing to tag your requests on PromptLayer
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- you can add `return_pl_id` when instantializing to return a PromptLayer request id to use [while tracking requests](https://magniv.notion.site/Track-4deee1b1f7a34c1680d085f82567dab9).
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PromptLayer also provides native wrappers for [`PromptLayerChatOpenAI`](../modules/chat/examples/promptlayer_chat_openai.ipynb)
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PromptLayer also provides native wrappers for [`PromptLayerChatOpenAI`](../modules/chat/examples/promptlayer_chat_openai.ipynb) and `PromptLayerOpenAIChat`
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@@ -123,6 +123,40 @@
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"id": "05e9e2fe",
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"metadata": {},
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"source": []
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "c43803d1",
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"metadata": {},
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"source": [
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"## Using PromptLayer Track\n",
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"If you would like to use any of the [PromptLayer tracking features](https://magniv.notion.site/Track-4deee1b1f7a34c1680d085f82567dab9), you need to pass the argument `return_pl_id` when instantializing the PromptLayer LLM to get the request id. "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b7d4db01",
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"metadata": {},
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"outputs": [],
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"source": [
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"chat = PromptLayerChatOpenAI(return_pl_id=True)\n",
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"chat_results = chat.generate([[HumanMessage(content=\"I am a cat and I want\")]])\n",
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"\n",
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"for res in chat_results.generations:\n",
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" pl_request_id = res[0].generation_info[\"pl_request_id\"]\n",
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" promptlayer.track.score(request_id=pl_request_id, score=100)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "13e56507",
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"metadata": {},
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"source": [
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"Using this allows you to track the performance of your model in the PromptLayer dashboard. If you are using a prompt template, you can attach a template to a request as well.\n",
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"Overall, this gives you the opportunity to track the performance of different templates and models in the PromptLayer dashboard."
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]
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}
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],
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"metadata": {
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@@ -141,11 +175,11 @@
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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": "3.8.8"
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"version": "3.8.8 (default, Apr 13 2021, 12:59:45) \n[Clang 10.0.0 ]"
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},
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"vscode": {
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"interpreter": {
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"hash": "c4fe2cd85a8d9e8baaec5340ce66faff1c77581a9f43e6c45e85e09b6fced008"
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"hash": "8a5edab282632443219e051e4ade2d1d5bbc671c781051bf1437897cbdfea0f1"
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}
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}
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},
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@@ -119,10 +119,39 @@
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "05e9e2fe",
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"metadata": {},
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"source": []
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"source": [
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"## Using PromptLayer Track\n",
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"If you would like to use any of the [PromptLayer tracking features](https://magniv.notion.site/Track-4deee1b1f7a34c1680d085f82567dab9), you need to pass the argument `return_pl_id` when instantializing the PromptLayer LLM to get the request id. "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "1a7315b9",
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"metadata": {},
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"outputs": [],
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"source": [
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"llm = PromptLayerOpenAI(return_pl_id=True)\n",
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"llm_results = llm.generate([\"Tell me a joke\"])\n",
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"\n",
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"for res in llm_results.generations:\n",
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" pl_request_id = res[0].generation_info[\"pl_request_id\"]\n",
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" promptlayer.track.score(request_id=pl_request_id, score=100)"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"id": "7eb19139",
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"metadata": {},
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"source": [
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"Using this allows you to track the performance of your model in the PromptLayer dashboard. If you are using a prompt template, you can attach a template to a request as well.\n",
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"Overall, this gives you the opportunity to track the performance of different templates and models in the PromptLayer dashboard."
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]
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}
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],
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"metadata": {
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@@ -145,7 +174,7 @@
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},
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"vscode": {
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"interpreter": {
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"hash": "c4fe2cd85a8d9e8baaec5340ce66faff1c77581a9f43e6c45e85e09b6fced008"
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"hash": "8a5edab282632443219e051e4ade2d1d5bbc671c781051bf1437897cbdfea0f1"
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}
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}
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},
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