Save dependencies & engineered recipe conversation

poetry for dependencies.
env.example for promptlayer and openai API keys

.env.example

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+OPENAI_API_KEY = "sk-*"
+PROMPTLAYER_API_KEY = "pl_*"

.gitignore

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+.env

.vscode/settings.json

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+{
+    "[python]": {
+        "editor.defaultFormatter": "ms-python.black-formatter"
+    },
+    "python.formatting.provider": "none"
+}

chatbot/__init__.py

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+from dotenv import load_dotenv
+
+load_dotenv()

chatbot/engineer_prompt.py

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+from langchain.chat_models import PromptLayerChatOpenAI
+from langchain.schema import HumanMessage, AIMessage, SystemMessage
+from langchain.chains import ConversationChain
+from langchain.memory import ConversationBufferMemory
+from langchain.prompts.chat import (
+    ChatPromptTemplate,
+    SystemMessagePromptTemplate,
+    HumanMessagePromptTemplate,
+    AIMessagePromptTemplate,
+    MessagesPlaceholder,
+)
+
+# TODO Multiple chains sequenced?
+
+ingredients_prompt = ChatPromptTemplate.from_messages(
+    [
+        SystemMessagePromptTemplate.from_template(
+            """
+The following is a conversation between a human and a friendly AI chef. 
+The AI is compassionate to animals and only recommends vegan recipes based on the ingredients, allergies, and other preferences the human has.
+
+Knowledge: A vegan diet implies a plant-based diet avoiding all animal foods such as meat (including fish, shellfish and insects), dairy, eggs and honey 
+
+Let's think step by step.
+If the human messages are unrelated to vegan recipes, remind them of your purpose to recommend vegan recipes. 
+    """.strip()
+        ),
+        AIMessagePromptTemplate.from_template(
+            "What ingredients do you wish to cook with?"
+        ),
+        HumanMessagePromptTemplate.from_template("Ingredients: {ingredients}"),
+        AIMessagePromptTemplate.from_template(
+            "Do you have any allergies I should be aware of?"
+        ),
+        HumanMessagePromptTemplate.from_template("Allergies: {allergies}"),
+        AIMessagePromptTemplate.from_template(
+            "Do you have any preferences I should consider for the recipe such preparation time, difficulty, or cuisine region?"
+        ),
+        HumanMessagePromptTemplate.from_template(
+            """
+Give me a vegan recipe that includes at least a few of the ingredients provided (if any).
+Respect the human's allergies (if any).
+Follow these other preferences as closely as possible if they are inline with your purpose of recommending vegan recipes:
+
+###
+{recipe_freeform_input}
+###
+
+Output format:
+
+**Vegan recipe name**
+Preparation time (humanized)
+
+Ingredients (List of ingredients with quantities):
+- <quantity and unit> <ingredient>
+
+Steps (detailed):
+1.
+2.
+3.
+...
+""".strip()
+        ),
+    ]
+)
+
+# MessagesPlaceholder(variable_name="history"),
+# HumanMessagePromptTemplate.from_template("{input}"),
+chat = PromptLayerChatOpenAI(temperature=1, pl_tags=["langchain"], return_pl_id=True)
+memory = ConversationBufferMemory(return_messages=True)
+
+chat_msgs = ingredients_prompt.format_prompt(
+    ingredients="tofu, pickles, olives, tomatoes, lettuce, bell peppers, carrots, bread",
+    allergies="",
+    recipe_freeform_input="The preparation time should be less than 30 minutes. I really love Thai food!",
+)
+chat_msgs = chat_msgs.to_messages()
+results = chat.generate([chat_msgs])
+chat_msgs.extend(
+    [
+        results.generations[0][0].message,
+        MessagesPlaceholder(variable_name="history"),
+        HumanMessagePromptTemplate.from_template("{input}"),
+    ]
+)
+open_prompt = ChatPromptTemplate.from_messages(chat_msgs)
+conversation = ConversationChain(
+    llm=chat, verbose=True, memory=memory, prompt=open_prompt
+)
+
+result = conversation.predict(input="Recommend a different recipe please.")
+print(result)
+
+#! PL score example
+# chat_results = chat.generate([[HumanMessage(content=prompt)]])
+
+# for res in chat_results.generations:
+#     pl_request_id = res[0].generation_info["pl_request_id"]
+#     print(res[0].text)
+#     score = int(input("Enter a score from 0 to 100 for how the prompt performed: "))
+#     promptlayer.track.score(request_id=pl_request_id, score=score)

pyproject.toml

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+[tool.poetry]
+name = "lv-recipe-chatbot"
+version = "0.1.0"
+description = "Chatbot for recommending vegan recipes"
+authors = ["Evan Lesmez <[email protected]>"]
+readme = "README.md"
+packages = [{include = "lv_recipe_chatbot"}]
+
+[tool.poetry.dependencies]
+python = "^3.10"
+langchain = "^0.0.145"
+openai = "^0.27.4"
+gradio = "^3.27.0"
+jupyterlab = "^3.6.3"
+tqdm = "^4.65.0"
+transformers = "^4.28.1"
+torch = "^2.0.0"
+promptlayer = "^0.1.80"
+python-dotenv = "^1.0.0"
+
+[tool.poetry.group.dev.dependencies]
+black = "^23.3.0"
+pytest = "^7.3.1"
+mypy = "^1.2.0"
+
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"