prompt refinement and dependency update

vizro-ai/changelog.d/20231101_175538_anna_xiong_prompt_refinement.md

@@ -0,0 +1,48 @@
+<!--
+A new scriv changelog fragment.
+
+Uncomment the section that is right (remove the HTML comment wrapper).
+-->
+
+<!--
+### Highlights ✨
+
+- A bullet item for the Highlights ✨ category with a link to the relevant PR at the end of your entry, e.g. Enable feature XXX ([#1](https://github.com/mckinsey/vizro/pull/1))
+
+-->
+<!--
+### Removed
+
+- A bullet item for the Removed category with a link to the relevant PR at the end of your entry, e.g. Enable feature XXX ([#1](https://github.com/mckinsey/vizro/pull/1))
+
+-->
+<!--
+### Added
+
+- A bullet item for the Added category with a link to the relevant PR at the end of your entry, e.g. Enable feature XXX ([#1](https://github.com/mckinsey/vizro/pull/1))
+
+-->
+<!--
+### Changed
+
+- A bullet item for the Changed category with a link to the relevant PR at the end of your entry, e.g. Enable feature XXX ([#1](https://github.com/mckinsey/vizro/pull/1))
+
+-->
+<!--
+### Deprecated
+
+- A bullet item for the Deprecated category with a link to the relevant PR at the end of your entry, e.g. Enable feature XXX ([#1](https://github.com/mckinsey/vizro/pull/1))
+
+-->
+<!--
+### Fixed
+
+- A bullet item for the Fixed category with a link to the relevant PR at the end of your entry, e.g. Enable feature XXX ([#1](https://github.com/mckinsey/vizro/pull/1))
+
+-->
+<!--
+### Security
+
+- A bullet item for the Security category with a link to the relevant PR at the end of your entry, e.g. Enable feature XXX ([#1](https://github.com/mckinsey/vizro/pull/1))
+
+-->

vizro-ai/pyproject.toml

@@ -16,7 +16,7 @@ dependencies = [
   "pandas",
   "tabulate",
   "openai>=0.27.8",
-  "langchain==0.0.317",
+  "langchain==0.0.325",
   "python-dotenv>=1.0.0",  # TODO decide env var management to see if we need this
   "vizro>=0.1.4",  # TODO set upper bound later
   "ipython>=8.10.0",  # not directly required, pinned by Snyk to avoid a vulnerability: https://app.snyk.io/vuln/SNYK-PYTHON-IPYTHON-3318382

vizro-ai/snyk/requirements.txt

@@ -1,7 +1,7 @@
 pandas
 tabulate
 openai>=0.27.8
-langchain==0.0.317
+langchain==0.0.325
 python-dotenv>=1.0.0
 vizro>=0.1.4
 ipython>=8.10.0

vizro-ai/src/vizro_ai/chains/_llm_models.py

@@ -1,11 +1,10 @@
 from typing import Callable, Dict, List, Union
 
 from langchain.chat_models import ChatOpenAI
-from langchain.llms import OpenAI
 from pydantic import BaseModel, Field
 
 # TODO add new wrappers in if new model support is added
-LLM_MODELS = Union[ChatOpenAI, OpenAI]
+LLM_MODELS = Union[ChatOpenAI]
 
 # TODO constant of model inventory, can be converted to yaml and link to docs
 PREDEFINED_MODELS: List[Dict[str, any]] = [
@@ -19,11 +18,6 @@
         "max_tokens": 8192,
         "wrapper": ChatOpenAI,
     },
-    {
-        "name": "text-davinci-003",
-        "max_tokens": 8192,
-        "wrapper": OpenAI,
-    },
 ]
 
 

vizro-ai/src/vizro_ai/components/dataframe_craft.py

@@ -25,14 +25,14 @@ class DataFrameCraft(BaseModel):
 
 
 # 2. Define prompt
-dataframe_prompt = (
-    "write pandas dataframe manipulation code for the given df, df info:{df_schema}, {df_head}, "
-    "and user question {input}?, DO NOT create a new dataframe"
-    "DO NOT include plot here, make sure each column exists and will have names and re-indexed "
-    "when there is aggregation"
-    "only write dataframe manipulation if required for visualization"
-    "DO NOT wrap into a function, use line by line code"
-)
+dataframe_prompt = """Context: You are working with a pandas DataFrame in Python named df.
+DataFrame Details Schema: {df_schema}, Sample Data: {df_head}, User Query: {input}
+Instructions: 1.Write code to manipulate the df DataFrame according to the user's query.
+2.Do not create any new DataFrames; work only with df.
+3.Ensure that any aggregated columns are named appropriately and re-indexed if necessary.
+4.If a visualization is implied by the user's query, only write the necessary DataFrame manipulation
+code for that visualization. 5.Do not include any plotting code.
+6. Produce the code in a line-by-line format, not wrapped inside a function."""
 
 
 # 3. Define Component

vizro-ai/src/vizro_ai/components/visual_code.py

@@ -21,7 +21,10 @@ class VizroCode(BaseModel):
 
 # 2. Define prompt
 visual_code_prompt = (
-    "Give plotly code for {chart_types}, and user question {input}, using this as df result: {df_code}?"
+    "Context: You are working with a pandas dataframe in Python. The name of the dataframe is `df`."
+    "Instructions: Given the code snippet {df_code}, generate Plotly visualization code to produce a {chart_types} "
+    "chart that addresses user query: {input}. "
+    "Please ensure the Plotly code aligns with the provided DataFrame details."
 )