Added langchain agent to talk to Giskard models

python-client/docs/guides/talk_to_your_model/index.md

@@ -0,0 +1,44 @@
+# 🗣️Talk to your model
+
+The **Talk to Your Model** feature allow you to engage in a *conversation* with your model in order to ask him to make
+predictions, explain those prediction and help understand those predictions.
+
+To talk to your model, you simply need [to wrap it into giskard](../wrap_model/index.md) and call the `talk` method:
+
+```python
+import giskard
+import os
+
+model, df = giskard.demo.titanic()
+giskard_dataset = giskard.Dataset(df=df, target="Survived", name="Titanic dataset")
+giskard_model = giskard.Model(model=model, model_type="classification",
+                              name="Titanic model that return yes if survived otherwise no",
+                              classification_labels=['no', 'yes'])
+
+# Set up your OpenAI API key, by default we are using GPT 3.5
+os.environ['OPENAI_API_KEY'] = 'sk-...'
+
+# Talk to your model
+print(giskard_model.talk('What is this model doing?'))
+print(giskard_model.talk('Can you tell me if "Webber, Miss. Susan" survived the titanic crash?', giskard_dataset, True))
+print(giskard_model.talk('Can you explain me why you predicted that "Webber, Miss. Susan" survived the titanic crash?',
+                         giskard_dataset, True))
+```
+
+## Using a custom language model
+
+By default, GPT 3.5 will be used to generate response. You can use
+any [language model](https://python.langchain.com/docs/modules/model_io/models/) by setting the default llm globally
+using `giskard.set_default_llm`:
+
+```python
+import giskard
+from langchain.llms import Cohere
+
+# Create your llm
+llm = Cohere()
+
+# Set your llm globally
+giskard.llm_config.set_default_llm(llm)
+```
+

python-client/docs/index.md

@@ -22,6 +22,7 @@ guides/scan/index
 guides/slice/index
 guides/transformation/index
 guides/test-suite/index
+guides/talk_to_your_model/index
 guides/cicd/pipeline
 guides/installation_app/index
 guides/upload/index
@@ -131,4 +132,3 @@ integrations/index
 ::::
 :::::
 
-

python-client/giskard/__init__.py

@@ -16,6 +16,7 @@
 from giskard.ml_worker.utils.logging import configure_logging
 from giskard.models.automodel import Model
 from . import demo
+from .llm.config import llm_config
 from .ml_worker.utils.network import check_latest_giskard_version
 from .scanner import scan
 from .utils.analytics_collector import analytics
@@ -54,4 +55,5 @@ def get_version() -> str:
     "TestResult",
     "GiskardTest",
     "demo",
+    "llm_config",
 ]

python-client/giskard/demo/__init__.py

@@ -29,6 +29,7 @@ def linear_pipeline():
     "titanic_df",
     "titanic",
     "titanic_pipeline",
+    "titanic_wrapped",
     "linear_df",
     "linear",
     "linear_pipeline",

python-client/giskard/demo/titanic_classification.py

@@ -1,4 +1,5 @@
 import os
+
 import pandas as pd
 from sklearn import model_selection
 from sklearn.compose import ColumnTransformer
@@ -16,6 +17,7 @@ def get_df():
     df["Survived"] = df["Survived"].apply(lambda x: _classification_labels[x])
     return df
 
+
 def get_test_df():
     df = pd.read_csv(os.path.join(os.path.dirname(__file__), "titanic.csv"))
     df.drop(["Ticket", "Cabin"], axis=1, inplace=True)

python-client/giskard/llm/config.py

@@ -0,0 +1,47 @@
+import os
+from typing import Tuple
+
+
+def _get_openai():
+    if "OPENAI_API_KEY" not in os.environ:
+        raise EnvironmentError(
+            """
+            You're trying to use giskard LLM features without providing any LLM or OpenAI API key.
+            To use the default OpenAI API please provide the OPENAI_API_KEY environment variable.
+            To use a custom model, please setup your llm by calling `giskard.set_default_llm(my_llm)`
+            """
+        )
+
+    from langchain.llms import OpenAI
+
+    return OpenAI(temperature=0.1)
+
+
+class _TalkConfig:
+    reliability_thresholds: Tuple[int, int] = 4, 6
+
+
+class _LlmConfig:
+    _default_llm = None
+    talk: _TalkConfig = _TalkConfig()
+
+    @property
+    def default_llm(self):
+        if self._default_llm is None:
+            # Lazily call _get_openai as fallback to avoid getting missing key or dependency errors when not required
+            self._default_llm = _get_openai()
+
+        return self._default_llm
+
+    def set_default_llm(self, default_llm=None):
+        from langchain.base_language import BaseLanguageModel
+
+        if default_llm is not None and not isinstance(default_llm, BaseLanguageModel):
+            raise ValueError(
+                "Please make sure that the default llm provided is instance of `langchain.base_language.BaseLanguageModel`"
+            )
+
+        self._default_llm = default_llm
+
+
+llm_config = _LlmConfig()