Dev

.gitignore

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+node_modules

api-reference/examples-notebook.mdx

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+---
+title: "Interactive Examples Notebook"
+description: "Explore a diverse collection of examples showcasing the versatility of the Julep platform for app creation and process automation."
+---
+
+<CardGroup cols={2}>
+  <Card title="Engaging Chat Interactions" icon="comments" href="https://github.com/future-agi/client/blob/main/fi/examples/chat.ipynb">
+    Master the art of creating dynamic chat-based applications
+  </Card>
+
+  <Card title="Multimodal Data Handling" icon="image" href="https://github.com/future-agi/client/blob/main/fi/examples/image.ipynb">
+    Learn to seamlessly integrate image and text data in your projects
+  </Card>
+
+  <Card title="Advanced RAG Techniques" icon="brain-circuit" href="https://github.com/future-agi/client/blob/main/fi/examples/rag_file.py">
+    Dive into Retrieval Augmented Generation for enhanced content creation
+  </Card>
+
+  <Card title="Efficient Text Summarization" icon="compress" href="https://github.com/future-agi/client/blob/main/fi/examples/summerizaton.ipynb">
+    Discover techniques for concise and accurate text summarization
+  </Card>
+
+  <Card title="Customizable Prompt Engineering" icon="wand-magic-sparkles" href="https://github.com/future-agi/client/blob/main/fi/examples/prompt_template.py">
+    Unlock the power of flexible prompt templates for diverse applications
+  </Card>
+</CardGroup>

api-reference/introduction.mdx

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+---
+title: 'Introduction'
+description: 'Example section for showcasing API endpoints'
+---
+
+<Note>
+  If you're not looking to build API reference documentation, you can delete
+  this section by removing the api-reference folder.
+</Note>
+
+## Welcome
+
+There are two ways to build API documentation: [OpenAPI](https://mintlify.com/docs/api-playground/openapi/setup) and [MDX components](https://mintlify.com/docs/api-playground/mdx/configuration). For the starter kit, we are using the following OpenAPI specification.
+
+<Card
+  title="Plant Store Endpoints"
+  icon="leaf"
+  href="https://github.com/mintlify/starter/blob/main/api-reference/openapi.json"
+>
+  View the OpenAPI specification file
+</Card>
+
+## Authentication
+
+All API endpoints are authenticated using Bearer tokens and picked up from the specification file.
+
+```json
+"security": [
+  {
+    "bearerAuth": []
+  }
+]
+```

api-reference/openapi.json

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+{
+  "openapi": "3.0.1",
+  "info": {
+    "title": "OpenAPI Plant Store",
+    "description": "A sample API that uses a plant store as an example to demonstrate features in the OpenAPI specification",
+    "license": {
+      "name": "MIT"
+    },
+    "version": "1.0.0"
+  },
+  "servers": [
+    {
+      "url": "http://sandbox.mintlify.com"
+    }
+  ],
+  "security": [
+    {
+      "bearerAuth": []
+    }
+  ],
+  "paths": {
+    "/plants": {
+      "get": {
+        "description": "Returns all plants from the system that the user has access to",
+        "parameters": [
+          {
+            "name": "limit",
+            "in": "query",
+            "description": "The maximum number of results to return",
+            "schema": {
+              "type": "integer",
+              "format": "int32"
+            }
+          }
+        ],
+        "responses": {
+          "200": {
+            "description": "Plant response",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "type": "array",
+                  "items": {
+                    "$ref": "#/components/schemas/Plant"
+                  }
+                }
+              }
+            }
+          },
+          "400": {
+            "description": "Unexpected error",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/Error"
+                }
+              }
+            }
+          }
+        }
+      },
+      "post": {
+        "description": "Creates a new plant in the store",
+        "requestBody": {
+          "description": "Plant to add to the store",
+          "content": {
+            "application/json": {
+              "schema": {
+                "$ref": "#/components/schemas/NewPlant"
+              }
+            }
+          },
+          "required": true
+        },
+        "responses": {
+          "200": {
+            "description": "plant response",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/Plant"
+                }
+              }
+            }
+          },
+          "400": {
+            "description": "unexpected error",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/Error"
+                }
+              }
+            }
+          }
+        }
+      }
+    },
+    "/plants/{id}": {
+      "delete": {
+        "description": "Deletes a single plant based on the ID supplied",
+        "parameters": [
+          {
+            "name": "id",
+            "in": "path",
+            "description": "ID of plant to delete",
+            "required": true,
+            "schema": {
+              "type": "integer",
+              "format": "int64"
+            }
+          }
+        ],
+        "responses": {
+          "204": {
+            "description": "Plant deleted",
+            "content": {}
+          },
+          "400": {
+            "description": "unexpected error",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "$ref": "#/components/schemas/Error"
+                }
+              }
+            }
+          }
+        }
+      }
+    }
+  },
+  "components": {
+    "schemas": {
+      "Plant": {
+        "required": [
+          "name"
+        ],
+        "type": "object",
+        "properties": {
+          "name": {
+            "description": "The name of the plant",
+            "type": "string"
+          },
+          "tag": {
+            "description": "Tag to specify the type",
+            "type": "string"
+          }
+        }
+      },
+      "NewPlant": {
+        "allOf": [
+          {
+            "$ref": "#/components/schemas/Plant"
+          },
+          {
+            "required": [
+              "id"
+            ],
+            "type": "object",
+            "properties": {
+              "id": {
+                "description": "Identification number of the plant",
+                "type": "integer",
+                "format": "int64"
+              }
+            }
+          }
+        ]
+      },
+      "Error": {
+        "required": [
+          "error",
+          "message"
+        ],
+        "type": "object",
+        "properties": {
+          "error": {
+            "type": "integer",
+            "format": "int32"
+          },
+          "message": {
+            "type": "string"
+          }
+        }
+      }
+    },
+    "securitySchemes": {
+      "bearerAuth": {
+        "type": "http",
+        "scheme": "bearer"
+      }
+    }
+  }
+}

api-reference/python-sdk-client.mdx

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+---
+title: " Python SDK Client"
+description: "Comprehensive Manager Class for System Components and API Interaction"
+---
+
+## **Installation**
+
+```python
+pip install futureagi
+```
+
+### **1. Required Parameters:**
+
+• **model\_id**: A unique identifier for your model. This helps in tracking and distinguishing between different models in your system.
+
+• **model\_type**: The type of model you are using. For instance, ModelTypes.GENERATIVE\_LLM specifies that the model is a Generative Language Learning Model.
+
+• **environment**: The environment in which the model is running, such as Environments.PRODUCTION for production environments. This helps in differentiating between development, testing, and production stages.
+
+• **conversation**: A dictionary containing the conversation data. For example, chat\_history can include user interactions. This is essential for models that deal with conversational AI to log the context of interactions.
+
+### 2. Optional Parameters:
+
+• **model\_version**: The version of the model being used. This is useful for tracking changes and improvements in different versions of your model.
+
+• **prediction\_timestamp**: A timestamp indicating when the prediction was made. This helps in logging the exact time of the event, which is crucial for time-series analysis and debugging.
+
+• **tags**: A dictionary of tags for additional metadata. This can include project names, specific identifiers, or any other relevant information to categorize and filter events.
+
+### 3. Supported Model Types:
+
+• **Generative LLM**: For text data.
+
+• **Generative Image**: For text and image data.
+
+### 4. Supported Environments:
+
+• **Training**: For models in the training phase.
+
+• **Validation**: For models in the validation phase.
+
+• **Production**: For models deployed in a production environment.
+
+• **Corpus**: For models dealing with a large collection of data or corpus.
+
+### Example Code:
+
+Below is an example of how to log an event with the Fi AI Client, including the usage of each parameter:
+
+```python
+from fi.utils.types import ModelTypes, Environments
+
+client.log(
+    model_id="your_model_id",  # Unique identifier for the model
+    model_type=ModelTypes.GENERATIVE_LLM,  # Type of model (e.g., Generative LLM)
+    environment=Environments.PRODUCTION,  # Environment (e.g., Production)
+    model_version="1.0.0",  # Version of the model (optional)
+    prediction_timestamp=1625216400,  # Timestamp of the prediction (optional)
+    conversation={
+        "chat_history": [
+            {"role": "user", "content": "How do I implement a neural network in Python?"},
+            {"role": "assistant", "content": "To implement a neural network in Python, you can use libraries like TensorFlow or PyTorch. Here’s a simple example using PyTorch..."}
+        ]
+    },  # Conversation data (optional)
+    tags={"project": "AI project"}  # Additional metadata tags (optional)
+)
+```
+
+## Explanation of Each Key:
+
+• **model\_id**: This key is crucial for identifying the specific model making the predictions. It allows for detailed tracking and management of different models within your system.
+
+• **model\_type**: Specifies the type of model being used, which helps in understanding the nature and purpose of the logged events. ModelTypes.GENERATIVE\_LLM indicates that the model generates language-based outputs.
+
+• **environment**: Indicates the deployment stage of the model. By specifying Environments.PRODUCTION, you ensure that the logs are appropriately categorized, helping in monitoring and managing production models.
+
+• **model\_version**: Helps in version control by logging which version of the model was used for a particular event. This is useful for tracking performance and debugging issues related to specific versions.
+
+• **prediction\_timestamp**: Provides the exact time when the prediction was made. This is essential for time-based analysis and understanding the sequence of events.
+
+• **conversation**: Contains the details of the conversation, including user inputs. This is particularly important for conversational models to retain context and improve the accuracy of responses.
+
+• **tags**: Allows for additional customization and categorization of events. By using tags, you can add project names or other identifiers to make filtering and searching through logs more efficient.
+
+By understanding and utilizing these parameters effectively, you can ensure comprehensive and organized logging of events, facilitating better monitoring, debugging, and analysis of your AI models.
+

evaluations/overview.mdx

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+---
+title: Overview
+description: Evaluations are a way to evaluate the quality of your models.
+---
+
+<CardGroup>
+  <Card title="Running Evaluations using the Python SDK" icon="code" href="/evaluations/quickstart">
+    Run preset evaluations using the Python SDK
+  </Card>
+  <Card title="Running Evaluations on Future AGI Platform" icon="code" href="/evaluations/datasets">
+    Run preset evaluations on the Future AGI Platform
+  </Card>
+</CardGroup>
+
+