Cohere's NLP model added and utilised it's methods to create bots in testbase.

docs/docs/examples/cohere-chat-bot.md

@@ -0,0 +1,52 @@
+---
+sidebar_position: 1
+---
+
+# Cohere Chat bot
+
+This chat bot makes an API call to Cohere and processes the user input and also maintain the chat history of user and system. It uses command  model by default. More information added in Cohere Class itself.
+
+```py
+from textbase import bot, Message
+from textbase.models import Cohere
+from typing import List
+
+# Load your Cohere API key
+Cohere.api_key = ""
+
+# Prompt for `command` (cohere's model)
+MESSAGE = "Is messi better than ronaldo or ronaldo better than messi?"
+
+@bot()
+def on_message(message_history: List[Message], state: dict = None):
+
+    # Generate `command` (cohere's model) response
+    bot_response = Cohere.chat(
+        system_prompt=MESSAGE,
+        user_name="user",
+        message_history=message_history, # Assuming history is the list of user messages
+        model="command",
+    )
+
+    response = {
+        "data": {
+            "messages": [
+                {
+                    "data_type": "STRING",
+                    "value": bot_response
+                }
+            ],
+            "state": state
+        },
+        "errors": [
+            {
+                "message": ""
+            }
+        ]
+    }
+
+    return {
+        "status_code": 200,
+        "response": response
+    }
+```

docs/docs/examples/cohere-prompt-bot.md

@@ -0,0 +1,53 @@
+---
+sidebar_position: 2
+---
+
+# Cohere Prompt bot
+
+This Prompt bot makes an API call to Cohere and processes the user input and resopond accordingly. It uses command  model by default. More information added in Cohere Class itself.
+
+```py
+from textbase import bot, Message
+from textbase.models import Cohere
+from typing import List
+
+# Load your Cohere API key
+Cohere.api_key = ""
+
+# Prompt for `command` (cohere's model)
+# you add your sample prompts here
+SYSTEM_PROMPT = """How much developer can love python language?
+"""
+
+@bot()
+def on_message(message_history: List[Message], state: dict = None):
+
+    # Generate `command` (cohere's model) response
+    bot_response = Cohere.generate(
+        system_prompt=SYSTEM_PROMPT,
+        message_history=message_history, # Assuming history is the list of user messages
+        model="command",
+    )
+
+    response = {
+        "data": {
+            "messages": [
+                {
+                    "data_type": "STRING",
+                    "value": bot_response
+                }
+            ],
+            "state": state
+        },
+        "errors": [
+            {
+                "message": ""
+            }
+        ]
+    }
+
+    return {
+        "status_code": 200,
+        "response": response
+    }
+```

docs/docs/examples/cohere-summarize-bot.md

@@ -0,0 +1,73 @@
+---
+sidebar_position: 3
+---
+
+# Cohere Summary bot
+
+This bot makes an API call to Cohere and processes the long user input and retruns short and crisp summary of the given para in different forms. It uses command  model by default. More information added in Cohere Class itself.
+
+```py
+from textbase import bot, Message
+from textbase.models import Cohere
+from typing import List
+
+# Load your Cohere API key
+Cohere.api_key = ""
+
+# Prompt for `command` (cohere's model)
+# you add your sample prompts here
+SYSTEM_PROMPT = """"Ice cream is a sweetened frozen food typically eaten as a snack or dessert. 
+  It may be made from milk or cream and is flavoured with a sweetener, 
+  either sugar or an alternative, and a spice, such as cocoa or vanilla, 
+  or with fruit such as strawberries or peaches. 
+  It can also be made by whisking a flavored cream base and liquid nitrogen together. 
+  Food coloring is sometimes added, in addition to stabilizers. 
+  The mixture is cooled below the freezing point of water and stirred to incorporate air spaces 
+  and to prevent detectable ice crystals from forming. The result is a smooth, 
+  semi-solid foam that is solid at very low temperatures (below 2 °C or 35 °F). 
+  It becomes more malleable as its temperature increases.
+  The meaning of the name ice cream varies from one country to another. 
+  In some countries, such as the United States, ice cream applies only to a specific variety, 
+  and most governments regulate the commercial use of the various terms according to the 
+  relative quantities of the main ingredients, notably the amount of cream. 
+  Products that do not meet the criteria to be called ice cream are sometimes labelled 
+  frozen dairy dessert instead. In other countries, such as Italy and Argentina, 
+  one word is used for all variants. Analogues made from dairy alternatives, 
+  such as goat's or sheep's milk, or milk substitutes 
+  (e.g., soy, cashew, coconut, almond milk or tofu), are available for those who are 
+  lactose intolerant, allergic to dairy protein or vegan.
+"""
+
+@bot()
+def on_message(message_history: List[Message], state: dict = None):
+
+    # Generate `command` (cohere's model) response
+    bot_response = Cohere.summarize(
+        text_input=SYSTEM_PROMPT,
+        message_history=message_history, # Assuming history is the list of user messages
+        model="command",
+        length="long"
+    )
+
+    response = {
+        "data": {
+            "messages": [
+                {
+                    "data_type": "STRING",
+                    "value": bot_response
+                }
+            ],
+            "state": state
+        },
+        "errors": [
+            {
+                "message": ""
+            }
+        ]
+    }
+
+    return {
+        "status_code": 200,
+        "response": response
+    }
+```

docs/docs/examples/huggingface-bot.md

@@ -1,5 +1,5 @@
 ---
-sidebar_position: 3
+sidebar_position: 4
 ---
 
 # HuggingFace bot

docs/docs/examples/mimicking-bot.md

@@ -1,5 +1,5 @@
 ---
-sidebar_position: 1
+sidebar_position: 5
 ---
 
 # Mimicking bot

docs/docs/examples/openai-bot.md

@@ -1,5 +1,5 @@
 ---
-sidebar_position: 2
+sidebar_position: 6
 ---
 
 # Open AI bot

examples/cohere-chat-bot/main.py

@@ -0,0 +1,42 @@
+from textbase import bot, Message
+from textbase.models import Cohere
+from typing import List
+
+# Load your Cohere API key
+Cohere.api_key = ""
+
+# Prompt for `command` (cohere's model)
+MESSAGE = "Hey there, How are you!"
+
+@bot()
+def on_message(message_history: List[Message], state: dict = None):
+
+    # Generate `command` (cohere's model) response
+    bot_response = Cohere.chat(
+        system_prompt=MESSAGE,
+        user_name="user",
+        message_history=message_history, # Assuming history is the list of user messages
+        model="command",
+    )
+
+    response = {
+        "data": {
+            "messages": [
+                {
+                    "data_type": "STRING",
+                    "value": bot_response
+                }
+            ],
+            "state": state
+        },
+        "errors": [
+            {
+                "message": ""
+            }
+        ]
+    }
+
+    return {
+        "status_code": 200,
+        "response": response
+    }

examples/cohere-prompt-bot/main.py

@@ -0,0 +1,43 @@
+from textbase import bot, Message
+from textbase.models import Cohere
+from typing import List
+
+# Load your Cohere API key
+Cohere.api_key = ""
+
+# Prompt for `command` (cohere's model)
+# you add your sample prompts here
+SYSTEM_PROMPT = """how python interpreter works!
+"""
+
+@bot()
+def on_message(message_history: List[Message], state: dict = None):
+
+    # Generate `command` (cohere's model) response
+    bot_response = Cohere.generate(
+        system_prompt=SYSTEM_PROMPT,
+        message_history=message_history, # Assuming history is the list of user messages
+        model="command",
+    )
+
+    response = {
+        "data": {
+            "messages": [
+                {
+                    "data_type": "STRING",
+                    "value": bot_response
+                }
+            ],
+            "state": state
+        },
+        "errors": [
+            {
+                "message": ""
+            }
+        ]
+    }
+
+    return {
+        "status_code": 200,
+        "response": response
+    }

examples/cohere-summarize-bot/main.py

@@ -0,0 +1,62 @@
+from textbase import bot, Message
+from textbase.models import Cohere
+from typing import List
+
+# Load your Cohere API key
+Cohere.api_key = ""
+
+# Prompt for `command` (cohere's model)
+# you add your sample prompts here
+SYSTEM_PROMPT = """"Ice cream is a sweetened frozen food typically eaten as a snack or dessert. 
+  It may be made from milk or cream and is flavoured with a sweetener, 
+  either sugar or an alternative, and a spice, such as cocoa or vanilla, 
+  or with fruit such as strawberries or peaches. 
+  It can also be made by whisking a flavored cream base and liquid nitrogen together. 
+  Food coloring is sometimes added, in addition to stabilizers. 
+  The mixture is cooled below the freezing point of water and stirred to incorporate air spaces 
+  and to prevent detectable ice crystals from forming. The result is a smooth, 
+  semi-solid foam that is solid at very low temperatures (below 2 °C or 35 °F). 
+  It becomes more malleable as its temperature increases.
+  The meaning of the name ice cream varies from one country to another. 
+  In some countries, such as the United States, ice cream applies only to a specific variety, 
+  and most governments regulate the commercial use of the various terms according to the 
+  relative quantities of the main ingredients, notably the amount of cream. 
+  Products that do not meet the criteria to be called ice cream are sometimes labelled 
+  frozen dairy dessert instead. In other countries, such as Italy and Argentina, 
+  one word is used for all variants. Analogues made from dairy alternatives, 
+  such as goat's or sheep's milk, or milk substitutes 
+  (e.g., soy, cashew, coconut, almond milk or tofu), are available for those who are 
+  lactose intolerant, allergic to dairy protein or vegan.
+"""
+
+@bot()
+def on_message(message_history: List[Message], state: dict = None):
+
+    # Generate `command` (cohere's model) response
+    bot_response = Cohere.summarize(
+        text_input=SYSTEM_PROMPT,
+        message_history=message_history, # Assuming history is the list of user messages
+        model="command",
+    )
+
+    response = {
+        "data": {
+            "messages": [
+                {
+                    "data_type": "STRING",
+                    "value": bot_response
+                }
+            ],
+            "state": state
+        },
+        "errors": [
+            {
+                "message": ""
+            }
+        ]
+    }
+
+    return {
+        "status_code": 200,
+        "response": response
+    }

pyproject.toml

@@ -15,6 +15,7 @@ tabulate = "^0.9.0"
 functions-framework = "^3.4.0"
 yaspin = "^3.0.0"
 pydantic = "^2.3.0"
+cohere = "^4.21"
 google-generativeai = "^0.1.0"
 rich = "^13.5.2"