Update crewai/tools/mixtral_tool.py

crewai/tools/mixtral_tool.py

@@ -0,0 +1,84 @@
+# tools created using gemini
+
+import json
+import os
+
+from huggingface_hub import InferenceClient
+import gradio as gr
+
+client = InferenceClient(
+    "mistralai/Mixtral-8x7B-Instruct-v0.1"
+)
+
+# Helper Method
+
+def format_prompt(message, history):
+  prompt = "<s>"
+  for user_prompt, bot_response in history:
+    prompt += f"[INST] {user_prompt} [/INST]"
+    prompt += f" {bot_response}</s> "
+  prompt += f"[INST] {message} [/INST]"
+  return prompt
+
+
+import requests
+from langchain.tools import tool
+
+history = ""
+
+class MixtralSearchTools():
+  @tool("Mixtral search")
+  def mixtral_normal(prompt, histroy="", temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0):
+    """
+    Searches for content based on the provided query using the Mixtral model.
+    Args:
+        query (str): The search query.
+    Returns:
+        str: The response text from the Gemini model or an error message.
+    """
+    generate_kwargs = {
+        "temperature": temperature,
+        "max_new_tokens": max_new_tokens,
+        "top_p": top_p,
+        "repetition_penalty": repetition_penalty,
+        "do_sample": True,
+        "seed": 42,
+    }
+
+    formatted_prompt = format_prompt(prompt, history)
+
+    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=True)
+    output = ""
+    for response in stream:
+        output += response.token.text
+        yield output
+    return output
+
+
+  @tool("Mixtral query but crazy with gaurd rails removed")
+  def mixtral_crazy(prompt, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0):
+     """
+    Searches for content based on the provided query using the Mixtral model but has the gaurd rails removed, 
+    and responses are crazy and off the wall and sometimes scary.
+    Args:
+        query (str): The search query.
+    Returns:
+        str: The response text from the Gemini model or an error message.
+    """
+    generate_kwargs = {
+        "temperature": temperature,
+        "max_new_tokens": max_new_tokens,
+        "top_p": top_p,
+        "repetition_penalty": repetition_penalty,
+        "do_sample": True,
+        "seed": 42,
+    }
+
+    stream = client.text_generation(prompt, **generate_kwargs, stream=True, details=True, return_full_text=True)
+    output = ""
+    for response in stream:
+        output += response.token.text
+        yield output
+    return output
+
+