Merge pull request #158 from MervinPraison/develop

Adding Search with Tavily Feature to Chat and Code

Author: MervinPraison

Dockerfile

@@ -1,6 +1,6 @@
 FROM python:3.11-slim
 WORKDIR /app
 COPY . .
-RUN pip install flask praisonai==0.0.70 gunicorn markdown
+RUN pip install flask praisonai==0.0.71 gunicorn markdown
 EXPOSE 8080
 CMD ["gunicorn", "-b", "0.0.0.0:8080", "api:app"]

docs/api/praisonai/deploy.html

@@ -110,7 +110,7 @@ <h2 id="raises">Raises</h2>
             file.write(&#34;FROM python:3.11-slim\n&#34;)
             file.write(&#34;WORKDIR /app\n&#34;)
             file.write(&#34;COPY . .\n&#34;)
-            file.write(&#34;RUN pip install flask praisonai==0.0.70 gunicorn markdown\n&#34;)
+            file.write(&#34;RUN pip install flask praisonai==0.0.71 gunicorn markdown\n&#34;)
             file.write(&#34;EXPOSE 8080\n&#34;)
             file.write(&#39;CMD [&#34;gunicorn&#34;, &#34;-b&#34;, &#34;0.0.0.0:8080&#34;, &#34;api:app&#34;]\n&#39;)
 

poetry.lock

@@ -3,7 +3,7 @@ class Praisonai < Formula
 
     desc "AI tools for various AI applications"
     homepage "https://github.com/MervinPraison/PraisonAI"
-    url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/0.0.70.tar.gz"
+    url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/0.0.71.tar.gz"
     sha256 "1828fb9227d10f991522c3f24f061943a254b667196b40b1a3e4a54a8d30ce32"  # Replace with actual SHA256 checksum
     license "MIT"
 

praisonai.rb

@@ -56,7 +56,7 @@ def create_dockerfile(self):
             file.write("FROM python:3.11-slim\n")
             file.write("WORKDIR /app\n")
             file.write("COPY . .\n")
-            file.write("RUN pip install flask praisonai==0.0.70 gunicorn markdown\n")
+            file.write("RUN pip install flask praisonai==0.0.71 gunicorn markdown\n")
             file.write("EXPOSE 8080\n")
             file.write('CMD ["gunicorn", "-b", "0.0.0.0:8080", "api:app"]\n')
 

praisonai/deploy.py

@@ -1,6 +1,6 @@
 import chainlit as cl
 from chainlit.input_widget import TextInput
-from chainlit.types import ThreadDict
+from chainlit.types import ThreadDict  # Change this import
 from litellm import acompletion
 import os
 import sqlite3
@@ -14,6 +14,7 @@
 import logging
 import json
 from sql_alchemy import SQLAlchemyDataLayer
+from tavily import TavilyClient
 
 # Set up logging
 logger = logging.getLogger(__name__)
@@ -171,6 +172,41 @@ def load_setting(key: str) -> str:
 
 cl_data._data_layer = SQLAlchemyDataLayer(conninfo=f"sqlite+aiosqlite:///{DB_PATH}")
 
+# Set Tavily API key
+tavily_api_key = os.getenv("TAVILY_API_KEY")
+tavily_client = TavilyClient(api_key=tavily_api_key) if tavily_api_key else None
+
+# Function to call Tavily Search API
+def tavily_web_search(query):
+    if not tavily_client:
+        return json.dumps({
+            "query": query,
+            "error": "Tavily API key is not set. Web search is unavailable."
+        })
+    response = tavily_client.search(query)
+    print(response)  # Print the full response
+    return json.dumps({
+        "query": query,
+        "answer": response.get('answer'),
+        "top_result": response['results'][0]['content'] if response['results'] else 'No results found'
+    })
+
+# Define the tool for function calling
+tools = [{
+    "type": "function",
+    "function": {
+        "name": "tavily_web_search",
+        "description": "Search the web using Tavily API",
+        "parameters": {
+            "type": "object",
+            "properties": {
+                "query": {"type": "string", "description": "Search query"}
+            },
+            "required": ["query"]
+        }
+    }
+}] if tavily_api_key else []
+
 @cl.on_chat_start
 async def start():
     initialize_db()
@@ -224,31 +260,130 @@ async def setup_agent(settings):
 async def main(message: cl.Message):
     model_name = load_setting("model_name") or os.getenv("MODEL_NAME") or "gpt-4o-mini"
     message_history = cl.user_session.get("message_history", [])
-    message_history.append({"role": "user", "content": message.content})
+    now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    
+    # Add the current date and time to the user's message
+    user_message = f"""
+Answer the question and use tools if needed:\n{message.content}.\n\n
+Current Date and Time: {now}
+"""
+    message_history.append({"role": "user", "content": user_message})
 
     msg = cl.Message(content="")
     await msg.send()
 
-    response = await acompletion(
-        model=model_name,
-        messages=message_history,
-        stream=True,
-        # temperature=0.7,
-        # max_tokens=500,
-        # top_p=1
-    )
+    # Prepare the completion parameters
+    completion_params = {
+        "model": model_name,
+        "messages": message_history,
+        "stream": True,
+    }
+
+    # Only add tools and tool_choice if Tavily API key is available
+    if tavily_api_key:
+        completion_params["tools"] = tools
+        completion_params["tool_choice"] = "auto"
+
+    response = await acompletion(**completion_params)
 
     full_response = ""
+    tool_calls = []
+    current_tool_call = None
+
     async for part in response:
-        if token := part['choices'][0]['delta']['content']:
-            await msg.stream_token(token)
-            full_response += token
+        if 'choices' in part and len(part['choices']) > 0:
+            delta = part['choices'][0].get('delta', {})
+            
+            if 'content' in delta and delta['content'] is not None:
+                token = delta['content']
+                await msg.stream_token(token)
+                full_response += token
+            
+            if tavily_api_key and 'tool_calls' in delta and delta['tool_calls'] is not None:
+                for tool_call in delta['tool_calls']:
+                    if current_tool_call is None or tool_call.index != current_tool_call['index']:
+                        if current_tool_call:
+                            tool_calls.append(current_tool_call)
+                        current_tool_call = {
+                            'id': tool_call.id,
+                            'type': tool_call.type,
+                            'index': tool_call.index,
+                            'function': {
+                                'name': tool_call.function.name if tool_call.function else None,
+                                'arguments': ''
+                            }
+                        }
+                    if tool_call.function:
+                        if tool_call.function.name:
+                            current_tool_call['function']['name'] = tool_call.function.name
+                        if tool_call.function.arguments:
+                            current_tool_call['function']['arguments'] += tool_call.function.arguments
+
+    if current_tool_call:
+        tool_calls.append(current_tool_call)
+
     logger.debug(f"Full response: {full_response}")
+    logger.debug(f"Tool calls: {tool_calls}")
     message_history.append({"role": "assistant", "content": full_response})
     logger.debug(f"Message history: {message_history}")
     cl.user_session.set("message_history", message_history)
     await msg.update()
 
+    if tavily_api_key and tool_calls:
+        available_functions = {
+            "tavily_web_search": tavily_web_search,
+        }
+        messages = message_history + [{"role": "assistant", "content": None, "function_call": {
+            "name": tool_calls[0]['function']['name'],
+            "arguments": tool_calls[0]['function']['arguments']
+        }}]
+
+        for tool_call in tool_calls:
+            function_name = tool_call['function']['name']
+            if function_name in available_functions:
+                function_to_call = available_functions[function_name]
+                function_args = tool_call['function']['arguments']
+                if function_args:
+                    try:
+                        function_args = json.loads(function_args)
+                        function_response = function_to_call(
+                            query=function_args.get("query"),
+                        )
+                        messages.append(
+                            {
+                                "role": "function",
+                                "name": function_name,
+                                "content": function_response,
+                            }
+                        )
+                    except json.JSONDecodeError:
+                        logger.error(f"Failed to parse function arguments: {function_args}")
+
+        second_response = await acompletion(
+            model=model_name,
+            stream=True,
+            messages=messages,
+        )
+        logger.debug(f"Second LLM response: {second_response}")
+
+        # Handle the streaming response
+        full_response = ""
+        async for part in second_response:
+            if 'choices' in part and len(part['choices']) > 0:
+                delta = part['choices'][0].get('delta', {})
+                if 'content' in delta and delta['content'] is not None:
+                    token = delta['content']
+                    await msg.stream_token(token)
+                    full_response += token
+
+        # Update the message content
+        msg.content = full_response
+        await msg.update()
+    else:
+        # If no tool calls or Tavily API key is not set, the full_response is already set
+        msg.content = full_response
+        await msg.update()
+
 username = os.getenv("CHAINLIT_USERNAME", "admin")  # Default to "admin" if not found
 password = os.getenv("CHAINLIT_PASSWORD", "admin")  # Default to "admin" if not found
 
@@ -267,7 +402,7 @@ async def send_count():
     ).send()
 
 @cl.on_chat_resume
-async def on_chat_resume(thread: cl_data.ThreadDict):
+async def on_chat_resume(thread: ThreadDict):  # Change the type hint here
     logger.info(f"Resuming chat: {thread['id']}")
     model_name = load_setting("model_name") or os.getenv("MODEL_NAME") or "gpt-4o-mini"
     logger.debug(f"Model name: {model_name}")
@@ -285,8 +420,14 @@ async def on_chat_resume(thread: cl_data.ThreadDict):
     thread_id = thread["id"]
     cl.user_session.set("thread_id", thread["id"])
 
-    # The metadata should now already be a dictionary
+    # Ensure metadata is a dictionary
     metadata = thread.get("metadata", {})
+    if isinstance(metadata, str):
+        try:
+            metadata = json.loads(metadata)
+        except json.JSONDecodeError:
+            metadata = {}
+    
     cl.user_session.set("metadata", metadata)
 
     message_history = cl.user_session.get("message_history", [])
@@ -298,7 +439,14 @@ async def on_chat_resume(thread: cl_data.ThreadDict):
             message_history.append({"role": "user", "content": message.get("output", "")})
         elif msg_type == "assistant_message":
             message_history.append({"role": "assistant", "content": message.get("output", "")})
+        elif msg_type == "run":
+            # Handle 'run' type messages
+            if message.get("isError"):
+                message_history.append({"role": "system", "content": f"Error: {message.get('output', '')}"})
+            else:
+                # You might want to handle non-error 'run' messages differently
+                pass
         else:
-            logger.warning(f"Message without type: {message}")
+            logger.warning(f"Message without recognized type: {message}")
 
     cl.user_session.set("message_history", message_history)