resolve conflict

.env.example

@@ -1,3 +1,9 @@
+# cp .env.example .env
+# Edit your .env file with your own values
+# Don't commit your .env file to git/push to GitHub!
+# Don't modify/delete .env.example unless adding extensions to the project
+# which require new variable to be added to the .env file
+
 # API CONFIG
 OPENAI_API_KEY=
 OPENAI_API_MODEL=gpt-3.5-turbo # alternatively, gpt-4, text-davinci-003, etc
@@ -9,4 +15,12 @@ TABLE_NAME=test-table
 
 # PROJECT CONFIG
 OBJECTIVE=Solve world hunger
-FIRST_TASK=Develop a task list
+# For backwards compatibility
+# FIRST_TASK can be used instead of INITIAL_TASK
+INITIAL_TASK=Develop a task list
+
+# Extensions
+# List additional extensions to load (except .env.example!)
+DOTENV_EXTENSIONS=
+# Set to true to enable command line args support
+ENABLE_COMMAND_LINE_ARGS=false

.gitignore

@@ -1,2 +1,12 @@
+__pycache__/
+*.py[cod]
+*$py.class
+
 .env
-.idea
+.env.*
+env/
+.venv
+venv/
+
+.vscode/
+.idea/

CNAME

@@ -0,0 +1 @@
+babyagi.org

README.md

@@ -36,13 +36,12 @@ To use the script, you will need to follow these steps:
 3. Set your OpenAI and Pinecone API keys in the OPENAI_API_KEY, OPENAPI_API_MODEL, and PINECONE_API_KEY variables.
 4. Set the Pinecone environment in the PINECONE_ENVIRONMENT variable.
 5. Set the name of the table where the task results will be stored in the TABLE_NAME variable.
-6. Set the objective of the task management system in the OBJECTIVE variable. Alternatively you can pass it to the script as a quote argument.
-```
-./babyagi.py ["<objective>"]
-```
-7. Set the first task of the system in the FIRST_TASK variable.
+6. (Optional) Set the objective of the task management system in the OBJECTIVE variable.
+7. (Optional) Set the first task of the system in the INITIAL_TASK variable.
 8. Run the script.
 
+All optional values above can also be specified on the command line.
+
 # Warning<a name="continous-script-warning"></a>
 This script is designed to be run continuously as part of a task management system. Running this script continuously can result in high API usage, so please use it responsibly. Additionally, the script requires the OpenAI and Pinecone APIs to be set up correctly, so make sure you have set up the APIs before running the script.
 

babyagi.py

@@ -1,6 +1,5 @@
 #!/usr/bin/env python3
 import os
-import sys
 import time
 from collections import deque
 from typing import Dict, List
@@ -9,7 +8,7 @@
 import pinecone
 from dotenv import load_dotenv
 
-# Set Variables
+# Load default environment variables (.env)
 load_dotenv()
 
 # Set API Keys
@@ -29,7 +28,7 @@
 PINECONE_API_KEY = os.getenv("PINECONE_API_KEY", "")
 assert PINECONE_API_KEY, "PINECONE_API_KEY environment variable is missing from .env"
 
-PINECONE_ENVIRONMENT = os.getenv("PINECONE_ENVIRONMENT", "us-east1-gcp")
+PINECONE_ENVIRONMENT = os.getenv("PINECONE_ENVIRONMENT", "")
 assert (
     PINECONE_ENVIRONMENT
 ), "PINECONE_ENVIRONMENT environment variable is missing from .env"
@@ -38,16 +37,44 @@
 YOUR_TABLE_NAME = os.getenv("TABLE_NAME", "")
 assert YOUR_TABLE_NAME, "TABLE_NAME environment variable is missing from .env"
 
-# Project config
-OBJECTIVE = sys.argv[1] if len(sys.argv) > 1 else os.getenv("OBJECTIVE", "")
-assert OBJECTIVE, "OBJECTIVE environment variable is missing from .env"
+# Goal configuation
+OBJECTIVE = os.getenv("OBJECTIVE", "")
+INITIAL_TASK = os.getenv("INITIAL_TASK", os.getenv("FIRST_TASK", ""))
 
-YOUR_FIRST_TASK = os.getenv("FIRST_TASK", "")
-assert YOUR_FIRST_TASK, "FIRST_TASK environment variable is missing from .env"
+DOTENV_EXTENSIONS = os.getenv("DOTENV_EXTENSIONS", "").split(" ")
+
+# Command line arguments extension
+# Can override any of the above environment variables
+ENABLE_COMMAND_LINE_ARGS = (
+    os.getenv("ENABLE_COMMAND_LINE_ARGS", "false").lower() == "true"
+)
+if ENABLE_COMMAND_LINE_ARGS:
+    from extensions.argparseext import parse_arguments
+
+    OBJECTIVE, INITIAL_TASK, OPENAI_API_MODEL, DOTENV_EXTENSIONS = parse_arguments()
+
+# Load additional environment variables for enabled extensions
+if DOTENV_EXTENSIONS:
+    from extensions.dotenvext import load_dotenv_extensions
+
+    load_dotenv_extensions(DOTENV_EXTENSIONS)
+
+# TODO: There's still work to be done here to enable people to get
+# defaults from dotenv extensions # but also provide command line
+# arguments to override them
+
+if "gpt-4" in OPENAI_API_MODEL.lower():
+    print(
+        "\033[91m\033[1m"
+        + "\n*****USING GPT-4. POTENTIALLY EXPENSIVE. MONITOR YOUR COSTS*****"
+        + "\033[0m\033[0m"
+    )
 
 # Print OBJECTIVE
-print("\033[96m\033[1m" + "\n*****OBJECTIVE*****\n" + "\033[0m\033[0m")
-print(OBJECTIVE)
+print("\033[94m\033[1m" + "\n*****OBJECTIVE*****\n" + "\033[0m\033[0m")
+print(f"{OBJECTIVE}")
+
+print("\033[93m\033[1m" + "\nInitial task:" + "\033[0m\033[0m" + f" {INITIAL_TASK}")
 
 # Configure OpenAI and Pinecone
 openai.api_key = OPENAI_API_KEY
@@ -87,30 +114,39 @@ def openai_call(
     temperature: float = 0.5,
     max_tokens: int = 100,
 ):
-    if not model.startswith("gpt-"):
-        # Use completion API
-        response = openai.Completion.create(
-            engine=model,
-            prompt=prompt,
-            temperature=temperature,
-            max_tokens=max_tokens,
-            top_p=1,
-            frequency_penalty=0,
-            presence_penalty=0,
-        )
-        return response.choices[0].text.strip()
-    else:
-        # Use chat completion API
-        messages = [{"role": "user", "content": prompt}]
-        response = openai.ChatCompletion.create(
-            model=model,
-            messages=messages,
-            temperature=temperature,
-            max_tokens=max_tokens,
-            n=1,
-            stop=None,
-        )
-        return response.choices[0].message.content.strip()
+    while True:
+        try:
+            if not model.startswith("gpt-"):
+                # Use completion API
+                response = openai.Completion.create(
+                    engine=model,
+                    prompt=prompt,
+                    temperature=temperature,
+                    max_tokens=max_tokens,
+                    top_p=1,
+                    frequency_penalty=0,
+                    presence_penalty=0,
+                )
+                return response.choices[0].text.strip()
+            else:
+                # Use chat completion API
+                messages = [{"role": "user", "content": prompt}]
+                response = openai.ChatCompletion.create(
+                    model=model,
+                    messages=messages,
+                    temperature=temperature,
+                    max_tokens=max_tokens,
+                    n=1,
+                    stop=None,
+                )
+                return response.choices[0].message.content.strip()
+        except openai.error.RateLimitError:
+            print(
+                "The OpenAI API rate limit has been exceeded. Waiting 10 seconds and trying again."
+            )
+            time.sleep(10)  # Wait 10 seconds and try again
+        else:
+            break
 
 
 def task_creation_agent(
@@ -123,7 +159,7 @@ def task_creation_agent(
     Based on the result, create new tasks to be completed by the AI system that do not overlap with incomplete tasks.
     Return the tasks as an array."""
     response = openai_call(prompt)
-    new_tasks = response.split("\n")
+    new_tasks = response.split("\n") if "\n" in response else [response]
     return [{"task_name": task_name} for task_name in new_tasks]
 
 
@@ -154,8 +190,8 @@ def execution_agent(objective: str, task: str) -> str:
     # print("\n*******RELEVANT CONTEXT******\n")
     # print(context)
     prompt = f"""
-    You are an AI who performs one task based on the following objective: {objective}.
-    Take into account these previously completed tasks: {context}.
+    You are an AI who performs one task based on the following objective: {objective}\n.
+    Take into account these previously completed tasks: {context}\n.
     Your task: {task}\nResponse:"""
     return openai_call(prompt, temperature=0.7, max_tokens=2000)
 
@@ -170,7 +206,7 @@ def context_agent(query: str, n: int):
 
 
 # Add the first task
-first_task = {"task_id": 1, "task_name": YOUR_FIRST_TASK}
+first_task = {"task_id": 1, "task_name": INITIAL_TASK}
 
 add_task(first_task)
 # Main loop
@@ -198,31 +234,25 @@ def context_agent(query: str, n: int):
             "data": result
         }  # This is where you should enrich the result if needed
         result_id = f"result_{task['task_id']}"
-        vector = enriched_result[
-            "data"
-        ]  # extract the actual result from the dictionary
+        vector = get_ada_embedding(
+            enriched_result["data"]
+        )  # get vector of the actual result extracted from the dictionary
         index.upsert(
-            [
-                (
-                    result_id,
-                    get_ada_embedding(vector),
-                    {"task": task["task_name"], "result": result},
-                )
-            ]
+            [(result_id, vector, {"task": task["task_name"], "result": result})]
         )
 
-    # Step 3: Create new tasks and reprioritize task list
-    new_tasks = task_creation_agent(
-        OBJECTIVE,
-        enriched_result,
-        task["task_name"],
-        [t["task_name"] for t in task_list],
-    )
+        # Step 3: Create new tasks and reprioritize task list
+        new_tasks = task_creation_agent(
+            OBJECTIVE,
+            enriched_result,
+            task["task_name"],
+            [t["task_name"] for t in task_list],
+        )
 
-    for new_task in new_tasks:
-        task_id_counter += 1
-        new_task.update({"task_id": task_id_counter})
-        add_task(new_task)
-    prioritization_agent(this_task_id)
+        for new_task in new_tasks:
+            task_id_counter += 1
+            new_task.update({"task_id": task_id_counter})
+            add_task(new_task)
+        prioritization_agent(this_task_id)
 
     time.sleep(1)  # Sleep before checking the task list again

extensions/argparseext.py

@@ -0,0 +1,76 @@
+import os
+import sys
+import argparse
+
+# Extract the env filenames in the -e flag only
+# Ignore any other arguments
+def parse_dotenv_extensions(argv):
+    env_argv = []
+    if '-e' in argv:
+        tmp_argv = argv[argv.index('-e') + 1:]
+        parsed_args = []
+        for arg in tmp_argv:
+            if arg.startswith('-'):
+                break
+            parsed_args.append(arg)
+        env_argv = ['-e'] + parsed_args
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument('-e', '--env', nargs='+', help='''
+    filenames for additional env variables to load
+    ''', default=os.getenv("DOTENV_EXTENSIONS", "").split(' '))
+
+    return parser.parse_args(env_argv).env
+
+def parse_arguments():
+    dotenv_extensions = parse_dotenv_extensions(sys.argv)
+    # Check if we need to load any additional env files
+    # This allows us to override the default .env file
+    # and update the default values for any command line arguments
+    if dotenv_extensions:
+        from extensions.dotenvext import load_dotenv_extensions
+        load_dotenv_extensions(parse_dotenv_extensions(sys.argv))
+
+    # Now parse the full command line arguments
+    parser = argparse.ArgumentParser(
+        add_help=False,
+    )
+    parser.add_argument('objective', nargs='*', metavar='<objective>', help='''
+    main objective description. Doesn\'t need to be quoted.
+    if not specified, get objective from environment.
+    ''', default=[os.getenv("OBJECTIVE", "")])
+    parser.add_argument('-t', '--task', metavar='<initial task>', help='''
+    initial task description. must be quoted.
+    if not specified, get initial_task from environment.
+    ''', default=os.getenv("INITIAL_TASK", os.getenv("FIRST_TASK", "")))
+    parser.add_argument('-4', '--gpt-4', dest='openai_api_model', action='store_const', const="gpt-4", help='''
+    use GPT-4 instead of the default GPT-3 model.
+    ''', default=os.getenv("OPENAI_API_MODEL", "gpt-3.5-turbo"))
+    # This will parse -e again, which we want, because we need
+    # to load those in the main file later as well
+    parser.add_argument('-e', '--env', nargs='+', help='''
+    filenames for additional env variables to load
+    ''', default=os.getenv("DOTENV_EXTENSIONS", "").split(' '))
+    parser.add_argument('-h', '-?', '--help', action='help', help='''
+    show this help message and exit
+    ''')
+
+    args = parser.parse_args()
+
+    openai_api_model = args.openai_api_model
+
+    dotenv_extensions = args.env
+
+    objective = ' '.join(args.objective).strip()
+    if not objective:
+        print("\033[91m\033[1m"+"No objective specified or found in environment.\n"+"\033[0m\033[0m")
+        parser.print_help()
+        parser.exit()
+
+    initial_task = args.task
+    if not initial_task:
+        print("\033[91m\033[1m"+"No initial task specified or found in environment.\n"+"\033[0m\033[0m")
+        parser.print_help()
+        parser.exit()
+
+    return objective, initial_task, openai_api_model, dotenv_extensions

extensions/dotenvext.py

@@ -0,0 +1,5 @@
+from dotenv import load_dotenv
+
+def load_dotenv_extensions(dotenv_files):
+    for dotenv_file in dotenv_files:
+        load_dotenv(dotenv_file)

requirements.txt

@@ -1,4 +1,5 @@
-openai==0.27.2
+argparse==1.4.0
+openai==0.27.4
 pinecone-client==2.2.1
 pre-commit>=3.2.0
 python-dotenv==1.0.0