Final push

Author: Tomdango

.gitignore

@@ -179,4 +179,140 @@ cython_debug/
 #  exclude from AI features like autocomplete and code analysis. Recommended for sensitive data
 #  refer to https://docs.cursor.com/context/ignore-files
 .cursorignore
-.cursorindexingignore
+.cursorindexingignore
+# Logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+lerna-debug.log*
+.pnpm-debug.log*
+
+# Diagnostic reports (https://nodejs.org/api/report.html)
+report.[0-9]*.[0-9]*.[0-9]*.[0-9]*.json
+
+# Runtime data
+pids
+*.pid
+*.seed
+*.pid.lock
+
+# Directory for instrumented libs generated by jscoverage/JSCover
+lib-cov
+
+# Coverage directory used by tools like istanbul
+coverage
+*.lcov
+
+# nyc test coverage
+.nyc_output
+
+# Grunt intermediate storage (https://gruntjs.com/creating-plugins#storing-task-files)
+.grunt
+
+# Bower dependency directory (https://bower.io/)
+bower_components
+
+# node-waf configuration
+.lock-wscript
+
+# Compiled binary addons (https://nodejs.org/api/addons.html)
+build/Release
+
+# Dependency directories
+node_modules/
+jspm_packages/
+
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+web_modules/
+
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+.rpt2_cache/
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+.node_repl_history
+
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+*.tgz
+
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+.yarn-integrity
+
+# dotenv environment variable files
+.env
+.env.development.local
+.env.test.local
+.env.production.local
+.env.local
+
+# parcel-bundler cache (https://parceljs.org/)
+.cache
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+
+# Next.js build output
+.next
+out
+
+# Nuxt.js build / generate output
+.nuxt
+dist
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+# Gatsby files
+.cache/
+# Comment in the public line in if your project uses Gatsby and not Next.js
+# https://nextjs.org/blog/next-9-1#public-directory-support
+# public
+
+# vuepress build output
+.vuepress/dist
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+# vuepress v2.x temp and cache directory
+.temp
+.cache
+
+# vitepress build output
+**/.vitepress/dist
+
+# vitepress cache directory
+**/.vitepress/cache
+
+# Docusaurus cache and generated files
+.docusaurus
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+# Serverless directories
+.serverless/
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+# FuseBox cache
+.fusebox/
+
+# DynamoDB Local files
+.dynamodb/
+
+# TernJS port file
+.tern-port
+
+# Stores VSCode versions used for testing VSCode extensions
+.vscode-test
+
+# yarn v2
+.yarn/cache
+.yarn/unplugged
+.yarn/build-state.yml
+.yarn/install-state.gz
+.pnp.*

README.md

@@ -0,0 +1,59 @@
+from fastapi import FastAPI, Body
+from langchain_core.messages import HumanMessage, SystemMessage, AIMessage
+
+from fastapi.middleware.cors import CORSMiddleware
+from api.llm import get_agent, parse_response
+
+app = FastAPI()
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+global USER_MESSAGES
+USER_MESSAGES = []
+
+
+@app.post("/whats-wrong")
+async def whats_wrong(user_input: str = Body()) -> dict:
+    """
+    Process the user's input and return the JSON response.
+    """
+    agent = get_agent()
+
+    USER_MESSAGES.append(HumanMessage(content=user_input))
+
+    response = agent.invoke({"messages": USER_MESSAGES})
+    USER_MESSAGES.append(response["messages"][-1])
+
+    response = parse_response(response["messages"][-1])
+    return response
+
+
+@app.get("/reset")
+async def reset():
+    """
+    Root endpoint.
+    """
+    USER_MESSAGES.clear()
+
+
+@app.get("/outcomes")
+async def outcomes() -> list[dict]:
+    """
+    Root endpoint.
+    """
+    messages = []
+
+    for message in USER_MESSAGES:
+        if isinstance(message, HumanMessage):
+            messages.append({"role": "user", "content": message.content})
+        elif isinstance(message, AIMessage):
+            messages.append({"role": "assistant", "content": message.content})
+        elif isinstance(message, SystemMessage):
+            messages.append({"role": "system", "content": message.content})
+
+    return messages

api/__init__.py

@@ -0,0 +1,114 @@
+import typer
+from api.llm import get_agent
+from langchain_core.messages import HumanMessage
+from api.llm import parse_response
+import rich
+from rich.prompt import Prompt
+from api.speech import recognizer
+
+import speech_recognition as sr
+from api.tts import speak
+from api.console import console
+
+cli = typer.Typer()
+
+
+@cli.command()
+def text():
+    agent = get_agent()
+    user_input = Prompt.ask("[bold blue]What are your symptoms?[/bold blue]")
+
+    messages = []
+
+    while user_input != "exit":
+        messages.append(HumanMessage(content=user_input))
+
+        response = agent.invoke({"messages": messages})
+        messages.append(response["messages"][-1])
+
+        response = parse_response(response["messages"][-1])
+
+        if response["type"] == "question":
+            rich.print("[green bold]Assistant[/green bold]:", response["content"])
+
+        if response["type"] == "outcome":
+            print("----- PATHWAY REACHED -----")
+            rich.print_json(response, indent=2)
+            print("----- END OF PATHWAY -----")
+            break
+
+        if response["type"] == "emergency":
+            print("----- EMERGENCY -----")
+            rich.print_json(response, indent=2)
+            print("----- END OF EMERGENCY -----")
+            break
+
+        user_input = Prompt.ask("[bold cyan]User[/bold cyan]")
+
+
+@cli.command()
+def voice(intro: bool = True, calibrate: bool = True):
+    agent = get_agent(enable_voice_tool=False)
+    messages = []
+
+    if calibrate:
+        with console.status("[bold]Calibrating microphone...[/bold]") as status:
+            with sr.Microphone() as source:
+                recognizer.adjust_for_ambient_noise(source)
+
+        console.print("[bold green]Microphone calibrated![/bold green]")
+
+    if intro:
+        speak(
+            "Good afternoon. Welcome to NHS one one one. Can you tell me why you are contacting us today?"
+        )
+
+    with sr.Microphone() as source:
+        with console.status("[bold cyan]Listening for input[/bold cyan]") as status:
+            audio = recognizer.listen(source, phrase_time_limit=None)
+            status.update("[bold green]Recognizing...[/bold green]")
+            text = recognizer.recognize_whisper(audio, language="en")
+
+    rich.print("[bold]You said:[/bold]", text)
+    messages.append(HumanMessage(content=text))
+
+    with console.status("[bold cyan]Running Agent...[/bold cyan]"):
+        response = agent.invoke({"messages": messages})
+        messages.append(response["messages"][-1])
+
+    parsed_response = parse_response(response["messages"][-1])
+
+    while parsed_response.get("type") == "question":
+        speak(parsed_response["content"])
+
+        with console.status("[bold cyan]Listening for input[/bold cyan]") as status:
+            with sr.Microphone() as source:
+                audio = recognizer.listen(source, phrase_time_limit=None)
+                status.update("[bold green]Recognizing...[/bold green]")
+                text = recognizer.recognize_whisper(audio, language="en")
+
+        rich.print("[bold]You said:[/bold]", text)
+        messages.append(HumanMessage(content=text))
+
+        with console.status("[bold cyan]Running Agent...[/bold cyan]"):
+            response = agent.invoke({"messages": messages})
+            messages.append(response["messages"][-1])
+
+        parsed_response = parse_response(response["messages"][-1])
+
+    rich.print_json(data=parsed_response, indent=2)
+    if parsed_response["type"] == "outcome":
+        rich.print("[bold blue]EXIT - PATHWAY REACHED[/bold blue]")
+        speak(
+            "Thank you. Your pathway has been selected and you will shortly be transferred to an agent."
+        )
+
+    if parsed_response["type"] == "emergency":
+        rich.print("[bold red]EXIT - EMERGENCY[/bold red]")
+        speak(
+            "Your symptoms indicate a medical emergency. Please call nine nine nine or go to your nearest A&E."
+        )
+
+
+if __name__ == "__main__":
+    cli()

api/app.py

@@ -0,0 +1,3 @@
+from rich.console import Console
+
+console = Console()

api/cli.py

@@ -0,0 +1,41 @@
+from langgraph.prebuilt import create_react_agent
+from langchain_aws import ChatBedrock
+import json
+from api.prompt import MAIN_PROMPT
+from langchain_core.messages import AIMessage
+from langchain_core.tools import tool
+from api.tts import speak
+import speech_recognition as sr
+from api.speech import ask_user
+
+
+def get_agent(enable_voice_tool: bool = False):
+    llm = ChatBedrock(
+        model="anthropic.claude-3-haiku-20240307-v1:0",
+        temperature=0.5,
+        max_tokens=48000,
+    )
+
+    print("Prompt Tokens", llm.get_num_tokens(MAIN_PROMPT))
+
+    tools = []
+    if enable_voice_tool:
+        tools.append(ask_user)
+
+    agent = create_react_agent(
+        model=llm,
+        prompt=MAIN_PROMPT,
+        tools=tools,
+    )
+
+    return agent
+
+
+def parse_response(response: AIMessage):
+    content = getattr(response, "content")
+    # Strip everything before the first '{' and after the last '}'
+    content = content[content.find("{") : content.rfind("}") + 1]
+
+    # Parse the JSON content
+    response = json.loads(content)
+    return response