audio history

.gitignore

@@ -1,4 +1,5 @@
 __pycache__/
 .venv/
 .env
-test.py 
+test.py 
+audio_files/

agent.py

@@ -48,7 +48,7 @@ async def call_agent(user_prompt, collection):
         system_prompt=system_prompt,
         user_prompt=user_prompt,
         output_format={
-            "function": 'Type of function to call, type: Enum["retriever", "translator", "speaker", "none"]',
+            "function": 'Type of function to call, type: Enum["retriever", "translator", "speaker", "none", "extractor"]',
             "keywords": "Array of keywords, type: List[str]",
             "src_lang": "Identify the language that the user query is in, type: str",
             "dest_lang": """Identify the target language from the user query if the function is either "translator" or "speaker". If language is not found, return "none", 
@@ -75,7 +75,7 @@ async def retriever(user_prompt, collection, client):
 
 
 async def extractor(user_prompt, url):
-    text = extract(user_prompt)
+    text = await extract(url)
 
     system_prompt = EXTRACT_SYS_PROMPT.format(url)
     user_prompt = EXTRACT_USER_PROMPT.format(text, user_prompt)
@@ -85,6 +85,7 @@ async def extractor(user_prompt, url):
 
 async def function_caller(user_prompt, collection, client):
     result = await call_agent(user_prompt, collection)
+    print(f"Agent log -\n {result} \n\n")
     function = result["function"].lower()
 
     if function == "none":

app.py

@@ -1,5 +1,4 @@
 import base64
-import tempfile
 
 import gradio as gr
 from fastapi import FastAPI
@@ -8,7 +7,7 @@ from pydantic import BaseModel
 
 from agent import function_caller, retriever
 from client import HybridClient
-from sarvam import speaker, translator
+from sarvam import save_audio, speaker, translator
 
 app = FastAPI()
 hclient = HybridClient()
@@ -42,13 +41,13 @@ class TTSQuery(BaseModel):
 
 @app.get("/agent")
 async def agent(query: ChatQuery):
-    collection = f"{grade}_{subject.lower()}_{chapter}"
+    collection = f"{query.grade}_{query.subject.lower()}_{query.chapter}"
     return await function_caller(query.query, collection, hclient)
 
 
 @app.get("/rag")
 async def rag(query: ChatQuery):
-    collection = f"{grade}_{subject.lower()}_{chapter}"
+    collection = f"{query.grade}_{query.subject.lower()}_{query.chapter}"
     return await retriever(query.query, collection, hclient)
 
 
@@ -67,22 +66,27 @@ async def gradio_interface(input_text, grade, subject, chapter, history):
 
     if "text" in response:
         output = response["text"]
-        history.append((input_text, output))
-
+        history.append((input_text, {"type": "text", "content": output}))
     elif "audios" in response:
         audio_data = base64.b64decode(response["audios"][0])
-
-        with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as audiofile:
-            audiofile.write(audio_data)
-            audiofile.flush()
-
-        return "", history, audiofile.name
-
+        audio_path = save_audio(audio_data)
+        history.append((input_text, {"type": "audio", "content": audio_path}))
     else:
         output = "Unexpected response format"
-        history.append((input_text, output))
+        history.append((input_text, {"type": "text", "content": output}))
 
-    return "", history, None
+    return "", history
+
+
+def format_history(history):
+    formatted_history = []
+    for human, assistant in history:
+        formatted_history.append((human, None))
+        if assistant["type"] == "text":
+            formatted_history.append((None, assistant["content"]))
+        elif assistant["type"] == "audio":
+            formatted_history.append((None, gr.Audio(value=assistant["content"], visible=True)))
+    return formatted_history
 
 
 with gr.Blocks() as iface:
@@ -96,11 +100,9 @@ with gr.Blocks() as iface:
 
     chatbot = gr.Chatbot(label="Chat History")
     msg = gr.Textbox(label="Your message", placeholder="Type your message here...")
-
     state = gr.State([])
-    audio_output = gr.Audio(label="Audio Response", type="filepath")  # Separate audio output component
 
-    msg.submit(gradio_interface, inputs=[msg, grade, subject, chapter, state], outputs=[msg, chatbot, audio_output])
+    msg.submit(gradio_interface, inputs=[msg, grade, subject, chapter, state], outputs=[msg, state]).then(format_history, inputs=[state], outputs=[chatbot])
 
 app = gr.mount_gradio_app(app, iface, path="/")
 

sarvam.py

@@ -62,3 +62,12 @@ async def speaker(text, src="hindi"):
                 return output
             else:
                 print(response.status)
+
+
+def save_audio(audio_data):
+    os.makedirs("audio_files", exist_ok=True)
+    file_count = len(os.listdir("audio_files"))
+    file_path = f"audio_files/audio_{file_count + 1}.wav"
+    with open(file_path, "wb") as audiofile:
+        audiofile.write(audio_data)
+    return file_path